NO20231190A1

NO20231190A1 - Target pretension of mooring lines

Info

Publication number: NO20231190A1
Application number: NO20231190A
Authority: NO
Inventors: Terje Nistad; Massimiliano Russo
Original assignee: Kongsberg Maritime As
Priority date: 2023-11-03
Filing date: 2023-11-03
Publication date: 2025-05-05
Also published as: WO2025095785A4; WO2025095785A1

Description

TARGET PRETENSION OF MOORING LINES

[0001] The present invention relates to a computer-implemented method of achieving a target pretension in one or more mooring lines of a physical floating offshore unit and an associated computer program product and system.

[0002] Floating offshore wind turbines (FOWTs) address the problem of sea depth being too great to build a support structure for a wind turbine out to sea, and they require mooring lines for anchoring. The mooring system characteristics and tension in mooring lines dictates the floater position and it is important to determine the pretension in the mooring lines in a calm sea environment, to ensure that the tensions across the mooring lines are correct for the floater to be positioned as desired in the water. “Pretension” is a term of art referring to the tension in mooring lines with “zero weather” i.e., in a calm sea or without accounting for weather. For the integrity of the power cable and the proper farm management the pretension of the mooring lines in calm environment which dictates the floater position is of paramount importance. Other floating structures may also be anchored and positioned by mooring lines, such as offshore rigs.

[0003] Typically, tension in mooring lines is measured by sensors mounted on winches installed on board a floater. Including winches onboard for each mooring line or cluster of lines together with sensors to provide tension measurements may become costly, especially for a wind farm or the like with multiple floaters. Sensors need to be maintained and may need manual repair, which may be difficult and/or inefficient where the sensors are arranged on board the floater.

[0004] One solution to determining the tension in mooring lines is to arrange tension sensors directly onto the mooring lines. The problem remains that there is a need to maintain and repair as many sensors as there are mooring lines, with the additional difficulty of the sensors being arranged subsea.

[0005] It is an aim of the present disclosure to improve determining the pretension in mooring lines.

SUMMARY STATEMENTS

[0006] The following statements summarise some aspects and embodiments of the disclosed technology, however, the scope of the invention is as defined by the accompanying claims.

[0007] A first aspect of the present disclosure comprises a computer-implemented method of achieving a target pretension in one or more mooring lines of a physical floating offshore unit, the method comprising: measuring a tension in an installation line configured to install the physical floating offshore unit, measuring a line length pull in/out of the installation line; generating a model comprising a digital representation of the physical floating offshore unit’s physical properties and/or physical behaviours, wherein the physical floating offshore unit comprises one or more mooring lines and wherein the model is configured to model the one or more mooring lines, the model further comprising a digital representation of physical properties and/or physical behaviours of an installation vessel that is configured to install the physical floating offshore unit, wherein generating the model comprises selecting a base design for the model from a set of base designs based on the measured tension and measured line length pull in/out and modelling the physical properties and/or physical behaviours based on initial data, wherein the initial data is to be updated based on as-built and as-installed data comprising (i) operations data specific to the physical floating offshore unit and the mooring lines and (ii) marine execution data, and estimating, by the model, based on the as-built and as-installed data, a predicted pretension in the one or more physical mooring lines such that vessel disconnection from the physical floating offshore unit can be performed based on the predicted pretension.

[0008] The tension may be measured using a tension sensor at a vessel separate from the physical floating offshore unit, wherein the installation line is routed through a tensioning device and connected to a mooring line of the physical floating offshore unit such that the vessel can tension up the mooring line and install the physical floating offshore unit, wherein the installation line is connected to a winch on board the vessel and wherein a line length sensor is arranged on the winch, wherein the line length pull in/out is measured using the line length sensor.

[0009] The method may further comprise obtaining operations data from one or more sensors, a memory, or a manual input into a computing device configured to run the model and/or a remote server as a data source and assigning system configuration variables for the model based on the operations data, wherein operations data includes installation line length and winch tension.

[00010]The method may further comprise obtaining marine execution data from one or more sensors, a memory, or by manual input into a computing device configured to run the model and/or a remote server as a data source, wherein the marine execution data comprises indications of vessel position and motion in water and/or physical floating offshore unit position and motion in the water respectively, and assigning one or more model calibration variables based on the marine execution data and/or applying a correction to the predicted pretension based on obtained marine execution data.

[00011]The method may further comprise obtaining environmental data from one or more sensors and/or a remote server as a data source, the environmental data comprising indications of the conditions at the location of the physical floating offshore unit and applying a correction to the predicted pretension based on obtained environmental data.

[00012]The method may further comprise comparing the predicted pretension with a predetermined range of values, wherein once the predicted tension is within the predetermined range of values, providing an indication of the predicted tension being within the predetermined range of values, such that vessel disconnection from the physical floating offshore unit can be performed based on the predicted pretension.

[00013]Generating the model comprising the digital representation of the physical floating offshore unit may comprise creating one or more base designs for the model and training each base design of the model to represent a physical floating offshore unit based on input synthesised training data and/or historical data, wherein the model is trained to generate a representation of the physical floating offshore unit based on initial data before any operations data, marine execution data or environmental data is obtained and to update the representation based on input as-built and/or as-installed data.

[00014]Obtaining marine execution data may comprise obtaining data about the physical floating offshore unit once it has been towed to or once it has been arranged at a desired geographical location for the physical floating offshore unit to be moored.

[00015]The operations data may comprise one or more of: as-installed anchor position(s), as built length of the mooring line, one or more physical properties of the mooring line(s), one or more properties of mooring line segments, the presence or absence of a power cable, ballast data, draft data, and present or predicted/target position data.

[00016]The physical floating offshore unit may comprise a floating wind turbine and wherein the operations data comprises one or more of: blade status, blade number, nacelle data and parked positions of the blades and/or nacelle.

[00017]Marine execution data may comprise one or more of: vessel geographical position, vessel motion, winch tension and winch line and winch/installation line length, physical floating offshore unit geographical position, and physical floating offshore unit motion.

[00018]Environmental data may comprise one or more of: wave height, wave direction, wind direction, wave period, current velocity and wind velocity and wherein the one or more model calibration variables based on the environmental data comprise one or more of: a wind coefficient, a wave coefficient and a current coefficient.

[00019]Obtaining marine execution data may comprise obtaining data from a motion reference unit – MRU - sensor that is configured to measure motion to six degrees of freedom, wherein the MRU is arranged on board the physical floating offshore unit, on board the vessel, or wherein a there is an MRU arranged on each of the physical floating offshore unit and the vessel such that motion of each of the physical floating offshore unit and vessel can be sensed.

[00020]Obtaining environmental data may comprise using a wave radar arranged on board the vessel to measure wave data and/or using a wind sensor arranged on board the vessel to measure wind data.

[00021]The method may further comprise performing a tension measurement for at least one of the physical mooring lines using a tension measuring device; and comparing results of the tension measurement with the predicted tension to verify the predicted tension.

[00022]A second aspect of the present disclosure comprises a computer program product embodied on a non-transitory computer readable medium comprising computer code that, when executed by a processor, causes the processor to perform the method of the first aspect as set out above.

[00023]A third aspect of the present disclosure comprises a system for achieving a target tension in one or more mooring lines of a physical floating offshore unit, the system comprising: a computing device comprising a processor and a memory, configured to perform the method of the first aspect, wherein the memory is configured to store instructions for running the model and wherein the processor is configured to run the model; a tension sensor and a line length sensor at a vessel configured to install the physical floating offshore unit, wherein the tension sensor is configured to measure a tension in the installation line, wherein the installation line is routed through a tensioning device at the vessel and connected to a mooring line of the physical floating offshore unit such that the vessel can tension up the mooring line and install the physical floating offshore unit, wherein the installation line is connected to the winch on board the vessel and wherein the line length sensor is arranged on the winch, configured to measure a length of the mooring line being pulled in or out of the winch.

[00024]The system may further comprise a first communication module, configured to provide an indication of the predicted pretension comprising sending a signal indicating the predicted pretension if the processor determines that the predicted pretension is within the predetermined range of values; a second communication module, arranged at the vessel, configured to receive the signal from the first communication module; an output module, arranged at the vessel, configured to indicate that the signal from the first communication module has been received.

[00025]The system may further comprise a line length sensor mounted on a winch of the vessel, configured to measure a length of the mooring line being pulled in or out of the winch, wherein the first communications module is configured to obtain line length data from the line length sensor and wherein the processor is configured to, by the model, use the line length data to select a base design for the model.

[00026]The system may further comprise at least one of: a vessel-mounted wave radar, configured to measure wave data and current; a floating weather buoy configured to measure wave and current data a vessel-mounted wind sensor, configured to measure wind data; a vessel-mounted MRU, configured to measure roll, pitch, yaw, heave, surge and sway; a physical floating offshore unit-mounted MRU, configured to measure roll, pitch, yaw, heave, surge and sway, wherein the first communications module is configured to obtain data from the or each of the vessel-mounted wave radar, the vessel-mounted wind sensor, the vesselmounted MRU and the physical floating offshore unit-mounted MRU to provide to the processor.

[00027]The system may further comprise the physical floating offshore unit comprising one or more mooring lines; and the vessel.

[00028]The physical floating offshore unit may comprise a floating wind offshore unit comprising a nacelle and one or more blades configured to be turned by the wind, wherein the system further comprises at least one of a blade position sensor and a nacelle position sensor.

[00029]The system may further comprise a tension sensor associated with one of the mooring lines of the physical floating offshore unit, wherein the first communications module is configured to obtain tension data from the tension sensor, wherein the processor is configured to include the tension data in the calculation of the predicted pretension.

BRIEF DESCRIPTION OF THE DRAWINGS

[00030]The foregoing will be apparent from the following more particular description of the example embodiments, as illustrated in the accompanying drawings in which like reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the example embodiments.

[00031]Figure 1 shows a physical floating offshore unit installed in the sea, indicating sea level and the subsea environment;

[00032]Figure 2a shows an example physical floating offshore unit installed in the sea, alongside an example vessel;

[00033]Figure 2b shows another example physical floating offshore unit installed in the sea, alongside an example vessel, having a different installation line and tensioner arrangement from Figure 2a;

[00034]Figure 2c shows another example physical floating offshore unit installed in the sea, alongside an example vessel, having a different installation line and tensioner arrangement from Figure 2a and Figure 2b;

[00035]Figure 3a shows example steps of the present method;

[00036]Figures 3b to 3d show example stages of the present method;

[00037]Figure 4 shows example machine learning model training using synthetic data;

[00038]Figure 5 shows an example table in which values for different categories of variables can be entered once the model has been created, to adjust parameters of the model;

[00039]Figure 6a shows an example graphical representation of an offshore unit, a vessel and mooring lines in the form of a digital representation, created with the model, representing an example of Model One;

[00040]Figure 6b shows an example graphical representation of an offshore unit and mooring lines in the form of a digital representation, created with the model, representing an example of Model Two;

[00041]Figure 7 shows an example table in which values for different categories of variables can be entered once the model has been created, to adjust parameters of the model at a later stage than Figure 5;

[00042]Figure 8 shows an updated example digital representation representing an example of Model One;

[00043]Figures 9 and 10 show example tables in which values for different categories of variables can be entered once the model has been created, to adjust parameters of the model at a later stage than Figures 5 and 7; and

[00044]Figure 11 shows a block diagram representing hardware elements of the present system.

DETAILED DESCRIPTION

[00045]Aspects of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings. The apparatus and method disclosed herein can, however, be realized in many different forms and should not be construed as being limited to the aspects set forth herein. Like numbers in the drawings refer to like elements throughout.

[00046]The terminology used herein is for the purpose of describing particular aspects of the disclosure only and is not intended to limit the invention. It should be emphasized that the term “comprises/comprising” when used in this specification is taken to specify the presence of stated features, integers, steps, or components, but does not preclude the presence or addition of one or more other features, integers, steps, components, or groups thereof. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[00047]Embodiments of the present disclosure will be described and exemplified more fully hereinafter with reference to the accompanying drawings. The solutions disclosed herein can, however, be realized in many different forms and should not be construed as being limited to the examples set forth herein.

[00048] It will be appreciated that when the present disclosure is described in terms of a method, it may also be embodied in one or more processors and one or more memories coupled to the one or more processors, wherein the one or more memories store one or more programs that perform the steps, services and functions disclosed herein when executed by the one or more processors.

[00049] In the following description of exemplary embodiments, the same reference numerals denote the same or similar components.

[00050]The target pretension concept is planned for use during hook-up operation of a floating offshore unit. This is to ensure that the final pretension level in the mooring lines is within required limitations set by the operator. If the mooring system is designed with fibre lines such as polyester or similar type of ropes, construction stretch must be removed from the system during the hook-up operation before the pretension target is reached.

[00051]Adjusting the pay-out of the top segment of the mooring lines is most likely required due to the phenomenon of construction stretches in the fibre rope. The fibre rope elongates itself over the course of time due to being subject to tension over a prolonged period. It is deemed that this phenomenon is especially pronounced for polyester ropes. To reduce the need of re-tension of the system during operational lifetime, it is required to pull in one or the mooring lines (or the mooring line) through one or more tensioners to reach a tension up to typically about 40% maximum of minimum braking load (MBL) of the mooring line and subsequently it will be most like required to pull out mooring line to reach the final pretension within target. The target tensioning concept will use the tensioning versus length measurement on vessel winch sensors and estimated permanent elongation of the polyester rope during removal of the construction stretch as basis for the advice on how much mooring line length is required to be pulled in or out of the tensioner during installation to reach final pretension in the mooring lines. The permanent elongation of polyester lines after construction stretch is uncertain. This pre-stretch operation is performed ahead of the target tensioning operation. The disclosed target pretension concept may also be used for non-polyester/fibre type lines/ropes, but it is of particular use where stretch is a consideration.

[00052] Figure 1 shows a system 100 comprising a moored floating offshore unit 102. In the depicted example, the offshore unit 102 (referred to as “the offshore unit” 102 for brevity but meaning the floating offshore unit 102) comprises a wind turbine 106, comprising blades 110 and a nacelle 108, supported on a tower 112. This is merely illustrative and any suitable offshore unit 102 may be installed and digitally represented according to the present disclosure.

[00053]The offshore unit 102 comprises mooring lines 104; in the depicted example, three mooring lines 104 are shown, but any number of mooring lines 104 (one, two, or more) may be suitable to moor the offshore unit 102. There may be a symmetrical mooring pattern (i.e. any even number of mooring lines 104, equally spread on the offshore unit 102) or not (e.g. a single mooring line/single anchor arrangement). Each mooring line 104 is connected to the offshore unit 102 at one end of the mooring line 104, with the other end extending into the water (in this example, the sea, although the offshore unit 102 may be installed in a lake or other body of water). The mooring lines 104 may comprise anchors or may be tethered to an underwater support offshore unit, otherwise tethered to the sea floor (in sufficiently shallow waters) or otherwise anchored to maintain the position of the offshore unit 102. The mooring lines 104 may comprise chains, wire or wire segments or polyester or polyester segments depending on field and project specific parameters. The polyester segment could also be nylon or other fibre rope types depending on the mooring system design. The nature of the anchoring/tethering and the number and material of the mooring line(s) 104 as well as other mooring line properties may provide useful input data for the present model. An aim of the present disclosure is to predict the pretension in one or more mooring lines, representing stiffness properties of the mooring system. A target pretension for desired mooring of the offshore unit may be known (from the designing process) and aimed for, such that when the predicted pretension is sufficiently close to the target pretension (i.e. within a predetermined range of tensions) then it is allowable for installation of the offshore unit in the water to be completed.

[00054]There are uncertainties in properties of the mooring line(s), such as stiffness, and for example where the mooring line(s) are polyester there is uncertainty in the length of polyester mooring lines after construction stretch, stretching of polyester lines. This could also be applicable for other types of fibre ropes such as nylon type. In the present disclosure, the model is created based on a variety of stiffnesses, lengths and other mooring line parameters such that uncertainties can be accounted for when estimating the pretension in the mooring line(s).

[00055] In the present solution, there are no winches on offshore units, but instead this target tensioning concept uses one or more sensors on the offshore unit 102 (motion and position) together with sensors on the installation vessel winch to predict pretension of the mooring line(s).

[00056] In Figure 1, the offshore unit 102 comprises three legs 114 at which the mooring lines 104 are connected, and connectors 116 connected the legs 114 and the tower 112. This is only one example of an offshore unit 102 configured to float on water, here with part of the offshore unit 102 above the surface of the water and part of the offshore unit 102 below the surface of the water (labelled as “sea level” and “subsea” although the physical floating offshore unit 102 may be configured to be installed in any suitable body of water). Properties of the offshore unit 102 such as number of legs 114 and properties of connectors 116 may provide useful input data for the present model. The offshore unit 102 may be configured to float on the water while minimising/damping the impact of waves and other disturbances on the turbine 106 (or whatever structure or device for which the offshore unit 102 is providing a floating support).

[00057]To reach its moored location, the offshore unit 102 is towed by a vessel 202. During hook-up and installation of the offshore unit, once the tension in the mooring lines 104 is an acceptable tension for the offshore unit 102 to stay in its position, with some acceptable ability to move while staying at its location such as the ability to move in reaction to waves, then the vessel can be disconnected from the offshore unit 102. As well as using one or more sensors of the offshore unit 102 to predict the pretension in the mooring line(s) 104, one or more vessel sensors and a winch at the vessel 102 are used to measure tension and pulled length in/out. Together with simulation data models and machine learning the sensor data is analyzed to ensure that the final tension in mooring line(s) after the vessel 202 is disconnected (pretension) is within target values from the mooring design analysis – i.e. a predetermined range of tensions whereby it is acceptable to disconnect the vessel 202 from the offshore unit 102.

[00058] Figures 2a, 2b and 2c show a vessel 202 coupled to the offshore unit 102 by an installation line 204. The installation line 204 may be connected to the vessel 202 on the vessel side at a winch 208. The installation line 204 may be connected to the offshore unit 102 on the floater side (i.e. the offshore unit 102 side of the line 204, where a “floater” herein means an offshore unit 102) at a tensioner 206, such as a vessel tensioner (mounted on the offshore unit), an in-line tensioner (on the line) or a seabed tensioner (on the line at the sea bed). The installation line 204 may be routed through the tensioner. In Figure 2a, the tensioner 206 is on the offshore unit 102 and out of the water so is a vessel tensioner 206. In Figure 2b, an in-line tensioner 206 is shown. Figure 2c shows a seabed tensioner 206. The present method 300 may be used to estimate mooring line tension whichever type of tensioner 206 is used.

[00059]Figures 2a, 2b and 2c are each example vessel 202 and offshore unit 102 configurations. As shown, the vessel 202 and offshore unit 102 may be suitably connected by the installation line 204 either on-board the offshore unit (Figure 2a), at a position on a mooring line 204 (Figure 2b) or even at the seabed/sea floor/bottom of a lake or at another plateau under the water, depending on where the offshore unit 102 is moored (Figure 2c). In each of Figures 2a, 2b and 2c, different configurations of the offshore unit 102 having legs 114 connected differently are shown, with different sized towers 112. In any of the examples, the offshore unit 102 may be configured to provide a floater for a turbine 106 or another offshore setup such as a rig or the like – the depicted turbines 106 are for example only.

[00060]To install the offshore unit 102 in the water, the vessel 202 tows the offshore unit 102 to the desired position using the installation line 204. The installation line 204 may be prerigged through the tensioner 206 during tow. The installation line 204 is connected to at least one of the mooring lines 104 of the offshore unit 102 during pull-in/tensioning. Adjustments may be made when the desired position is reached, such that the mooring lines 104 are arranged as desired to keep the offshore unit 102 at the desired position in the water. Adjustments are made by changing the pull in/out length of the mooring line 104 connected to the installation line 204 to reach the final target pretension. The vessel 202 is configured to create bollard pull, or using reaction anchor, with the winch 208 that causes the mooring line 104 connected to the installation line 204 to be pulled in. By adjusting the mooring line 104 that is connected to the installation line 204, other mooring lines 104 of the offshore unit 102 will experience a change in reaction load. The vessel 202 comprises a sensor 118 configured to measure tension (i.e., a tension sensor) for example using a shear pin which may be arranged at the winch. Although the present disclosure relates to a method of estimating pretension without the need to use a tension sensor to measure the pretension in a mooring line 104, the sensor 118 is used to provide a measured tension to be compared with pull in length on the winch. This comparison of measured tension versus winch pull in length allows the model to determine which of a set of representations of the installation to use in the prediction of the pretension on the mooring line(s). It is not known to an exact amount how much line is needed to pull in before tensioning starts during installation. This is particularly relevant when using fibre lines (polyester, nylon or similar types) that are pre stretched during or before hook-up and installation. For example, a pull in of 10 Metres (m) may be expected to give 400 Kilonewtons (kN) tension in line, but the sensor 118 shows 500kN , then one must find the right machine learning model with input values (operation and execution data as described below) to use as basis for the pretension prediction.

[00061]The vessel 202 may be a typical spot-market AHT-vessel (anchor handling tug vessel) or AHTS-vessel (anchor handling tug supply vessel), for example, or any other suitable vessel 202 that can be steered to the desired position of the offshore unit 102. The vessel 202 may be manned or unmanned (i.e. remotely controlled). Such properties of the vessel 202 (and any other physical properties that are known, for example, from manufacturer’s information or from experience using the vessel 202) may provide useful input data for the present model such that vessel behaviour can be modelled.

[00062]A vessel tensioner (VT) 206 as shown in Figure 2a is a combined fairlead, chain stopper (mooring line stopper) and remote tensioning device. The VT 206 comprises a sheave and as the line 204 runs over the sheave, the reaction load on the respective leg 114 where the VT 206 is mounted will increase compared with the applied bollard pull and winch tension from the vessel 202. The mooring lines 104 elsewhere on the offshore unit 102, for example on other legs 114, will experience the increased reaction load.

[00063]The offshore unit 102 may comprise a tension sensor for use in validating the estimated pretension, for example in early uses of the model during the installation campaign, to verify that the predicted pretension and measured pretension are sufficiently similar for the estimation to be considered accurate.

[00064] Multiple offshore units 102 may form a cluster of offshore units 102, and one or more of the cluster may include a tension sensor, whereas the estimation method disclosed herein may be applied to any of the offshore units 102 in the cluster (tension sensor) and a tension measurement may be used to calibrate and/or verify the estimations.

[00065]Figures 1, 2a, 2b and 2c show example locations of sensors 118 on the offshore unit 102 and the tensioners 206. One or more sensors 118 configured to measure environmental factors such as wave properties and wind properties, sensors 118 configured to measure physical properties of the offshore unit 102 such as properties of the blades 110 where the load on the offshore unit 102 is a wind turbine 106, sensors 118 at the vessel 202 configured to measure vessel variables such as motion in the water and other sensors 118 may be arranged throughout the system 100 comprising the offshore unit 102 and vessel 202.

[00066]The tension in the mooring lines 104 should be such that the offshore unit 102 is allowed to react to waves in the water, high wind speeds and other changes, while maintaining its position within predefined targets, geographically, in the water. During hook-up and installation of the offshore unit, once the tension in the mooring lines 104 (which may be a mean tension where there is more than one line 104) is within a predetermined range of tensions, the vessel 202 can disconnect from the offshore unit 102 and leave the offshore unit 102 behind in the water. The method of the present disclosure includes correction of environmental forces and changes to a model compared with the final installed offshore unit 102, where the pretension is a tension value at zero weather.

[00067] Measuring the tension in the mooring lines 104 using a tension sensor, such as a load monitoring unit comprising a load cell, at each of the mooring lines 104 is one option for calculating the mean tension across all of the mooring lines 104 of the offshore unit 102. The tension sensor may be arranged on a mooring line 104 or may be arranged on onboard offshore unit 102. However, the present disclosure offers a solution that removes the need for a tension sensor on the offshore unit 102 in order to predict the pretension in the mooring lines(s). The present disclosure offers a computer-implemented method 300 in which mooring line pretension is estimated/predicted. A tension sensor at the vessel 202 is used instead, to measure the winch line/installation line 204 tension and a sensor 118 at the vessel 202 is also used to measure the line length pull in/out. Tension sensing at the winch may comprise measuring the hydraulic pressure during pull in or a load measuring pin or a load bearing pin in a winch sheave of the winch. From the measured winch line/installation line tension and the line length pull in/out, the present model is configured to determine an appropriate digital representation of the physical offshore unit 102 (and vessel 202) for modelling their respective behaviours and from this estimating the pretension in the mooring line(s) 104. The present method 300 comprises generating a digital representation of the offshore unit 102, which may be a digital twin. A digital twin is an up-to-date representation of a physical offshore unit and/or vessel and/or mooring line(s) including an installation line linking the offshore unit and vessel (in this case) that includes the condition of the physical elements and relevant historical data. The offshore unit 102 is herein referred to as the “physical” floating offshore unit 102 and the digital representation can be considered to be the “virtual” floating offshore unit. The digital representation is used to model physical behaviours and properties of the physical/real offshore unit 102 in a digital space, based on input data about the operations being performed, the marine execution (i.e. data about the vessel, the offshore unit in the water and the like, such as position data, bollard pull or reaction anchor data) and environmental data (the environment in which the offshore unit 102 is placed, such as wave data, wind data and the like). Based on the model, the pretension in the mooring line(s) 104 can be estimated and this estimation can guide release of the vessel 202 from the offshore unit 102.

[00068]The digital representation may comprise a graphical representation of the offshore unit 102 and/or the vessel 202 and/or the or each mooring line 104 such that a user can view how different input data about the offshore unit 102, vessel 202, mooring line(s) 104 and the environment (waves, wind and the like) affect the digital representation and so are predicted to affect the real offshore unit 102, mooring line(s) 104 and vessel 202. A computing device comprising a display may be configured to display the graphical representation and may include an input/output (I/O) module enabling a user to interact with the model (e.g. select between data inputs or enter their own data for input) such as via a keyboard or touchscreen.

[00069]The digital representation is based on a base design, depicting the offshore unit 102 and mooring line(s) 104 and, if the vessel 202 is to be included in the digital representation, the vessel 202. The base design is selected by the model from a set of base designs based on the measured winch line tension and line length pull in/out, guiding which base design of the available base designs is most suitable to represent the offshore unit 102, mooring line(s) 104 and, where modelled, the vessel 202. The base designs may be stored on the computing device that is configured to display the digital representation(s), for example in local storage, or the base designs may be stored at a remote server and retrievable by the computing device.

[00070]As input data from the offshore unit 102, vessel 202, mooring lines 104 or other elements of the system becomes available, it is used to update the model from the base design. If no input data is received or is available for a particular property of any of the elements of the real (non-digital) system such as the offshore unit 102, the model is based on the base design only until it is updateable.

[00071]Each base design in the set of base designs includes a simulation of the physical properties and/or behaviours of at least an offshore unit and its associated mooring line(s), and may also include a simulation of an installation vessel. When creating the digital representations of these physical objects, the model is configured to draw on the most suitable base design as a starting point for the representation(s). As set out below, the most suitable base design is selected based on the measured tension and line pull in/out from the real-life (as-built) offshore unit 102 and installation vessel 202 and then field data is input into the model to update the graphical representation(s) to give the offshore unit 102, the mooring line(s) 104 and the vessel 202 a more accurate set of physical properties and behaviours than the base design.

[00072] In order for the vessel 202 to detach from the offshore unit 102, the pretension in the mooring line(s) 104 needs to fall within a predetermined range of tensions. The present method 300 allows the tension to be estimated and corrected for environmental forces and changes to the model compared with the offshore unit 102 as installed. The tension as estimated may be a mean tension; influence of dynamic tension due to motion is evaluated and tension is corrected/adjusted to the mean tension. It can be predicted how the line length pull in affects the pretension using the present model.

[00073] Figure 3a shows steps of the method 300. The method steps are represented as blocks of a flowchart; any suitable software or hardware may be configured to put the method steps into action as will be understood by the skilled person. Examples are given herein. The method 300 comprises measuring the tension in the installation line 204 which may be performed at the vessel side of the installation line 204 to avoid requiring measuring equipment (a suitable sensor) from being arranged at the offshore unit 102. The method 300 comprises measuring the line length pull in/out 304, which may also be on the vessel side for the same reason. This may be done at a winch of the vessel 202.

[00074]From these two measurements, the most appropriate base design is selected 306 to represent the offshore unit 102, mooring line(s) 104 and vessel 202 digitally as a graphical representation. The set of base designs includes base designs having different installation line tensions and different line length pull/in needs. Of the set of base designs, one will most closely resemble to real-life installation line tension and line length pull in/out, providing a good starting point for the digital representations to be generated and updated.

[00075]At step 308 of the method, using the selected base design the physical properties and/or behaviours of the offshore unit 102, mooring line(s) 104 and vessel 202 are modelled based on initial data. Initial data may be historical or estimated properties or behaviours of the offshore unit, mooring line(s) or vessel. Initial data is to be replaced with measured data or otherwise known data, if and when it becomes available to make the graphical representations more accurate to the as-built and as-installed offshore unit 102, its mooring line(s) 104 and the installation vessel 202.

[00076]Step 310 comprises updating the model based on as-installed and as-built data 310 as described below, particularly in relation to Figure 3c.

[00077]The method 300 comprises predicting the pretension in the mooring line(s) 104 using the model. As the digital representations of the offshore unit 102, the mooring line(s) 104 and the vessel 202 take shape and are updated and calibrated as described herein, the model is trained to estimate/predict the pretension in the mooring line(s) 104 based on more “knowns” (fewer unknowns or mere estimations) as input into the model.

[00078]Figure 3b shows method steps comprising obtaining initial data/training data 314a and generating the base designs 314b. The method 300 comprises generating a digital representation of the offshore unit 102, and a digital representation of the vessel 202. The digital representations start out based on a selected base design, of a set of base designs, which is the most suitable base design of the set chosen following measurement of the tension in the installation line and the line length pull in/out. The model comprises two parts, one mapping to the other – Model One is a digital representation of the vessel and the mooring lines and the offshore unit, representing their behaviour during hook-up and installation based on input data from hook-up and installation, and Model Two is a digital representation of the offshore unit and its mooring lines wherein properties of the mooring lines are predicted based on Model One. Model Two is a digital representation of the offshore unit having disconnected from the vessel and with zero weather. It is from Model Two that the pretension in the mooring line(s) is estimated. From the measurement of line length pull in versus tension in Model One, the model is configured to determine how much line length is needed to be pulled in to get the pretension (without weather) in corresponding Model Two. Modelling the behaviour of the offshore unit 102, mooring line(s) 104 and vessel 202 in Model One with fewer unknowns allows improved modelling of how different line length pull in/out values affect the pretension in Model Two by the model.

[00079]Model One and Model Two are created in a suitable software simulation suite as the skilled person will appreciate. The model is trained with different parameters to generate a set of pairs of Model One and Model Two, where a pair comprises a Model One representation and an accompanying Model Two representation based on the same parameter values. Once a tension sensor 118 on the vessel 202 provides a tension measurement for the winch line/installation line 204 and a pull in/out line length is known from an appropriate sensor in the field (such as a sensor on the winch on the vessel 202), an appropriate Model One and Model Two pair can be chosen to represent the physical offshore unit 102 and vessel 202 in their real installation scenario. From there, other variables can be updated based on input data from the field or otherwise sourced as described herein and Model One can be updated to represent the installation happening in the real world. Updates to Model One are mapped (by the model) to Model Two and from this an estimated pretension in the mooring line(s) can be predicted. A static simulation of Model Two without environmental forces is used to estimate the pretension.

[00080]Each digital representation is part of a machine learning (ML) model. The digital representations may be built based on a training data set, which may include historical data from similar offshore units and/or similar installation operations, which may have taken place in similar conditions (e.g. the same body of water, the same time of year, the same weather and the like). The method 300 comprises creating base designs 314b based on initial/training data 314a. Training may further comprises training the model to select the most appropriate base design for the given measured installation line tension and line length pull in/out. Training may further comprise training the model to generate the graphical representations and update the digital offshore unit, mooring line(s) and vessel based on input data about their physical equivalents. Training 316 is shown in Figure 3b. The training data may be synthesised data, which may be based on historical data or predictions about properties of the offshore unit 102 or the environmental conditions for example. As shown in Figure 3b, initial data is provided 314a for generating the model. The model comprises a set of pairs of Model One and Model Two representations based on different parameters of installation such as different winch line tensions and line lengths. The method 300 comprises the model selecting a suitable part of the model (Model One and Model Two pair) for modelling the installation of the physical offshore unit 102 using the vessel 202 based on the measured winch line tension and the measured line length pull in/out.

[00081]Data originally entered into the model is updated based on as-built and/or as-installed data from the offshore unit 102, which may be obtained during project execution, fabrication, marine operations and even installation operations. As data from the real offshore unit 102 and the real operations is obtained, variables of the model can be fixed reducing the model unknowns, which is detailed below. Data is obtained from sensors 118 arranged suitably throughout the system 100 to collect relevant data. For example, data about the offshore unit 102, for example motion data, may be collected from one or more sensors 118 on board the offshore unit 102. Data about environmental factors such as wind or waves may be retrieved from one or more sensors 118 arranged at the offshore unit 102, or underwater for example arranged at a subsea tensioner 106 or on a mooring line 104, or on the vessel 202 for example. Vessel-specific data may be retrieved from one or more sensors 118 at the vessel 202. When it comes to the installation line 204 or one or more mooring lines 104, for example, a sensor 118 at the winch 208 on the vessel side may be used to calculate changes in length/pull in data about lines on the offshore unit side based on changes in length/pull in data at the winch 208. This way, the need for sensors 118 at the offshore unit 102 can be minimised to address the problem of having to maintain sensors 118 at the offshore unit 102 once it has been moored. By estimating the pretension in the mooring line(s) using the present method 300, the need for tension sensors at the offshore unit 102 is also reduced or removed, addressing the problem of having to maintain sensors 118 at the offshore unit 102 once it has been moored. It is also an aim of the present disclosure to reduce the amount of extra technology or extra weight or extra items taking up space on the offshore unit 102 by estimating, rather than measuring, pretension in the mooring line(s) 104. The estimation uses sensors 118 that are typically arranged on offshore units 102 (for example, a motion sensor) without the need for additional sensors 118 specific to tension measurements. The offshore unit 102 of the present disclosure does not include winches onboard, which is a cost-saving design choice, and so tension is not measured using a sensor at an onboard winch of the offshore unit.

[00082]The model is created “in office” ahead of installation operations in a suitable software simulation suite, meaning that the model may be created prior to installation operations commencing. Installation operations comprise hook-up of the offshore unit 102 to the vessel 202.

[00083]The method 300 comprises generating Model One and Model Two, including controller modes of dynamic positioning system elements (for example, sensors on board the vessel 202 such as wind sensors) and winches onboard the vessel 202. Any number of mooring lines may be used for the offshore unit 102 and any suitably number of mooring lines may be modelled to represent the physical offshore unit’s mooring lines. In one example, at least two virtual mooring lines are modelled. Model One comprises a digital representation configured to represent the physical floating offshore unit 102 virtually, based on input data about the physical floating offshore unit 102. The physical floating offshore unit 102 is not necessarily “floating” when the digital representation is created. The offshore unit 102 is designed to float on water once installed on water, but the physical floating offshore unit 102 may be being assembled or checked at a factory/shipyard or the like, or otherwise on shore, at the time when the digital representation is created; in other words, “floating” is a label meaning “configured to float” in this context.

[00084]The digital representation of Model One is configured to represent both the offshore unit 102 and the vessel 202 interacting with one another, so that Model One can be used to represent properties and behaviours of both the offshore unit 102 and the vessel 202 and such that Model Two can be used to predict/estimate properties and behaviours of the mooring line(s) as a result of the representation in Model One. Pre-generated digital representations of different example vessels 202 that may be generated based on design data about vessels 202 and/or historical data may be insertable into the model such that the Model One can be used to predict how different vessels 202 will behave in installing the offshore unit 102, for example.

[00085] The model is a machine learning (ML) model configured to simulate how the offshore unit 102 behaves in the water, in response to variables such as its own physical properties, properties of the vessel 202, environmental properties (for example wave height and direction) and the like. An aim of the machine learning model is to calculate an estimated pretension in the mooring line(s) 104 of the offshore unit 102, by creating a digital representation of the offshore unit 102 and modelling its physics-based behaviours/responses to changes in input data. The estimated pretension is that in a calm sea/calm water – i.e. with negligible weather effects or waves. By establishing that the tension falls within a predetermined range, the range comprising tensions that are acceptable for the vessel 202 to disconnect from the offshore unit 102, the model can determine when the offshore unit 102 is at a target pretension and installation can be completed. Disconnecting the vessel 202 from the offshore unit 102 involves disconnecting the installation line 204 from a mooring line 104 of the offshore unit 102.

[00086]The model may be configured to receive input data and run the model to update the representation(s) in Model One, representing the vessel, mooring line(s) and offshore unit (as well as the installation line, if properties of the installation line are measured or otherwise established – which may be comprised in “offshore unit data” or “vessel data” along with anchor data or other relevant data of the system, and other elements of the system such as a power cable or anchor or the like). The model may be configured to update Model Two based on updates to Model One, which may be automatic when changes to Model One occur, or the user may be enabled to cause Model Two to be run within the model to refresh Model Two in view of Model One.

[00087]The ML model is trained 316 with multiple parameters (for example position, tension, lengths, weather etc.) to establish a decision base using the model simulating floater (offshore unit) hook-up to mooring lines and installation operations. The model receives floater (offshore unit 102), vessel 202 and mooring line 104 parameters together with field specifics input, for example water depths. These are incorporated into Model One. Data may be obtained from one or more sensors 118 arranged in the field, for example at the offshore unit 102 or the vessel 202. One or more sensors 118 may be arranged elsewhere in the field such as in the water, for example on a mooring line 104 as described above. Data may be obtained for input into the model from a memory 1106 (which may be storage or random-access memory at a computing device 1102 configured to run the model at a processor 1104), for example data retrieved about the offshore unit 102 such as design data provided by a manufacturer for example, from documentation, or historical data stored at the memory 1106. Data may be obtained from paper or electronic documents and provided to the model. Data may be obtained from a third-party data source, for example where weather data is desired for input into the model to represent environmental conditions, weather data may be obtained from a third-party source such as a third-party remote server. Data may be obtained from a remote server associated with the present mooring operations (i.e., not a third-party data source but a remote server linked with the operations, which may be configured to store and provide data for input into the model).

[00088]The model is configured to incorporate input data to update Model One’s representation, such that variables can be fixed based on the real conditions to drive the prediction of the pretension. Before hook-up operations of the offshore unit starts, parameters (system variables) that can be fixed based on known properties are fixed 309. Step 309 would take place between steps 308 and 310 of Figure 3a – once the base design has been chosen, can it be updated based on knowns before any as-built or as-installed data is obtained, for example from documentation about the offshore unit’s properties. Estimated values of system variables which may be a result of training of the model or may be input as an estimated/expected value prior to the values becoming known (for example taken from the memory 1106) are replaced. Once known parameters are fixed (any that can be fixed based on the data available during project execution) the digital representation of Model One is calibrated to replace the initial data (which may be historical or estimated and therefore can be made more applicable to the real-life offshore unit 102 during project execution) and unknowns can be reduced. Model Two may be automatically updated based on updates to Model One, for example the predicted/estimated mooring line pretension in Model Two may be updated once one or more variables of Model One are fixed.

[00089] By changing the value of one or more system variables, the model may be configured to cause the digital representation of Model One to be updated in line with a predicted behaviour of the physical offshore unit 102 and/or vessel 202.

[00090]The model may comprise a model of one or more installation operations, which may comprise a physics-based coupled model of the vessel 202 (or multiple vessels 202 – for example, where different types of vessels 202 could be used and the model is used to test installation operations using different vessels 202). The model may comprise a model of a mooring system, which may comprise the mooring line(s) 104 and may comprise one or more winches 208, tensioners 206 or the like.

[00091]The offshore unit 102 may comprise a power cable where the offshore unit 102 is configured to provide a floating support for a power generation system, such as the wind turbine 106 shown in Figure 1. The model may comprise a physics-based coupled model of the power cable, which may be part of the model of the offshore unit 102.

[00092]Once the model has been created and trained, it may be configured to estimate a pretension for the mooring line(s) 104 as represented in Model Two based on the data available to the model at that stage. This estimate is then updated as the method 300 progresses, improving as variables that the model uses to estimate the pretension become known so the estimated variables are replaced and a known value is fixed.

[00093]The model may be updated based on the detailed engineering of planned operations at step 309, for example. The model may be configured to determine how the offshore unit 102 will respond to operations performed on the offshore unit 102 or the system that the offshore unit 102 is configured to support in water, and/or how the offshore unit 102 will respond to weather conditions or other environmental changes such as changes in wave height or frequency. As shown in Figure 3c, the method 300 may comprise obtaining operations data 318 which may comprise information about planned operations. Once installation operations have been planned, variables such as line length, details of the installation line 204 such as material and length, details about any winches 208 and/or tensioners 206 such as make, model, position on the offshore unit 102 and other relevant variables may be fixed (i.e. any estimated or historical data may be replaced with known values).

[00094]Obtaining data from sensors 118 in the field may comprise requesting data from the one or more sensors 118, for example using a first communication module 1110 of the computing device 1102 that is configured to run the model. The communication module 1110 may comprise a transmitter and receiver or a transceiver configured to send and receive digital signals accordingly. The computing device 1102 may be configured to cause the transmitter/transceiver to send a request for data to the one or more sensors 118, which may be based on any variables that are not yet fixed in the model. For example, the processor 1104 may be configured to determine that wave direction (for example) is currently an unfixed variable in the model based on an initial estimate or based only on training data. The processor 204 may be configured to cause the transmitter to request data from a suitable sensor 118, a wave direction sensor 118, such that wave direction data can be obtained and wave direction is a fixable variable. Any of the variables discussed herein may be fixed in this way, where the transmitter may request sensor data from one or more suitable sensors 118.

[00095]Obtaining data from a remote server or from memory/storage 1106 may follow the same process wherein the processor 1104 may be configured to identify that a variable is currently unfixed (based only on an estimate or historical data or training data) and seek out up-to-date data about the real operations to replace the unfixed value of the variable with upto date- data and fix the value. The transmitter may be configured to request data from the remote server, which may be a third-party server. Third-party server data may comprise weather data, global positioning data or the like, that is not measured using a specific sensor 118 in the field.

[00096]Figure 3c also shows obtaining marine execution data 322 and obtaining environmental data 326. Obtaining data about the as-built and/or as-installed offshore unit 102, mooring line(s) 104 and vessel 202 as well as the environment or other elements such as the anchors or other features of the system may occur concurrently. For example, the model may receive input data pertaining to operations, marine execution and/or the local environment of the offshore unit 102 as and when it is measured or otherwise becomes available. As shown in Figure 3c, model configuration variables are assigned 320, 324, 328, based on the respective types of input data, to update the model to represent the physical objects more accurately. Model configuration variables based on environmental data may be used to offset for weather when estimation the pretension.

[00097]Configuring Model One based on operations data, marine execution data and/or means that Model One represents the situation in real life – the vessel, the offshore unit and the mooring lines are digitally represented based on the real scenario (as built and as installed). From Model One, it can be predicted how the offshore unit and mooring lines will behave in a “no weather” hypothetical case by offsetting the Model One prediction for weather effects, to determine the pretension in the mooring line(s) and present this in the graphical representation of Model Two.

[00098] The method 300 comprises coupling data obtained – any of operations data, marine executions data and environmental data – with the model to update the model based on the input data. Any estimated variables that can be fixed based on measured/obtained data is fixed. The method 300 may comprise processing obtained data to place the data in a format suitable to be input into the model, for example at the processor 1104.

[00099]Predicting a tension 312 comprises calculating, from the fixed variables of Model One, a pretension in one or more mooring lines 104 of Model Two. The tension calculation may account for environmental conditions such as wind and wave and current variables to establish what the tension would be in calm conditions – i.e. the pretension. Predicting/calculating the pretension may comprise comparing the tension with a predetermined range of tensions to determine whether the tension falls within the predetermined range and therefore whether the vessel 202 can be disconnected from the offshore unit 102. The processor 1104 may be configured to perform the prediction/calculation.

[000100] Figure 3d shows that the method 300 comprises providing an indication 330 of the predicted pretension being within the predetermined range of values, such that vessel disconnection from the physical floating offshore unit (through disconnection of the installation line 204 from a mooring line 104 of the offshore unit 102) can be performed based on the predicted pretension. This may comprise sending a digital signal to a computing device on board the vessel 202 indicating that the pretension is within the predetermined range. The vessel side computing device may be configured to indicate that the pretension is within the predetermined range by causing an alarm to be sounded or presenting an indication to a user at the vessel in the form of a text alert or other graphical representation at the on board computing device. The indication may comprise an indication that disconnection from the offshore unit 102 can be instigated based on the predicted pretension. However, it may be down to a professional user at the vessel 202 to interpret the tension indication or the indication that the vessel 202 can be disconnected and proceed with disconnection, rather than blindly following the indication, from a safety standpoint. The tension prediction should be used as a guide when disconnecting the vessel 202.

[000101] Creating the model may take into account the following physical properties: Aero- & Hydrodynamic properties of the system to be supported by the offshore unit 102, for example a FOWT 106, mooring system properties, power cable presence/absence/properties, installation vessels(s) properties, aero- and hydrodynamic properties of the offshore unit 102, winch and current coefficients, and tensioner set up. The aerodynamic properties of a FOWT 106 may include properties of the blades 110 or the tower 112, for example, or historical data. Such variables may be fixable once details of the engineering of planned operations is known.

[000102] The model may comprise a winch plug-in with planned controller modes. The model may be configured to model the digital representation of Model One comprising different numbers of winches, winches of different properties, different winch positions and the like. The winch plug-in may allow the model to estimate how different winches having different properties will affect the offshore unit 102, which may be a useful tool when planning which types of winches to use, or for example where a new winch has been developed. Operations data may comprise winch data and variables within the winch plug-in may be fixable once winch data becomes available. Although it is possible to include one or more winches 208 on the offshore unit 102 and the model may be configured to model winches as above when mounted on the offshore unit 102, in a preferred example the offshore unit 102 does not includes any winches 208 and any winches 208 in the system 100 are arranged at the vessel 202.

[000103] The digital representations of both Model One and Model Two may be updated based on data gathered during assembly of the offshore unit 102 or once the offshore unit 102 has been assembled. Examples of the types of data that may be gathered during assembly and used to update the digital representations are: dimensions of mooring segments and component parts of the offshore unit 102, weights of component parts, materials of component parts, the presence or absence of a power cable, number of winches/tensioners/other connectors, number and nature/type of sensors 118, the type of system that the offshore unit 102 is intended to support (e.g. turbine 106). If the system that the offshore unit 102 is intended to support is assembled with the offshore unit 102, then the data may comprise data relating to the system, for example: dimensions of component parts of the system (e.g. turbine 106), weights of component parts and mooring segments, characteristics and lengths of mooring segments and materials of component parts and the like.

[000104] The model may be updated based on any of the physical properties above once they become known. The physical properties may fall within the initial data 301 known prior to creating the model or may be contextual to a specific offshore unit 102 being created and may be provided to the model as data for the model to be updated based upon, at step 304 of the method 300 after the model has been created and trained.

[000105] Such data used to create or update the digital representations may or may not change once the offshore unit 102 is undergoing installation operations. For example, weights and materials and the like will not change between fabrication and installation. At the stage of obtaining operations data 304, it may be confirmed that an estimated or historical variable value is sufficiently accurate or is accurate and does not need to be updated, so the value may become fixed.

[000106] The model may comprise a digital representation of a physical vessel 202 that is going to be used in installation operations, in Model One. Elements on-board the vessel 202 may form a dynamic positioning system (DP system) and the properties of the DP system may be included in the model, to allow the model to model how the offshore unit 102 and vessel 202 will interact, for example during installation operations. The model may comprise a dynamic positioning (DP) plug-in with planned controller modes to model physical reactions/behaviours of the real vessel 202 based on different variable values. The model may be configured to swap in different vessels 202 that could be used for installation operations to allow a user to decide on a good choice of vessel 202 for a particular operation or otherwise to predict vessel 202 performance and guide vessel selection, and so the model may not comprise a digital representation based on a single real vessel 202 but may otherwise comprise one or more vessel models that represent/approximate real vessels 202 insofar as their physical properties and physics-based behaviours. For example, the model may be enabled to change the position, number, or type of sensors arranged at a vessel within the model.

[000107] In order to create the model including the digital representations, simulations are performed for all possible combinations of the following variables (within a possible range of uncertainties) in order to create a model that is able to estimate mooring line tension based on vessel variables and offshore unit variables during installation operations: system configuration variables (anchor locations, mooring line lengths, stiffness properties etc.), model calibration variables (wind, current, wave coefficients etc.), environmental forces (wind, waves, current), winch tension, vessel and offshore unit positions. This is not an exhaustive list of possible variables that may contribute to the creation of the model. It will be understood by a person skilled in the art that other variables relating to the physics of how the offshore unit 102 and vessel 202 interact, in particular with relation to the mooring line(s) 104, installation line 204, power cable, winch(es) and the like may be simulated in developing the model.

[000108] During model training, the simulations may be repeated so as to cover an expected range of uncertainties in each variable. The range of uncertainties may be based on historical data or on test data taken from similar offshore units, for example.

[000109] The simulations used to create and train the model may comprise simulating different weather conditions and how the offshore unit 102 and/or vessel 202 may respond to the different weather conditions. This may be done by modelling the physics of the offshore unit 102 and/or vessel 202 based on wind, wave, current data and the like.

[000110] The simulations may comprise different positions of the vessel with respect to the offshore unit and modelling their physics-based behaviours.

[000111] The simulations may comprise different configurations of other variables such as mooring line length or position on the offshore unit 102, for example.

[000112] From the simulations, a matrix of offshore unit 102 and/or vessel 202 behaviours/properties/responses to changes made to other variables may be created to determine how the model represents the offshore unit 102 (including the mooring lines 104) and/or the vessel 202 in the digital representation in Model One. The model may be configured to perform tension calculations based on the different variables and output estimated tensions, which may differ depending on the values of the variables.

[000113] Figure 4 shows an example method 400 of training the model. Training parameters of the model may include wind, wave and vessel heading data. The data may be historical data, may be test data obtained specifically for training the model, or may be synthetic data based on a hypothetical offshore unit/vessel or one or more environmental variables. These parameters may be input to a suitable physics-based model such as SIMO (Simulation of Marine Operations), or Orcaflex, which are computer programs for simulation of motions, marine operations and station-keeping behaviour of complex systems of floating vessels and suspended loads.

[000114] The SIMO/Orcaflex/other suitable model output may provide target output information, which may be used as a training input for the model, which may comprise expected vessel response, for example.

[000115] The digital representation of Model One is updated such that any data known from project execution is used to fix one or more variables of the model and reduce the unknowns in the ML model. The digital representation is calibrated to the knowns found at that stage of the method 300.

[000116] Marine execution may include preparing and installing anchors and pre-lay mooring lines for the offshore unit 102, for example. Data from the marine execution may be used to update the model and fix variables that become known during marine operations, for example data about the anchor(s) such as their positions, number of anchors, water depth and the like. Properties of mooring lines 104 may become known during marine operations, for example stiffness of lines/ropes, line length and the like during installation of the offshore unit 102 in the water as set out below. Marine execution data may be obtained when the vessel 202 and offshore unit 102 are launched in the water, based on which the model may be updated to calibrate the model to the offshore unit 102 undergoing installation operations – allowing any relevant parameters that can be fixed, to be fixed.

[000117] Data obtained may be stored and used to train the model for modelling future offshore unit installation behaviours or as training data for a future model created using the method 300. Once the digital representations have been created for a particular offshore unit 102, they may be used as a representation of other offshore units 102 having the same properties as the offshore unit 102 based on which the digital representation was created, for example for a cluster of offshore units 102 for which the calibrations performed as part of the method 300 are relevant. In this way, the digital representations may initially require input data about a particular offshore unit 102 in order to represent that offshore unit 102 and be trained to model the offshore unit 102 successfully but may then be used to predict/estimate properties and behaviours of another offshore unit 102 without any data specific to that other offshore unit 102.

[000118] Figure 5 shows an example table in which values for different categories of variables can be entered once the model has been created, to adjust parameters of the model. The model may be run on a computing device 1102 having an I/O module 1108 enabling a user to enter values of variables to be provided to the model. During marine operations values may be obtained from sources such as sensors 118, memory 1106, or a remote server that may be used to populate the variable values to be input into the model.

[000119] As shown in the table of Figure 5, variables may fall under the categories of: system configuration, model calibration and operational variables. As shown, operational variables that require an input are environmental data and vessel offset data, which is part of marine execution data according to the present disclosure. In Figure 5, the variables are yet to be populated or fixed.

[000120] Figure 6a shows an example graphical representation of Model One, of an offshore unit, a vessel and mooring lines in the form of a digital representation, created with the model. This is an example of what a user may see on a display 1108a of the computing device 1102 running the model. In this example, the digital representation comprises a FOWT digital representation and a vessel digital representation. The digital representation comprises a winch on the vessel connected to a modelled installation line connected to the digital representation of the offshore unit. In the physical setup, connecting the physical offshore unit 102 to the vessel 202, the installation line 204, which may also be referred to as a winch line/reaction line/ pulling line or towing line, is connected to one of the mooring lines 104, routed through a winch on board vessel and connected at the offshore unit 102, for example through a vessel tensioner 206. This is to tension up the mooring system without the need of having winches onboard the offshore unit 102. The installation line 204 is pulled in by the winch until the mooring line 104 is pulled a desired length through the tensioner 206 (depending on required pretension).

[000121] Figure 6b shows an example graphical representation of Model One, of an offshore unit and mooring lines in the form of a digital representation, created with the model. Model Two is updated to represent the offshore unit 102 and mooring line(s) 104 when the vessel 202 has been disconnected, and it is from the modelled physical properties and/or behaviours of the offshore unit and mooring line(s) in Model Two that the pretension is estimated. It is of interest to estimate the pretension at the time when the vessel 202 is no longer connected, to determine if it is acceptable (within the range of pretension values) to disconnect the vessel 202. From the predicted pretension, disconnection can be initialised (for example, sending a signal to the vessel 202 indicated that the pretension is predicted to be within a range that is allowable for disconnection).

[000122] The method 300 comprises obtaining operations data 318 once the physical floating offshore unit 102 is in water and assigning 320 system configuration variables based on the operations data. Operations data may comprise one or more of: as-installed anchor position(s), length of the mooring line, one or more physical properties of the mooring line, one or more properties of mooring line segments, the presence or absence of a power cable, ballast data, draft data, and position data. The operations data may comprise data about the type of winch provided, location of the winch, a tensioner, or a tension sensor, and whether any of the mooring lines 104 include any buoyancy to prevent them from clashing with subsea elements such as one another or the power cable, for example. This is not an exhaustive list of operations data and other suitable operations data may be provided to the model. Operations data may be obtained from one or more sensors arranged on the anchor(s), the mooring lines 104, or the offshore unit 102. The operations data may comprise third party data obtained from a data source such as cloud storage or a suitable server. For example, a worker who assembles the offshore unit 102 may provide data to a data storage such as cloud storage or another suitable server while assembling the offshore unit 102/once the offshore unit 102 has been assembled, based on features of the offshore unit 102 as fabricated that are, now at this stage, known. Operations data regarding physical properties of the offshore unit 102 may be obtained during or after assembly from machines used in assembly or cameras at the assembly site, for example machine usage data or image processing data from a camera at the assembly site may indicate how many legs 114 have been included on the offshore unit 102 or the like.

[000123] Where the system being supported by the offshore unit 102 is a FOWT 106, the operations data may comprise FOWT data, for example one or more of: blade status, blade number, nacelle data and parked positions of the blades and/or nacelle.

[000124] An operator (e.g. a user of the computing device 1102 configured to run the model) may determine that other operations data would be applicable/useful on a case-bycase basis. The method 300 may comprise requesting specific operations data from a relevant data source, such as a cloud server or other remote server or pulling data from the memory 1106 of the computing device 1102, for example from previous marine operations, or obtaining specific operations data from a sensor 118 configured to provide that operations data.

[000125] Figure 7 shows an updated table from Figure 5, following steps 318 and 320 of the method 300. The system configuration variables are filled in based on the operations data and provided to the model. No specific values are shown in the example, but the dark colour indicates that the values for those variables are now fixed. It should be noted that as the variables are updated, both Model One and Model Two may both be updated automatically. The model is configured to map updates of Model One to Model Two. The model may be configured to compare Model One with earlier simulations during the steps of obtaining data.

[000126] Figure 8 shows an updated example digital representation of Model One following the system configuration variables being entered as inputs to the model. In this example, it has been indicated in the operations data that a vessel tensioner 206 is present on the offshore unit 102, so this is reflected in the digital representation together with using a reaction anchor on the vessel 202. It is indicated, from the operations data, that the mooring line being represented is assumed to be a chain but may otherwise in practice be a wire or fibre. It is indicated, based on the operations data, that a mooring line 104 comprises a buoyancy aid and that the vessel’s anchor line comprises a buoyancy aid, to avoid them clashing and prevent fibre rope on bottom in this example. This will have been included in the operations data in this example.

[000127] The method 300 may further comprise calibrating the model based on data gathered in marine operations. Calibration data may be obtained from sensors 118 arranged at the offshore unit 102, the vessel 202, or from third party data sources (for example obtaining weather data). Calibration data may generally be categorised into either: operations data, vessel offset data and environmental data as shown in the tables (for example Figure 7) but generally “vessel offset” data falls into marine execution data as it relates to data obtained during marine operations.

[000128] The method 300 comprises obtaining marine execution data 322 once the physical floating offshore unit is installed in water, wherein the physical floating offshore unit has been towed to its installed position by the vessel 202 and or additional towing vessel in a spread and wherein the vessel offset data comprises indications of vessel motion in the water. The method 300 further comprises assigning 324 one or more model calibration variables based on the marine execution data. During the beginning of installation operations, one or more of the following sensors 118 may be used to measure offshore unit motions and/or vessel motions: motion reference unit (MRU) installed on offshore unit 102 to measure position and motions, vessel-mounted MRU (part of the DP system) to measure position and motion, tension sensor (which may be arranged on a winch or on a mooring line 104 itself) or a line length sensor configured to measure a length of the mooring line 104, for example a length that is pulled in/out by the winch through the tensioner. An MRU is a sensor configured to measure roll, pitch, yaw and heave motion as well as surge and sway. An MRU is configured to measure motion with six degrees of freedom.

[000129] Each of the sensors 118 used to obtain measurements to formulate vessel offset data may comprise a transmitter/receiver/transceiver such that a request for data can be received and such that measurements can be transmitted to the requestor. One or more of the sensors 118 may be configured to deliver measurements to a remote storage, for example a suitable server such as a cloud server, and the computing device 1102 that runs the model may be configured to request data from the remote storage to provide as input to the model.

[000130] The method 300 further comprises obtaining environmental data 326, the environmental data comprising indications of the conditions at the location of the physical floating offshore unit. These weather data are forecasted and made available by third party suppliers or measured by sensors in the field, wave, wind and current including directions. The method 300 further comprises assigning 328 one or more model calibration variables based on the environmental data. During the beginning of installation operations, one or more of the following sensors may be used to environmental data: vessel mounted wave radar to measure wave data (significant wave height, direction and period for wind and swell driven waves, for example) and vessel mounted wind sensors (part of DP system).

[000131] The method 300 comprises coupling the obtained operations data, marine execution data and the environmental data with the digital representation to update the digital representation of Model One. This may comprise using the data to update the model with calibrated properties for hydrodynamic properties of the offshore unit 102 and/or the vessel 202, which may comprise one or more of wind coefficients, wave coefficients and current coefficients. Retrieving more than one of the types of data is not essential – the model could be updated based only on operations data, for example; however, providing input data comprising operations data and marine execution data fixes more previous unknowns or mere estimates in the model and so improves the pretension prediction. Environmental data may provide input data for improving the pretension prediction and/or for offsetting for weather in the pretension calculation.

[000132] Some or all of the obtained marine execution data and/or environmental data may build on operations data to update the digital representation of Model One. Some or all of the obtained marine execution data and/or environmental data may provide new data to update the digital representation of Model One – instead of building on operations data, new information about the offshore unit 102 and/or vessel 202 may be taken from the marine execution data and/or environmental data.

[000133] Figure 9 shows an updated table of Figure 7 once model calibration has been performed, by inputting calibration data to the model.

[000134] Calibrated Model One is mapped to Model Two and the model is configured to compare calibrated Model One with earlier simulations to establish what the estimated/predicted pretension is for Model Two. The model is then configured to compare the pretension with the predetermined range of tensions that would be allowable for vessel disconnection and determine whether the pretension falls within that range. The predetermined range of tensions may be determined as part of designing the offshore unit or the system, for example.

[000135] The steps 318, 322 and 326 may be performed in any suitable order based on the availability of the data, the time taken to obtain the data and other factors that may influence the order in which the data is obtained. Likewise, step 320 may occur before step 324, for example, or each of the assigning steps 320, 324, 328 may take place after all of the data has been obtained for example.

[000136] Including one or more sensors 118 on the vessel 202 and coupling vessel behaviours with behaviours of the offshore unit 102 avoids the need to add sensors 118 to the offshore unit 102 that would need to be serviced/replaced in due course. It is simpler and more convenient to maintain sensors 118 and replace sensors 118 on the vessel 202, which returns to land and may have crew on-board who can perform maintenance during a journey of the vessel 202 for example. The offshore unit 102, however, may be unmanned and may not be intended to return to shore. Of course, some sensors 118 are arranged on the offshore unit 102 and would typically be arranged on offshore units 102 such that the present method 300 does not require any additional sensors 118 to be arranged at the offshore unit 102, but rather makes use of existing sensors 118 while circumventing the need for a tension sensor at the offshore unit 102.

[000137] The method 300 further comprises calculating 312 a predicted pretension in the mooring line(s) 104. For example, the model may be configured to calculate the expected mean tension in the mooring line(s) (correct for the effect of dynamic influence on the tension due to motions). The model may be configured to calculate the expected mean tension in the mooring line(s) 104 based on the physics of the digital representations of Models One and Two. An aim of the model is to calculate an estimated pretension at a time when the vessel 202 is disconnected from the offshore unit 102. In this way, it can be established whether the offshore unit 102 is ready to be disconnected from the vessel 202 or whether any further tensioning operations, winch line pulled in or out are required to achieve a desired pretension in the mooring line(s) 104. Model Two may comprise advice on required pull in/out length to reach the target pretension after disconnection of the vessel 202.

[000138] Additional data may be provided to the model at this stage, to facilitate the calculation of the estimated pretension. Example inputs into the model include at least one of: tension in the installation line 204 measured by a sensor on a winch, length of the line pulled in or out measured by sensor on a winch, vessel 202 and offshore unit 102 positions, and environmental data comprising at least one of wave, wind and current data. The tension in winch line could be adjusted without the environmental conditions. However, in order to correct for environmental conditions and get the pretension in the corresponding as-installed model environmental input such as weather data is incorporated and corrected for.

[000139] Figure 10 shows an updated table of Figure 9, where environmental and vessel offset data (an example of marine execution data) has been obtained.

[000140] The model is configured to calculate the pretension when the vessel 202 is disconnected and to provide a signal indicating the predicted pretension with the tension falling in a target range. The method 300 may comprise, once the predicted pretension is within a predetermined range of values, indicating 330 that vessel disconnection from the physical floating offshore unit is to be instigated. The target range of tensions is project dependent. An example target range of tensions is minimum 900kN, ideal target 1000kN, maximum 1100kN, for an example offshore unit 102. The pretension is most often calculated at the mooring line end that is connected to the offshore unit.

[000141] Based on the obtained operations data, marine execution data, vessel offset data and environmental data, the model will take into account dynamic effects during the installation operations in order to discount these effects in the estimated final pretension value.

[000142] The method 300 may further comprise storing part or all of the data obtained during installation operations and associating the stored data with the particular offshore unit 102 (for example, suitably labelling or tagging files). Some or all of the data may be made available as part of “as-built” documentation for the offshore unit 102. The memory 1006 may be configured to store part or all of the data obtained during installation operations and/or a remote server storage may be used. The digital representation of Model One and/or Model Two, once a desired number of variables have been fixed based on measurements or otherwise obtained data, may be used as documentation for the offshore unit 102.

[000143] The method 300 may comprise performing an additional measurement of tension in the mooring lines 104 to compare with the estimated pretension that the model calculates, which may be to verify the result (for example to check the accuracy of the model). It may be that early operations include both an estimated pretension calculated by the model and a measured tension, to prove the concept, and then subsequent operations for similar offshore units 102 (having similar or the same physical properties) may only rely on the model to calculate the pretension and determine when the disconnect the vessel 202.

[000144] Measurement of the tension may be performed by any suitable tensioner equipment, for example by the Kongsberg Maritime device Riser tension monitoring system (RTMS), which has a main functionality related to a riser, but could be used to measure tension in a mooring chain.

[000145] A computer program product is provided, embodied on a non-transitory computer readable medium comprising computer code that, when executed by a processor, causes the processor to perform the method 300. Figure 11 shows a block diagram of elements that may be used to run the model and perform the method 300. The person skilled in the art will recognise that any suitable software/hardware elements may be used to perform the method 300.

[000146] A system 100 is provided, configured to perform steps of the method 300. The system 100 comprises the computing device 1102 comprising the processor 1104 or processing circuitry and the memory/storage 1106. The computing device 1102 may be a computing array comprising multiple computing devices. The computing device may comprise a server or cloud-based computing to facilitate performing the method 300.

[000147] The computing device 1102 comprises the input/output (I/O) module 1108. The I/O module 1108 may comprise the display 1108a for presenting information to a user, for example for displaying the graphical representation of the digital representations. The computing device 1102 may be configured to generate a user interface into which a user is enabled to enter data – for example, data obtained from sensors (operations data, vessel offset data, and/or environmental data for example). The I/O module 1108 may comprise data input tools, for example a keyboard, touchscreen or microphone or the like. The data I/O module 1108 may comprise a transmitter configured to transmit a request for data to an external data source (e.g. a sensor or a server or cloud-based storage). The data I/O module 1108 may comprise a receiver configured to receive data signals from external data sources. The transmitter and receiver may be part of a transceiver.

[000148] Generating the model may occur at the processor 1104 and computer code may be stored at the memory 1106 that, when executed by the processor 1104, runs the model.

[000149] Obtaining operations data, marine execution data and environmental data is performed by the data I/O module 1108. The data I/O module 1108 is configured to provide the variables to the model as input, or the data I/O module 1108 is configured to provide the variables to the processor 1104, wherein the processor 1104 is configured to organise/sort the variables for input into the model (or not – the processor 1104 may determine that data is not suitable to be input into the model for one or more reasons including that the data is surplus, not relevant, already input into the model).

[000150] The processor 1104 is configured to couple at least one of the obtained operations data, vessel offset data and the environmental data with the digital representation of Model One to update the digital representation of Model One. The processor 1104 is configured to map updates of Model One to Model Two. The processor 1104 is configured to compare Model One with earlier simulations in order to predict an appropriate pretension for Model Two.

[000151] The processor 1104 is configured to run the model and so calculating the predicted pretension takes place, by the model, at the processor 1104. In some examples the processor 1104 is remote, for example the model may be run partly or completely at a remote server such as a cloud server through an application programming interface (API), for example.

[000152] The processor 1104 is configured to compare the output predicted pretension from the model with a predetermined range of values. The predetermined range of values may be set by the user using the user interface, for example. The predetermined range of values may be based on one or more industry standards, which may be provided by the user (for example using the user interface) or may be obtained from a third party data source using the data I/O module 1108 for example.

[000153] The system 100 further comprises a first communication module 1110. The first communication module 1110 may be configured to send a signal indicating the predicted pretension to the vessel 202 if the processor 1104 determines that the predicted pretension is within the predetermined range of values. The signal may indicate that vessel disconnection from the offshore unit 102 is to be instigated. The first communication module 1110 may comprise processing circuitry configured to generate the signal and a controller configured to cause the signal to be sent. The first communication module 1110 may comprise a transmitter/transceiver configured to send the signal. The first communication module 1110 may comprise a receiver configured to receive a signal, for example a signal indicating safe receipt of the transmitted signal. The first communication module 1110 may be part of the computing device 1102 or may be arranged at the same location as the computing device 1102 (e.g. on land, or on the same vessel or a nearby vessel if the computing device 1102 is being used on a vessel). It may be possible to use the computing device 1102 on the vessel 202 that is towing the offshore unit 102. It is envisioned that running the model and calculating the predicted pretension will take place on shore in a remote environment from the vessel 202 and offshore unit 102 from a practicality standpoint, for example in order to power the powered elements (e.g. computing device 1102) and avoid the need for those running the model to need training/expertise in being on board the vessel 202. It may be desirable to run the model on board the vessel 202 where data from on board sensors 118 may be easily obtained, for example.

[000154] The system 100 may comprise a second communication module 1112, arranged at the vessel 202, configured to receive the signal from the first communication module 1110. The second communication module 1112 needs to be on board the vessel 202 because, based on the received signal, an operation may be performed at the vessel 202. The system 100 comprises an output module 1114, arranged at the vessel 202, configured to indicate that the signal from the first communication module 1110 has been received.

[000155] The output module 1114 may comprise a display and/or a speaker, configured to indicate to a user on the vessel 202 (such as a crew member) that a signal has been received from the first communication module 1110 to the second communication module 1112. An indication from the output module 1114 may comprise a graphical indication presented on the display, such as an image or message indicating that the vessel 202 can be disconnected from the offshore unit 102. The indication may comprise an audible alert such as a bell sound, other alarm sound or voice message, emitted by the speaker. The signal may indicate a time frame in which the vessel 202 can be disconnected from the offshore unit 102 while the predicted tension is within the predetermined range of tensions. For example, the calculation of the predicted pretension may have a lifetime for which it is valid for the offshore unit 102 and conditions may change, causing the predicted pretension to be invalid/need to be updated. The indication from the output module 1114 may indicate the time frame in which the vessel 202 needs to be disconnected from the offshore unit 102.

[000156] The model output predicted pretension may be presented to a user who determines whether to send a signal indicating that the vessel 202 can proceed with disconnection. Presentation of the predicted pretension may be at a computing device having a display and may be automatic following the tension being predicted. The signal may be sent by a user using a communication channel between the vessel 202 and a location on land, for example. The computing device 1102 may be on board the vessel 202 and so there may not be a need to issue a signal from the computing device 1102 to the vessel 202; a user on board may be able to initiate disconnection of the vessel 202 from the offshore unit 102 in person based on the predicted pretension. However, the minimise the need for specially trained personnel to form part of the crew of the vessel 202 it is expected that the model will be run on a computing device 1102 on land and that a signal will be sent to the second communication module 1112 accordingly.

[000157] Disconnecting the vessel 202 from the offshore unit 102 may move towards automatic disconnection based on the predicted pretension in the future but for safety reasons it is expected that a trained and professional user would review the predicted tension indication before instigating disconnection of the vessel 202 from the offshore unit 102, for example by reviewing at the display 1108a or at a display on board the vessel 202. Of course, once reviewed, the system 100 may be configured to cause disconnection (for example via a controller 1116 on the vessel 202 configured to cause disconnection) automatically based on a confirmation of the indication of the predicted tension from a user. It is envisioned that in future a signal based on the estimated pretension from the model may cause automatic disconnection of the vessel 202 from the offshore unit 102 but at present this is considered to be a potential safety hazard.

[000158] The system 100 may comprise a tension sensor associated with one of the mooring lines 104 of the offshore unit 102. The data input/output module 1108 may be configured to obtain tension data from the tension sensor and the processor 1104 may be configured to include the tension data in the calculation of the predicted pretension.

[000159] The tension sensor may be mounted on a tensioner 206 of the offshore unit 102, such as the VT described above. The tension sensor may be arranged on a mooring line 104 itself and may comprise a load sensor as described above.

[000160] The system comprises a tension sensor on the vessel 202 configured to measure tension in the winch line/installation line 204. The processor 1104 is configured to, by the model, select a suitable Model One and Model two based on the measured tension in the winch line/installation line 204 for calculation of the predicted pretension.

[000161] The system 100 comprises a line length sensor mounted on the winch 208, configured to measure a length of the mooring line 104 being pulled in or out of the winch 208. The data input/output module 1108 may be configured to obtain line length data from the line length sensor. The processor 1104 is configured to, by the model, select a suitable Model One and Model two based on the line length (versus tension) data for calculation of the predicted pretension.

[000162] The system 100 may comprise one or more sensors 118 comprising a vesselmounted wave radar, configured to measure wave data; a vessel-mounted wind sensor, configured to measure wind data, a vessel-mounted MRU, configured to measure roll, pitch, yaw and heave motion; an offshore unit-mounted MRU, configured to six degrees of freedom of motion, wherein the data input/output module 1108 may be configured to obtain data from the or each of the vessel-mounted wave radar, the vessel-mounted wind sensor, the vesselmounted MRU and the offshore unit-mounted MRU to provide to the processor 1104. The processor 1104 may be configured to include data from one or more of these data sources in the calculation by providing data from the data sources as an input to the model.

[000163] The system 100 may further comprise the offshore unit 102 comprising one or more mooring lines 104 and the vessel 202, which may comprise the second communication module 1112 and the output module 1114.

[000164] The system 100 may further comprise a power cable connected to the offshore unit 102, wherein the offshore unit 102 comprises a power generation offshore unit (for example a FOWT 106) and wherein the power cable is configured to deliver power generated at the offshore unit to a power storage facility.

[000165] The offshore unit 102 may comprise a floating wind offshore unit 106 comprising a nacelle 108 and one or more blades 110 configured to be turned by the wind. The system 100 may further comprise at least one of a blade position sensor and a nacelle position sensor. The blade position sensor may be arranged on one of the blades 110 accordingly. Each blade 110 may comprise a position sensor. The nacelle position sensor may be arranged on the nacelle 108 accordingly. Data from the blade position sensor and/or the nacelle position sensor may be provided as operations data to the model as set out above.

[000166] The offshore unit 102 may further comprise an anchor. The system 100 may further comprise an anchor sensor configured to measure the position (geographical location and/or relative position from another anchor for example) of the anchor.

[000167] The estimated pretension may be used – as well as for guiding disconnection of the vessel 202 from the physical offshore unit 102 – for documentation about the offshore unit 102 and/or installation, hook-up and other processes. When the pretension target is reached, all data from the operation is stored and made available in an as built documentation. To ensure and prove that the pretension target concept, method and Model One and Two representations give sufficient accuracy level, it is intended that the mooring line tension on early in-use examples (where the model is used with real offshore unit(s) for the first time) will be measured by “tensioner equipment” as set out above for comparison of the predicted pretension with measured tensions.

[000168] It is envisioned that the model may be used during the lifetime of the offshore unit 102, post-installation, to predict properties of the offshore unit 102 such as maintenance requirements, estimated life time of one or more on-board sensors or other working parts, estimated time before a service is needed and the like. For example:

- Monitor tension in the lines and power cable for fatigue monitoring

- Provide indication of lines that have accumulated to high fatigue damage

- In combination with statistical data and measured data indicate when fatigue damage could be reaching limits and initiate inspection and replacement campaign on time

- Based on measured weather and measured floater motion detect possible line failure - Based on measured floater motions and assesses tension in the lines estimate mooring line optimization for next generation floater (offshore unit)

- Potentially integrate with floater/turbine control system for optimization.

[000169] The embodiments disclosed herein can be implemented through at least one software program running on at least one hardware device and performing network management functions to control the elements.

[000170] The following clauses set out examples of the present disclosure:

[000171] 1. A computer-implemented method of achieving a target tension in one or more mooring lines of a physical floating offshore unit, the method comprising: generating a model comprising a digital representation of the physical floating offshore unit’s physical properties and/or physical behaviours, wherein the physical offshore unit comprises one or more mooring lines and wherein the model is configured to model the one or more mooring lines, wherein generating the model comprises modelling the physical floating offshore unit’s physical properties and/or physical behaviours based on initial data, wherein the initial data is to be updated based on as-built and as-installed data comprising (i) operations data specific to the physical floating offshore unit and the mooring lines and (ii) marine execution data; by the model, estimating a predicted tension in the one or more physical mooring lines, comprising:

obtaining operations data from one or more sensors, a memory, a manual input into a computing device configured to run the model and/or a remote server as a data source, and assigning system configuration variables for the model based on the operations data, wherein operations data includes installation line length and winch tension;

obtaining marine execution data from one or more sensors, wherein a vessel is configured to install the physical floating offshore unit and wherein the marine execution data comprises indications of vessel motion in water and/or physical floating offshore unit motion in the water respectively, and assigning one or more model calibration variables based on the marine execution data and/or applying a correction to the predicted tension based on obtained marine execution data;

obtaining environmental data from one or more sensors and/or a remote server as a data source, the environmental data comprising indications of the conditions at the location of the physical floating offshore unit and applying a correction to the predicted tension based on obtained environmental data; and

once the predicted tension is within a predetermined range of values, providing an indication of the predicted tension being within the predetermined range of values, such that vessel disconnection from the physical floating offshore unit can be performed based on the predicted tension.

[000172] 2. The method of clause 1, wherein generating the model comprising the digital representation of the physical floating offshore unit comprises training the model to represent a physical floating offshore unit based on input synthesised training data and/or historical data, wherein the model is trained to generate a representation of the physical floating offshore unit based on generic data before any operations data, marine execution data or environmental data is obtained and to update the representation based on input situational data, which is as-built and/or as-installed data as opposed to estimated, predicted, historical or otherwise obtained data that is not from the real physical offshore unit as installed or as built.

[000173] 3. The method of clause 1 or clause 2, wherein obtaining marine execution data comprises obtaining data about the physical floating offshore unit once in water and/or once it has been towed to or once it has been arranged at a desired geographical location for the physical floating offshore unit to be moored.

[000174] 4. The method of any preceding clause, wherein the operations data comprises one or more of: as-installed anchor position(s), length of the mooring line, one or more physical properties of the mooring line(s), one or more properties of mooring line segments, the presence or absence of a power cable, ballast data, draft data, and present or predicted/target position data.

[000175] 5. The method of any preceding clause, wherein the physical floating offshore unit comprises a floating wind turbine and wherein the operations data comprises one or more of: blade status, blade number, nacelle data and parked positions of the blades and/or nacelle.

[000176] 6. The method of any preceding clause, wherein marine execution data comprises one or more of: vessel geographical position, vessel motion, winch tension and winch line and mooring line length, physical floating offshore unit geographical position, and physical floating offshore unit motion.

[000177] 7. The method of any preceding clause, wherein environmental data comprises one or more of: wave height, wave direction, wind direction, wave period, current velocity and wind velocity and wherein the one or more model calibration variables based on the environmental data comprise one or more of: a wind coefficient, a wave coefficient and a current coefficient.

[000178] 8. The method of any preceding clause, wherein obtaining marine execution data comprises obtaining data from a motion reference unit – MRU - sensor that is configured to measure motion to six degrees of freedom, wherein the MRU is arranged on board the physical floating offshore unit, on board the vessel, or wherein a there is an MRU arranged on each of the physical floating offshore unit and the vessel such that motion of each of the physical floating offshore unit and vessel can be sensed.

[000179] 9. The method of any preceding clause, wherein obtaining environmental data comprises using a wave radar arranged on board the vessel to measure wave data and/or using a wind sensor arranged on board the vessel to measure wind data.

[000180] 10. The method of any preceding clause, wherein an installation line is connected between the vessel and the physical floating offshore unit such that the vessel can install the physical floating offshore unit, wherein the installation line is connected to a winch on board the vessel and wherein a line length sensor is arranged on the winch, configured to measure a length of the mooring line being pulled in or out of the winch, wherein the method comprises obtaining line length data from the line sensor and, by the model, including the line length data in the estimation of the tension.

[000181] 11. The method of any preceding clause, further comprising:

[000182] performing a tension measurement for at least one of the physics mooring lines using a tension measuring device; and

[000183] comparing results of the tension measurement with the predicted tension to verify the predicted tension.

[000184] 12. A computer program product embodied on a non-transitory computer readable medium comprising computer code that, when executed by a processor, causes the processor to perform the method of any one of clauses 1 to 11.

[000185] 13. A system for achieving a target tension in one or more mooring lines of a physical floating offshore unit, the system comprising:

[000186] a computing device comprising a processor, a memory and a first communications module, configured to perform the method of any one of clauses 1 to 11, wherein the memory is configured to store instructions for running the model and wherein the processor is configured to run the model, wherein the first communications module is configured to provide the indication of the predicted tension comprising sending a signal indicating the predicted tension if the processor determines that the predicted tension is within the predetermined range of values.

[000187] 14. The system of clause 13, further comprising:

[000188] a second communication module, arranged at the vessel, configured to receive the signal from the first communication module;

[000189] an output module, arranged at the vessel, configured to indicate that the signal from the first communication module has been received.

[000190] 15. The system of clause 13 or clause 14, further comprising a line length sensor mounted on a winch of the vessel, configured to measure a length of the mooring line being pulled in or out of the winch, wherein the first communications module is configured to obtain line length data from the line length sensor and wherein the processor is configured to, by the model, include the line length data in the calculation of the predicted tension.

[000191] 16. The system of any preceding system clause, further comprising at least one of:

[000192] a vessel-mounted wave radar, configured to measure wave data;

[000193] a vessel-mounted wind sensor, configured to measure wind data

[000194] a vessel-mounted MRU, configured to measure roll, pitch, yaw, heave, surge and sway;

[000195] a physical floating offshore unit-mounted MRU, configured to measure roll, pitch, yaw, heave, surge and sway, wherein the first communications module is configured to obtain data from the or each of the vessel-mounted wave radar, the vesselmounted wind sensor, the vessel-mounted MRU and the physical floating offshore unitmounted MRU to provide to the processor.

[000196] 17. The system of any preceding clause, further comprising:

[000197] the physical floating offshore unit comprising one or more mooring lines; and

[000198] the vessel.

[000199]

[000200] 18. The system of clause 17, wherein the physical floating offshore unit comprises a floating wind offshore unit comprising a nacelle and one or more blades configured to be turned by the wind, wherein the system further comprises at least one of a blade position sensor and a nacelle position sensor.

[000201] 19. The system of any preceding system clause, further comprising a tension sensor associated with one of the mooring lines of the physical floating offshore unit, wherein the first communications module is configured to obtain tension data from the tension sensor, wherein the processor is configured to include the tension data in the calculation of the predicted tension.

Claims

1. A computer-implemented method of achieving a target pretension in one or more mooring lines of a physical floating offshore unit, the method comprising:

measuring a tension in an installation line configured to install the physical floating offshore unit,

measuring a line length pull in/out of the installation line;

generating a model comprising a digital representation of the physical floating offshore unit’s physical properties and/or physical behaviours, wherein the physical floating offshore unit comprises one or more mooring lines and wherein the model is configured to model the one or more mooring lines, the model further comprising a digital representation of physical properties and/or physical behaviours of an installation vessel that is configured to install the physical floating offshore unit,

wherein generating the model comprises selecting a base design for the model from a set of base designs based on the measured tension and measured line length pull in/out and modelling the physical properties and/or physical behaviours based on initial data, wherein the initial data is to be updated based on as-built and as-installed data comprising (i) operations data specific to the physical floating offshore unit and the mooring lines and (ii) marine execution data, and

estimating, by the model, based on the as-built and as-installed data, a predicted pretension in the one or more physical mooring lines such that vessel disconnection from the physical floating offshore unit can be performed based on the predicted pretension.

2. The method of claim 1, wherein the tension is measured using a tension sensor at a vessel separate from the physical floating offshore unit, wherein the installation line is routed through a tensioning device and connected to a mooring line of the physical floating offshore unit such that the vessel can tension up the mooring line and install the physical floating offshore unit, wherein the installation line is connected to a winch on board the vessel and wherein a line length sensor is arranged on the winch, wherein the line length pull in/out is measured using the line length sensor.

3. The method of claim 1 or claim 2, further comprising:

obtaining operations data from one or more sensors, a memory, or a manual input into a computing device configured to run the model and/or a remote server as a data source, and assigning system configuration variables for the model based on the operations data, wherein operations data includes installation line length and winch tension.

4. The method of any preceding claim, further comprising:

obtaining marine execution data from one or more sensors, a memory, or by manual input into a computing device configured to run the model and/or a remote server as a data source, wherein the marine execution data comprises indications of vessel position and motion in water and/or physical floating offshore unit position and motion in the water respectively, and assigning one or more model calibration variables based on the marine execution data and/or applying a correction to the predicted pretension based on obtained marine execution data.

5. The method of any preceding claim, further comprising:

obtaining environmental data from one or more sensors and/or a remote server as a data source, the environmental data comprising indications of the conditions at the location of the physical floating offshore unit and applying a correction to the predicted pretension based on obtained environmental data.

6. The method of any preceding claim, further comprising comparing the predicted pretension with a predetermined range of values, wherein once the predicted tension is within the predetermined range of values, providing an indication of the predicted tension being within the predetermined range of values, such that vessel disconnection from the physical floating offshore unit can be performed based on the predicted pretension.

7. The method of any preceding claim, wherein generating the model comprising the digital representation of the physical floating offshore unit comprises creating one or more base designs for the model and training each base design of the model to represent a physical floating offshore unit based on input synthesised training data and/or historical data, wherein the model is trained to generate a representation of the physical floating offshore unit based on initial data before any operations data, marine execution data or environmental data is obtained and to update the representation based on input as-built and/or as-installed data.

8. The method of claim 4 or any claim depending from claim 4, wherein obtaining marine execution data comprises obtaining data about the physical floating offshore unit once it has been towed to or once it has been arranged at a desired geographical location for the physical floating offshore unit to be moored.

9. The method of claim 3 or any claim depending from claim 3, wherein the operations data comprises one or more of: as-installed anchor position(s), as built length of the mooring line, one or more physical properties of the mooring line(s), one or more properties of mooring line segments, the presence or absence of a power cable, ballast data, draft data, and present or predicted/target position data.

10. The method of any preceding claim, wherein the physical floating offshore unit comprises a floating wind turbine and wherein the operations data comprises one or more of: blade status, blade number, nacelle data and parked positions of the blades and/or nacelle.

11. The method of claim 4 or any claim depending from claim 4, wherein marine execution data comprises one or more of: vessel geographical position, vessel motion, winch tension and winch line and winch/installation line length, physical floating offshore unit geographical position, and physical floating offshore unit motion.

12. The method of claim 5 or any claim depending from claim 5, wherein environmental data comprises one or more of: wave height, wave direction, wind direction, wave period, current velocity and wind velocity and wherein the one or more model calibration variables based on the environmental data comprise one or more of: a wind coefficient, a wave coefficient and a current coefficient.

13. The method of claim 4 or any claim depending from claim 4, wherein obtaining marine execution data comprises obtaining data from a motion reference unit – MRU - sensor that is configured to measure motion to six degrees of freedom, wherein the MRU is arranged on board the physical floating offshore unit, on board the vessel, or wherein a there is an MRU arranged on each of the physical floating offshore unit and the vessel such that motion of each of the physical floating offshore unit and vessel can be sensed.

14. The method of claim 5 or any claim depending from claim 5, wherein obtaining environmental data comprises using a wave radar arranged on board the vessel to measure wave data and/or using a wind sensor arranged on board the vessel to measure wind data.

15. The method of any preceding claim, further comprising:

performing a tension measurement for at least one of the physical mooring lines using a tension measuring device; and

comparing results of the tension measurement with the predicted tension to verify the predicted tension.

16. A computer program product embodied on a non-transitory computer readable medium comprising computer code that, when executed by a processor, causes the processor to perform the method of any one of claims 1 to 15.

17. A system for achieving a target tension in one or more mooring lines of a physical floating offshore unit, the system comprising:

a computing device comprising a processor and a memory, configured to perform the method of any one of claims 1 to 15, wherein the memory is configured to store instructions for running the model and wherein the processor is configured to run the model;

a tension sensor and a line length sensor at a vessel configured to install the physical floating offshore unit, wherein the tension sensor is configured to measure a tension in the installation line, wherein the installation line is routed through a tensioning device at the vessel and connected to a mooring line of the physical floating offshore unit such that the vessel can tension up the mooring line and install the physical floating offshore unit, wherein the installation line is connected to the winch on board the vessel and wherein the line length sensor is arranged on the winch, configured to measure a length of the mooring line being pulled in or out of the winch.

18. The system of claim 17, further comprising:

a first communication module, configured to provide an indication of the predicted pretension comprising sending a signal indicating the predicted pretension if the processor determines that the predicted pretension is within the predetermined range of values;

a second communication module, arranged at the vessel, configured to receive the signal from the first communication module;

an output module, arranged at the vessel, configured to indicate that the signal from the first communication module has been received.

19. The system of claim 18, further comprising a line length sensor mounted on a winch of the vessel, configured to measure a length of the mooring line being pulled in or out of the winch, wherein the first communications module is configured to obtain line length data from the line length sensor and wherein the processor is configured to, by the model, use the line length data to select a base design for the model.

20. The system of any one of claims 17 to 19, further comprising at least one of:

a vessel-mounted wave radar, configured to measure wave data and current;

a floating weather buoy configured to measure wave and current data

a vessel-mounted wind sensor, configured to measure wind data

a vessel-mounted MRU, configured to measure roll, pitch, yaw, heave, surge and sway;

a physical floating offshore unit-mounted MRU, configured to measure roll, pitch, yaw, heave, surge and sway, wherein the first communications module is configured to obtain data from the or each of the vessel-mounted wave radar, the vessel-mounted wind sensor, the vessel-mounted MRU and the physical floating offshore unit-mounted MRU to provide to the processor.

21. The system of any preceding claim, further comprising:

the physical floating offshore unit comprising one or more mooring lines; and the vessel.

22. The system of claim 21, wherein the physical floating offshore unit comprises a floating wind offshore unit comprising a nacelle and one or more blades configured to be turned by the wind, wherein the system further comprises at least one of a blade position sensor and a nacelle position sensor.

23. The system of any preceding system claim, further comprising a tension sensor associated with one of the mooring lines of the physical floating offshore unit, wherein the first communications module is configured to obtain tension data from the tension sensor, wherein the processor is configured to include the tension data in the calculation of the predicted pretension.