Method and device for determining anisotropy parameters

Abstract

The application discloses a method and device for obtaining anisotropy parameters, and the method comprises the following steps: obtaining an isotropic depth domain velocity body and well logging layering data, determining an interpreted horizon body, an isotropic dip angle, an isotropic azimuth angle, an anisotropy velocity body, and converting the isotropic dip angle and the isotropic azimuth angle into an anisotropy dip angle and an anisotropy azimuth angle; performing interpolation processing on the well logging layering data to obtain a well logging horizon body; calculating a depth difference value of the well logging horizon body and the interpreted horizon body at each horizon to obtain a well-seismic error body; constructing a tomographic matrix, iteratively inverting the anisotropy velocity body and an anisotropy parameter body to obtain a final anisotropy velocity body, a final anisotropy parameter body and a corresponding final seismic migration imaging profile. The application can improve the accuracy of anisotropy parameter calculation and obtain a seismic migration imaging profile with high precision.

Description

Technical Field

[0001] This invention relates to the field of petroleum seismic exploration technology, and in particular to a method and apparatus for obtaining anisotropy parameters. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] Conventional seismic imaging techniques for isotropic media and pre-stack time / depth migration seismic imaging techniques have been widely used in structural interpretation and lithological identification, achieving certain results. However, their seismic resolution is clearly insufficient to meet the needs of thin reservoir identification and oilfield development. Currently, seismic exploration is moving towards refined, ultra-deep, and high-resolution processing and interpretation. Anisotropic processing methods are particularly important for improving imaging accuracy and mitigating well-seismic errors, and are also an essential step in improving drilling success rates.

[0004] In anisotropic tomographic inversion, researchers initially derived the travel time perturbation equation for anisotropic media using the Hamiltonian form of the "equation function" for anisotropic media. Later, researchers modified the travel time perturbation equation and implemented a three-dimensional anisotropic media travel time tomographic imaging method, but its application in real-world data was not very successful. Other researchers, when performing parameter inversion on VTI media, proposed a method to separately obtain the sensitive kernel functions for the three slowness components (horizontal, vertical, and dynamic correction slowness). Still others have investigated the linear relationship between the data space and model space in 3D stereo tomography, primarily based on the ray perturbation theory of Hamiltonian operators. The tomographic equations established after tomographic mesh partitioning are often ill-conditioned or singular, representing a typical highly nonlinear inversion problem. Therefore, first-arrival travel time tomographic inversion is inherently an ill-posed problem, requiring regularization techniques to constrain the inversion process and incorporate prior information into the inversion equations. Later researchers incorporated prior information into first-arrival travel-time tomography using regularization methods, replacing the traditional external constraint model. However, with the development and deepening of seismic exploration from two-dimensional to three-dimensional, the dimension of seismic tomography inversion equations has increased exponentially. Traditional inversion algorithms based on Tikhonov regularization suffer from drawbacks such as slow convergence speed, numerous iterations, and poor inversion stability. Subsequently, researchers proposed a shaping regularization method, which maps the model to a smooth function space through a shaping operator during iterative inversion, significantly improving the convergence speed and stability of traditional regularization methods.

[0005] From the above-mentioned research progress of anisotropic tomography inversion, TTI anisotropic parameter modeling and pre-stack depth migration technology have gradually become the mainstream processing methods. However, the traditional TTI anisotropic parameter calculation method still has the problem of low accuracy, resulting in low precision of the obtained seismic migration images. Summary of the Invention

[0006] This invention provides a method for obtaining anisotropy parameters to improve the accuracy of anisotropy parameter calculation and obtain highly accurate seismic migration imaging profiles. The method includes:

[0007] Acquire isotropic depth-domain velocity volumes and well logging layer data;

[0008] Based on the isotropic depth domain velocity volume, the interpretation layer volume, isotropic dip angle, isotropic azimuth angle, and anisotropic velocity volume are determined, and the isotropic dip angle and isotropic azimuth angle are converted into anisotropic dip angle and anisotropic azimuth angle.

[0009] Interpolation processing is performed on the well logging stratification data to obtain the well logging strata volume;

[0010] The depth difference between the logging layer and the interpretation layer at each layer is calculated to obtain the well-seismic error volume;

[0011] Based on the well seismic error volume, the interpreted layer volume, the anisotropic velocity volume, the anisotropic dip angle, and the anisotropic azimuth angle, a tomography matrix is ​​constructed;

[0012] The anisotropic velocity volume and anisotropic parameter volume are inverted using the tomography matrix to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile.

[0013] This invention also provides an apparatus for obtaining anisotropy parameters, which improves the accuracy of anisotropy parameter calculation and obtains high-precision seismic migration imaging profiles. The apparatus includes:

[0014] The acquisition module is used to acquire isotropic depth domain velocity volumes and well logging layer data;

[0015] The determination module is used to determine the interpretation layer volume, isotropic dip angle, isotropic azimuth angle, and anisotropic velocity volume based on the isotropic depth domain velocity volume, and to convert the isotropic dip angle and isotropic azimuth angle into the anisotropic dip angle and anisotropic azimuth angle.

[0016] The interpolation module is used to interpolate well logging stratification data to obtain well logging stratification volumes;

[0017] The calculation module is used to calculate the difference between the logging layer volume and the interpretation layer volume at each layer, and obtain the well-seismic error volume;

[0018] The matrix construction module is used to construct a tomography matrix based on the well seismic error volume, the interpreted layer volume, the anisotropic velocity volume, the anisotropic dip angle, and the anisotropic azimuth angle.

[0019] The inversion module is used to iteratively invert the anisotropic velocity volume and anisotropic parameter volume using the tomography matrix, to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile.

[0020] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method for obtaining anisotropy parameters.

[0021] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for obtaining anisotropy parameters.

[0022] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for obtaining anisotropy parameters.

[0023] In this embodiment of the invention, the traditional TTI anisotropy parameter calculation method is modified by incorporating the interpretation layer volume into the anisotropic tomographic inversion. In most areas lacking well data, a more reasonable velocity model is used for optimization, resulting in a more reasonable anisotropic parameter volume and velocity volume, and consequently, a more reasonable final migration imaging profile. Furthermore, a well-seismic error volume is calculated using the interpretation layer volume and the logging layer volume. This well-seismic error volume is utilized during tomographic inversion, thus incorporating formation information into the inversion process. Prior information from marker layers is added during tomographic inversion, fully considering the importance of marker layers and obtaining more reasonable inversion results. Anisotropic migration then eliminates well-seismic errors caused by formation anisotropy, effectively avoiding the layer distortion problems caused by conventional single-well-point well-seismic error inversion, further improving the accuracy of anisotropic parameter calculation. Meanwhile, using the well-seismic error volume for tomographic inversion effectively solves the problem of errors in well-seismic matching, significantly improving the imaging quality of 3D seismic profiles under complex surface topography conditions and ensuring the rationality and reliability of structural morphology. It can accurately image complex structures such as faults and thrust faults, providing technical support for improving drilling success rates and reservoir prediction. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0025] Figure 1 This is a flowchart of a method for obtaining anisotropy parameters in an embodiment of the present invention;

[0026] Figure 2 This is a schematic diagram of an isotropic depth domain velocity body in an embodiment of the present invention;

[0027] Figure 3 This is a schematic diagram of an interpretation layer based on an isotropic pre-stack depth migration profile in an embodiment of the present invention;

[0028] Figure 4 This is a schematic diagram of a well logging layer body obtained by interpolation of well logging layer data in an embodiment of the present invention;

[0029] Figure 5 This is a planar schematic diagram of anisotropic parameter results obtained by mesh tomography in an embodiment of the present invention;

[0030] Figure 6(a) is a schematic diagram of an isotropic pre-stack depth offset profile according to the prior art;

[0031] Figure 6(b) is a schematic diagram of the anisotropic pre-stack depth offset profile obtained according to an embodiment of the present invention;

[0032] Figure 7 This is a schematic diagram of the structure of an anisotropy parameter obtaining device in an embodiment of the present invention;

[0033] Figure 8 This is a schematic diagram of the structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0035] This invention provides a method for obtaining anisotropy parameters, such as... Figure 1 As shown, the method includes steps 101 to 106:

[0036] Step 101: Obtain isotropic depth domain velocity volume and well logging stratification data.

[0037] An isotropic depth-domain velocity volume is a three-dimensional model in which a corresponding velocity exists at each position. For example, Figure 2 This is a schematic diagram of an isotropic depth-domain velocity volume.

[0038] Step 102: Determine the interpretation layer volume, isotropic dip angle, isotropic azimuth angle, and anisotropic velocity volume based on the isotropic depth domain velocity volume, and convert the isotropic dip angle and isotropic azimuth angle into the anisotropic dip angle and anisotropic azimuth angle.

[0039] Within the test area, based on the geological conditions, major geological layers were selected on the pre-stack time migration data volume, and seismic interpretation horizons were picked up by combining the interfaces of well logging sonic velocity changes, resulting in an interpretation horizon volume. This interpretation horizon volume typically corresponds to strong seismic phase axes, has a high signal-to-noise ratio, and is beneficial for subsequent travel time residual picking.

[0040] For example, Figure 3 A schematic diagram of the interpretable layer volume obtained based on the isotropic depth domain velocity volume is presented.

[0041] The determination of the interpretation layer volume based on the isotropic depth domain velocity volume, as well as the conversion between anisotropic dip angle and anisotropic azimuth angle, can all be carried out using existing methods. The specific implementation process will not be elaborated here.

[0042] Step 103: Interpolate the well logging stratification data to obtain the well logging strata.

[0043] Interpolation is a method of interpolating a continuous function onto discrete data so that the continuous curve passes through all given discrete data points. By using interpolation, the approximate value of the function at other points can be estimated based on the value of the function at a finite number of points.

[0044] For example, the well logging layer volume obtained by interpolation of well logging layer data can be referred to Figure 4 As shown.

[0045] In practice, outliers in the interpolation can be removed before interpolation is performed. If necessary, the interpolation results can be optimized multiple times by humans to obtain a stratigraphic position that is more consistent with geological understanding.

[0046] The well logging strata can be obtained by interpolating well logging strata data using existing technologies. The specific implementation process will not be elaborated here.

[0047] Step 104: Calculate the depth difference between the logging layer volume and the interpretation layer volume at each layer to obtain the well-seismic error volume.

[0048] Well-seismic errors exist only at the well site, while stratigraphic information permeates the entire work area. Therefore, by introducing stratigraphic-related errors into subsequent anisotropic tomography inversion, and by integrating stratigraphic thickness information and well-seismic errors, an anisotropic body that avoids inverting stratigraphic thickness anomalies can be obtained.

[0049] Let F0 represent the velocity value of any layer in the interpretation layer, and F1 represent the velocity value of any layer in the logging layer. Then, the layer error value (Mistie) for each layer is calculated according to Mistie = F1 - F0. The calculated layer error values ​​for all layers are defined as the well-seismic error body. For example, for an interpretation layer and a logging layer containing 10 layers, first calculate the velocity difference between the first layer in the logging layer and the depth difference between the first layer in the interpretation layer, then calculate the velocity difference between the second layer in the logging layer and the depth difference between the second layer in the interpretation layer, and so on for each layer until the depth differences for all 10 layers are obtained. These 10 depth differences are then used as the well-seismic error body.

[0050] Step 105: Construct the tomography matrix based on the well seismic error volume, the interpreted stratigraphic volume, the anisotropic velocity volume, the anisotropic dip angle, and the anisotropic azimuth angle.

[0051] Specifically, the well-seismic error volume, interpreted layer volume, anisotropic velocity volume, anisotropic dip angle, and anisotropic azimuth angle are first used as inputs to perform grid tomography inversion to obtain the layer velocity volume model. Then, the layer velocity volume model, interpreted layer volume, well-seismic error volume, anisotropic dip angle, and anisotropic azimuth angle are used as inputs to perform ray tracing travel time calculation according to the given grid points to establish the tomography matrix.

[0052] Compared to conventional methods for calculating anisotropic parameters, this invention incorporates formation information (including interpreted stratigraphic volumes and logging stratigraphic volumes) into the inversion process when constructing the tomography matrix. It also adds prior information from a marker layer—the well-seismic error volume—as a regularization condition for anisotropic parameter inversion, resulting in more reasonable inversion results. In subsequent steps, anisotropic migration eliminates well-seismic errors caused by formation anisotropy, effectively avoiding stratigraphic distortion problems arising from conventional single-well-point well-seismic error inversion and improving the accuracy of anisotropic parameters.

[0053] Step 106: Iteratively invert the anisotropic velocity volume and anisotropic parameter volume using the tomography matrix to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile.

[0054] Specifically, automatic picking is performed on the common imaging point gathers to obtain the depth domain residual delay. Using the flattening of the common imaging point gathers as the error functional, the anisotropic velocity volume and anisotropic parameter volume are iteratively inverted using the depth domain residual delay and the tomography matrix to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile. In this way, the advantages of horizon control and grid tomography global inversion are combined. The model is built based on the geological horizon, and parameters are updated simultaneously along the geological horizon grid in the horizontal direction and the inter-layer grid in the vertical direction. It can simultaneously approximate the true velocity volume in both directions along a reasonable geological horizon in the horizontal direction and along the optimized inter-layer grid in the vertical direction. Furthermore, multiple final surface attribute information such as the continuity of the phase axis, azimuth angle, formation dip angle, and well logging data are jointly applied to the velocity inversion modeling process, which can accurately obtain the high wavenumber components and low wavenumber components in the velocity field as well as the anisotropic parameters.

[0055] For example, Figure 5 A schematic diagram of anisotropic parameter inversion results via mesh tomography is presented.

[0056] Iterative inversion can yield multiple sets of corresponding anisotropic velocity volumes and anisotropic parameter volumes. These need to be selected to obtain the final anisotropic velocity volumes and final anisotropic parameter volumes that meet the accuracy requirements. Whether the anisotropic velocity volumes and anisotropic parameter volumes meet the accuracy requirements needs to be demonstrated by the seismic migration imaging profiles obtained from them. Therefore, using the flattening of common imaging point gathers as the error functional, and utilizing the depth domain residual delay and tomography matrix, the anisotropic velocity volume and anisotropic parameters are iteratively inverted to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile. This can be performed as follows: using the flattening of common imaging point gathers as the error functional, the tomography matrix is ​​solved using the depth domain residual delay to obtain the update amount of velocity, anisotropic parameters, and interpreted layer volume for each grid point. The intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are inverted using the update amount of velocity, anisotropic parameters, and interpreted layer volume for each grid point. Seismic migration imaging is performed using the intermediate anisotropic velocity volume and intermediate anisotropic parameter volume to obtain the intermediate seismic migration imaging profile.

[0057] If the intermediate seismic migration imaging profile meets the preset error requirements, then the intermediate anisotropic velocity volume, the intermediate anisotropic parameter volume, and the intermediate seismic migration imaging profile are determined as the final anisotropic velocity volume, the final anisotropic parameter volume, and the final seismic migration imaging profile, respectively.

[0058] If the intermediate seismic migration imaging profile does not meet the preset error requirements, the tomography matrix is ​​resolved and the intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are inverted until the obtained intermediate seismic migration imaging profile meets the preset error requirements. The intermediate anisotropic velocity volume, intermediate anisotropic parameter volume and intermediate seismic migration imaging profile that meet the preset error requirements are determined as the final anisotropic velocity volume, final anisotropic parameter volume and final seismic migration imaging profile, respectively.

[0059] It should be noted that, in this embodiment of the invention, the intermediate anisotropic velocity volume, intermediate anisotropic parameter volume, and intermediate seismic migration imaging profile are the inversion results of a set of anisotropic velocity volumes, anisotropic parameter volumes, and seismic migration imaging profiles obtained during the inversion process. The final anisotropic velocity volume, final anisotropic parameter volume, and final seismic migration imaging profile are the inversion results of the intermediate anisotropic velocity volume, intermediate anisotropic parameter volume, and intermediate seismic migration imaging profiles obtained during the inversion process after meeting the preset error requirements.

[0060] Figures 6(a) and 6(b) are schematic diagrams of an isotropic pre-stack depth migration profile obtained according to the prior art and an anisotropic pre-stack depth migration profile obtained according to the embodiment of the present invention, respectively. From the comparison of the two pre-stack depth migration profiles, the profile finally obtained by the embodiment of the present invention has higher continuity of phase axis and signal-to-noise ratio, clearer fracture imaging, and better imaging of the target layer. The depth of the pre-stack depth migration is not only consistent with the depth of the old well, but also consistent with the depth of the new well. This shows that the velocity model obtained by the present invention has high accuracy and accurate imaging of the structural location, and effectively solves the problem of imaging complex structures in this region.

[0061] In this embodiment of the invention, the traditional TTI anisotropy parameter calculation method is modified by incorporating the interpretation layer volume into the anisotropic tomographic inversion. In most areas lacking well data, a more reasonable velocity model is used for optimization, resulting in a more reasonable anisotropic parameter volume and velocity volume, and consequently, a more reasonable final migration imaging profile. Furthermore, a well-seismic error volume is calculated using the interpretation layer volume and the logging layer volume. This well-seismic error volume is utilized during tomographic inversion, thus incorporating formation information into the inversion process. Prior information from marker layers is added during tomographic inversion, fully considering the importance of marker layers and obtaining more reasonable inversion results. Anisotropic migration then eliminates well-seismic errors caused by formation anisotropy, effectively avoiding the layer distortion problems caused by conventional single-well-point well-seismic error inversion, further improving the accuracy of anisotropic parameter calculation. Meanwhile, using the well-seismic error volume for tomographic inversion effectively solves the problem of errors in well-seismic matching, significantly improving the imaging quality of 3D seismic profiles under complex surface topography conditions and ensuring the rationality and reliability of structural morphology. It can accurately image complex structures such as faults and thrust faults, providing technical support for improving drilling success rates and reservoir prediction.

[0062] This invention also provides an apparatus for obtaining anisotropic parameters, as described in the following embodiments. Since the principle by which this apparatus solves the problem is similar to the method for obtaining anisotropic parameters, the implementation of this apparatus can be found in the implementation of the method for obtaining anisotropic parameters; repeated details will not be elaborated further.

[0063] like Figure 7 As shown, the device 700 includes an acquisition module 701, a determination module 702, an interpolation module 703, a calculation module 704, a matrix construction module 705, and an inversion module 706.

[0064] Among them, the acquisition module 701 is used to acquire isotropic depth domain velocity volume and well logging layer data;

[0065] The determination module 702 is used to determine the interpretation layer volume, isotropic dip angle, isotropic azimuth angle, and anisotropic velocity volume based on the isotropic depth domain velocity volume, and to convert the isotropic dip angle and isotropic azimuth angle into the anisotropic dip angle and anisotropic azimuth angle.

[0066] Interpolation module 703 is used to interpolate well logging stratification data to obtain well logging stratification volume;

[0067] The calculation module 704 is used to calculate the depth difference between the logging layer and the interpretation layer at each layer to obtain the well-seismic error volume;

[0068] The matrix construction module 705 is used to construct a tomography matrix based on the well seismic error volume, the interpreted layer volume, the anisotropic velocity volume, the anisotropic dip angle, and the anisotropic azimuth angle.

[0069] The inversion module 706 is used to iteratively invert the anisotropic velocity volume and anisotropic parameter volume using the tomography matrix to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile.

[0070] In one implementation of this invention, the matrix construction module 705 is used for:

[0071] Using the well seismic error volume, interpreted layer volume, anisotropic velocity volume, anisotropic dip angle, and anisotropic azimuth angle as inputs, grid tomography inversion is performed to obtain the layer velocity volume model.

[0072] Using the layer velocity volume model, interpreted layer volume, well-seismic error volume, anisotropic dip angle, and anisotropic azimuth angle as inputs, the tomography matrix is ​​established by ray tracing travel time calculation according to the given grid points.

[0073] In one implementation of this invention, the inversion module 706 is used for:

[0074] Automatic picking is performed on the common imaging point gather to obtain the remaining delay in the depth domain;

[0075] Using the flattening of common imaging point gathers as the error functional, and utilizing the depth domain residual delay and tomography matrix, the anisotropic velocity volume and anisotropic parameter volume are iteratively inverted to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile.

[0076] In one implementation of this invention, the inversion module 706 is used for:

[0077] Using the flattening of the common imaging point gather as the error functional, the tomography matrix is ​​solved using the residual delay in the depth domain to obtain the velocity, anisotropic parameters and the update amount of the interpretation layer volume for each grid point. The intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are then obtained by inverting the velocity, anisotropic parameters and the update amount of the interpretation layer volume for each grid point.

[0078] Seismic migration imaging was performed using the intermediate anisotropic velocity volume and the intermediate anisotropic parameter volume to obtain the intermediate seismic migration imaging profile.

[0079] If the intermediate seismic migration imaging profile meets the preset error requirements, then the intermediate anisotropic velocity volume, the intermediate anisotropic parameter volume, and the intermediate seismic migration imaging profile are determined as the final anisotropic velocity volume, the final anisotropic parameter volume, and the final seismic migration imaging profile, respectively.

[0080] If the intermediate seismic migration imaging profile does not meet the preset error requirements, the tomography matrix is ​​resolved and the intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are inverted until the obtained intermediate seismic migration imaging profile meets the preset error requirements. The intermediate anisotropic velocity volume, intermediate anisotropic parameter volume and intermediate seismic migration imaging profile that meet the preset error requirements are determined as the final anisotropic velocity volume, final anisotropic parameter volume and final seismic migration imaging profile, respectively.

[0081] In this embodiment of the invention, the traditional TTI anisotropy parameter calculation method is modified by incorporating the interpretation layer volume into the anisotropic tomographic inversion. In most areas lacking well data, a more reasonable velocity model is used for optimization, resulting in a more reasonable anisotropic parameter volume and velocity volume, and consequently, a more reasonable final migration imaging profile. Furthermore, a well-seismic error volume is calculated using the interpretation layer volume and the logging layer volume. This well-seismic error volume is utilized during tomographic inversion, thus incorporating formation information into the inversion process. Prior information from marker layers is added during tomographic inversion, fully considering the importance of marker layers and obtaining more reasonable inversion results. Anisotropic migration then eliminates well-seismic errors caused by formation anisotropy, effectively avoiding the layer distortion problems caused by conventional single-well-point well-seismic error inversion, further improving the accuracy of anisotropic parameter calculation. Meanwhile, using the well-seismic error volume for tomographic inversion effectively solves the problem of errors in well-seismic matching, significantly improving the imaging quality of 3D seismic profiles under complex surface topography conditions and ensuring the rationality and reliability of structural morphology. It can accurately image complex structures such as faults and thrust faults, providing technical support for improving drilling success rates and reservoir prediction.

[0082] This invention also provides a computer device. Figure 8 This is a schematic diagram of a computer device in an embodiment of the present invention. This computer device is capable of implementing all steps in the anisotropy parameter calculation method described in the above embodiments. Specifically, the computer device includes the following components:

[0083] Processor 801, memory 802, communications interface 803, and communication bus 804;

[0084] The processor 801, memory 802, and communication interface 803 communicate with each other through the communication bus 804; the communication interface 803 is used to realize information transmission between related devices.

[0085] The processor 801 is used to call the computer program in the memory 802, and when the processor executes the computer program, it implements the method for obtaining the anisotropy parameters in the above embodiments.

[0086] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for obtaining anisotropy parameters.

[0087] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the above-described method for obtaining anisotropy parameters.

[0088] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0090] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0091] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0092] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining anisotropy parameters, characterized in that, The method includes: Acquire isotropic depth-domain velocity volumes and well logging layer data; Based on the isotropic depth domain velocity volume, the interpretation layer volume, isotropic dip angle, isotropic azimuth angle, and anisotropic velocity volume are determined, and the isotropic dip angle and isotropic azimuth angle are converted into anisotropic dip angle and anisotropic azimuth angle. Interpolation processing is performed on the well logging stratification data to obtain the well logging strata volume; The depth difference between the logging layer and the interpretation layer at each layer is calculated to obtain the well-seismic error volume; Based on the well seismic error volume, the interpreted layer volume, the anisotropic velocity volume, the anisotropic dip angle, and the anisotropic azimuth angle, a tomography matrix is ​​constructed; The anisotropic velocity volume and anisotropic parameter volume are iteratively inverted using the tomography matrix to obtain the final anisotropic velocity volume and final anisotropic parameter volume, as well as the corresponding final seismic migration imaging profile. The process involves iteratively inverting the anisotropic velocity volume and anisotropic parameter volume using the tomography matrix to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile. This includes: automatically picking up common imaging point gathers to obtain the depth domain residual delay; using whether the common imaging point gathers are flattened as an error functional, iteratively inverting the anisotropic velocity volume and anisotropic parameter volume using the depth domain residual delay and the tomography matrix to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile. The error functional is based on whether the common imaging point gather is flattened. Using the depth-domain residual delay and tomography matrix, the anisotropic velocity volume and anisotropic parameters are iteratively inverted to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile, including: Using the flattening of the common imaging point gather as the error functional, the tomography matrix is ​​solved using the residual delay in the depth domain to obtain the velocity, anisotropic parameters and the update amount of the interpretation layer volume for each grid point. The intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are then obtained by inverting the velocity, anisotropic parameters and the update amount of the interpretation layer volume for each grid point. Seismic migration imaging was performed using the intermediate anisotropic velocity volume and the intermediate anisotropic parameter volume to obtain the intermediate seismic migration imaging profile. If the intermediate seismic migration imaging profile meets the preset error requirements, then the intermediate anisotropic velocity volume, the intermediate anisotropic parameter volume, and the intermediate seismic migration imaging profile are determined as the final anisotropic velocity volume, the final anisotropic parameter volume, and the final seismic migration imaging profile, respectively. If the intermediate seismic migration imaging profile does not meet the preset error requirements, the tomography matrix is ​​resolved and the intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are inverted until the obtained intermediate seismic migration imaging profile meets the preset error requirements. The intermediate anisotropic velocity volume, intermediate anisotropic parameter volume and intermediate seismic migration imaging profile that meet the preset error requirements are determined as the final anisotropic velocity volume, final anisotropic parameter volume and final seismic migration imaging profile, respectively.

2. The method according to claim 1, characterized in that, Based on the wellbore error volume, interpreted stratigraphic volume, anisotropic velocity volume, anisotropic dip angle, and anisotropic azimuth angle, a tomography matrix is ​​constructed, including: Using the well seismic error volume, interpreted layer volume, anisotropic velocity volume, anisotropic dip angle, and anisotropic azimuth angle as inputs, grid tomography inversion is performed to obtain the layer velocity volume model. Using the layer velocity volume model, interpreted layer volume, well-seismic error volume, anisotropic dip angle, and anisotropic azimuth angle as inputs, the tomography matrix is ​​established by ray tracing travel time calculation according to the given grid points.

3. A device for determining anisotropy parameters, characterized in that, The device includes: The acquisition module is used to acquire isotropic depth domain velocity volumes and well logging layer data; The determination module is used to determine the interpretation layer volume, isotropic dip angle, isotropic azimuth angle, and anisotropic velocity volume based on the isotropic depth domain velocity volume, and to convert the isotropic dip angle and isotropic azimuth angle into the anisotropic dip angle and anisotropic azimuth angle. The interpolation module is used to interpolate well logging stratification data to obtain well logging stratification volumes; The calculation module is used to calculate the depth difference between the logging layer and the interpretation layer at each layer, and obtain the well-seismic error volume; The matrix construction module is used to construct a tomography matrix based on the well seismic error volume, the interpreted layer volume, the anisotropic velocity volume, the anisotropic dip angle, and the anisotropic azimuth angle. The inversion module is used to iteratively invert the anisotropic velocity volume and anisotropic parameter volume using the tomography matrix, to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile. The inversion module is used for: Automatic picking is performed on the common imaging point gather to obtain the remaining delay in the depth domain; Using the flattening of common imaging point gathers as the error functional, and utilizing the depth domain residual delay and tomography matrix, the anisotropic velocity volume and anisotropic parameter volume are iteratively inverted to obtain the final anisotropic velocity volume, the final anisotropic parameter volume, and the corresponding final seismic migration imaging profile. Inversion module, used for: Using the flattening of the common imaging point gather as the error functional, the tomography matrix is ​​solved using the residual delay in the depth domain to obtain the velocity, anisotropic parameters and the update amount of the interpretation layer volume for each grid point. The intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are then obtained by inverting the velocity, anisotropic parameters and the update amount of the interpretation layer volume for each grid point. Seismic migration imaging was performed using the intermediate anisotropic velocity volume and the intermediate anisotropic parameter volume to obtain the intermediate seismic migration imaging profile. If the intermediate seismic migration imaging profile meets the preset error requirements, then the intermediate anisotropic velocity volume, the intermediate anisotropic parameter volume, and the intermediate seismic migration imaging profile are determined as the final anisotropic velocity volume, the final anisotropic parameter volume, and the final seismic migration imaging profile, respectively. If the intermediate seismic migration imaging profile does not meet the preset error requirements, the tomography matrix is ​​resolved and the intermediate anisotropic velocity volume and intermediate anisotropic parameter volume are inverted until the obtained intermediate seismic migration imaging profile meets the preset error requirements. The intermediate anisotropic velocity volume, intermediate anisotropic parameter volume and intermediate seismic migration imaging profile that meet the preset error requirements are determined as the final anisotropic velocity volume, final anisotropic parameter volume and final seismic migration imaging profile, respectively.

4. The apparatus according to claim 3, characterized in that, The matrix building module is used for: Using the well seismic error volume, interpreted layer volume, anisotropic velocity volume, anisotropic dip angle, and anisotropic azimuth angle as inputs, grid tomography inversion is performed to obtain the layer velocity volume model. Using the layer velocity volume model, interpreted layer volume, well-seismic error volume, anisotropic dip angle, and anisotropic azimuth angle as inputs, the tomography matrix is ​​established by ray tracing travel time calculation according to the given grid points.

5. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 2.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 2.

7. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 2.

Images