WO2012060888A1 - System and method for providing a physical property model - Google Patents

Abstract

There is provided a system and method for creating a physical property model representative of a physical property of a region. The exemplary method comprises creating a data structure to store physical property data elements for each cell of the region in a common format. A physical property data element is transformed from a source data format into the common format. The physical property data element is stored in the data structure in the common format.

Description

SYSTEM AND METHOD FOR PROVIDING A PHYSICAL PROPERTY MODEL

CROSS-REFERENCE TO RELATED APPLICATION [0001] This application claims the benefit of U.S. Provisional Patent Application 61//311,000, filed March 5, 2010, entitled SYSTEM AND METHOD FOR PROVIDING A PHYSICAL PROPERTY MODEL, the entirety of which is incorporated by reference herein.

FIELD

[0002] The present techniques relate to a system and method for providing a physical property model representative of a physical property of a region of interest. In particular, an exemplary embodiment of the present techniques relates to providing a three-dimensional (3D) volume interpretation based on two-dimensional (2D) magnetic inversion profile data.

BACKGROUND

[0003] This section is intended to introduce various aspects of the art, which may be associated with exemplary embodiments of the present invention. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the present invention. Accordingly, it should be understood that this section should be read in this light, and not necessarily as admissions of prior art.

[0004] Many applications involve processing information about physical properties. When processing information relating to physical properties of complex systems, it may be desirable to provide a physical property model representative of physical properties that are useful for a specific purpose. In the field of hydrocarbon exploration, one example of a property that may be useful is magnetic inversion profile data. Magnetic inversion profile data may be manipulated to help hydrocarbon exploration professionals to locate hydrocarbon resources in the subsurface of the earth or to improve production of known hydrocarbon resources.

[0005] Interpretation of magnetic inversion profile data using deconvolution techniques (such as Werner and Euler Deconvolution) has long been time consuming, and labor intensive. In addition, while the computation of inversion depth solutions is digital, the interpretation of those solutions has historically been a non-digital, paper format process requiring production of large amounts of paper products from large scale plotters, the use of light tables used to organize work efforts, the creation of semi-transparencies via the light through glass to support integration of geologic and geophysical data sets, and serve as a surface to work the hand interpretation and hand contouring of interpretation surfaces. The effectiveness of the interpretation and the integration process is clearly degraded by the 2D, analog process. Furthermore, since other data (for example, seismic, gravity, electromagnetic, topography, bathymetry, Landsat) are often digital, integrated interpretation is difficult. Moreover, integration is frequently limited to example, area, or in some cases, only to qualitative states.

[0006] A known interpretation tool employs Werner Deconvolution to calculate estimates of geometry, susceptibility and depth-to-basement using profile magnetic data. Werner Deconvolution is explained in Werner, S., "Interpretation of Magnetic Anomalies at Sheetlike Bodies", Sveriges Geologiska Undersokning, Arsbok 43 (1949), No. 6, 1955) ("the Werner paper"). The technique disclosed in the Werner paper employs profiles and a small moving window, to solve a simple linear equation system for location, depth, dip and susceptibility-thickness of a dyke. The technique may be generalized to solve for a step by processing the along-line gradient.

[0007] Werner Deconvolution is an example of a widely-used deconvolution technique that is capable of being automated. An automated implementation is described in Hartman, R.R., Teskey, D.J. and J.L. Friedberg, "A system for rapid digital aeromagnetic interpretation", Geophysics, 36, 891-918, 1971.

[0008] Witherly. K., "The Use Of Volume Visualization Technology To Aid In The Interpretation Of Electromagnetic And Potential Field Data", 66th Annual Society of Exploration Geophysicists International Meeting (Denver, 11/10-15/96) expanded abstracts with author biography v.2, p.1908, 1996. (ISSN 1052-3812; Pap. no.SS 2-2; Abstract only)) ("the Witherly paper") describes volume visualization of potential field data using a known voxel volume visualization and interpretation software application. The disclosure of the Witherly paper speculates that the visualization software could act as a platform for interpretation of potential field data, although significant technical hurdles are acknowledged.

[0009] Connard and Johnson, "Technical note on integrating gravity, magnetic, well and seismic reflection data in the National Petroleum Reserve, Alaska (NPRA)", First Break, v.20, no.8, pp.520-524, Aug. 2002 (ISSN 0263-5046) provides a description of using gravity, magnetic, well and seismic data for exploration.

[0010] Canadian Patent No. 2265063 describes a system and method in which magnetic field depth solutions are calculated for a magnetic field survey. These depth solutions are defined spatially by x, y and z co-ordinates. A digital three dimensional zero matrix is constructed by a computer program to represent a prism of earth underlying the area of the magnetic field survey. The matrix is subdivided evenly into elements representing smaller bins or prisms. Unit values are assigned to those elements to which the depth solutions correspond spatially. The resulting matrix values therefore represent a density or frequency of occurrence per unit volume of the magnetic depth solution points. The matrix elements are then spread to surrounding elements by three-dimensional convolution methods using Gaussian wavelets in each of three directions, thereby smoothing the data. The resulting data volume, or three dimensional digital matrix is then converted to a format compatible with a computerized seismic data visualization and interpretation tool and loaded into the tool. The integrated analysis of aeromagnetic depth solution data with seismic data is thereby enabled.

[0011] Pearson et al, "Aeromagnetic Structural Interpretation Using Neural Networks: A Case Study From The Northern Denver- Julesberg Basin", 60TH ANNU. SEG INT. MTG. (San Francisco, 9/23-27/90) EXPANDED TECH. PROGRAM ABSTR. BIOGR. v. l, pp.587- 590, 1990. (ISBN 1-56080-013-5; Pap. No. GM1.4; 14 refs; Abstract only) describes how neural networks can be used to automate the laborious process of profile interpretation and improve the consistency, accuracy and overall quality for basement relief mapping.

[0012] European (EP) Patent Application Publication Nos. 0539018 and 0731363 disclose a method for determining depth-to-basement from aeromagnetic data. The disclosed method utilizes neural networks to automate the laborious process of profile interpretation. A network is provided having input, intermediate and output layers. A two-dimensional profile magnetic basement model is formed. Reprocessed aeromagnetic survey profiles are windowed for input to the network. The network is trained by weight adjustment using profiles from known basement structures. The trained network is tested and then applied to aeromagnetic profiles over an unknown earth formation.

[0013] What is needed is a fields data interpretation system and/or method that allows for improved processing of magnetic inversion profile data. A software tool that facilitates the presentation of visualizations that incorporate magnetic inversion profile data is also desirable.

SUMMARY

[0014] An exemplary embodiment of the present techniques comprises a method for creating a physical property model representative of a physical property of a region. The exemplary method comprises creating a data structure to store physical property data elements for each cell of the region in a common format. A physical property data element is transformed from a source data format into the common format. The physical property data element is stored in the data structure in the common format.

[0015] The physical data element may comprise magnetic field data. A survey may be conducted to measure the magnetic field data in the source format. In one exemplary embodiment, an inversion on the physical property data element is performed before transforming the physical property data element from the source data format into the common format.

[0016] According to an exemplary embodiment, a depth-to-magnetic basement value may be predicted based on the magnetic field data. A visualization of the data structure may be provided. The visualization of the physical property data element may be provided using a three-dimensional (3D) smash technique.

[0017] The visualization of the physical property data element may be provided in conjunction with other data. Data that may be displayed in conjunction with the physical property data element include gravity inversion data, interpretation guide data or reference data, to name just a few examples. In an exemplary embodiment, interpretation guide data and/or reference data may comprise a grid.

[0018] One exemplary embodiment of the present techniques comprises a computer system that is adapted to create a physical property model representative of a physical property. An exemplary computer system comprises a processor and a tangible, machine- readable storage medium that stores machine-readable instructions for execution by the processor. The tangible machine-readable instructions comprise code that, when executed by the processor, is adapted to cause the processor to create a data structure to store physical property data elements for each cell of the region in a common format. The tangible machine-readable instructions also comprise code that, when executed by the processor, is adapted to cause the processor to transform a physical property data element from a source data format into the common format. The tangible machine-readable instructions additionally comprise code that, when executed by the processor, is adapted to cause the processor to store the physical property data element in the data structure in the common format. According to the present techniques, the physical data element may comprise magnetic field data. [0019] In one exemplary computer system, the machine-readable instructions comprise code that, when executed by the processor, is adapted to cause the processor to predict a depth -to-magnetic basement value based on the physical property data element. The machine-readable instructions may comprise code that, when executed by the processor, is adapted to cause the processor to provide a visualization of the data structure. Additionally, the machine-readable instructions may comprise code that, when executed by the processor, is adapted to cause the processor to provide a visualization of the physical property data element in conjunction with other data. The machine-readable instructions may comprise code that, when executed by the processor, is adapted to cause the processor to perform an inversion on the physical property data element before transforming the physical property data element from the source data format into the common format.

[0020] One exemplary embodiment of the present techniques comprises a method for producing hydrocarbons from an oil and/or gas field using a physical property model representative of a physical property of the oil and/or gas field. The exemplary method of producing hydrocarbons may comprise creating a data structure to store physical property data elements for each cell of the oil and/or gas field in a common format. A physical property data element may be transformed from a source data format into the common format. The physical property data element may be stored in the data structure in the common format. An evaluation of the physical property data elements may be performed. Hydrocarbons may be extracted from the oil and/or gas field based on the evaluation.

DESCRIPTION OF THE DRAWINGS

[0021] Advantages of the present techniques may become apparent upon reviewing the following detailed description and drawings of non-limiting examples of embodiments in which:

[0022] Fig. 1 is a process flow diagram showing data acquisition, data formatting, data importation and loading, and data interpretation in accordance with an exemplary embodiment of the present techniques;

[0023] Fig. 2 is depth surface map from a gravity inversion performed in accordance with an exemplary embodiment of the present techniques;

[0024] Fig. 3 is a diagram of a synthetic cube for use in an exemplary embodiment of the present techniques; [0025] Fig. 4 is a diagram showing predicted geometries in accordance with an exemplary embodiment of the present techniques;

[0026] Fig. 5 is a graph showing a visualization of properties of interest in accordance with an exemplary embodiment of the present techniques;

[0027] Fig. 6 is a process flow diagram showing a method for providing a physical property model, in accordance with an exemplary embodiment of the present techniques;

[0028] Fig. 7 is a process flow diagram showing a method for producing hydrocarbons from a subsurface region such as an oil and/or gas field according to exemplary embodiments of the present techniques; and

[0029] Fig. 8 is a block diagram of a computer system that may be used to perform a method for providing a physical property model according to exemplary embodiments of the present techniques.

[0030] While the present disclosure is susceptible to various modifications and alternative forms, specific example embodiments thereof have been shown in the drawings and are herein described in detail. It should be understood, however, that the description herein of specific example embodiments is not intended to limit the disclosure to the particular forms disclosed herein, but on the contrary, this disclosure is to cover all modifications and equivalents as defined by the appended claims. It should also be understood that the drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating principles of exemplary embodiments of the present invention. Moreover, certain dimensions may be exaggerated to help visually convey such principles.

DETAILED DESCRIPTION

[0031] In the following detailed description section, the specific embodiments of the present invention are described in connection with preferred embodiments. However, to the extent that the following description is specific to a particular embodiment or a particular use of the present invention, this is intended to be for exemplary purposes only and simply provides a description of the exemplary embodiments. Accordingly, the invention is not limited to the specific embodiments described below, but rather, it includes all alternatives, modifications, and equivalents falling within the true spirit and scope of the appended claims.

[0032] At the outset, and for ease of reference, certain terms used in this application and their meanings as used in this context are set forth. To the extent a term used herein is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in at least one printed publication or issued patent.

[0033] As used herein, the terms "basement" or "basement rock" refer to those formations below the bottom of sedimentary rocks.

[0034] As used herein, the term "computer component" refers to a computer-related entity, either hardware, firmware, software, a combination thereof, or software in execution. For example, a computer component can be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. One or more computer components can reside within a process and/or thread of execution and a computer component can be localized on one computer and/or distributed between two or more computers.

[0035] As used herein, the terms "computer-readable medium", "tangible machine- readable medium" or the like refer to any tangible storage that participates in providing instructions to a processor for execution. Such a medium may take many forms, including but not limited to, non-volatile media, and volatile media. Non- volatile media includes, for example, NVRAM, or magnetic or optical disks. Volatile media includes dynamic memory, such as main memory. Computer-readable media may include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, magneto-optical medium, a CD-ROM, any other optical medium, a RAM, a PROM, and EPROM, a FLASH- EPROM, a solid state medium like a holographic memory, a memory card, or any other memory chip or cartridge, or any other physical medium from which a computer can read. When the computer-readable media is configured as a database, it is to be understood that the database may be any type of database, such as relational, hierarchical, object-oriented, and/or the like. Accordingly, exemplary embodiments of the present techniques may be considered to include a tangible storage medium or tangible distribution medium and prior art- recognized equivalents and successor media, in which the software implementations embodying the present techniques are stored.

[0036] As used herein, the terms "controlled source electromagnetic" or "CSEM" refer to methods that employ electromagnetic (EM) transmitters, called sources, as energy sources, and the receivers measure the responses of the geological structures to the transmitted signals. The transmitter may be a direct current (DC) source, which injects a DC current into the geological formations. DC currents are typically injected into the formations using contacting electrodes. Recent EM measurement methods use EM sources that produce time- varying electrical and/or magnetic fields. The EM fields may be a pulse- generated by turning on and off an EM transmitter, and in this case, the receivers effectively measure a pulse response of the geological structures. EM measurements may use a transmitter that transmits a fixed frequency or a range of frequencies. The higher frequency EM sources permit resolution of finer structures, whereas the lower frequency EM sources allow one to probe deeper into the formations.

[0037] As used herein, "horizons" or "seismic horizons" are mechanically marked boundaries in the subsurface structures that are deemed important by an interpreter. Marking these boundaries is done by interpreters when they interpret seismic volumes by drawing lines on a seismic section. Each line represents the presence of an interpreted surface at that location. An interpretation project typically generates several dozen and sometimes hundreds of horizons.

[0038] As used herein, "impedance" is the product of seismic velocity and the density.

Impedance typically varies among different rock layers, e.g., opposing sides of an interface have different impedances. Two types of impedance terms are generally defined, I_p and I_s, wherein I_p is P-wave impedance, also called acoustic impedance, and I_s S-wave impedance.

The reflection coefficient of an interface generally depends on the contrast in the velocities and densities of the rock on either side of the interface. Specifically, the contrast in these properties of geological layers affects the reflection coefficient at the boundary separating the two layers. One geophysical process for determining the velocity and/or the density structure of a subsurface region based on recorded seismic reflection data is seismic inversion.

[0039] As used herein, the term "inversion" refers to a process by which one attempts to find a model of one or more properties that reproduce the measured response of data such as CSEM data or seismic data within a tolerance and satisfies geological and geophysical constraints. There are a large number of well-known methods of inversion. These well- known methods fall into one of two categories, iterative inversion and non- iterative inversion. Non-iterative inversion is accomplished by assuming some simple background model and updating the model based on the input data. In comparison, iterative inversion uses the updated model as input to another step of inversion. Moreover, an inversion process may refer to the iterative process of using forward modeling to transform information from the model domain into the data domain and using misfit to adjust either information in the model domain or data in the data domain so that a physical property model in the model domain more closely approximates an actual region. [0040] As used herein, the term "magnetotelluric (MT) analysis" refers to an established technique that uses measurements of naturally occurring electromagnetic fields to determine the electrical resistivity, or conductivity, of subsurface rocks. An MT survey employs time series measurements of orthogonal components of the electric and magnetic fields, which define a surface impedance. This impedance, observed over a broad band of frequencies and over the surface, determines the electrical conductivity distribution beneath that surface, with horizontal layers of the earth being mathematically analogous to segments of a transmission line. Factors affecting the resistivity of subsurface materials include temperature, pressure, saturation with fluids, structure, texture, composition and electrochemical parameters. Resistivity information may be used to map major stratigraphic units, determine relative porosity or support a geological interpretation. A significant application of MT surveying is oil exploration. An MT survey may be performed in addition to seismic, gravity and magnetic data surveys. A combination of data from two or more different survey methods leads to a more complete understanding of subsurface structure than may be possible through the use of any single technique alone, particularly where the structure is such that measurement using a given technique may be contraindicated.

[0041] As used herein, the term "property" refers to a characteristic associated with different topological elements on a per element basis.

[0042] As used herein, "receivers" are devices that are adapted to receive signals transmitted as part of a data gathering process. For example, seismic receivers are adapted to receive transmitted seismic signals and EM receivers are adapted to receive transmitted EM signals. Receivers may be used to collect observed data that may be stored in the data domain.

[0043] As used herein, the term "sedimentary rock" refers generally to rock formed by the accumulation and cementation of mineral grains transported by wind, water, or ice to the site of deposition or chemically precipitated at the depositional site. Sedimentary rock includes source rock.

[0044] As used herein, the term "seismic data" refers to information collected by creating seismic waves with sources of seismic energy and observing the arrival times and amplitudes of the waves reflected from interfaces with contrasting acoustic velocity and/or bulk density or refracted through high-velocity intervals. These data are processed using procedures such as filtering, removing of multiples, muting, stacking, and migration. [0045] As used herein, the term "source rock" refers to rocks capable of producing hydrocarbons.

[0046] Some portions of the detailed description which follows are presented in terms of procedures, steps, logic blocks, processing and other symbolic representations of operations on data bits within a computer memory. These descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. In the present application, a procedure, step, logic block, process, or the like, is conceived to be a self-consistent sequence of steps or instructions leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, although not necessarily, these quantities take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer system.

[0047] It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussions, it is appreciated that throughout the present application, discussions using the terms such as "adjusting", "comparing", "computing", "creating", "defining", "determining", "displaying", "limiting", "obtaining", "processing", "performing", "predicting", "producing", "providing", "selecting", "storing", "transforming", "updating" or the like, refer to the action and processes of a computer system, or similar electronic computing device, that transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices. Example methods may be better appreciated with reference to flow diagrams.

[0048] While for purposes of simplicity of explanation, the illustrated methodologies are shown and described as a series of blocks, it is to be appreciated that the methodologies are not limited by the order of the blocks, as some blocks can occur in different orders and/or concurrently with other blocks from that shown and described. Moreover, less than all the illustrated blocks may be required to implement an example methodology. Blocks may be combined or separated into multiple components. Furthermore, additional and/or alternative methodologies can employ additional, not illustrated blocks. While the figures illustrate various serially occurring actions, it is to be appreciated that various actions could occur concurrently, substantially in parallel, and/or at substantially different points in time. [0049] One exemplary embodiment of the present techniques comprises a software tool that loads and formats magnetic data and inversion solutions into a 3D volume. Data obtained in a native or source format is transformed into a common format so that it may be more easily studied by way of a visualization of data representing a plurality of properties of interest at the same time using the common format.

[0050] Physical property models produced in accordance with an exemplary embodiment of the present techniques may allow the preparation of useful visualizations of information related to a subsurface environment. Moreover, exemplary embodiments of the present techniques may be used in conjunction with known visualization tools such as Voxel-Geo to provide interpretation volumes from 2D and 3D inversion elements. Thus, exemplary embodiments provide a digital platform for interpretation, and facilitate the interpretation of depth inversion solutions, while integrating multiple geophysical and geologic data types. Interpretation efficiency may be achieved, while mitigating the negative drawbacks of the analog method of interpretation.

[0051] In order to search for hydrocarbon accumulations within the Earth, geoscientists use remote sensing methods to "look" below the Earth's surface. The Earth possesses a magnetic field generated primarily by sources in the core. The form of the field is roughly the same as would be caused by a dipole or bar magnet located near the Earth's center and aligned sub parallel to the geographic axis. Many rocks and minerals are weakly magnetic or are magnetized by induction in the Earth's field, and cause spatial perturbations or "anomalies" in the Earth's main field. When a ferrous material is placed within the earth's magnetic field, it develops an induced magnetic field. The induced field is superimposed on the Earth's field at that location creating a magnetic anomaly. Magnetic anomaly detection is a function of the amount of magnetic material present and its distance from the sensor. In the routinely used magnetic method, variations in the magnetic field are measured to determine the location, size, and shape of such bodies.

[0052] In hydrocarbon exploration, depth-to-magnetic basement information is used to locate basins and to define their geometries. One exemplary application of the present techniques provides depth-to-magnetic basement mapping. The magnetic susceptibility of sedimentary rock is generally orders of magnitude less than that of igneous or metamorphic rock. Consequently, the major magnetic anomalies observed in surveys of sedimentary basins usually result from the underlying basement rocks. Determining the depths of the tops of magnetic bodies is thus a way of estimating the depth-to-magnetic basement rocks and the thickness of the sediments.

[0053] Magnetic basement information may define structural high, sediment "thicks" and potential migration pathways and may determine whether or not structures are basement- involved. Burial history/maturation studies may be constrained and regional tectonic constraints may be provided through definition of large-scale basement structures. Depth-to- magnetic basement information may also be used to avoid drilling into unexpected basement or intra-sedimentary igneous rocks.

[0054] Fig. 1 is a process flow diagram showing a method of data acquisition, data formatting, data importation and loading, and data interpretation in accordance with an exemplary embodiment of the present techniques. The method is generally referred to by the reference number 100. The method 100 relates to the provision of a physical property model that includes a physical property or properties that affect magnetic survey data, e.g. magnetic susceptibility or structure dip or type.

[0055] As explained herein, magnetic survey data may be transformed from its native or source format and integrated into a common format with one or more other types of data to provide useful visualizations in accordance with exemplary embodiments of the present techniques. At block 102, the method 100 begins with the acquisition of digital magnetic profile data in a source format. For example, magnetic data such as CSEM data or MT data may be obtained by performing a magnetic survey of a region of interest. The magnetic data is typically in a raw or source format when it is obtained. Potential field data can be of any form including point data, line-oriented data or gridded data. Moreover, such potential field data may be acquired on platforms such as stationary points or moving vehicles such as boats, air, satellite or the like.

[0056] Line data may be processed to create a formatted line file, still in the source format. The line file associates grid positions with specific data values. Data corresponding to one or more properties of interest may then be associated with each cell. In populating the cells with data corresponding to properties of interest, data of varying source formats may be transformed into a common format for display with other types of data. In this manner, data related to a wide range of properties of interest may be presented in a single visualization, allowing assessments of the data to be made more easily. As explained herein, one exemplary embodiment relates to transforming magnetic profile data into a common format for the purpose of predicting a depth-to-basement value in a subsurface region. [0057] Using the magnetic data acquired at block 102, depth solutions may be calculated using magnetic inversion techniques, as shown at block 104. Estimates of rock properties and spatial elements may be calculated by running 2D profile inversion software. Such 2D profile inversion software may simultaneously solve for source rock property elements and source geometry elements. In one exemplary embodiment, the process of Werner Deconvolution is used to identify, isolate and characterize magnetic anomaly patterns to capture source depth, position, structure, dip, source type, magnetic susceptibility and source probability type. The inversion solutions are characterized by geometric elements and serve as control points for interpretation and mapping of geologic sources.

[0058] A formatted inversion solutions file may be created to store the depth solution data, as shown at block 106. The solutions file may comprise 2D magnetic profile inversion solution complete with attributes.

[0059] At block 108, inversion attributes may be assigned character elements. The assignment of character elements may facilitate processing the depth solution data with visualization software.

[0060] As explained herein, the inversion attributes solutions may be incorporated into a software program that integrates a wide range of data originating in different source formats into a common format. Customized software code and/or scripts may be used to accomplish the transformation. In the exemplary embodiment shown in Fig. 1, the magnetic inversion attribute data are transformed into a common format, as shown at block 1 10. The source format of the inversion solutions are represented, or characterized by a set of spatial reference digits, or attributes. These attributes include information like source depth, location, geometry, dip, and magnetic susceptibility. The source spatial attributes ultimately define a point of reference, while the common format is the transformation of the point attribute references into volume attribute references. By placing the magnetic inversion solutions into a common format, such as a format supported by a visualization program, the magnetic inversion solutions can be posted, visualized in a 3D volume sense, and integrated with other reference surfaces such as depth surfaces, gravity data, magnetic data, etc. Additionally, the volume visualization enhances the interpretation processes by providing spatial prediction characteristics and signal and source stacking. This will facilitate a depth-to-basement analysis, as explained herein.

[0061] In an exemplary embodiment, customized code may be developed to create a pseudo 3D volume to facilitate digital interpretation of the inversion solutions. The volume may be created parallel to the direction of the flight lines used during the survey when the data was obtained. The pseudo 3D volume may be displayed using a technique referred to herein as "3D smash," which is explained in greater detail with reference to Fig. 5. In this manner, analysis and interpretation of multiple lines of data may be performed simultaneously. The cell size may be user-defined and may determine the granularity of the final interpretation. Importing the reference data into an analysis tool that allows inversion elements to be interpreted separately provides additional information that can be used to better define the depth and geometry of a measured source.

[0062] At block 112, reference grids are created. As shown in Fig. 1, the process of creating reference grids may be done in parallel with the process steps shown in blocks 104, 106, 108 and 110. Exemplary reference grids include total magnetic intensity (TMI), gravity, residuals and derivatives. The reference grids are desirably formatted in the common format to facilitate their use with a visualization of the magnetic profile data after it has been transformed into the common format.

[0063] In addition to reference grids, additional grids may also be created to be used as interpretation guides, as shown at block 114. Examples of interpretation guide grids include one or more depth surfaces derived from any other geophysical, geological or well log database.

[0064] At block 116, data developed at block 1 10, as well as grids created at blocks 112 and 114 are loaded into a 3D cube or volume in the common format. As set forth herein, other data representative of properties of interest of a physical region may also be loaded into the 3D cube or volume. Examples of other types of data relating to subsurface features for which visualizations may be prepared using data in a common format include boundaries, geologic layers, geological scenario data horizons, and/or interfaces. Additional examples of property data that may be integrated include gravity, magnetic derivative data, topography, Landsat, electromagnetic and well data. Other examples of data that may be integrated include seismic attribute volumes; geophysical data (for example, seismic velocities, densities, or electrical resistivities), petrophysical data, geological data (for example, lithology, environment of deposition), geologic models and simulations, reservoir simulations, borehole/well data or engineering and production data. Those of ordinary skill in the art will appreciate that the data incorporated into a physical property model in accordance with an exemplary embodiment of the present techniques varies depending on the desired application and the properties of interest for that application. [0065] Transforming data from a source format into a common format with other types of data allows a user to create visualizations of data representative of multiple properties of interest for interpretation. The data thus presented may then be interpreted by a user, as shown at block 1 18.

[0066] Fig. 2 is depth surface map from a gravity inversion performed in accordance with an exemplary embodiment of the present techniques. The depth surface map is generally referred to by the reference number 200. The depth surface map 200 may comprise information such as grids of potential field data and depth-to-magnetic basement interpretation guides. Visualizations in accordance with the present techniques may be based in part on the data set forth in the surface map 200.

[0067] Fig. 3 is a diagram of a synthetic cube for use in an exemplary embodiment of the present techniques. The synthetic cube is generally referred to by the reference number 300. The synthetic cube 300 may be built from 2D survey magnetic profiles, as described herein. Estimates of rock properties and spatial (depth) elements may be calculated by running 2D profile inversion software program. The inversion depth solutions file is transformed into the common format, as set forth herein. Inversion attributes are assigned character elements to enable processing by an interpretation tool.

[0068] The synthetic cube 200 comprises a boundary 302. Also shown are a plurality of horizontal grid lines 304.

[0069] Fig. 4 is a diagram showing predicted geometries in accordance with an exemplary embodiment of the present techniques. The diagram is generally referred to by the reference number 400. The diagram 400 shows inversion attribute solutions 402 as well as potential field grid/grids and depth to magnetic basement interpretation guides 404. The data that comprises the inversion attribute solutions 402 may be operated on in the source format before being transformed into the common format to be displayed. As set forth herein, customized code and/or scripts may be used to transform the various inversion results into the common format for display with other data types such as the magnetic interpretation guides 404. An interpretation software tool may then be used to provide a visualization of data in the common format for purposes of volume interpretation and integration.

[0070] Fig. 5 is a graph showing a visualization of properties of interest in accordance with an exemplary embodiment of the present techniques. The visualization is generally referred to by the reference number 500. The visualization 500 includes an upper panel 502 and a lower panel 504. A magnetic data trace 506 is shown in the upper panel 502 of the visualization 500. Also shown in the upper panel 502 are a calculated horizontal gradient trace 508 of the magnetic data trace 506 and a gravity trace 510. The data for the magnetic data trace 506, a calculated horizontal gradient trace 508 of the magnetic data trace 506 and a gravity trace 510 have been calculated from various source formats into the common format for purposes of being displayed in the visualization 500.

[0071] The upper panel 502 demonstrates the use of a display technique referred to herein as the 3D smash approach. The 3D smash approach provides visualization prediction and line tie capabilities not available in a single line by line investigation and interpretation effort. This may be seen in the display of the calculated horizontal gradient trace 508 and the gravity trace 510.

[0072] In the 3D smash display technique, calculated horizontal gradient trace 508 and the gravity trace 510 are represented as having a 3D character. As shown in Fig. 5, the 3D smash technique allows a simultaneous multi-profile view with progressive transparency applied to line data and inversion attributes such that reference surfaces, interpretation guide surfaces and inversion attributes are brightest on the line profile undergoing interpretation and progressively fading out of view as these lines (elements) are located further away from the focal profile on interpretation. The advantage of the 3D smash is that it provides visualization prediction and line tie capabilities not available in a single line by line investigation and interpretation effort.

[0073] The lower panel 504 of the visualization 500 includes representations of one or more properties of interest, shown as a plurality of traces 512. Each of the plurality of traces 512 may correspond to an estimate of a depth-to-basement profile from a different source. Examples of sources of data that may be used to create the plurality of traces 512 include horizon data, seismic data, gravity data inversion data, and grid revisions of magnetic picks, to name just a few examples. The lower panel 504 additionally shows a plurality of magnetic inversion elements 514, which may facilitate a determination of a depth-to-basement value by a user.

[0074] Fig. 6 is a process flow diagram of a process of providing a physical property model according to an exemplary embodiment of the present techniques. The process is generally referred to by the reference number 600. At block 602, the method begins. [0075] As shown at block 604, a data structure is created to store physical property data elements for each cell of the region in a common format. As explained herein, a physical property data element is transformed from a source data format into the common format. The data transformation is represented at block 606. As shown at block 608, the physical property data element is stored in the data structure in the common format. At block 610, the process ends.

[0076] Fig. 7 is a process flow diagram showing a method for producing hydrocarbons from a subsurface region such as an oil and/or gas field according to exemplary embodiments of the present techniques. The process is generally referred to by the reference number 700. According to an exemplary embodiment of the present techniques, hydrocarbon production is facilitated through the use of a physical property model.

[0077] Those of ordinary skill in the art will appreciate that the present techniques may facilitate the production of hydrocarbons by producing visualizations that allow geologists, engineers and the like to determine a course of action to take to enhance hydrocarbon production from a subsurface region. By way of example, a visualization produced according to an exemplary embodiment of the present techniques may allow an engineer or geologist to determine a well placement to increase production of hydrocarbons from a subsurface region. At block 702, the process begins.

[0078] At block 704, a data structure is created to store physical property data elements for each cell of the oil and/or gas field in a common format. A physical property data element is transformed from a source data format into the common format, as shown at block 706.

[0079] At block 708, the physical property data element is stored in the data structure in the common format. An evaluation of the physical property data elements, as shown at block 710. Hydrocarbons are extracted from the oil and/or gas field based on the evaluation, as shown at block 712. The process ends at block 714.

[0080] Fig. 8 is a block diagram of a computer system that may be used to perform a method for providing a physical property model according to exemplary embodiments of the present techniques. The computer network is generally referred to by the reference number 800.

[0081] A central processing unit (CPU) 801 is coupled to system bus 802. The CPU 801 may be any general-purpose CPU, although other types of architectures of CPU 801 (or other components of exemplary system 800) may be used as long as CPU 801 (and other components of system 800) supports the inventive operations as described herein. The CPU 801 may execute the various logical instructions according to various exemplary embodiments. For example, the CPU 801 may execute machine-level instructions for performing processing related to providing physical property models according to the operational flow described herein with reference to Fig. 6 and Fig. 7.

[0082] The computer system 800 may also include computer components such as a random access memory (RAM) 803, which may be SRAM, DRAM, SDRAM, or the like. The computer system 800 may also include read-only memory (ROM) 804, which may be PROM, EPROM, EEPROM, or the like. RAM 803 and ROM 804 hold user and system data and programs, as is known in the art. The computer system 800 may also include an input/output (I/O) adapter 805, a communications adapter 81 1, a user interface adapter 808, and a display adapter 809. The I/O adapter 805, the user interface adapter 808, and/or communications adapter 811 may, in certain embodiments, enable a user to interact with computer system 800 in order to input information.

[0083] The I/O adapter 805 preferably connects a storage device(s) 806, such as one or more of hard drive, compact disc (CD) drive, floppy disk drive, tape drive, etc. to computer system 800. The storage device(s) may be used when RAM 803 is insufficient for the memory requirements associated with storing data for operations of embodiments of the present techniques. The data storage of the computer system 800 may be used for storing information and/or other data used or generated as disclosed herein. The communications adapter 811 may couple the computer system 800 to a network 812, which may enable information to be input to and/or output from system 800 via the network 812 (for example, the Internet or other wide-area network, a local-area network, a public or private switched telephony network, a wireless network, any combination of the foregoing). User interface adapter 808 couples user input devices, such as a keyboard 813, a pointing device 807, and a microphone 814 and/or output devices, such as a speaker(s) 815 to the computer system 800. The display adapter 809 is driven by the CPU 801 to control the display on a display device 810 to, for example, display information or a representation pertaining to a portion of a subsurface region under analysis, such as displaying a visualization of a physical property model, according to certain exemplary embodiments.

[0084] The architecture of system 800 may be varied as desired. For example, any suitable processor-based device may be used, including without limitation personal computers, laptop computers, computer workstations, and multi-processor servers. Moreover, embodiments may be implemented on application specific integrated circuits (ASICs) or very large scale integrated (VLSI) circuits. In fact, persons of ordinary skill in the art may use any number of suitable structures capable of executing logical operations according to the embodiments.

[0085] Exemplary embodiments of the present techniques improve the integration and interpretation of potential field data like profile magnetic data. Such exemplary embodiments may allow the integration of data produced by proprietary software developed for specific analysis techniques with more readily available interpretation and visualization software. One example of proprietary software is adapted to provide estimates for geometry, susceptibility, position, type and depth of a magnetic source using profile magnetic data.

[0086] In addition to providing improved abilities to determine depth-to-magnetic basement information, exemplary embodiments of the present techniques may be useful for mapping or interpretation support of hydrocarbon play elements. Such hydrocarbon play elements include, without limitation, traps, maturation, crustal thinning/Moho structure (geothermal gradient), volcanics (localization of heat issues), basement lithology (geothermal gradient), and migration. Examples of traps include carbonate reefs, basement horst structures, basement faults, salt structures or the like. Examples of maturation include depth- to-magnetic basement burial history or the like. Examples of migration include basement architecture such as play trends and migration pathways.

[0087] The present techniques may be susceptible to various modifications and alternative forms, and the exemplary embodiments discussed above have been shown only by way of example. However, the present techniques are not intended to be limited to the particular embodiments disclosed herein. Indeed, the present techniques include all alternatives, modifications, and equivalents falling within the spirit and scope of the appended claims.

Claims

Claims

What is claimed is:

I . A method for creating a physical property model representative of a physical property of a region, comprising:

creating a data structure to store physical property data elements for each cell of the region in a common format;

transforming a physical property data element from a source data format into the common format; and

storing the physical property data element in the data structure in the common format.

2. The method recited in claim 1, wherein the physical data element comprises magnetic field data.

3. The method recited in claim 2, comprising conducting a survey to measure the magnetic field data in the source format.

4. The method recited in claim 2, comprising predicting a depth -to-magnetic basement value based on the magnetic field data.

5. The method recited in claim 1, comprising providing a visualization of the data structure.

6. The method recited in claim 1, comprising providing a visualization of the physical property data element in conjunction with other data.

7. The method recited in claim 6, wherein the other data comprises gravity inversion data.

8. The method recited in claim 6, wherein the other data comprises interpretation guide data.

9. The method recited in claim 8, wherein the interpretation guide data comprises a grid.

10. The method recited in claim 6, wherein the other data comprises reference data.

I I. The method recited in claim 10, wherein the reference data comprises a grid.

12. The method recited in claim 6, wherein the visualization of the physical property data element is provided using a three-dimensional (3D) smash technique.

13. The method recited in claim 1, comprising performing an inversion on the physical property data element before transforming the physical property data element from the source data format into the common format.

14. A computer system that is adapted to create a physical property model representative of a physical property, the computer system comprising:

a processor; and

a tangible, machine-readable storage medium that stores machine-readable instructions for execution by the processor, the machine-readable instructions comprising:

code that, when executed by the processor, is adapted to cause the processor to create a data structure to store physical property data elements for each cell of the region in a common format;

code that, when executed by the processor, is adapted to cause the processor to transform a physical property data element from a source data format into the common format; and

code that, when executed by the processor, is adapted to cause the processor to store the physical property data element in the data structure in the common format.

15. The computer system recited in claim 14, wherein the physical data element comprises magnetic field data.

16. The computer system recited in claim 14, wherein the machine-readable instructions comprise code that, when executed by the processor, is adapted to cause the processor to predict a depth -to-magnetic basement value based on the physical property data element.

17. The computer system recited in claim 14, wherein the machine-readable instructions comprise code that, when executed by the processor, is adapted to cause the processor to provide a visualization of the data structure.

18. The computer system recited in claim 14, wherein the machine-readable instructions comprise code that, when executed by the processor, is adapted to cause the processor to provide a visualization of the physical property data element in conjunction with other data.

19. The computer system recited in claim 14, wherein the machine-readable instructions comprise code that, when executed by the processor, is adapted to cause the processor to perform an inversion on the physical property data element before transforming the physical property data element from the source data format into the common format.

20. A method for producing hydrocarbons from an oil and/or gas field using a physical property model representative of a physical property of the oil and/or gas field, the method comprising:

creating a data structure to store physical property data elements for each cell of the oil and/or gas field in a common format;

transforming a physical property data element from a source data format into the common format;

storing the physical property data element in the data structure in the common format; performing an evaluation of the physical property data elements; and

extracting hydrocarbons from the oil and/or gas field based on the evaluation.

21. A method for exploring for hydrocarbons in a subsurface region, comprising:

(a) obtaining digital magnetic profile data that were acquired from the subsurface region in a geophysical survey, meaning magnetic measurements made along two or more survey lines;

(b) using a computer to numerically invert the magnetic profile data to infer one or more rock properties of the subsurface region affecting the magnetic profile data, resulting in a 2-D discrete-cell depth model of each parameter for each of the survey lines;

(c) after making any necessary data format transformation, loading the 2-D depth models into a 3-D grid of cells to create a 3-D data volume for each rock property; and

(d) interpreting each 3-D data volume for indications of hydrocarbons or structural conditions conducive to hydrocarbon deposits.

22. The method of claim 21 , further comprising: obtaining a second 3-D data volume for a different rock property of the subsurface region based on a different type of geophysical survey of said subsurface region;

transforming one or both 3-D data volumes such that each is in a common format, including a common reference grid of cells; and

co-rendering both 3-D data volumes in a single display for the interpretation.