GB2553505A

GB2553505A - Processing data from a subsea oil and gas production system

Info

Publication number: GB2553505A
Application number: GB1614614.4A
Authority: GB
Inventors: Arnesen Gudbrand; Erik Klevan Kjell
Original assignee: Aker Solutions Ltd
Current assignee: Aker Solutions Ltd
Priority date: 2016-08-29
Filing date: 2016-08-29
Publication date: 2018-03-14
Anticipated expiration: 2036-08-29
Also published as: GB2553505B; GB201614614D0

Abstract

Apparatuses, including a data controller 222, for processing data from a subsea oil and gas production system are disclosed. The apparatus may include memory 430 and one or more processing units 420 configured to receive, originating from and transmitted through at least one Subsea Electronic Module 212, SEM, an inventory of a corresponding Condition Performance Monitoring 240, CPM, apparatus connected to the at least one SEM, the inventory specifying an operational configuration for the CPM apparatus, the processors configured to reformat the monitoring data into a universal data format and transmit the reformatted data to a centralized data bus 405. Methods and computer readable media for processing data from a subsea oil and gas production system are also claimed. The one or more processing units may also be configured to receive monitoring data generated by the corresponding CPM apparatus.

Description

(54) Title of the Invention: Processing data from a subsea oil and gas production system Abstract Title: Processing Data from a Subsea Oil and Gas Production System (57) Apparatuses, including a data controller 222, for processing data from a subsea oil and gas production system are disclosed. The apparatus may include memory 430 and one or more processing units 420 configured to receive, originating from and transmitted through at least one Subsea Electronic Module 212, SEM, an inventory of a corresponding Condition Performance Monitoring 240, CPM, apparatus connected to the at least one SEM, the inventory specifying an operational configuration for the CPM apparatus, the processors configured to reformat the monitoring data into a universal data format and transmit the reformatted data to a centralized data bus 405. Methods and computer readable media for processing data from a subsea oil and gas production system are also claimed. The one or more processing units may also be configured to receive monitoring data generated by the corresponding CPM apparatus.

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PROCESSING DATA FROM A SUBSEA OIL AND GAS PRODUCTION SYSTEM [0001] Examples embodiments presented herein relate to data controllers, methods and computer readable media carrying instructions for processing data, particularly condition and performance monitoring system, from a subsea oil and gas production system.

BACKGROUND [0002] To extract oil and gas product from geological formations in subsea reservoirs located under the sea bed, a wellbore can be drilled to the formation and a subsea production system can be installed to interface between the downhole apparatus and topside and effect the recovery of product through a pipeline. Some or all of the components making up the subsea production system may be provided on one or more of the seabed itself, in a floating location subsea, or at a topside location. Subsea production systems thus comprise apparatus that may be installed in relatively difficult-to-access locations and to be effective in their operation the may be reliably controllable and operable for timespans on the order of the productive life of the well in such a way as to efficiently recover the product from the well. To aid this effective and reliable control and operation, the condition and performance of components of the subsea apparatus may be monitored to determine the integrity and operational effectiveness of the subsea system.

[0003] It is in the above context that the disclosure of the present application has been devised.

SUMMARY [0004] Subsea oil and gas production systems may include components and subsystems from various vendors. The content and functionality of such components and subsystems often varies from one another. Therefore, subsea oil and gas production systems, and in particular control and monitoring systems for monitoring the condition and performance of the various components and subsystems are typically implemented requiring various extensions and adaptations in order to account for such differences in the content and functionality of the components and subsystems.

[0005] .

[0006] In accordance with some of the examples the present disclosure, a flexible integration platform may be provided whereby a subsea oil and gas production system may serve to control, monitor and interface with components and subsystems from various vendors without the need of multiple extensions and adaptations. Accordingly, some of the example embodiments presented herein are directed towards a single subsea oil and gas production system which may provide ‘out of the box’-type processing for various types of subsystems without the need of constant add-ons of different software of hardware components.

[0007] According, some of the example embodiments are directed towards a data controller arranged to process data from a subsea oil and gas production system. The data controller comprises memory and one or more processing units. The memory and/or one or more processing units are configured to receive, originating from and transmitted through at least one Subsea Electronic Module (SEM), an inventory of a corresponding Condition Performance Monitoring (CPM), apparatus connected to the at least one SEM. The inventory specifies an operational configuration for the CPM apparatus. The memory and/or one or more processing units are configured to receive, from the at least one SEM, monitoring data generated by the corresponding CPM apparatus, and reformat the monitoring data into a universal data format based on the received inventory. The memory and/or one or more processing units are configured to transmit the reformatted data to a centralized data bus.

[0008] The data controller described above has the example advantage of being able to obtain information, in the form of an inventory of monitored data, from any type of system or manufacture. Specifically, the data controller may receive and process incoming data regardless or the data’s original format. Furthermore, the data controller translates the received data in a universal data format and placing such data on a same centralized data bus. Thereby provided a single system for various types of monitoring devices and manufactures. Such a system reduces overall costs and increases the efficiency of data processing and data analysis. It should be appreciated herein that the term data controller and Field Management System (FMS) may be used interchangeably.

[0009] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to receive the inventory upon a detected change in the monitoring data or the operational configuration.

[0010] An example advantage of the ability to receive the inventory upon a detected change in the monitoring data or the operational configuration is providing updated information in real time. Such real time updates may be provided regardless of the data type of manufacture.

[0011] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to receive the inventory on a periodic time basis.

[0012] An example advantage of the ability to receive the inventory data on a periodic basis pre-emptively evaluating the inventory for possible errors.

[0013] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to reformat the monitoring data and transmit the reformatted data to the centralized data bus in directly upon receipt of the monitoring data.

[0014] An example advantage of the reformatting and transmitting is the ability to process data in real time regardless of any differences in received data format.

[0015] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to receive respective inventories from a plurality of SEMs and further configured to receive monitoring data from a plurality of corresponding CPM apparatuses.

[0016] An example advantage of being able to receive respective inventories from a plurality of SEMs and monitoring data from a plurality of corresponding CPM apparatus is being able to simultaneously process and analyse data of different formats. A further example advantage is the ability of comparing or analysing data of different formats with respect to one another. Such an analysis may be provided in real time thereby reducing processing times and the complexity of the system.

[0017] According to some of the example embodiments, the plurality of SEMs and corresponding CPM apparatuses are located within a designated geographical area monitored by the data controller. An example advantage of such an embodiment is increased flexibility in the operations of the data controller with respect to the plurality of devices the data controller may receive data from.

[0018] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to analyse common data points of the reformatted data from a plurality of different CPM apparatuses, wherein at least two of the plurality of different CPM apparatuses provide monitoring data in distinct formats and/or physical locations.

[0019] An example advantage of the example embodiments described above is providing real time data processing and analysis of diverse monitoring systems, thereby reducing processing times and the complexity of the system.

[0020] According to some of the example embodiments, the one or more processing units, of the data controller is further configured to calculate average values and/or standard deviations of data points of the reformatted data, and alert a detected change in the calculated average value and/or standard deviation.

[0021] An example advantage of the example embodiments described above is providing real time data processing and analysis, as well as setting dynamic alerts, of diverse monitoring systems, thereby reducing processing times and the complexity of the system.

[0022] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to selectively process at least a portion of the reformatted data on the centralized data bus based on a user subscription.

[0023] An example advantage of the example embodiments described above is providing data protection in an efficient and easy manner as users may access information which they are subscribed to and may be denied access to information they are not subscribed to.

[0024] According to some of the example embodiments, the inventory comprises a configuration fingerprint comprising information of the CPM apparatus relating to a geographical location, an apparatus type, sensor values, or measurement meta data.

[0025] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to detect a change in the inventory or monitoring data and record a corresponding timestamp when the detected change occurs.

[0026] An example advantage of the example embodiments described above is the ability to efficiently determine if an error or change has occurred with respect to a current fingerprint and a previously saved fingerprint. According to some of the example embodiments, such an analysis may be provided using a checksum calculating of the previously saved and current fingerprint.

[0027] According to some of the example embodiments, the one or more processing units, of the data controller, are further configured to correlate changes in the inventory or monitoring data with an operational state of a plurality of CPM apparatuses and further to provide a graphical representation of the correlated changes with respect to the recorded timestamps.

[0028] An example advantage of the example embodiments described above is the ability to provide a visual representation of data processing and analysis for data of different formats and originating from devices in different locations. Such visual representation may be provided in real time, increasing the efficiency of the overall system.

[0029] According to some of the example embodiments, the data controller may further comprise at least one software module configured to provide a quality control analysis of the reformatted data. The quality control analysis comprises at least one of a validation of values within a data range, a detection of missing data values and/or a detection or overlapping data values.

[0030] According to some of the example embodiments, the data controller may further comprise at least one software module configured to provide a normalization analysis of high frequency data of the reformatted data. The normalization analysis comprises at least one of a transformation of at least a portion of the reformatted data to process data, a transformation of at least a portion of the reformatted data to root mean square values and/or a transformation of at least a portion of the reformatted data to peak-to-peak values.

[0031] According to some of the example embodiments, the data controller may further comprise at least one software module configured to provide a statistical analysis of the reformatted data. The statistical analysis comprises at least one of a calculation of an average data for the reformatted data and/or a calculation of a standard deviation of the reformatted data.

[0032] According to some of the example embodiments, the data controller may further comprise at least one software module configured to provide a fault management analysis of the reformatted data. The fault management analysis comprises at least one of a setting of an alarm with respect to a specific data value or data trend and/or an establishment of an alarm aggregation of said set alarms.

[0033] According to some of the example embodiments, the data controller may further comprise at least one software module configured to provide an inventory management analysis of the reformatted data. The inventory management analysis comprises an analysis of operational configurations changes.

[0034] An example advantage of the example embodiments above is providing a variety of data analyses on the received data. As the data analysis is provided on the reformatted data, data of different types and originating from different locations may be evaluated.

[0035] Some of the example embodiments are directed towards a subsea oil and gas production system comprising at least one data controller as described in any of the example embodiments set forth above.

[0036] According to some of the example embodiments, the subsea oil and gas production system may further comprise an equipment and operational data unit configured to receive, from a plurality of data controllers, reformatted data wherein at least two the plurality of data controllers comprise a distinct physical location. The equipment and operational data unit may further be configured to store the received reformatted data.

[0037] According to some of the example embodiments, the equipment and operational data unit may be further configured to process the reformatted data to determine at least one of lifecycle equipment management, field optimisation, predictive services, prognostics and/ or diagnostics.

[0038] An example advantage of some of the example embodiments described above is the ability to analyse and process data in real time and in a large scale as different data controllers may be designated to process data from distinct physical regions.

[0039] Some of the example embodiments are directed towards a method, in a data controller, comprising any of the operations described above.

[0040]

BRIEF DESCRIPTION OF THE DRAWINGS [0041] Embodiments are further described hereinafter with reference to the accompanying drawings, in which:

Figure 1 is a schematic illustration of a subsea production system in accordance with some examples of the present disclosure;

Figure 2 is a schematic illustration of a subsea production control system and components which may supporting a subsea production control system in accordance with some examples of the present disclosure;

Figure 3 is an illustration of an abstracted view of a software architecture of a subsea production control system and data flows within it in accordance with some examples of the present disclosure;

Figure 4 is an illustration of some components of a Field Management Server (FMS) and subsea production control system in accordance with some examples of the present disclosure;

Figures 5A and 5B show an illustration of certain components of a condition and performance monitoring apparatus for a pump apparatus in accordance with some examples of the present disclosure, with Figure 5B being a representative cross sectional view through the pump shaft showing the positioning of the proximity sensors for measuring the orbit of the pump shaft;

Figure 6 is an illustration of data flows from a condition and performance monitoring apparatus for a pump apparatus to a pump application and of the dataprocessing therein to produce a real-time pump plot in accordance with some examples of the present disclosure;

Figure 7 is an illustration of a Subsea Production Control System Architecture in accordance with some examples of the present disclosure;

Figure 8 is an illustration of an arrangement for the duplication of plural offshore subsea production control systems can be to an onshore location in accordance with some examples of the present disclosure;

Figure 9 is an illustration of a logical view of a Subsea Production Control System Architecture in accordance with some examples of the present disclosure;

Figures 10-13 show message sequence charts for a controller of a Subsea Production Control System discovering CPM components and creating an inventory therefor, and transforming the data into a universal data format in accordance with some examples of the present disclosure;

Figures 14 and 15 show message sequence charts for example use cases of the logical components of a controller of a Subsea Production Control System in accordance with some examples of the present disclosure;

Figure 16 illustrates an example information model of a controller of a Subsea Production Control System in accordance with some examples of the present disclosure; and

Figure 17 shows an arrangement to integrate third party systems with a controller of a Subsea Production Control System in accordance with some examples of the present disclosure.

DETAILED DESCRIPTION [0042] Some of the example embodiments presented herein are directed towards a single subsea oil and gas production system which may provide ‘out of the box’ processing for various types of subsystems without the need of constant add-ons of different software of hardware components.

[0043] Such a system may be used to check the state, health and history of installed subsea equipment. Furthermore, the system, according to the example embodiments, may also facilitate online diagnostics in real time and leverage obtained information to host higher level business decisions. A further example advantage of the system described herein is the ability to facilitate collaboration between people onshore and offshore and across onshore sites, as well as key vendors by providing data analysis in a uniform manner.

[0044] The system described herein has the further example advantage of providing services for data acquisition, data and application management, remote communication and distribution and for information exchange between software components installed offshore and onshore. Furthermore, the system described herein is capable of processing large amounts of data in various formats.

[0045] According to some of the example embodiments, the subsea oil and gas production system is further capable of enabling new services on existing installations thereby allowing for new components and/or subsystems to be easily added and integrated. Specifically, the system described herein is scalable and allows for cost effective installation and deployment of low-end and high-end subsystems.

[0046] According to some of the example embodiments, raw data may be logged and stored on an offshore platform, or data controller also known as a Field Management System (FMS). The data controller allows for the extraction of logged data for later offline analysis and/or simulations both onshore and offshore.

[0047] A further example advantage of the embodiments described herein is the ability to correlate information produced by different data sources. According to some of the example embodiments, this may be provided with the use of fine grained time stamps on monitored values and events. Raw data, as well as any information obtained in the acquisition chain, may also be time stamped. According to some of the example embodiments, the system may provide a user interface in which a visual representation of processed data in a universal format may be provided. Furthermore, the system may restrict or regulate access to data based on a user subscription.

[0048] A subsea oil and gas production system, and the various components of such a system, for receiving subsea based monitored data and processing such data into a reformatted universal format is described herein. The system has the example advantages of being adaptable. Specifically, such a system is compatible with a number of different data formats and manufactures. Similarly, such a system may retrieve data from any number of distinct data sources providing data in different formats and situated in different physical locations.

[0049] System Overview [0050] Referring now to Figure 1, to extract oil and gas product from a subsea reservoir R found in a geological formation located under the sea bed, a wellbore W has been drilled to the formation. The wellbore W may be a cased wellbore or open hole and may include a production tubing for conveying the oil and gas product up the wellbore W.

[0051] A subsea production system 100 extracting the oil and gas product from the wellbore W is provided. A subsea production system 100 may extract product from plural wellbores, although only a single well is shown in Figure 1. The subsea production system 100 can be installed to interface between the apparatus downhole in the well W and topside and effect the recovery of product to onshore locations through a flowline F. Some or all of the components of the subsea production system 100 may be provided at subsea locations on the seabed or floating subsea, at topside locations at the sea surface in the field, or at onshore locations away from the field.

[0052] In terms of equipment, the subsea production system 100 may include wellhead apparatus 110 located at the head of the well. The wellhead apparatus 110 and may include subsea structures and manifolds which may include a Christmas tree to seal the well and provide valves, spools, connectors and a manifold system. The well may be tied-in through the Christmas tree to a subsea flowline system F through which the product may be retrieved to an onshore location 150. The subsea structures and production system 100 may also provide a subsea access or intervention system to allow access to the well for monitoring and control of the downhole apparatus such as chokes and valves, cabling, sensors and strain gauges, and other tools, and also for interventions and workovers. The subsea production system 100 may at the wellhead apparatus 110 also include one or more subsea pumps to control the production or to transport the hydrocarbons from the well W to the sea surface or to land, for example through flowline F.

[0053] The subsea production system 100 may also include subsea apparatus 120 providing production system equipment located on the seabed or floating subsea. The subsea apparatus 120 may be coupled to one or more wellhead apparatuses 110 at one or more subsea wells. The subsea apparatus 120 may also include one or more pumps for pumping product from one or more wellbores or for pumping product along one or more flow lines. The subsea apparatus 120 may also include one or more Subsea Control Modules (SCM) to facilitate the management and monitoring of the subsea production system 100. The SCM may include plural Subsea Electronics Modules (SEM) providing a data communications interface with components of the subsea production system 100, including various Condition and Performance Monitoring apparatus (CPM). The SCMs, SEMs and CPMs will be described further below.

[0054] The subsea production system 100 may also include an umbilical apparatus 130 configured to couple the subsea apparatus 120 to a topside apparatus 140 of the subsea production system 100. The umbilical apparatus 130 may carry hydraulic and other fluid flow lines, and electrical and other signal-carrying cabling to transmit control and monitoring signals between the components of the subsea production system 100 located topside and subsea.

[0055] The topside apparatus 140 may be located at one or more topside platforms provided on rigs or semi-submersibles to perform one or more production functions such as allowing an operator of the subsea production system 100 in the field to manage the operation of the apparatus of the subsea production system 100. The topside apparatus 140 may include a Master Control Station (MCS) provided as a centralised hardware and software platform for enabling the monitoring, control and logging of the subsea production system and the condition and performance monitoring of the components. The MCS may also provide an operator with one or more user interfaces at a workstation to monitor and control the subsea production system. The MCS may be coupled to plural SCMs located subsea via umbilical 130.

[0056] The subsea production system 100 may also include onshore apparatus 150 by which the operator of the production system may monitor and control certain components and functions of the subsea production system 100 from onshore, live and in real time, or offline. For example, the logical components and software and data storage architecture making up the subsea production control system (described in more detail below) maintained in the MCS or in particular the FMS thereof) may be duplicated or synchronised to one or more onshore locations. Further, while not shown, plural subsea production systems 100 may be coupled, for example via onshore apparatuses 150, to a centralised production monitoring system, which may, for example, be used to aggregate information about the performance and operation of the plural subsea production systems 100 across different fields. Analysis of the aggregated information be shared among operators of subsea production systems to facilitate their management and optimisation, and may be used to facilitate and improve the designing and installation of production systems to improve yields and efficiency.

[0057] Referring to Figure 2, at the equipment level, across one or more of the locations the subsea production apparatus 100 shown in Figure 1, the subsea production apparatus 100 may include a subsea production control system 200 in accordance with certain examples of the present disclosure.

[0058] The subsea production control system 200 may include various components configured to operate together to enable the monitoring of the condition and the performance of and the control of various components and subsystems of the subsea production system 100, such as the pumps. The various components supporting the subsea production control system 200 may be provided at or across one or more of the locations of the subsea production apparatus 100 as described in relation to Figure 1. It is to be understood that the example arrangement of the components of the subsea production control system 200 described in the following passages is not intended to be limiting. Indeed, variations in the locations of the various components and data processing are envisaged to fall within the scope of the present disclosure.

[0059] The subsea production control system 200 may include one or more subsea control modules SCMs 210a,b...n. These are typically provided in one or more centralised locations as subsea apparatus 120 and may be configured as shown to contain plural Subsea Electronics Modules SEMs 212a,b...n sealed inside a cylindrical canister in a controlled environment.

[0060] The SEMs 212a,b...n provide a data communications interface with components of the subsea production system 100, including various Condition and Performance Monitoring apparatuses CPMs 240a,b...n. The different CPMs 240a,b...n comprise different sets of sensors or other instruments or hardware arranged to monitor the condition and performance of different components of the subsea production apparatus 100. Each of the CPMs 240a,b...n provides one or more of the SEMs 212a,b...n with sensor data which the SEMs 212a,b...n may pass on or partially or fully process and relay to a Master Control Station (MCS) 220.

[0061] In the example, the MCS 220 may be located topside and is coupled to the SCMs 210a,b...n and SEMs 212a,b...n to send and receive monitoring and control data there with via an umbilical (as shown in Figure 1). However, it is specifically envisage that one or more or all of the components of the MCS 220 may be provided at locations exclusively subsea, or the components of the MCS 220 may be provided across various locations, for example subsea and topside.

[0062] In examples of the present disclosure, the MCS 220 may include a Field Management Server (FMS) 222, which may be provided as a server in a server rack of the MCS 220. The FMS 222 may be provided to receive and process condition and performance monitoring data, received as streaming sensor data, from the CPMs 240a,b... n via the SEMs 212a,b...n. As will be explained in further detail below, the FMS 222 may, in accordance with examples of the present disclosure, implement in software a Pump App that provides a pump monitoring system that may monitor the operating condition of the pump based on the pump CPM data at a high sampling rate and may provide an operator with a continually updated report of the actual performance of the pump online at the same time the pump is in operation, effectively in real time in relation to the instant performance of the pump. The reporting of the actual performance of the pump may be at a user interface of a workstation 230 located topside or even onshore, for example in the form of a live pump performance plot. In the example embodiment, the FMS 222 is co-located or located in the MCS 220 but in other examples, one or more or all of the hardware and/or software components of the FMS 222 could be provided at locations subsea, topside and/or onshore.

[0063] By monitoring the condition and performance of these subsea production apparatus 100 using the subsea production control system 200, the subsea production control system 200 may automatically, semi-automatically or by manual operation by an operator at workstation 230 generate one or more control signals which may be transmitted to one or more components of the subsea production apparatus 100, for example via the umbilical, to control their operation and configuration.

[0064] For example, the MCS 220 may generate control signals for the operation of various valves and instruments 250a,b...n of one or more components of the subsea production apparatus 100 which may be transmitted to those components via one or more of the SEMs 212a,b...n. Similarly the MCS 220 may generate control signals for the operation of a control system 260 or a variable speed drive VSD 270, for example of a motor driving a pump for pumping product. In accordance with some examples of the present disclosure, the operation of the pump application at the FMS 222 may identify, effectively in real time, a pump shaft speed that would produce an optimal operational efficiency for pumping the product and this may enable the MCS 222 to automatically, semi-automatically or manually, by user operation at a workstation 230, to control a shaft speed of a pump (for example using VSD 270) to efficiently pump the product from the well. Similarly, the operation of the pump application at the FMS 222 may identify, effectively in real time, when the pump is being operated in a state which risks excessive wear on the pump components and this may enable the MCS 222 to automatically, semi-automatically or manually, by user operation at a workstation 230, to control a shaft speed of a pump (for example using VSD 270) or other operational control mechanisms to pump the product from the well in a way such that excessive wear of the pump is avoided.

[0065] Turning now to Figure 3, in an abstracted view of example subsea production control systems 200 of the present disclosure, a software architecture of a subsea production control system 200 is provided that may enable improved operational efficiency and effectiveness by providing a platform which is flexible and scalable enough to meet the requirements from a wide range of applications, such as CPMs 240a,b...n. According to some of the example embodiments, such a scalable architecture may be provided with a Service Orientated Architecture to allow for decoupling between components and ease the process of building and changing system components incrementally. Patterns for asynchronous and event driven information exchange are used to make sure that the platform scales and may handle increased processing capacity requirements.

[0066] Referring also Figure 4, this shows components which may be included in a Field Management Server (FMS) 222 and subsea production control system 100 in accordance with some examples of the present disclosure. The FMS 222 may include a communications module 410 for transmitting and receiving data from various components of the subsea production control system 100, including receiving data from the CPMs 240a,b...n received via SEMs 212a,b...n, and transmitting and receiving data with workstation 230. The workstation 230 may be provided by a general purpose computer accessing software, such as a Pump App, or data, served by FMS 222.

[0067] The FMS 222 further includes a bus 405 logically coupling the communications module 410 with one or more processors 420a,b... n and data storage 430 to transfer data and signals therebetween. The storage 430 may include volatile memory such as random access memory (RAM) 432 which the processors 420a,b...n may read from and write to to instantiate one or more applications in a runtime session and implement instructions codifying these applications read from persistent storage 434 such as a solid-state drive. The processors 420a,b...n may also read data from persistent storage to facilitate the operation of various applications. For example, the processors 420a,b...n may retrieve data from a pump performance prediction model 436 stored as a lookup table (LUT) to enable the pump’s application 432 to provide a real-time plot of actual versus predicted pump performance.

[0068] The implementation of application software in the FMS 222 may provide processing circuity that implements a data or logic controller. Processing circuitry or circuitry such as the circuitry implemented in the controller provided by the Pumps App 432 or SCM app 434 of examples described herein may be, as described above, general purpose processor circuitry configured by program code to perform specified processing functions. In other examples, the processing circuitry may be special purpose processing circuitry for implementing the corresponding function by modification to the processing hardware. Configuration of the circuitry to perform a specified function may be entirely in hardware, entirely in software or using a combination of hardware modification and software execution. Machine-readable instructions may be used to configure logic gates of general purpose or special-purpose processing circuitry to perform a processing function. Program instructions may be provided on a non-transitory medium such as storage 430 or via a transitory medium. The transitory medium may be a transmission medium.

[0069] Processing hardware may comprise, for example, one or more processors such as processors 420a,b...n, or in other examples, very large scale integration (VLSI) circuits or field programmable gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. The storage medium 430 readable by the processor, may include volatile memory such as RAM 432 and non-volatile memory such as persistent storage 434 and/or storage elements. The volatile and non-volatile memory and/or storage elements may be a random access memory (RAM), erasable programmable read-only memory (EPROM), flash drive, optical drive, magnetic hard drive, or other medium for storing electronic data.

[0070] Program code or machine-readable program instructions for implementing the CPM apps or other layers in the hierarchy of the software architecture as described herein in relation to Figure 3 may be implemented in a high level procedural or object-oriented programming language. However, the code may be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language, and combined with hardware implementation.

[0071] Referring again to Figure 3 in particular, data from the different CPMs 240a,b...n is received via SEMs 212a,b...n at a hardware and software platform 320 of the FMS 222. Typically, the CPM data is received as a live data stream at a high sampling rate. For example, for the pump CPM sensors, proximity and vibration sensor data is received in a data stream with a sampling rate of 12 kHz. An appropriate protocol for the data stream, such as Real-time Transport Protocol (RTP), is used.

[0072] From there, be received CPM data is passed up to the next player in the software stack in which the data is processed by fundamental methods and data validation software 330, which may be based on inventory information regarding the CPM sensors and other data models in order to validate data and prepare it to conform to a universal data format. From there, the processed CPM data is immediately published onto a data bus. The data bus may function as a messaging (publish/subscribe) system that is capable of handling large amount of data from different producers (publishers). Each producer may typically publish data from a single data source, but each source might receive data from many data points. Consumers may receive the data by subscribing to them. This will allow real time data to flow from a producer to one or more consumers.

[0073] At the next level up in the FMS software architecture, one or more modularised software components may be provided as CPM “Apps” 340. As described in relation to Figure 4, these may be instantiated in a RAM 432 of the FMS 222 by one or more of the processors of the FMS 222 carrying out instructions that codify the CPM Apps 340 stored in persistent storage 434. Each CPM App 340 effectively causes the FMS to provide a data or logic controller by implementing and operating appropriately configured processing circuitry in the FMS hardware.

[0074] As can be seen in Figure 4, the FMS 222 can implement a Pumps App 342 for monitoring the condition and performance of one or more subsea pumps, and a Subsea

Control Module (SMC) App 344 for monitoring the condition and performance of one or more SMCs 210a,b,...n. Further CPM Apps 346, 348... can be developed and implemented by FMS 222.

[0075] In accordance with the software architecture, CPM software apps can be developed and implemented in a modularised fashion that subscribe to and consume selected data published to the data bus by the FMS 222. If the subsea production control apparatus 200 is configured such that the CPM data is published to the data bus in a universal data format independently of the different specific configuration and operation of the CPM apparatuses 240a,b...n, then the CPM Apps 340 can be developed to operate in a decoupled fashion, independently of the different CPM apparatus used, and the data processing and the monitoring and control provided by the CPM Apps 340 can be more standardised and comparable between equipment, wells and fields.

[0076] Referring again to Figure 4, the persistent storage 434 may also be used as a permanent store of data received from CPMs 240a,b...n published data bus, which may provide a historical log of the operation and performance of the various components of the subsea production apparatus 100. Some or all of this data may also be conveyed to onshore locations 150, for example by intermittent or continuous transmission by a wired or wireless connection, or by physical transfer by one or more physical persistent data storage devices. The collection of live or historical CPM data in a universal data format from one or more fields at a centralised location, for example onshore, permits significant insights into the operational performance and condition of various subsea production apparatuses, for example by using big data analytics.

[0077] The operation of the Subsea Production Control Apparatus 200 to publish data to data bus in a universal format may perform the reformatting in the software stack of the FMS as shown in Figure 3 based an inventory of the different CPM apparatus 240a,b...n installed in the subsea production system 100. The inventory of the CPM apparatus 240a,b...n may be populated supported by the SEMs 212a.b...n. The SEMs 212a.b...n are generally provide as physical cards that support electronic assemblies (such as printed circuit boards, PCBs) arranged in slots connected by a backplane all contained within a robust housing of the Subsea Control Modules 210a,b... n that can withstand the extreme high pressure environment subsea.

[0078] The different types of equipment, instruments and sensors provided downhole that are required to be electronically interfaced with for control and sensor data processing are often supplied from a range of different manufacturers and there has been little standardisation of the electronic operation and interfacing protocols. Thus there would be required a different card type to perform each specific role for each specific equipment type from each different manufacturer. This can lead to a proliferation of hardware requirements that would significantly complicate the SEM design and assembly process to fulfil a desired functional specification for the SEM [0079] As a result, the SEMs 212a.b...n normally consist of specific electronic assemblies (cards) dedicated to control a certain type of instrument, actuator or other equipment. Often, the cards must be themselves provided by the manufacturer of the equipment. As a result, for each type of equipment, a specific type of card may be necessary for the SEMs 212a.b...n to be able to communicate with the equipment, leading to a high number of card variants. The functionality of the card is fixed at the time of subsea deployment and the card type is programmed in the centrally stored configuration database of the SEMs 212a.b...n to allow it to function.

[0080] This approach can achieve the processing of the CPM data into a universal data format in FMS 222.

[0081] To facilitate interfacing with the CPMs and processing of the CPM data at the FMS 222 into a universal data formal, an electronic inventory of the different components making up the CPMs and the subsea apparatus connected through the SEMs 212a.b...n may be built up, for example, in the MCS 210 or the FMS 222 by cooperation with the SEMs 212a.b...n. The SEMs 212a.b...n may be configured to be software configurable or self-configurable and to contribute to the maintenance of an electronic inventory of the CPM apparatus 240a,b...n.

[0082] The FMS 222 may store in its persistent memory 424, besides monitored data, information associated with the components of the CPM apparatuses 240a,b...n. An example of information associated with the components of the CPM apparatuses 240a,b...n is the inventory. The inventory may comprise operational information or a configuration of the components of the CPM apparatuses 240a,b...n.

[0083] The inventory may include, for the different components, an identification of the component manufacturer, type, software version, communication protocol, and other identification information. The knowledge of the component identification information through the inventory may allow the MCS 210 and the FMS 222 to communicate with the CPM apparatuses 240a,b...n via the SEMs 212a.b...n for control thereof and to process and understand the data received for the monitoring of the condition and performance of the subsea apparatus monitored by that CPM apparatus.

[0084] United Kingdom patent application publication no. GB2531032 discloses SEMs provided by software-configurable generic card types having an electronic assembly thereon for communication with different equipment from different manufacturers. This may be achieved by providing in the electronic assembly a hardware architecture which is capable of communicating with a range of different supported equipment from different manufacturers. Then, program instructions provided on a memory storage of the generic card type in the form of firmware is capable of configuring the card in used to perform a set of electronic functions for a selected one of a plurality of defined card roles, and the different defined card roles allow the electronic assembly to communicate successfully with the different equipment from the different manufacturers. In this way, a generic card type is provided that, by the use of firmware, can be selectively configured to emulate the operation of a plurality of different proprietary cards required in the art for communication with different equipment from different manufacturers.

[0085] In this way, an inventory of the different subsea apparatus and components making up the different CPM apparatuses 240a,b...n connected through the SEMs 212a.b...n can be built up. As indicated above, this may be stored at locations in the subsea production apparatus, for example, in the MCS 210 or the FMS 212. The inventory of the different subsea apparatus may be built up in part automatically by the SEMs selfconfiguring for example on connection to the CPM apparatuses 240a,b...n, for example by the SEMs recognizing the components making up the CPM apparatuses 240a,b...n through, for example, a handshake protocol. The inventory of the subsea apparatus may be built up in part manually, by the operator using the workstation to configure the or each SEM of an SCM with the component identification information. This may be appropriate for example in brownfield sites where legacy systems are installed that cannot be automatically recognized by the SEM, or where the subsea apparatus is not designed and configured on the SEMs on or before installation. The inventory of the different subsea apparatus may be built up in part semi-automatically. That is, the SEMs may attempt to automatically generate at least part of the identification information for the CPM apparatus for the inventory, which may be checked and validated manually by an operator.

[0086] To facilitate monitoring of the subsea apparatus to ensure the identity of the subsea components is known to the MCS 210 and FMS 212, the inventory may comprise a configuration fingerprint comprising information of the CPM apparatus relating for example its geographical location, an apparatus type, sensor values, or measurement meta data. The SEMs 212a.b...n or the FMS 210 or MCS 212 may be configured to detect a change in the inventory or monitoring data and record a corresponding timestamp when the detected change occurs. This change detection may occur by comparing the configuration fingerprint for a CPM apparatus with the configuration fingerprint for the CPM apparatus stored in the inventory. In this way, the subsea production system 100 can identify when changes occur to component apparatus, for example by way of software updates or installations, etc, and the inventory can be updated accordingly. Thus the CPM apparatuses 240a,b...n can be interfaced with effectively.

[0087] The SEMs 212a.b...n or the FMS 210 or MCS 212 may correlate changes in the inventory or monitoring data with an operational state of a plurality of CPM apparatuses and further to provide a graphical representation of the correlated changes with respect to the recorded timestamps.

[0088] In operation, the different SEMs 212a.b...n may initiate a transmission, for example, to the FMS 212, of an inventory specifying an operational configuration of a subsea component associated with a corresponding CPM apparatus 240a,b...n or an operational configuration of the CPM apparatus 240a,b...n itself. The FMS 212 may utilize information from the inventory to determine an expected data format for incoming data from the associated CPM apparatus 240a,b...n. Using the knowledge of the expected data format, the FMS 212 may reformat the incoming data into a universal data format. The FMS 222 may be coupled to a standard reference timer for the subsea production control system 200, and the received data may, on being reformatted into the universal data format, include a timestamp with reference to the standard reference timer. This may facilitate historical logging and synchronisation of data received from the CPM apparatuses 240a,b...n.

[0089] It should be appreciated that each CPM apparatus 240a,b...n is associated with a different CPM component and therefore obtaining data in a variety of formats. Thus, the reformatting of received data into the universal data format allows for analytics to be performed across different types of data. The FMS 212 may also transmit any reformatted data or data analytics to a centralized data bus, as indicated above. The FMS 212 may regulate the disclosure of data on the centralized bus based on a user subscription.

[0090] Turning now to the CPM apparatuses 240a,b...n in more detail, the CPM apparatuses may be located in distinct physical locations and associated with different monitored components of the subsea oil and gas production system.

[0091] For example, one or more CPM apparatuses may also be associated with and monitor the Subsea Control Modules (SCM) themselves, which may be subsea-located components of the subsea production control system 200. The SCM CPM apparatus may include sensers: for monitoring the electrical power supply provided by a Power Supply Module (PSM); for monitoring the connectivity status, uptime, and traffic and error statistics of data-carrying communications channels; for monitoring the environmental conditions including the pressure, temperature and humidity inside the canisters providing the housing of the subsea control modules (SCM) enclosing and supporting the SEMs; for monitoring the status and utility of the SEM cards themselves and software modules implemented thereby; and for monitoring the integrity and condition of hydraulic components in the subsea production system, such as valves, valve profiles and hydraulic distribution lines.

[0092] For example, one or more CPM apparatuses may be associated with and monitor the operations of a pump. The Pump CPM apparatus may include: vibration sensors for sensing a vibration state and a vibration frequency spectrum of the pump; proximity sensors for sensing the position of the drive shaft of the pump for plotting its rotational orbit; motor cartridge sensors may sense torque, slip, efficiency and cooling temperature; power system sensors for sensing motor current, voltage, and frequency, power usage, quality and earth insulation integrity; barrier fluid system sensor for sensing fluid consumption, accumulator status and pressure; and run time sensors for sensing an operational usage of the pump and run time statistics. A pump shaft rotational speed may be sensed directly by a CPM apparatus, or indirectly using for example a proximity sensor and an indicator disc mounted to the shaft. Shaft power and shaft efficiency may be sensed indirectly by determining them based on other sensed quantities.

[0093] Further, one or more CPM apparatuses may also be associated with and monitor the process system, for example at or in relation to the pump. The process system CPM apparatus may include: sensors for sensing a suction pressure and a discharge pressure of the product from the pump, for use in calculating a differential pressure of the pump; sensors for sensing a flow rate of the product, particularly through the pump, such as a volumetric flow rate; sensors for sensing a temperature of the product; sensors for sensing a density ratio of the product; and sensors for sensing a gas volume fraction (GVF) of the product.

[0094] The CPM Apps 340 of the FMS 222 may compile and store monitored data from the CPM apparatus and provide analytics in the form of, for example, hydraulic pressure and flow, valve profiles, electrical power efficiency, network communication, software revision and configuration, pressure, temperature and humidity monitoring and advanced electronics state monitoring. The Pump App 342, for example, may provide pump analytics including vibration and proximity (e.g., speed, orbit plot, phase spectrums and harmonics), pump cartridge (e.g., dynamic pump plot, pressure, output power, efficiency), motor cartridge (e.g., dynamic torque plot, slip, efficiency and cooling performance), barrier fluid system (e.g., consumption, working accumulators, pressure, pressure and volume regulator) and power (e.g., usage, quality and insulation).

[0095] The SEMs 212a,b...n receive live sensor data from the various CPM apparatuses 240a,b...n, processes it and sends it to the FMS 212 as a data stream. The update interval of input sensing data in the data streams may be at a sample rate of at least 100

Hz, optionally at least 1000 Hz, optionally at least 5000 Hz, optionally at least 10 kHz, optionally 12 kHz.

[0096] Referring to Figures 5A and 5B, a subsea pump 500 is illustrated showing its key components and some components of the pump CPM apparatus for providing sensor data to the Pumps App 432 in a live stream of sensor readings. The subsea pump 500 comprises a shaft driven by a motor 510 which may be a variable speed drive. The shaft 505 is connected to a pump 520, which may be a centrifugal pump including one or more impellers, which creates a differential pressure as a difference between a suction pressure and a discharge pressure for pumping product in a flow line. Pump CPM sensor components for monitoring the running of the pump may be provided at locations around the drive shaft bearings at a Motor Non-Drive End (MNDE) 532, Motor Drive End (MDE) 534, Pump Drive End (PNDE) 536 and Pump Non-Drive End (PNDE) 538. The sensors shown in Figure 5A can be used to identify pump shaft vibration, orbit to help identify wear, and rotational speed.

[0097] The core input data for the algorithms and resulting calculations and views are the high-speed signals from the accelerometers radial and axial and x and y proximity probes placed around the bearings of the pump shaft at the Motor Non-Drive End (MNDE) 532, Motor Drive End (MDE) 534, Pump Drive End (PNDE) 536 and Pump Non-Drive End (PNDE) 538. There is at least one accelerometer measuring radial vibration in mm/s^A2 on each of the four positions. As shown in Figure 5B, there are also at least two proximity probes x and y measuring the distance to the shaft in pm at each of the four positions. The proximity x and y probes are placed 90° from each other and serves as input to the Orbit plots, the figure below illustrates the sensor setup.

[0098] At MDE 534 and PDE 536 there are also axial vibration sensors as well as proximity probe measuring distance in the z direction. These sensors monitor the magnitude of vibrations on the mechanical seal between the motor and the pump module. On the MDE 534 the proximity z sensor measures the distance to a speed disc (not shown), the signal from this sensor is input to the Pump App 432 to calculate a rotation speed, a rotation direction, by algorithms that identify in the proximity z sensor data a series of marks on the of the shaft.

[0099] Thus pump CPM components shown in Figure 5 provide a live stream of sensor data to the Pump App 432 which includes algorithms to contemporaneously and continuously process the live stream of data on the data bus and provide an operator at workstation 230 with views and live updates for: pump shaft vibration frequency spectra; pump shaft rotational speed; bode plots; and orbit plots and orbit alignment. Further Pump CPM components may be provided to monitor other aspects of the pump performance for processing by the Pump App 432. The sensor data from the Pump CPM Apparatus and the processing thereof in accordance with various examples of the present disclosure will be described further below in relation to Figures 6, 7 and 8 in particular.

[00100] Figure 6 shows data flows from one or more CPM apparatuses 240a,b...n including a Pump CPM apparatus 612 monitoring the pump 500 and a Process CPM apparatus 614 monitoring the process system in relation to the pump 500.

[00101] Pump CPM apparatus 612 provides to the Pump App 342 a stream of sensor signals indicating the current of the pump motor 510, the motor frequency, the motor cooling temperature, and also z proximity probe data from the MDE 534 indicative of the rotation of the speed disc connected to drive shaft 505.

[00102] Process CPM apparatus 612 provides to the Pump App 342 a stream of sensor signals indicating: a sensed gas volume fraction of the pumped product; a sensed density ratio of the pumped product; a temperature of the flowing product; a volumetric flow rate of the flowing product; and a suction pressure and discharge pressure in the flow line before and after the pump 500.

[00103] Together, the Pump CPM apparatus 612 and Process CPM apparatus 614 produce CPM Sensor Data 610 used by the Pump App 342 to monitor the condition and performance of the pump seamlessly and in real time. The data flows from the CPM apparatuses 240a,b...n may be relayed as CPM Sensor Data 610 to the FMS Pump app 342 seamlessly and in real time, in examples as data published in a universal data format on a data bus as described above in relation to Figures 2, 3 and 4. The Pump App 342 may subscribe to the Pump CPM Sensor Data 610, which may be received at the pump app as one or more data streams on the data bus.

[00104] Reference will now be made to Figures 7 onwards, and a more detailed description will now be provided of the architecture and logical components of the subsea production control system 200, in particular the data controller provided in examples by the FMS 222, and their operation for processing data received from CPM apparatuses 240a,b...n of a subsea oil and gas production system 100 and reformatting the monitoring data into a universal data format based on an inventory specifying an operational configuration for the CPM apparatuses 240a,b...n.

[00105] Structural view [00106] Figure 7 illustrates a structural view of the organization of applications which may be found in the architecture layers of the data controller. It should be appreciated that such an organization of applications may be provided in both the offshore data controller, which may be provided, in part, by FMS 222.

[00107] It should be noted that the components of the data controller located offshore, e.g. topside at FMS 222, may be duplicated to an onshore location 150 to synchronise the data and control functions between onshore and offshore locations. As can be seen from Figure 8, plural offshore subsea production control systems 200 can be duplicated to onshore location 150.

[00108] Referring now to Figure 7, according to some of the example embodiments, the presentation layer works as a common entry point for all users of the platform. It is mainly web based, but allows product specific clients where a web based solution does not make sense. The displayed information is decoupled from the implementation details of the system and/or business logic. Information may be presented based on a user subscription.

[00109] The presentation layer may be web based and provide an integrated view to particular situations, possibly by combining information from different systems on the platform. It may provide the user with role based log-in and gives authority and access according to predefined roles. The presentation layer gives a single location where authorized personnel may find and use information adapted to their needs. For example, if a problem occurs on an offshore installation, the operator is provided with necessary tools to easily drill down and analyse the situation. He is also provided with tools that ease the collaboration with support personnel onshore.

[00110] As shown in Figure 7, examples of tools which may be utilized in the presentation layer is a process and trend module, an alarm and events module, a work flow Graphics User Interface (GUI) and an administration GUI. The presentation layer may use data streams provided by the “Data bus” layer, and services provided by the “Integration service bus” layer, to extract and present relevant information to the users. It does not interact directly with any of the components deployed on the platform.

[00111] According to some of the example embodiments, the business layer is where collected data may be processed and analysed in near real-time, producing key performance indicators for various equipment etc. In combination with knowledge of the process and the equipment, these results enable the delivery of new services. Additional value creation and operational support is provided through applications for Asset Management, Fault Management, etc.

[00112] Requirements for data processing on the offshore platform are ranging from large complex installations producing large amounts of data, to small and simple installations with less complexity and data to process.

[00113] Applications in this layer are processing data originating from one or more data source. The processing can be done to validate data (e.g., compare collected with expected value), or it can be done to analyse the data (e.g., FFT and frequency analysis). Different kinds of management applications are also part of this layer, e.g. components used to discover connected equipment and/or how equipment are configured etc.

[00114] A processing component may typically consume one or more data streams from the “Data bus” layer. These data streams may be enriched with information extracted through services on the “Integration service bus”. The processing results are published as new data streams on the data bus. These streams may be further processed, persisted in the DataStore or presented in a GUI.

[00115] With several infinite data streams flowing in at real-time speed, processing and detecting complex situations is incompatible with what data storage technologies are designed for (which is storing data for later query). Complex Event Processing (CEP) can be considered precisely the opposite of a database; data is not pushed to storage for later query, an express request for data can but utilized and run the data through in real-time speed. With CEP standard data processing capabilities are provided, such as joining or correlating two or more data streams, enriching output with historical data or use historical data to further filter a stream etc.

[00116] In summary; the processing components are consumers of data streams and services. They combine information from different sources and/or analysing events and time series. The processed data can originate from real-time acquisition systems, simulators and/or historical data.

[00117] According to some of the example embodiments, components publishing data (raw and/or processed) are feeding a data stream on the data bus. The data bus does not have knowledge of who their consumers are, or if there are any consumers at all. They are all designed to publish data without any concern for the consumers. As soon as data is published on the bus, the component may consider its task completed (and assumes that other components are taking responsibility for further processing and persistence). If there are no components taking interest of the data, the data may evaporate from the bus immediately.

[00118] Consumers of a data stream (raw and/or processed) may create a “continuous query” on the bus. The data bus may return an infinite series of data and/or events matching the criteria in the query. Consumers are not required to know which component is producing or publishing the data, they just query for specific data and trust the bus to does the necessary processing and sort out all incoming data streams.

[00119] A common domain model may describe all data transmitted on the bus, i.e., systems that do not support this model need an adaptor before they may be plugged into the system. The adaptors are doing simple translation between the domain model and the components native representation of the same objects.

[00120] The data bus is capable of routing and bridging between several buses (e.g., one offshore data bus might be connected to one or several onshore data buses and visa versa). How data flows between the buses are configurable.

[00121] According to some of the example embodiments, data that is being processed, analyzed and/or displayed in the system originates from a data source. Before data can be published by a source and used by any of the consumers, it may be transformed to a common semantic representation, or universal data format, that all components share and understand. The data sources are responsible for adapting their internal representation of an object to this common domain model. For third party systems, there will typically be an adapter between the system and the bus doing this transformation.

[00122] Data sources are all the systems producing and/or persisting information for later retrieval, e.g., various acquisition systems, Object linking and embedding Process Control (OPC) servers and third party systems such as flow simulators etc., are typical examples of data sources. Databases holding raw data, Key Performance Indicators (KPIs), events, inventory and asset configuration are also considered as data sources.

[00123] According to some of the example embodiments, real-time data is pushed on the data bus by various data sources, and made available for other components through continuous queries/subscriptions on the data bus. Services which are not directly part of this data flow may be provided by a service layer, exposed by a service bus. These are, for example, services such as read historical data, read or update configuration etc.

[00124] According to some examples, at the core of the service layer are fine grained services, exposing data and functionality provided by various components on the platform. These fine grained services may be combined and bundled to flows orchestrated by the service bus, providing new services supporting specific use cases and/or business processes.

[00125] The approach described above facilitates decoupling between producers and consumers of services. Components should either produce or consume a service, and the services shall be exposed by the service layer. Thus, components on the platform do not need to have direct connections.

[00126] According to some examples, a responsibility for the service bus is to provide a unified point of access to all systems and components on the platform. But in addition to monitoring and routing of client requests to appropriate answering components, the service bus may be used for commodity services such as data transformation, protocol conversion, exception handling etc.

[00127] There may be several interconnected service buses which are setup to offer services to each other. Typically there will be one service bus for each offshore installation, connected to one or more onshore. According to some of the example embodiments, the backend infrastructure provides components needed to ensure secure, robust interaction between applications and flexible, cost effective deployment of the platform.

[00128] Logical view [00129] Figure 9 illustrates a logical view of the data controller as described herein, where an application such as Pump App 342 refers to a logical package of functionality. This package may be built on top of several components shared between all applications running on the platform. For example, a pump condition monitoring application 342 may share an acquisition system with a data validation component, etc.

[00130] The Figure 9 shows the different components needed for the Pumps Condition Monitoring System. The grey areas indicate application specific implementations, within a component that might be shared between several applications.

[00131] Data bus: The data bus may function as a messaging (publish/subscribe) system that is capable of handling large amount of data from different producers (publishers).

Each producer may typically publish data from a single data source, but each source might receive data from many data points. Consumers may receive the data by subscribing to them. This will allow real time data to flow from a producer to one or more consumers.

[00132] According to some of the example embodiments, components on the platform participating in the real time data flow, may not communicate directly with each other. They may be producers and/or consumers of data exposed by the data bus. This ensures loose coupling between the components.

[00133] An example of a real time data flow can be an acquisition system publishing a signal (a data stream) on the data bus. This stream of data can be picked up by any component which is connected to the data bus. This component can the process the data and publish the results on the data bus (as a new signal), and so on. Clients of the data bus may log on to the data bus. When logged on, clients will have access to all the streams published by the data bus.

[00134] WEB Backend: The WEB backend may be used to serve clients visualizing the collected and processed data. It decouples the platform components from its clients and provides a consistent and well defined REST API. This ensures loose coupling and makes it possible to change the components without affecting the clients.

[00135] The services published by the WEB Backend are called online services, as opposed to real time services on the data bus. Clients may be authenticated before they are allowed to consume any of the services.

[00136] RTP Adapter: A special purpose condition monitoring card may be utilized for the subsea pumps. This is a card capable of doing high-speed data acquisition, handling sampling rates up to 10-15 kHz. Data from this card may be streamed to the top-side system over the RTP protocol. The RTP adapter may function as a data source.

[00137] Examples of responsibilities for the RTP Adapter are:

[00138] · Discovery and configuration of acquisition chain [00139] · Connection handling towards the condition monitoring card [00140] · Consume data streams containing high-speed data [00141] · Transform data streams to the domain model [00142] · Push the received data on to the data bus.

[00143] SCMP Adapter: SEM nodes may collect housekeeping and process data subsea. The data can be read topside over the SCMP protocol. The SCMP Adapter is communicating with SEM nodes to collect necessary housekeeping data for condition monitoring of subsea electronics. The SCMP adapter may act as a data source.

[00144] OCP Adapter: The OPC Adapter is an OPC client, collecting data from OPC servers and making it available in the subsea oil and gas system. This component may act as a data source.

[00145] Example responsibilities for the OPC Adapter are:

[00146] · Discovery and configuration of acquisition chain [00147] · Connection handling towards OPC servers [00148] · Consume data from OPC servers [00149] · Transform OPC data to the domain model [00150] · Push data on to the data bus, to make it available for use in the subsea system.

[00151] File Streamer: The File streamer is a component picking up data points from one or more files. The component may support various file formats and may act as a data source.

[00152] Example responsibilities for the File streamer are:

[00153] · Discovery and configuration of acquisition chain [00154] · Parse various data files and transform data to the domain model [00155] · Push data on to the data bus, to make it available for use in the subsea oil and gas system.

[00156] This component may be used as a simulator, pushing predefined streams of data on the bus simulating various behaviour of subsea equipment.

[00157] Data Store: The data store can store all kinds of data, for example, unformatted raw data, processed data, various KPIs, inventory data and so on. All data originating from data points may have a corresponding tag name, a quality code, and a timestamp. The time for which the data should be available in the data store (time-to-live) can be set per table. Whenever the time-to-live expires, the data store is free to delete the data.

[00158] The component may provide the following functionality:

[00159] · Configuration of data storage [00160] · Aging and clean-up according to current configuration [00161] · Provide services to read time series or snap-shots from the storage [00162] · Provide services to update data in the storage [00163] · Moving data to data archive [00164] Discovery system (not shown): The various data acquisition systems may be able to publish information about what data points they can deliver, default configuration and how they can be configured. This information may be published periodically on the data bus, and is picked up by the inventory module. The information may be stored in the inventory data store. The inventory module may be able to detect that an acquisition system is no longer publishing information about a data point.

[00165] Data Processing Engine: The data processing engine may be consuming the data streams which are being published on the data bus. A series of operations, or algorithms, are applied to these streams - producing new streams of data with increased value for the user. The algorithms in use can be mathematical computations on one specific stream of data, or they can correlate data in several streams with historical data or recent events, etc. The data processing engine may provide a framework where algorithms can be deployed, utilizing modern techniques for parallel processing through hardware and software parallelism. Any number of algorithms can be deployed, for various application usages.

[00166] Inventory (see Figure 7): The inventory module comprises information about all the fields and their installed equipment. Inventory is a registry of items describing static aspects of the monitored system. These items give a clue about physical and logical position of the signal source, it’s location in the hierarchy of different components in the field and additional meta information as e.g. alarm context. The information is divided into three logical types I main information carriers:

[00167] · Facility. A facility can represent the whole world or a single oil field. A facility can contain other facilities or system [00168] · System. A system represents some physical equipment, e.g. a SEM. A system can contain other systems (subsystems) or signals. For each system, the serial number and type can be stored [00169] · Signal. A signal represents a signal from a single data point. For each signal, the tag name, engineering unit and sampling rate will be stored.

[00170] System Log (see Figure 7): Alarms and events may be used when describing discrete changes for the physical processes, including equipment and devices. These events may be used for surveillance of the process. In a similar fashion all significant actions performed by users of the platform may be tracked in the system log. This log provides a system which keeps track of all activities and actions on “system level”. For example, all actions are logged with user name and timestamp to provide full traceability of actions that might influence services or the physical process (or monitoring of the process). For example, user actions such as changing configuration, updating alarm limits or stopping acquisition of a data point is typically stored in the audit log (which is a logical part of the system log). The audit log provides basic functionality for traceability of actions, such as persisting and searching the log entries.

[00171] Basic Alarm and Event functionality may be provided through functionality such as:

[00172] · Alarm and event archiving [00173] · Alarm and event filtering (such as display current active alarms and events etc) [00174] · Clear active alarms and events [00175] · Add reason / description to alarms and events [00176] · Aggregate, correlate and drill-down alarm and events [00177] · Alarm and event notification: email (and sms) [00178] Domain Model: A common domain model may be shared between all components on the platform. This model may be optimized and adapted to special needs with regards to transport mechanisms and the processing done on the data. The model allows various users to be provided with different views of equipment and devices in the system. External clients will not be exposed to the domain model, they will instead see an external representation of the domain model. This means that the internal model may be changed without affecting the external clients.

[00179] Web Application: The web-app may provide a consistent look and feel to all components on the platform. It may give a way to access the system without being concerned about the underlying components, for example, functionality on the platform can be used without knowledge about which components are providing the various services. The web-app may provide security through authentication and authorization, and a fine grained service layer provides role based access.

[00180] [00181] Discovery and inventory creation and data transformation [00182] Reference will now be made to the message sequence charts in Figures 10 to 13 to describe an example operation of a data controller to discover CPM components and create an inventory therefor, and to transform the data into a universal data format.

[00183] Referring to Figure 10, to reduce the amount of configuration that needs to be performed the data acquisition chain may be implemented as a push model, i.e. streaming the data from subsea to topside acquisition system. As can be seen, the subsea equipment connects to the topside acquisition system, delivers necessary meta information for each data point and starts streaming the data according to the sequence diagram below.

[00184] The mechanism described, is implemented to reduce sources to errors and amount of manual work that must be done to configure and set-up a new system. The sequence diagram in Figure 10 shows how “discovery” is done for a high speed Digital Processing Card (DPC) - which may be a SEM - for a pump.

[00185] The acquisition system can be connected to several DPCs/SEMs, and receive meta data from all these modules. The received information is aggregated and periodically published as inventory messages on the data bus and stored in the inventory component of the data store, as shown in Figure 7.

[00186] Referring now to Figure 11, the RTP Adapter uses the data bus client to open a connection (output stream) towards the data bus. To open the output stream, the adapter must pass inventory information to the data bus client. As long as the output stream is open, the data bus client will periodically (e.g. once every minute) trigger an event with inventory information on the data bus. These events are picked up by the inventory topology (in the data processing layer). The inventory topology will then call the inventory service which will insert/updates the information in data store.

[00187] When the output stream is closed by the acquisition system, the inventory information will no longer be published. This will be discovered by the inventory topology which again will call the inventory service to mark the signal as lost.

[00188] When the DPC card is configured to enable acquisition for data points, one connection is established for each data point, providing one separate stream of data for each of them.

[00189] The sequence diagram of Figure 12 shows how the DPC is establishing one connection for each data point. When the connection is established, an infinite stream of data starts flowing from the DPC to the RTP adapter. This system receives the samples, and adds them to the data bus one by one via an output stream. The data bus aggregates samples for one second and transports second chunks internally.

[00190] When the persistence topology is granted execution time by the data processing framework, it reads samples from the data bus until there are no more samples to read, or the maximum no of samples to read in each execution slot is reached. The topology aggregates samples for one second, before sending the samples to the historian service. The historian service inserts the data in storage (see Figure 7).

[00191] Processing of data for condition monitoring of a pump is done by pump topologies, running in the data processing layer.

[00192] The sequence diagram of Figure 13 is logically connected to the sequence diagram shown in Figure 12. It picks up raw data published by the pump acquisition system.

[00193] The pump topology opens an input stream against the data bus for each data point it wants to receive data from. When the topology is granted execution time by the data processing framework, it reads samples from the data bus until there are no more samples to read, or the maximum no of samples to read in each execution slot is reached. The samples are read one by one, but the topology buffers them for one second, before emitting the samples to the data processing layer. The data processing layer will then pass the samples on to the next component within the topology, and so on.

[00194] When the data has gone through all processing steps and finally reach the endpoint of the topology, the results are emitted to the data bus via output streams opened for the processed data. The samples are published one by one on the output stream.

[00195] Processed data that are published on the data bus will also be picked up by the persistence topology and persisted. It is also possible for the topologies to publish temporary data on the data bus. Temporary data will not be persisted. FFT data is an example of temporary data.

[00196] Specific Work flow examples [00197] Figure 14 illustrates a sequence diagram of a typical data flow from a CPM apparatus sensor, such as a vibration sensor or accelerometer, to the data controller platform presenting such data to a user. According to some of the example embodiments, the data stream is processed in two steps; first data validation and then a Fast Fourier Transform (FFT) algorithm may be used to transform the data to the frequency domain. The user may be watching the data in real-time, looking for unwanted patterns both in time and frequency domain.

[00198] The following is an explanation of the example steps illustrated in Figure 14:

[00199] 1: Data may sampled periodically and delivered to the acquisition system where the received data is transformed to the domain model.

[00200] 2: The collected data may be passed on as a continuous, infinite data stream to the Data Bus.

[00201] 3: The raw data may be persisted in the historian (which may subscribe for all raw data going through the bus).

[00202] 4: The same data may be passed on as a stream from the Data Bus to the DataValidation component (which may be subscribing for raw data from this specific sensor). The published sensor data may go through a quality control and corresponding quality codes are updated.

[00203] 5: When data validation is done, the DataValidation component may feed the data back to the Data Bus (with updated quality codes).

[00204] 6: The GUI may subscribe for validated data from this specific sensor. The received data is used to update a trend display continuously.

[00205] 7: A Condition Monitoring system (CM) may subscribe for data which has been through data validation. The received data may be transformed to the frequency domain through an FFT algorithm.

[00206] 8: The transformed data may be returned as a new data stream on the Data Bus.

[00207] 9: The GUI may subscribe for the frequency domain data from this specific sensor. The received data stream may be used to continuously update a frequency spectrum display.

[00208] 10: The historian may be concerned about the dominant frequency in the frequency spectrum. For example, the dominant frequency may be read from the data bus and persisted.

[00209] Figure 15 illustrates a sequence flow diagram of how the onshore data controller may include a service offered by the offshore data controller, thus depicting how the two controllers may interact with one another in obtaining data and information.

[00210] The following is an explanation of the example steps illustrated in Figure 15:

[00211] 1: A request for a specific time series from a specific sensor may be submitted to the service bus on the onshore platform.

[00212] 2: A lookup may be done to check if the data exists in the internal raw data storage I historian (on the onshore platform).

[00213] 3: Result is returned from the Historian (see Figure 7) (requested data does not exist).

[00214] 4: The request may be forwarded to the service bus on the offshore platform which is the “owner” of this sensor.

[00215] 5: The request may be processed by the Historian on the offshore platform. A file containing the requested data is created.

[00216] 6: Name and path to the file is returned [00217] 7: The file is transferred to the onshore platform and picked up by the acquisition system.

[00218] 8: The data is transmitted as a stream of raw data on the data bus.

[00219] 9: The Historian is subscribing for all incoming raw data. The data is written to persistence [00220] 10: The GUI is still open and has an active subscription for this specific data series. The received data is displayed in various ways on the GUI [00221] Functional data flow models [00222] Easy access to a variety of views, combined with a good understanding of the semantics of the provided data is one of the example advantages of some of the example embodiments presented herein. In addition to being a system that can handle a huge amount of data, the example embodiments also provide an improved understanding of the data and the context therein.

[00223] According to some of the example embodiments, an information model with focus on semantics and different ways to view the data, rather than a “pure” data centric approach is provided. The concept is illustrated in Figure 16.

[00224] The data controller domain model provides information to understand the underlying data model. The domain model gives a common understanding of the acquired data. The data brings forth more value when it may be put it into a context. For, example a measured value might give the temperature of a liquid inside a pump or it can be the flow of a liquid, etc.

[00225] Figure 16 illustrates an example concept. The semantic model describes the underlying domain model and allow various views of the equipment for different user groups. Therefore, the users may keep their own “language” or data format and understanding of how equipment is used in their domain.

[00226] According to some of the example embodiments, a data point is the source of an infinite stream of samples flowing into the system. It can provide measured values or values derived from one or more measured values. All such data points may have unique identifiers and provide a context which can be used to understand the data.

[00227] Data points may comply with the following additional requirements:

[00228] · Unique identifiers which follow a consistent naming convention [00229] · unlimited restriction on a practical length of the identifiers [00230] · It may be possible to map the identifiers between “internal” and “external” systems, i.e. identifiers used internally on the platform might be different from tag names used by external systems.

[00231] To ensure that such requirements are met, data points may include the following static and dynamic information:

[00232] · Static information: Tag (Name, Source and Stage) and Signal context [00233] · Dynamic information: Value, Quality code and Timestamp [00234] According to some of the example embodiments, static information may be used to identify a data point, and may include meta data. The data point may be identified by a unique Tag, and the Signal context may explain what information can be extracted from the signal. For a calculated value, a list of all the data points, on which the calculations are based, may also be included.

[00235] The dynamic information may be described through a Value, a Quality code indicating whether the value may be trusted or not and a Timestamp indicating when this data was collected. Except for the Value, these attributes may be consistent and easy to interpret for a user. The value can have different types for various measuring points, e.g. it might be a simple floating point value or it might have a more complex representation.

[00236] The base model (described above) may be extended to allow more specific information for different kinds of measuring points. For example, analog and binary measuring points may be adding the following static information to what is already defined:

[00237] · Measured Analog Value: Engineering unit, Sampling rate, Measurement accuracy [00238] · Measured Binary Value: Event text when true, Event text when false [00239] In addition to measured values, derived/calculated values may also be supported. Some of these might contain the same information as a measured value, but it may be possible for a user to easily identify whether it is a derived or a measured value. Derived types may also model complex data types. For example, the value in a FFT calculated type may not hold one single value, but a two dimensional array with frequency and amplitude.

[00240] It may also be possible to add monitoring information to all data points. For example, a measured analog value might be configured with the following threshold limits: [00241] · AlarmContext: HiHi, Hi, Lo, LoLo [00242] The HiHi and LoLo thresholds generate alarms in the system. The Hi and Lo thresholds generate warnings.

[00243] According to some of the example embodiments, the systems and servers of the subsea oil and gas system may be synchronized to one common time server using a Network Time Protocol (NTP). Time may be represented in a Coordinated Universal Time (UTC).

[00244] According to some of the example embodiments, events, measured and calculated values may have a corresponding timestamp. The resolution of this time stamp may be nanoseconds and may be added as close to the origin as possible. The time stamp may be retained throughout the platform and may not be altered by any of the systems touching the data. If a value is manually updated, this may be reflected by the quality code and not by the time stamp.

[00245] When calculated values and/or events are time tagged, the timestamp may reflect the time of the originating data (not when the value was calculated or the event generated by the platform). In case the resulting value is based on a time series or a calculation where several measuring points with different timestamps are included, the timestamp to use shall be the latest one.

[00246] According to some of the example embodiments, the following data may be stored and available online for analysis and/or presentation:

[00247] · Time tagged data (e.g. raw data, process data, events and derived data), [00248] · Configuration data (for systems, devices and measurement points) [00249] · Manufacturing data (such as serial numbers, production batch, etc) [00250] · Project I Plant specific data [00251] The storage mechanisms used may support high speed data, with up to 20 kHz sampling rates.

[00252] According to some of the example embodiments, the subsea oil and gas system may include a real-time processing engine, capable to process high speed data and event streams as they flow into the system. The processing engine may provide a framework for doing calculations and correlation of information available in the data streams and/or in other parts of the system. According to some of the example embodiments, it may also be possible to update the system with new or improved calculations and algorithms without stopping or restarting the engine and without disturbing the other running calculations.

[00253] According to some of the example embodiments, the subsea system may allow several data acquisition systems to co-exist and there may be an abstraction of the interfaces to these systems. For example, adapters may be implemented to ensure proper support of the shared acquisition interface. According to some of the example embodiments, data acquisition may be non-intrusive to existing control loops. According to some of the example embodiments, data acquisition may be streaming and/or event driven. If poll based acquisition systems are introduced, adapters with configurable update rates may be created. These adapters may push data into the platform and make them appear as streams of data.

[00254] System integration [00255] Figure 17 provides an illustrative example of how third party systems (PI) may be integrated into an existing system. Depending on what functionality a third party system is providing, integration may be done through the data source layer or the data processing layer, or both. In any of such cases, the component may be adapted to the interfaces published and/or consumed by other components on the platform. As shown in Figure 17, any system may be integrated into the platform. Once it is integrated, the system may have access to services and/or data provided by all existing systems in the platform.

[00256] Throughout the description and claims of this specification, the words “comprise” and “contain” and variations of them mean “including but not limited to”, and they are not intended to (and do not) exclude other moieties, additives, components, integers or steps. Throughout the description and claims of this specification, the singular encompasses the plural unless the context otherwise requires. In particular, where the indefinite article is used, the specification is to be understood as contemplating plurality as well as singularity, unless the context requires otherwise.

[00257] Features, integers, characteristics, compounds, chemical moieties or groups described in conjunction with a particular aspect, embodiment or example of the invention are to be understood to be applicable to any other aspect, embodiment or example described herein unless incompatible therewith. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and/or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features and/or steps are mutually exclusive. The invention is not restricted to the details of any foregoing embodiments.

The invention extends to any novel one, or any novel combination, of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel one, or any novel combination, of the steps of any method or process so disclosed.

[00258] The reader's attention is directed to all papers and documents which are filed concurrently with or previous to this specification in connection with this application and which are open to public inspection with this specification, and the contents of all such papers and documents are incorporated herein by reference.

Claims

1. A data controller arranged to process data from a subsea oil and gas production system, the data controller comprising:

memory; and one or more processing units configured to:

receive, originating from and transmitted through at least one Subsea

Electronic Module, SEM, an inventory of a corresponding Condition Performance Monitoring, CPM, apparatus connected to the at least one SEM, the inventory specifying an operational configuration for the CPM apparatus;

receive, from the at least one SEM, monitoring data generated by the corresponding CPM apparatus;

reformat the monitoring data into a universal data format based on the received inventory; and transmit the reformatted data to a centralized data bus.

2. The data controller of claim 1, wherein the one or more processing units are further configured to receive the inventory upon a detected change in the monitoring data or the operational configuration.

3. The data controller of any of claims 1-2, wherein the one or more processing units are further configured to receive the inventory on a periodic time basis.

4. The data controller of any of claims 1-3, wherein the one or more processing units are further configured to reformat the monitoring data and transmit the reformatted data to the centralized data bus in directly upon receipt of the monitoring data.

5. The data controller of any of claims 1-4, wherein the one or more processing units are further configured to receive respective inventories from a plurality of SEMs and further configured to receive monitoring data from a plurality of corresponding CPM apparatuses.

6. The data controller of claim 5, wherein the plurality of SEMs and corresponding CPM apparatuses are located within a designated geographical area monitored by the data controller.

7. The data controller of any of claims 1-6, wherein the one or more processing units are further configured to analyse common data points of the reformatted data from a plurality of different CPM apparatuses, wherein at least two of the plurality of different CPM apparatuses provide monitoring data in distinct formats and/or physical locations.

8. The data controller of claim 7, wherein the one or more processing units are further configured to:

calculate average values and/or standard deviations of data points of the reformatted data; and alert a detected change in the calculated average value and/or standard deviation.

9. The data controller of any of claims 1-8, wherein the one or more processing units are further configured to selectively process at least a portion of the reformatted data on the centralized data bus based on a user subscription.

10. The data controller of any of claims 1-9, wherein the inventory comprises a configuration fingerprint comprising information of the CPM apparatus relating to a geographical location, an apparatus type, sensor values, or measurement meta data.

11. The data controller of any of claims 1-10, wherein the one or more processing units are further configured to detect a change in the inventory or monitoring data and record a corresponding timestamp when the detected change occurs.

12. The data controller of claim 11, wherein the one or more processing units are further configured to correlate changes in the inventory or monitoring data with an operational state of a plurality of CPM apparatuses and further to provide a graphical representation of the correlated changes with respect to the recorded timestamps.

13. The data controller of any of claims 1-12, further comprising at least one software module configured to provide a quality control analysis of the reformatted data, wherein said quality control analysis comprises at least one of a validation of values within a data range, a detection of missing data values and/or a detection or overlapping data values.

14. The data controller of any of claims 1-13, further comprising at least one software module configured to provide a normalization analysis of high frequency data of the reformatted data, wherein said normalization analysis comprises at least one of a transformation of at least a portion of the reformatted data to process data, a transformation of at least a portion of the reformatted data to root mean square values and/or a transformation of at least a portion of the reformatted data to peakto-peak values.

15. The data controller of any of claims 1-14, further comprising at least one software module configured to provide a statistical analysis of the reformatted data, wherein said statistical analysis comprises at least one of a calculation of an average data for the reformatted data and/or a calculation of a standard deviation of the reformatted data.

16. The data controller of any of claims 1-15, further comprising at least one software module configured to provide a fault management analysis of the reformatted data, wherein said fault management analysis comprises at least one of a setting of an alarm with respect to a specific data value or data trend and/or an establishment of an alarm aggregation of said set alarms.

17. The data controller of any of claims 1-16, further comprising at least one software module configured to provide an inventory management analysis of the reformatted data, wherein said inventory management analysis comprises an analysis of operational configurations changes.

18. A subsea oil and gas production system comprising at least one data controller of any of claims 1-17.

19. The system of claim 18, further comprising an equipment and operational data unit configured to:

receive, from a plurality of data controllers, reformatted data wherein at least two the plurality of data controllers comprise a distinct physical location; and store the received reformatted data.

20. The system of claim 19, wherein the equipment and operational data unit is further configured to process the reformatted data to determine at least one of lifecycle equipment management, field optimisation, predictive services, prognostics and/ or diagnostics.

21. A method for processing data from a subsea oil and gas production system, the method comprising:

processing an inventory received, originated from and transmitted through at least one Subsea Electronic Module, SEM, the inventory comprising an operational configuration for a corresponding Condition Performance Monitoring, CPM, apparatus connected to the at least one SEM;

processing monitoring data generated by the corresponding CPM apparatus, said monitoring data being received from the at least one SEM;

reformatting the monitoring data into a universal data format based on the received inventory; and generating communications to transmit the reformatted data to a centralized data bus.

22. The method of claim 21, further comprising processing the inventory upon a detected change in the monitoring data or the operational configuration.

23. The method of any of claims 21-22, processing the inventory on a periodic time basis.

24. The method of any of claims 21-23, wherein the reformatting and generating communications to transmit is performed directly upon receipt of the monitoring data.

25. The method of any of claims 21-24, further comprising processing respective inventories from a plurality of SEMs and processing monitoring data from a plurality of corresponding CPM apparatuses.

26. The method of any of claims 21-25, further comprising analysing common data points of the reformatted data from a plurality of different CPM apparatuses, wherein at least two of the plurality of different CPM apparatuses provide monitoring data in distinct formats.

27. The method of claim 26, further comprising:

calculating average values and/or standard deviations of data points of the reformatted data; and generating an alert a detected change in the calculated average value and/or standard deviation.

28. The method of any of claims 21-27, further comprising selectively at least a portion of the reformatted data on the centralized data bus based on a user subscription.

29. The method of any of claims 21-28, wherein the inventory comprises a configuration fingerprint comprising information of the CPM apparatus relating to a geographical location, an apparatus type, sensor values, or measurement meta data.

30. The method of any of claims 21-29, further comprising detecting a change in the inventory or monitoring data and record a corresponding timestamp when the detected change occurs.

31. The method of claim 30, further comprising:

correlating changes in the inventory or monitoring data with an operational state of a plurality of CPM apparatuses; and displaying a graphical representation of the correlated changes with respect to the recorded timestamps.

32. A data controller arranged to process data from a subsea oil and gas production system, the data controller comprising:

processing means to process an inventory receive, originating from and transmitted through at least one Subsea Electronic Module, SEM, the inventory comprising an operational configuration for a corresponding Condition Performance Monitoring, CPM, apparatus connected to the at least one SEM;

processing means to process monitoring data generated by the corresponding CPM apparatus, said monitoring data being received from the at least one SEM;

reformatting means to reformat the monitoring data into a universal data format based on the received inventory; and generating means to generate communications to transmit the reformatted data to a centralized data bus.

33. The data controller of claim 32, wherein the processing means is further to process respective inventories from a plurality of SEMs and process monitoring data from a plurality of corresponding CPM apparatuses.

34. The data controller of any of claims 32-33, further comprising a detecting means to detect a change in the inventory or monitoring data and record a corresponding timestamp when the detected change occurs.

35. The data controller of claim 34, further comprising:

a correlating means to correlate changes in the inventory or monitoring data with an operational state of a plurality of CPM apparatuses; and a displaying means to display a graphical representation of the correlated changes with respect to the recorded timestamps.

36. A computer-readable storing machine comprising executable instructions such that when executed by data controller to process data from a subsea oil and gas production system, the instructions comprising:

process an inventory received from at least one Subsea Electronic Module, SEM, the inventory comprising an operational configuration for a corresponding Condition Performance Monitoring, CPM, apparatus connected to the at least one SEM;

process monitoring data generated by the corresponding CPM apparatus, said monitoring data being received from the at least one SEM;

reformat the monitoring data into a universal data format based on the received inventory; and generate communications to transmit the reformatted data to a centralized data bus.

37. The computer-readable storing machine of claim 36, wherein the instructions further comprise process respective inventories from a plurality of SEMs and process monitoring data from a plurality of corresponding CPM apparatuses.

38. The computer-readable storing machine of any of claims 36-37, wherein the instructions further comprise detect a change in the inventory or monitoring data and record a corresponding timestamp when the detected change occurs.

39. The computer-readable storing machine of claim 38, wherein the instructions further comprise:

correlate changes in the inventory or monitoring data with an operational state of a plurality of CPM apparatuses; and display a graphical representation of the correlated changes with respect to the recorded timestamps.

40. A data controller arranged to process data from a plurality of Condition Performance Monitoring, CPM, apparatus in a subsea oil and gas production system, wherein the processed data is received in at least two distinct formats and said data controller to reformat all data in a universal data format.

41. A data controller substantially as hereinbefore described, with reference to the accompanying drawings.

42. An equipment and operational data unit as hereinbefore described, with reference to the accompanying drawings.

43. A subsea oil and gas production system as hereinbefore described, with reference to the accompanying drawings.

Intellectual

Property

Office

Application No: GB 1614614.4