An air content prediction method and device, computer equipment and storage medium

Abstract

This invention discloses a gas-bearing prediction method, apparatus, computer equipment, and storage medium. The method includes: acquiring pre-stack azimuth gathers for each azimuth angle of a fractured reservoir; determining the incident angle corresponding to each azimuth angle in the pre-stack azimuth gathers, and stacking the pre-stack azimuth gathers based on the incident angle to obtain angular domain stacked data; calculating the attenuation gradient corresponding to different azimuth angles and incident angles in the angular domain stacked data; and predicting the gas-bearing capacity of the fractured reservoir based on the attenuation gradient. Applying the gas-bearing prediction scheme of this invention, the fracture identification method based on azimuth gathers has significant effects; the prediction of gas-bearing reservoirs based on post-stack attenuation attributes has good effects; and the attribute of attenuation gradient variation with incident angle extracted from pre-stack incident angle gathers can effectively predict the gas-bearing capacity of the reservoir. Therefore, predicting gas-bearing capacity based on the variation of attenuation gradient with incident angle in different azimuth gathers can achieve the effect of directly predicting the gas-bearing capacity of fractures.

Description

Technical Field

[0001] This invention relates to the field of petroleum exploration, and more particularly to a method, apparatus, computer equipment, and storage medium for predicting gas content. Background Technology

[0002] Currently, the gas-bearing potential prediction process for fractured reservoirs involves first predicting fracture development or directly inverting fracture parameters to predict gas-bearing potential. This approach presents several problems:

[0003] (1) The current azimuth data is divided based on the azimuth of ground acquisition, not based on the illumination azimuth of the target layer. Since accurate crack prediction requires pre-stack gathers with azimuth information, the crack parameters calculated in the above manner will result in inaccurate results.

[0004] (2) Predicting the development of cracks before predicting the fluid content of cracks results in cumulative errors.

[0005] In view of this, there is an urgent need for a gas content prediction scheme in the existing technology. Summary of the Invention

[0006] The technical problem to be solved by the present invention is that predicting the development of cracks or directly inverting crack parameters to complete the gas content prediction will lead to inaccurate results or accumulated errors. Therefore, the present invention provides a gas content prediction method, device, computer equipment and storage medium.

[0007] To solve the above-mentioned technical problems, the present invention provides a method for predicting gas content, comprising:

[0008] Obtain front-stack trace sets for each azimuth angle of the fractured reservoir;

[0009] Determine the incident angles corresponding to each azimuth angle in the pre-stacked front-side trace set, and stack each pre-stacked front-side trace set based on the incident angles to obtain angle domain stacked data;

[0010] Calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data;

[0011] The gas content of the fractured reservoir is predicted based on the attenuation gradient.

[0012] Preferably, the step of determining the incident angles corresponding to each azimuth angle and stacking the pre-stack gathers based on the incident angles to obtain angular domain stacked data includes:

[0013] The front-end gathers of N directions are superimposed according to the incident angle to obtain M angular domain superimposed data of N directions, where N and M are natural numbers.

[0014] Preferably, the step of stacking the front-end gathers of N azimuths according to the incident angle to obtain M angular domain stacked data of N azimuths includes:

[0015] Calculate the N*M attenuation gradients corresponding to the M pre-stack front gathers in N directions.

[0016] Preferably, the step of predicting the gas content of the fractured reservoir based on the attenuation gradient includes:

[0017] Linear fitting is performed on the N*M attenuation gradients to obtain N seismic attributes of the attenuation gradient as a function of the incident angle at each azimuth.

[0018] Nonlinear fitting is performed on the N seismic attributes to obtain the target seismic attribute whose attenuation gradient varies with the incident angle and azimuth angle.

[0019] Preferably, the step of performing nonlinear fitting on the N seismic attributes includes:

[0020] Ellipse fitting is performed on the N seismic attributes.

[0021] Preferably, the step of predicting the gas content of the fractured reservoir based on the attenuation gradient includes:

[0022] The gas content of the fracture is determined based on the preset correspondence between the attenuation gradient and the gas content of the fracture.

[0023] The relationship between the attenuation gradient and the gas content of the fracture is determined based on the attenuation gradients of different fracture gas contents and seismic attributes in actual drilling data.

[0024] This invention provides a gas content prediction device, comprising:

[0025] The pre-stack data acquisition module is used to acquire pre-stack source gathers of each azimuth angle of the fractured reservoir;

[0026] The post-stack data acquisition module is used to determine the incident angles corresponding to each azimuth angle in the pre-stack front-side gathers, and to stack each pre-stack front-side gather based on the incident angles to obtain angle domain stacked data.

[0027] The gradient calculation module is used to calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data;

[0028] A gas-bearing prediction module is used to predict the gas-bearing capacity of the fractured reservoir based on the attenuation gradient.

[0029] Preferably, the post-stack data acquisition module is used for:

[0030] The front-end gathers of N directions are superimposed according to the incident angle to obtain M angular domain superimposed data of N directions, where N and M are natural numbers.

[0031] Preferably, the post-stack data acquisition module is specifically used to calculate N*M attenuation gradients corresponding to M pre-stack front gathers in N directions.

[0032] Preferably, the gas content prediction module is used to perform linear fitting on the N*M attenuation gradients to obtain N seismic attributes in each azimuth where the attenuation gradient varies with the incident angle; and to perform nonlinear fitting on the N seismic attributes to obtain target seismic attributes where the attenuation gradient varies with the incident angle and azimuth angle.

[0033] Preferably, the gas content prediction module is specifically used to perform ellipse fitting on the N seismic attributes.

[0034] Preferably, the gas content prediction module is used to determine the gas content of the fracture based on a preset correspondence between the attenuation gradient and the fracture gas content; the correspondence between the attenuation gradient and the fracture gas content is determined based on the attenuation gradient of different fracture gas contents and seismic attributes in actual drilling data.

[0035] The present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method.

[0036] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method.

[0037] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0038] The gas-bearing prediction method, apparatus, computer equipment, and storage medium of the present invention have significant effects on crack identification based on azimuth gathers because the energy of seismic waves parallel to and perpendicular to the direction of cracks shows a significant difference during the underground propagation of seismic waves.

[0039] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Therefore, predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The property of attenuation gradient as a function of incident angle extracted from pre-stack incident angle gathers can effectively predict the gas content of reservoirs.

[0040] It is evident that by using the attenuation gradient to predict the gas content of fractures based on the variation of the incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted. Attached Figure Description

[0041] 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.

[0042] Figure 1 A flowchart of a gas content prediction method provided in an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of a pre-stack azimuth gather provided by the present invention;

[0044] Figure 3 Another flowchart of the gas content prediction method provided in the embodiments of the present invention;

[0045] Figure 4 A comparison chart of the prediction results provided by this invention and actual drilling data;

[0046] Figure 5 A structural diagram of a gas content prediction device provided in an embodiment of the present invention;

[0047] Figure 6 A structural diagram of a computer device provided by the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Currently, the gas-bearing potential prediction process for fractured reservoirs involves first predicting fracture development or directly inverting fracture parameters to predict gas-bearing potential. This approach presents several problems:

[0050] (1) The current azimuth data is divided based on the azimuth of ground acquisition, not based on the illumination azimuth of the target layer. Since accurate crack prediction requires pre-stack gathers with azimuth information, the crack parameters calculated in the above manner will result in inaccurate results.

[0051] (2) Predicting the development of cracks before predicting the fluid content of cracks results in cumulative errors.

[0052] In view of this, in order to solve the problem that the existing technology of first predicting the development of cracks or directly inverting crack parameters to complete the gas content prediction will lead to inaccurate results or accumulated errors, the present invention provides a gas content prediction method, device, computer equipment and storage medium.

[0053] The gas content prediction method provided by the embodiments of the present invention will be described below.

[0054] Example 1

[0055] like Figure 1 The diagram shown is a flowchart of a gas content prediction method provided by the present invention. The gas content prediction method may include the following steps:

[0056] Step S101: Obtain the front-stack gathers of each azimuth angle of the fractured reservoir, such as... Figure 2 As shown.

[0057] Step S102: Determine the incident angles corresponding to each azimuth angle in the pre-stacked front-side gathers, and stack each pre-stacked front-side gather based on the incident angles to obtain angle domain stacked data.

[0058] Step S103: Calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data.

[0059] Step S104: Predict the gas content of the fractured reservoir based on the attenuation gradient.

[0060] Applying the gas-bearing prediction scheme of the present invention, since the seismic wave energy parallel to the direction of the fracture and perpendicular to the direction of the fracture exhibits significant differences during the underground propagation of seismic waves, the fracture identification method based on azimuth gathers has a significant effect.

[0061] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The attenuation gradient extracted from pre-stack incident angle gathers as a function of the incident angle can effectively predict the gas content of the reservoir, effectively mining seismic data information and having strong generalization capabilities.

[0062] It is evident that by using the attenuation gradient to predict gas content based on the change of incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted, reducing the amount of computation and the impact of other factors such as the degree of fracture filling on the prediction results.

[0063] Example 2

[0064] like Figure 3 The diagram shown is another flowchart of the gas content prediction method provided by the present invention. The gas content prediction method may include the following steps:

[0065] Step S201: Obtain the front-stack gathers of each azimuth angle of the fractured reservoir, such as... Figure 2 As shown.

[0066] Step S202: Stack the front-end gathers of N directions according to the incident angle to obtain M angular domain stacked data of N directions, where N and M are natural numbers.

[0067] Preferably, N*M attenuation gradients can be calculated corresponding to M pre-stack front gathers in N directions.

[0068] Step S203: Calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data.

[0069] Step S204: Perform linear fitting on the N*M attenuation gradients to obtain N seismic attributes of the attenuation gradient as a function of the incident angle at each azimuth.

[0070] Step S205: Perform nonlinear fitting on the N seismic attributes to obtain the target seismic attribute whose attenuation gradient varies with the incident angle and azimuth angle.

[0071] Preferably, the step of performing nonlinear fitting on the N seismic attributes includes performing elliptic fitting on the N seismic attributes.

[0072] In one scenario, the gas content of the fracture is determined based on a preset correspondence between the attenuation gradient and the gas content of the fracture; the correspondence between the attenuation gradient and the gas content of the fracture is determined based on the attenuation gradient of different fracture gas contents and seismic attributes in actual drilling data.

[0073] Understandably, based on actual drilling data, we can identify high-gas-producing sections and low-gas-producing sections, and thus determine which attenuation gradient range corresponds to a high-gas-producing section and which corresponds to a low-gas-producing section. This allows us to determine the corresponding thresholds. In practical applications, once the attenuation gradient attribute values ​​are obtained, the gas content of the fracture, such as high-gas-producing sections and low-gas-producing sections, can be determined based on the preset correspondence.

[0074] It should be noted that the actual drilling data in this invention is not used in the calculation but only to confirm the threshold of the final data volume. It can be seen that the prediction results objectively reflect the gas-bearing properties of the fractured reservoir and have low ambiguity.

[0075] This invention is based on pre-stack gathers with different azimuths and incident angles. It calculates the attenuation gradient that is sensitive to gas content, greatly extracting the effective information from seismic data. The prediction results are compared and analyzed with actual drilling production wells to complete the final prediction of fracture gas content. It has high accuracy, good stability, and strong lateral and longitudinal prediction capabilities.

[0076] Applying the gas-bearing prediction scheme of the present invention, since the seismic wave energy parallel to the direction of the fracture and perpendicular to the direction of the fracture exhibits significant differences during the underground propagation of seismic waves, the fracture identification method based on azimuth gathers has a significant effect.

[0077] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The attenuation gradient extracted from pre-stack incident angle gathers as a function of the incident angle can effectively predict the gas content of the reservoir, effectively mining seismic data information and having strong generalization capabilities.

[0078] It is evident that by using the attenuation gradient to predict gas content based on the change of incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted, reducing the amount of computation and the impact of other factors such as the degree of fracture filling on the prediction results.

[0079] The gas content prediction method provided by this invention will be illustrated below with a specific example.

[0080] According to steps S201 and S202, front-stack lookup data with azimuth and incident angle are obtained, where the azimuth is 0°, 30°, 60°, 90°, 120°, and 150°. Partial angle superposition is performed on the angle domain lookup data with different azimuth angles. The angle superposition range is 0°~7°, 7°~14°, 14°~21°, 21°~28°, and 28°~35°, for a total of 30 superposition data volumes.

[0081] It should be noted that the azimuth angles of 0°, 30°, 60°, 90°, 120°, and 150° listed above are preferred embodiments provided by this invention. Similarly, the angle superposition ranges of 0°–7°, 7°–14°, 14°–21°, 21°–28°, and 28°–35° are also preferred embodiments provided by this invention. Of course, other numerical settings are possible, and this invention does not limit these. Those skilled in the art can make reasonable settings according to the specific circumstances of actual applications.

[0082] Based on step S203, the corresponding attenuation gradient is calculated by superimposing data from the five angular domains in the six directions.

[0083] According to step S204, the five attenuation gradient attributes in the six directions are linearly fitted to obtain the seismic attribute Q of the attenuation gradient as a function of the incident angle in the six directions.

[0084] According to step S205, ellipse fitting is performed on the seismic attributes Q in the six azimuths to obtain the final Qvaz, which is the seismic attribute whose attenuation gradient varies with the incident angle and azimuth angle.

[0085] Please see Figure 4 This is a comparison chart of the prediction results provided by this invention and actual drilling data. Figure 4 It can be seen that the actual drilled well A has well-developed fractures and high gas content, while the actual drilled well B has well-developed fractures but is filled with mud and has poor gas content. The predicted results are consistent with the actual drilled wells.

[0086] The gas content prediction device provided in the embodiments of the present invention will be described below.

[0087] Example 3

[0088] like Figure 5 The diagram shown is a structural diagram of a gas content prediction device provided by the present invention. The gas content prediction device may include the following modules:

[0089] The pre-stack data acquisition module 310 is used to acquire pre-stack azimuth gathers of each azimuth angle of the fractured reservoir.

[0090] The post-stack data acquisition module 320 is used to determine the incident angles corresponding to each azimuth angle in the pre-stack front-side gathers, and to stack each pre-stack front-side gather based on the incident angles to obtain angle domain stacked data.

[0091] The gradient calculation module 330 is used to calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data.

[0092] Gas-bearing prediction module 340 is used to predict the gas-bearing capacity of the fractured reservoir based on the attenuation gradient.

[0093] In one scenario, the post-stack data acquisition module 320 is used to superimpose the pre-stack lookup data of N directions according to the incident angle to obtain M angular domain superimposed data of N directions, where N and M are both natural numbers.

[0094] In another scenario, the post-stack data acquisition module 320 is specifically used to calculate the N*M attenuation gradients corresponding to the M pre-stack front gathers in N directions.

[0095] In one scenario, the gas content prediction module 340 is used to perform linear fitting on the N*M attenuation gradients to obtain N seismic attributes in each azimuth where the attenuation gradient varies with the incident angle; and to perform nonlinear fitting on the N seismic attributes to obtain the target seismic attribute where the attenuation gradient varies with the incident angle and azimuth angle.

[0096] In another scenario, the gas content prediction module 340 is specifically used to perform ellipse fitting on the N seismic attributes.

[0097] In another scenario, the gas content prediction module 340 is used to determine the gas content of the fracture based on a preset correspondence between the attenuation gradient and the fracture gas content; the correspondence between the attenuation gradient and the fracture gas content is determined based on the attenuation gradient of different fracture gas contents and seismic attributes in actual drilling data.

[0098] Understandably, based on actual drilling data, we can identify high-gas-producing sections and low-gas-producing sections, and thus determine which attenuation gradient range corresponds to a high-gas-producing section and which corresponds to a low-gas-producing section. This allows us to determine the corresponding thresholds. In practical applications, once the attenuation gradient attribute values ​​are obtained, the gas content of the fracture, such as high-gas-producing sections and low-gas-producing sections, can be determined based on the preset correspondence.

[0099] It should be noted that the actual drilling data in this invention is not used in the calculation but only to confirm the threshold of the final data volume. Therefore, the prediction results objectively reflect the gas-bearing capacity of the fractured reservoir, with low ambiguity. This invention is based on pre-stack gathers divided by azimuth and incident angle, calculating the attenuation gradient sensitive to gas-bearing capacity, greatly extracting effective information from the seismic data. The prediction results are compared and analyzed with actual drilling production wells to complete the final prediction of fracture gas-bearing capacity, demonstrating high accuracy, good stability, and strong lateral and vertical prediction capabilities.

[0100] The gas content prediction method provided by this invention will be illustrated below with a specific example.

[0101] According to steps S201 and S202, front-stack lookup data with azimuth and incident angle are obtained, where the azimuth is 0°, 30°, 60°, 90°, 120°, and 150°. Partial angle superposition is performed on the angle domain lookup data with different azimuth angles. The angle superposition range is 0°~7°, 7°~14°, 14°~21°, 21°~28°, and 28°~35°, for a total of 30 superposition data volumes.

[0102] It should be noted that the azimuth angles of 0°, 30°, 60°, 90°, 120°, and 150° listed above are preferred embodiments provided by this invention. Similarly, the angle superposition ranges of 0°–7°, 7°–14°, 14°–21°, 21°–28°, and 28°–35° are also preferred embodiments provided by this invention. Of course, other numerical settings are possible, and this invention does not limit these. Those skilled in the art can make reasonable settings according to the specific circumstances of actual applications.

[0103] Based on step S203, the corresponding attenuation gradient is calculated by superimposing data from the five angular domains in the six directions.

[0104] According to step S204, the five attenuation gradient attributes in the six directions are linearly fitted to obtain the seismic attribute Q of the attenuation gradient as a function of the incident angle in the six directions.

[0105] According to step S205, ellipse fitting is performed on the seismic attributes Q in the six azimuths to obtain the final Qvaz, which is the seismic attribute whose attenuation gradient varies with the incident angle and azimuth angle.

[0106] Please see Figure 4 This is a comparison chart of the prediction results provided by this invention and actual drilling data. Figure 4 It can be seen that the actual drilled well A has well-developed fractures and high gas content, while the actual drilled well B has well-developed fractures but is filled with mud and has poor gas content. The predicted results are consistent with the actual drilled wells.

[0107] Applying the gas-bearing prediction scheme of the present invention, since the seismic wave energy parallel to the direction of the fracture and perpendicular to the direction of the fracture exhibits significant differences during the underground propagation of seismic waves, the fracture identification method based on azimuth gathers has a significant effect.

[0108] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Therefore, predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The property of attenuation gradient as a function of incident angle extracted from pre-stack incident angle gathers can effectively predict the gas content of reservoirs.

[0109] It is evident that by using the attenuation gradient to predict the gas content of fractures based on the variation of the incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted.

[0110] Example 3

[0111] To address the aforementioned technical problems, the present invention provides a computer device, such as... Figure 6 As shown, it includes a memory 410, a processor 420, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method described above.

[0112] In some cases, the method implemented by the processor when executing the computer program may include steps S101 to S104:

[0113] like Figure 1 The diagram shown is a flowchart of a gas content prediction method provided by the present invention. The gas content prediction method may include the following steps:

[0114] Step S101: Obtain the front-stack gathers of each azimuth angle of the fractured reservoir, such as... Figure 2 As shown.

[0115] Step S102: Determine the incident angles corresponding to each azimuth angle in the pre-stacked front-side gathers, and stack each pre-stacked front-side gather based on the incident angles to obtain angle domain stacked data.

[0116] Step S103: Calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data.

[0117] Step S104: Predict the gas content of the fractured reservoir based on the attenuation gradient.

[0118] Applying the gas-bearing prediction scheme of the present invention, since the seismic wave energy parallel to the direction of the fracture and perpendicular to the direction of the fracture exhibits significant differences during the underground propagation of seismic waves, the fracture identification method based on azimuth gathers has a significant effect.

[0119] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The attenuation gradient extracted from pre-stack incident angle gathers as a function of the incident angle can effectively predict the gas content of the reservoir, effectively mining seismic data information and having strong generalization capabilities.

[0120] It is evident that by using the attenuation gradient to predict gas content based on the change of incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted, reducing the amount of computation and the impact of other factors such as the degree of fracture filling on the prediction results.

[0121] In other cases, the method implemented by the processor when executing the computer program may include steps S201 to S205:

[0122] like Figure 3 The diagram shown is a flowchart of a gas content prediction method provided by the present invention. The gas content prediction method may include the following steps:

[0123] Step S201: Obtain the front-stack gathers of each azimuth angle of the fractured reservoir, such as... Figure 2 As shown.

[0124] Step S202: Stack the front-end gathers of N directions according to the incident angle to obtain M angular domain stacked data of N directions, where N and M are natural numbers.

[0125] Preferably, N*M attenuation gradients can be calculated corresponding to M pre-stack front gathers in N directions.

[0126] Step S203: Calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data.

[0127] Step S204: Perform linear fitting on the N*M attenuation gradients to obtain N seismic attributes of the attenuation gradient as a function of the incident angle at each azimuth.

[0128] Step S205: Perform nonlinear fitting on the N seismic attributes to obtain the target seismic attribute whose attenuation gradient varies with the incident angle and azimuth angle.

[0129] Preferably, the step of performing nonlinear fitting on the N seismic attributes includes performing elliptic fitting on the N seismic attributes.

[0130] In one scenario, the gas content of the fracture is determined based on a preset correspondence between the attenuation gradient and the gas content of the fracture; the correspondence between the attenuation gradient and the gas content of the fracture is determined based on the attenuation gradient of different fracture gas contents and seismic attributes in actual drilling data.

[0131] Understandably, based on actual drilling data, we can identify high-gas-producing sections and low-gas-producing sections, and thus determine which attenuation gradient range corresponds to a high-gas-producing section and which corresponds to a low-gas-producing section. This allows us to determine the corresponding thresholds. In practical applications, once the attenuation gradient attribute values ​​are obtained, the gas content of the fracture, such as high-gas-producing sections and low-gas-producing sections, can be determined based on the preset correspondence.

[0132] It should be noted that the actual drilling data in this invention is not used in the calculation but only to confirm the threshold of the final data volume. It can be seen that the prediction results objectively reflect the gas-bearing properties of the fractured reservoir and have low ambiguity.

[0133] This invention is based on pre-stack gathers with different azimuths and incident angles. It calculates the attenuation gradient that is sensitive to gas content, greatly extracting the effective information from seismic data. The prediction results are compared and analyzed with actual drilling production wells to complete the final prediction of fracture gas content. It has high accuracy, good stability, and strong lateral and longitudinal prediction capabilities.

[0134] Applying the gas-bearing prediction scheme of the present invention, since the seismic wave energy parallel to the direction of the fracture and perpendicular to the direction of the fracture exhibits significant differences during the underground propagation of seismic waves, the fracture identification method based on azimuth gathers has a significant effect.

[0135] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The attenuation gradient extracted from pre-stack incident angle gathers as a function of the incident angle can effectively predict the gas content of the reservoir, effectively mining seismic data information and having strong generalization capabilities.

[0136] It is evident that by using the attenuation gradient to predict gas content based on the change of incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted, reducing the amount of computation and the impact of other factors such as the degree of fracture filling on the prediction results.

[0137] The computer device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The computer device may include, but is not limited to, processor 420 and memory 410. Those skilled in the art will understand that... Figure 6 This is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the computer device may also include input / output devices, network access devices, buses, etc.

[0138] The processor 420 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0139] The memory 410 can be an internal storage unit of the computer device, such as a hard drive or memory. The memory 410 can also be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card.

[0140] Furthermore, the memory 410 may include both internal storage units and external storage devices of the computer device. The memory 410 is used to store the computer program and other programs and data required by the computer device. The memory 410 can also be used to temporarily store data that has been output or will be output.

[0141] Example 4

[0142] This application also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the memory described in the above embodiments; or it may be a standalone computer-readable storage medium not assembled into a computer device. The computer-readable storage medium stores one or more computer programs, which, when executed by a processor, implement the methods described above.

[0143] In some cases, the method implemented by the processor when executing the computer program may include steps S101 to S104:

[0144] like Figure 1 The diagram shown is a flowchart of a gas content prediction method provided by the present invention. The gas content prediction method may include the following steps:

[0145] Step S101: Obtain the front-stack gathers of each azimuth angle of the fractured reservoir, such as... Figure 2 As shown.

[0146] Step S102: Determine the incident angles corresponding to each azimuth angle in the pre-stacked front-side gathers, and stack each pre-stacked front-side gather based on the incident angles to obtain angle domain stacked data.

[0147] Step S103: Calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data.

[0148] Step S104: Predict the gas content of the fractured reservoir based on the attenuation gradient.

[0149] Applying the gas-bearing prediction scheme of the present invention, since the seismic wave energy parallel to the direction of the fracture and perpendicular to the direction of the fracture exhibits significant differences during the underground propagation of seismic waves, the fracture identification method based on azimuth gathers has a significant effect.

[0150] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The attenuation gradient extracted from pre-stack incident angle gathers as a function of the incident angle can effectively predict the gas content of the reservoir, effectively mining seismic data information and having strong generalization capabilities.

[0151] It is evident that by using the attenuation gradient to predict gas content based on the change of incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted, reducing the amount of computation and the impact of other factors such as the degree of fracture filling on the prediction results.

[0152] In other cases, the method implemented by the processor when executing the computer program may include steps S201 to S205:

[0153] like Figure 3 The diagram shown is a flowchart of a gas content prediction method provided by the present invention. The gas content prediction method may include the following steps:

[0154] Step S201: Obtain the front-stack gathers of each azimuth angle of the fractured reservoir, such as... Figure 2 As shown.

[0155] Step S202: Stack the front-end gathers of N directions according to the incident angle to obtain M angular domain stacked data of N directions, where N and M are natural numbers.

[0156] Preferably, N*M attenuation gradients can be calculated corresponding to M pre-stack front gathers in N directions.

[0157] Step S203: Calculate the attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain superimposed data.

[0158] Step S204: Perform linear fitting on the N*M attenuation gradients to obtain N seismic attributes of the attenuation gradient as a function of the incident angle at each azimuth.

[0159] Step S205: Perform nonlinear fitting on the N seismic attributes to obtain the target seismic attribute whose attenuation gradient varies with the incident angle and azimuth angle.

[0160] Preferably, the step of performing nonlinear fitting on the N seismic attributes includes performing elliptic fitting on the N seismic attributes.

[0161] In one scenario, the gas content of the fracture is determined based on a preset correspondence between the attenuation gradient and the gas content of the fracture; the correspondence between the attenuation gradient and the gas content of the fracture is determined based on the attenuation gradient of different fracture gas contents and seismic attributes in actual drilling data.

[0162] Understandably, based on actual drilling data, we can identify high-gas-producing sections and low-gas-producing sections, and thus determine which attenuation gradient range corresponds to a high-gas-producing section and which corresponds to a low-gas-producing section. This allows us to determine the corresponding thresholds. In practical applications, once the attenuation gradient attribute values ​​are obtained, the gas content of the fracture, such as high-gas-producing sections and low-gas-producing sections, can be determined based on the preset correspondence.

[0163] It should be noted that the actual drilling data in this invention is not used in the calculation but only to confirm the threshold of the final data volume. It can be seen that the prediction results objectively reflect the gas-bearing properties of the fractured reservoir and have low ambiguity.

[0164] This invention is based on pre-stack gathers with different azimuths and incident angles. It calculates the attenuation gradient that is sensitive to gas content, greatly extracting the effective information from seismic data. The prediction results are compared and analyzed with actual drilling production wells to complete the final prediction of fracture gas content. It has high accuracy, good stability, and strong lateral and longitudinal prediction capabilities.

[0165] Applying the gas-bearing prediction scheme of the present invention, since the seismic wave energy parallel to the direction of the fracture and perpendicular to the direction of the fracture exhibits significant differences during the underground propagation of seismic waves, the fracture identification method based on azimuth gathers has a significant effect.

[0166] During the propagation of seismic waves, there is a significant phenomenon of seismic wave energy attenuation in gas-bearing reservoirs. Predicting gas-bearing reservoirs based on post-stack attenuation properties has a good effect. The attenuation gradient extracted from pre-stack incident angle gathers as a function of the incident angle can effectively predict the gas content of the reservoir, effectively mining seismic data information and having strong generalization capabilities.

[0167] It is evident that by using the attenuation gradient to predict gas content based on the change of incident angle in trace collections at different azimuth angles, the gas content of fractures can be directly predicted, reducing the amount of computation and the impact of other factors such as the degree of fracture filling on the prediction results.

[0168] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0169] Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of the various method embodiments described above.

[0170] The computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0171] It should be noted that the content contained in the computer-readable medium may be appropriately added to or subtracted from the content as required by the legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium may not include electrical carrier signals and telecommunication signals.

[0172] For system or device embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to in the description of the method embodiments.

[0173] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0174] Furthermore, the specific names of each functional unit and module are only for easy differentiation and are not intended to limit the scope of protection of this application.

[0175] The specific working process of the units and modules in the above system can be referred to the corresponding process in the aforementioned method embodiments, and will not be repeated here.

[0176] It should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0177] Moreover, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0178] In the absence of further restrictions, an element defined by the phrase "comprising a..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0179] It should be understood that the terminology used in this application specification is for the purpose of describing particular embodiments only and is not intended to limit the application. As used in this application specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0180] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0181] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0182] The above description is merely a preferred embodiment of the present invention and is 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 are included within the scope of protection of the present invention.

Claims

1. A gas content prediction method characterized by, The method comprises the following steps: acquiring prestack azimuth gathers of each azimuth angle of a fractured reservoir; determining an incident angle corresponding to each azimuth angle in the prestack azimuth gathers, and stacking each prestack azimuth gather based on the incident angle to obtain angle domain stacked data; calculating an attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain stacked data; predicting gas content of the fractured reservoir based on the attenuation gradient; The step of determining an incident angle corresponding to each azimuth angle and stacking each prestack azimuth gather based on the incident angle to obtain angle domain stacked data comprises: stacking N prestack azimuth gathers according to incident angles respectively to obtain M angle domain stacked data of N azimuths, wherein N and M are both natural numbers. The step of stacking N prestack azimuth gathers according to incident angles respectively to obtain M angle domain stacked data of N azimuths comprises: calculating N*M attenuation gradients corresponding to M prestack azimuth gathers of N azimuths. The step of predicting gas content of the fractured reservoir based on the attenuation gradient comprises: performing linear fitting on the N*M attenuation gradients to obtain N seismic attributes of changes of the attenuation gradient with the incident angle at each azimuth; and performing nonlinear fitting on the N seismic attributes to obtain a target seismic attribute of changes of the attenuation gradient with the incident angle and the azimuth angle. The step of predicting gas content of the fractured reservoir based on the attenuation gradient comprises: determining the gas content of the fractured reservoir based on a preset corresponding relationship between the attenuation gradient and the gas content of the fractured reservoir; and the corresponding relationship between the attenuation gradient and the gas content of the fractured reservoir is determined according to different gas contents of the fractured reservoir and the attenuation gradient of the seismic attribute in actual drilling data.

2. The air content prediction method according to claim 1, characterized by, The step of performing nonlinear fitting on the N seismic attributes comprises: performing elliptical fitting on the N seismic attributes.

3. A gas content prediction device characterized by comprising: The method comprises the following steps: a prestack data acquisition module is configured to acquire prestack azimuth gathers of each azimuth angle of a fractured reservoir; a poststack data obtaining module is configured to determine an incident angle corresponding to each azimuth angle in the prestack azimuth gathers, and stack each prestack azimuth gather based on the incident angle to obtain angle domain stacked data; a gradient calculation module is configured to calculate an attenuation gradient corresponding to different azimuth angles and incident angles in the angle domain stacked data; a gas content prediction module is configured to predict gas content of the fractured reservoir based on the attenuation gradient; The poststack data obtaining module is configured to: stack N prestack azimuth gathers according to incident angles respectively to obtain M angle domain stacked data of N azimuths, wherein N and M are both natural numbers. The step of stacking N prestack azimuth gathers according to incident angles respectively to obtain M angle domain stacked data of N azimuths comprises: calculating N*M attenuation gradients corresponding to M prestack azimuth gathers of N azimuths. The step of predicting gas content of the fractured reservoir based on the attenuation gradient comprises: performing linear fitting on the N*M attenuation gradients to obtain N seismic attributes of changes of the attenuation gradient with the incident angle at each azimuth; and performing nonlinear fitting on the N seismic attributes to obtain a target seismic attribute of changes of the attenuation gradient with the incident angle and the azimuth angle. The step of predicting the gas-bearing property of the fractured reservoir based on the attenuation gradient comprises: determining the gas-bearing property of the fracture based on a preset corresponding relationship between the attenuation gradient and the gas-bearing property of the fracture; and the corresponding relationship between the attenuation gradient and the gas-bearing property of the fracture is determined according to the attenuation gradient of different gas-bearing properties of the fracture and seismic attributes in actual drilling data.

4. A computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the method of claim 1 or 2 when executing the computer program.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the method of claim 1 or 2.

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