A fracture detection method, device and apparatus based on azimuth discontinuity difference

Abstract

The present invention discloses a fracture detection method, device and equipment based on azimuth discontinuity difference, which may include: sorting the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic trace, and stacking the sorted multiple groups of seismic pre-stack gather data pairs with different azimuths to obtain multiple groups of azimuth stack data pairs; performing discontinuity detection on the multiple groups of azimuth stack data pairs to determine multiple groups of discontinuity detection data volume pairs; performing discontinuity difference analysis on the multiple groups of discontinuity detection data volume pairs respectively to determine multiple groups of discontinuity difference volumes; fusing the multiple groups of discontinuity difference volumes to determine the fracture data in the seismic azimuth pre-stack gather data. The present invention can realize discontinuity detection for each azimuth data, analyze the discontinuity difference of the azimuth stack data, determine the difference between the discontinuity detection results of different azimuth data, and improve the effect of fracture detection.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum exploration, and in particular to a fracture detection method, device and equipment based on azimuthal discontinuity differences. Background Art

[0002] In the crust and lithosphere, due to the influence of compression, stretching, shearing and other forces, the rock mass often breaks to form faults and cracks. This fault structure not only controls the regional or local geological structure and evolution characteristics, but also constitutes an important migration channel and storage space that affects mineral resources such as oil and natural gas, thereby affecting the flow and distribution of oil and gas resources. Therefore, identifying the fault structure and carefully describing its morphology and distribution characteristics are important tasks of seismic exploration, which are of great significance for reservoir prediction and accumulation analysis.

[0003] The seismic data used for fault characterization usually include offset stacking data and azimuthal anisotropy data. Based on the changes in seismic wave reflection characteristics caused by faults, a variety of fault detection methods have been developed using offset stacking data, including coherence body, curvature body, ant body, variance body and other common detection methods. The coherence body utilizes the similarity between adjacent seismic traces. When there is no fault in the stratum, the stratum is stably deposited, the amplitude, frequency and phase characteristics of adjacent seismic traces change little, the waveform similarity is high, and therefore the coherence value is also high; when there is a fault in the stratum, the stable stratigraphic deposition relationship is destroyed, the waveform similarity between the seismic traces deteriorates, resulting in a decrease in the coherence value, so low coherence values ​​have a good correspondence with faults. Based on this principle, three coherence body algorithms have been developed, including the first generation algorithm based on cross-correlation (cross-correlation algorithm C1, Bahorich and Farmer, 1995), the second generation algorithm based on multi-channel correlation (multi-channel correlation algorithm C2, Marfurt, 1998) and the third generation algorithm based on covariance matrix eigenvalue analysis (covariance matrix eigenvalue analysis algorithm C3, Gersztenkorn and Marfurt, 1999), and their fault detection capabilities have been gradually enhanced. The curvature body mainly describes the degree of curvature or mutation of seismic reflection phase axis. When the formation is stably deposited, the formation trend is relatively straight, and the curvature is zero at this time. Under the action of tectonic stress, the formation deforms, breaks and displaces, which is reflected in the seismic data as changes in the bending and extension of the phase axis, that is, changes in curvature. Therefore, the curvature change of the event axis has an obvious corresponding relationship with the fault characteristics. By solving the curvature of the structural layer where the event axis is located, the fault characterization of the stratum can be achieved. Commonly used fault characterization methods include mean curvature, Gaussian curvature, tilt curvature, strike curvature, etc. (Chopra, 2007). The ant body algorithm is a bionic optimization algorithm that simulates the foraging behavior of real ant colonies in nature. It uses the spatial discontinuity of seismic data to find faults through nonlinear optimization. As a kind of statistical information, the variance body mainly reflects the difference between adjacent seismic data by calculating the variance accumulation of each sampling point in the analysis time window. When the event axis is relatively continuous and the lateral change is small, the variance value is close to zero, and when the lateral change of the event axis is more drastic, the variance value will increase. Therefore, this constitutes the theoretical basis for using the change of variance value to reflect the fault information, and this method has also been widely used in practice (Liu Haiyan, 2016).

[0004] Azimuth anisotropy data is seismic data obtained after anisotropic migration. Compared with conventional data, this data adds dimensional information related to azimuth. Considering the changes in travel time and reflection characteristics in different azimuths caused by faults and cracks during seismic wave propagation, azimuth information can be used to detect faults. Commonly used methods include travel time azimuth anisotropy analysis and amplitude anisotropy analysis (Bakulin and Tsvankin, 2000). In the azimuth gather, due to the influence of anisotropy, the travel time and reflection amplitude of seismic waves show periodic variation characteristics with the azimuth, and appear as an ellipse on the plane. For the travel time ellipse feature, the propagation speed of seismic waves in the long axis direction is slow and the travel time is long, while the propagation speed in the short axis direction is fast and the travel time is short; for the amplitude ellipse feature, the stratum difference in the long axis direction is large and the amplitude is strong, while the stratum difference in the short axis direction is small and the amplitude is weak. It is generally believed that the directional arrangement of cracks is the main cause of anisotropy, so the detection of small-scale cracks can be achieved based on anisotropy analysis. Summary of the invention

[0005] The inventor found in practical applications that the offset stacking data is seismic data processed by the conventional reflection wave data processing flow. When fault detection is performed based on this data, the requirements for data quality are usually low, the amount of calculation is relatively small, and the stability is high. However, this data often has a better response to large-scale faults, and for small-scale cracks, since the energy of the seismic wave mainly manifests as scattering when it passes, the reflected energy is weak, and at the same time, it is limited by the resolution of the seismic data, resulting in unclear response characteristics, that is, the sensitivity of small faults is not strong. Although the azimuth anisotropic data can detect small-scale quantitatively arranged cracks, that is, the method based on the travel time or amplitude ellipse feature analysis of the azimuth gather can realize the prediction of small-scale cracks, the data quality requirements for the azimuth gather are high. In addition, since the amount of data in the azimuth gather is large and the amount of calculation is relatively large, the computer performance is required to be high, and the stability of the method is easily affected. When the data quality is low, it is often difficult to achieve a stable solution of the ellipse feature, thereby reducing the accuracy of crack prediction.

[0006] Therefore, the fracture detection method based on conventional superposition data has high stability, but low detection accuracy for small-scale fractures, while the method based on azimuthal anisotropy data improves the accuracy of small-scale fracture prediction, but generally has poor stability. In view of the above problems, the present invention is proposed to provide a fracture detection method, device and apparatus based on azimuthal discontinuity difference that overcomes the above problems or at least partially solves the above problems.

[0007] In a first aspect, an embodiment of the present invention provides a fracture detection method based on azimuthal discontinuity difference, which may include:

[0008] The seismic azimuth pre-stack gather data in the survey area are sorted according to the azimuth information of the seismic traces, and a plurality of groups of seismic pre-stack gather data pairs with different azimuths are stacked to obtain a plurality of groups of azimuth stack data pairs;

[0009] Performing discontinuity detection on the plurality of groups of azimuth stacking data pairs to determine a plurality of groups of discontinuous detection data volume pairs;

[0010] Performing discontinuity difference analysis on the plurality of groups of discontinuity detection data volume pairs respectively to determine a plurality of groups of discontinuity difference volumes;

[0011] A plurality of groups of discontinuity difference bodies are fused to determine the fracture data in the seismic azimuth prestack gather data.

[0012] Optionally, the seismic azimuth pre-stack gather data in the survey area are sorted according to the azimuth information of the seismic traces, and a plurality of groups of sorted seismic pre-stack gather data with different azimuths are stacked to obtain a plurality of groups of azimuth stack data pairs, including:

[0013] Separate the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic traces to determine multiple groups of seismic pre-stack gather data pairs with different azimuths;

[0014] The seismic pre-stack gather data pairs are stacked to obtain multiple groups of azimuth stack data pairs.

[0015] Optionally, the sorting of the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic traces includes:

[0016] Determine multiple sets of orthogonal azimuth pairs within the survey area;

[0017] The seismic azimuth pre-stack gather data in the survey area are sorted according to the azimuth information of the multiple groups of orthogonal azimuth pairs and seismic traces.

[0018] Optionally, determining a plurality of groups of orthogonal orientation pairs within the survey area includes:

[0019] The azimuth angles of multiple groups of orthogonal azimuth pairs are determined according to the initial azimuth angle and the number of orthogonal azimuth pairs.

[0020] Optionally, the method may further include: determining the initial azimuth angle according to a priori value of the azimuth of the fracture.

[0021] Optionally, performing discontinuity detection on the plurality of groups of azimuth stacking data pairs includes:

[0022] The azimuth superposition data is detected using at least one of the following detection methods: a coherence volume detection algorithm, a curvature volume detection algorithm, an ant volume detection algorithm, and a variance volume detection algorithm.

[0023] In a second aspect, an embodiment of the present invention provides a fracture detection device based on azimuthal discontinuity difference, which may include:

[0024] A sorting module is used to sort the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic trace, and to stack the sorted multiple groups of seismic pre-stack gather data pairs with different azimuths to obtain multiple groups of azimuth stack data pairs;

[0025] A detection module, used for performing discontinuity detection on the plurality of groups of azimuth superposition data pairs, and determining a plurality of groups of discontinuous detection data volume pairs;

[0026] An analysis module, used for performing discontinuity difference analysis on the plurality of groups of discontinuity detection data volume pairs respectively, to determine a plurality of groups of discontinuity difference volumes;

[0027] A fusion module is used to fuse multiple groups of discontinuity difference bodies to determine the fracture data in the seismic azimuth pre-stack gather data.

[0028] In a third aspect, an embodiment of the present invention provides a reservoir distribution prediction method, which may include: predicting reservoir distribution based on fracture data obtained by the fracture detection method based on azimuthal discontinuity difference described in the first aspect.

[0029] In a fourth aspect, an embodiment of the present invention provides a reservoir distribution prediction device, which may include: a prediction module and a fracture detection device based on azimuthal discontinuity difference as described in the second aspect;

[0030] The prediction module is used to predict reservoir distribution based on the fracture data obtained by the fracture detection device based on azimuthal discontinuity difference.

[0031] In a fifth aspect, an embodiment of the present invention provides a method for analyzing oil reservoir migration, which may include: analyzing oil reservoir migration based on fracture data obtained according to the fracture detection method based on azimuthal discontinuity difference described in the first aspect.

[0032] In a sixth aspect, an embodiment of the present invention provides an oil reservoir migration analysis device, which may include: a migration analysis module and a fracture detection device based on azimuthal discontinuity difference as described in the second aspect;

[0033] The migration analysis module is used to analyze reservoir migration based on the fracture data obtained by the fracture detection device based on azimuthal discontinuity difference.

[0034] In the seventh aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the fracture detection method based on azimuthal discontinuity differences as described in the first aspect, or implements the reservoir distribution prediction method as described in the third aspect, or implements the oil reservoir migration analysis method as described in the fifth aspect.

[0035] In an eighth aspect, an embodiment of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for detecting fractures based on azimuthal discontinuity differences as described in the first aspect is implemented, or the method for predicting reservoir distribution as described in the third aspect is implemented, or the method for analyzing oil reservoir migration as described in the fifth aspect is implemented.

[0036] The beneficial effects of the above technical solution provided by the embodiment of the present invention include at least:

[0037] In an embodiment of the present invention, a method, device and equipment for fracture detection based on azimuth discontinuity difference is provided. The method may include: sorting the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic trace, and stacking the sorted multiple groups of seismic pre-stack gather data pairs with different azimuths to obtain multiple groups of azimuth stacked data pairs; performing discontinuity detection on the multiple groups of azimuth stacked data pairs to determine multiple groups of discontinuity detection data volume pairs; performing discontinuity difference analysis on the multiple groups of discontinuity detection data volume pairs respectively to determine multiple groups of discontinuity difference volumes; fusing the multiple groups of discontinuity difference volumes to determine fracture data in the seismic azimuth pre-stack gather data. The present invention is aimed at azimuth stacked data, that is, each azimuth data can realize discontinuity detection. On this basis, the discontinuity difference of the azimuth stacked data is analyzed to determine the difference between the discontinuity detection results of different azimuth data, and the conventional post-stack fracture detection method is introduced. By designing a technical process for solving discontinuity differences based on azimuth stacked volumes, the quality requirements for azimuth seismic data are weakened, and the effect of fracture detection is improved.

[0038] Furthermore, compared with the conventional coherent detection results, the resolution has been significantly improved, and the edge and interior features of the fracture have been clearly depicted. At the same time, some small fracture features in the blank area that cannot be detected in the conventional results are also clearly depicted, reflecting the advantages of this method in small fracture detection. With the help of azimuthal seismic data, based on the difference characteristics of the discontinuity of seismic wave propagation in different azimuths, the present invention can improve the detection effect of the edge and interior of the fracture, and further improve the detection ability of small-scale fractures.

[0039] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0040] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0042] Figure 1 This is a flow chart of the fracture detection method based on azimuthal discontinuity difference provided in Example 1 of the present invention;

[0043] Figure 2 This is a specific flow chart of the fracture detection method provided in Example 1 of the present invention;

[0044] Figure 3 This is a flowchart for implementing step S21 provided in Embodiment 1 of the present invention;

[0045] Figure 4 A schematic diagram of a planar result of coherent detection based on full superposition data provided in Embodiment 1 of the present invention;

[0046] Figure 5 This is a schematic diagram of the fracture detection plane result based on the azimuthal discontinuity difference provided in Example 1 of the present invention;

[0047] Figure 6 This is a schematic diagram of a fracture detection device based on azimuthal discontinuity difference provided in Example 1 of the present invention. DETAILED DESCRIPTION

[0048] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0049] Example 1

[0050] Embodiment 1 of the present invention provides a fracture detection method based on azimuth discontinuity difference, which belongs to the field of petroleum geophysical exploration and is mainly used to improve the detection capability of formation fractures. Figure 1As shown, the method may include the following steps:

[0051] Step S11, sorting the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic traces, and stacking the sorted multiple groups of seismic pre-stack gather data pairs with different azimuths to obtain multiple groups of azimuth stack data pairs.

[0052] This step mainly groups the seismic azimuth pre-stack gather data according to the azimuth information of the seismic traces, and stacks the determined multiple groups of seismic pre-stack gather data pairs of different azimuths to obtain multiple groups of azimuth stack data pairs.

[0053] Step S12: performing discontinuity detection on the multiple sets of azimuth superposition data pairs to determine multiple sets of discontinuity detection data volume pairs.

[0054] Step S13: performing discontinuity difference analysis on the multiple groups of discontinuity detection data volumes respectively to determine multiple groups of discontinuity difference volumes.

[0055] Step S14: fuse multiple groups of discontinuity difference volumes to determine the fracture data in the seismic azimuth prestack gather data.

[0056] In the embodiments of the present invention, the inventors have discovered that seismic waves are affected by underground faults and cracks during propagation, and their propagation characteristics will change with the change of azimuth. Therefore, for the same underground medium, the seismic reflection characteristics extracted from different azimuths will be different. In order to highlight this difference and weaken the influence of background information, a difference comparison method can be used, which also constitutes the inventive concept of fracture detection based on azimuth discontinuity differences.

[0057] The inventor targets azimuth stacking data, that is, each azimuth data can realize discontinuity detection. On this basis, the discontinuity differences of the azimuth stacking data are analyzed, the differences between the discontinuity detection results of different azimuth data are determined, and the conventional post-stack fracture detection method is introduced. By designing a technical process for solving discontinuity differences based on azimuth stacking bodies, the quality requirements for azimuth seismic gather data are weakened, and the effect of fracture detection is improved.

[0058] In a specific embodiment, referring to Figure 2 As shown, the above-mentioned fracture detection method based on azimuth discontinuity difference provided by the embodiment of the present invention may include the following steps:

[0059] Step S21, sorting the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic traces, and determining a plurality of groups of seismic pre-stack gather data pairs with different azimuths.

[0060] This step is to divide the seismic azimuth pre-stack gather data in the survey area according to the azimuth, and generate multiple pre-stack gather data pairs with different azimuths. For more details, refer to Figure 3 As shown, the implementation of this step may include:

[0061] Step S211: determine multiple groups of orthogonal orientation pairs within the survey area.

[0062] The inventors based their work on the fact that seismic waves will exhibit anisotropic characteristics related to azimuth when propagating in anisotropic media, that is, the propagation characteristics vary with the change of azimuth. For faults or directional cracks and longitudinal wave seismic exploration, when seismic waves propagate parallel to the fault direction, the seismic waves are least affected; when propagating perpendicular to the fault direction, the seismic waves are most affected; and when propagating along other directions, the impact on seismic waves is between the above two. Therefore, when the propagation directions of seismic waves are respectively parallel and perpendicular to the fault direction, the greatest difference will be exhibited. In order to utilize this difference feature, when determining the seismic pre-stack gather data pairs with different azimuths in the survey area, the orthogonality of the azimuth is used, that is, while sorting out N azimuth stacking data, another N azimuth stacking data perpendicular to the N azimuths are also sorted out, totaling 2N azimuth stacking data, and these data are combined in pairs to form orthogonal azimuth pairs.

[0063] Specifically, this step determines the azimuths of multiple groups of orthogonal azimuth pairs according to the initial azimuth and the number of orthogonal azimuth pairs, that is, the azimuths of the orthogonal azimuth pairs The value of N and the initial azimuth angle θ 0 It can be obtained by formula (1):

[0064]

[0065] For example, taking N=3 as an example, 6 azimuth stacking data can be selected. Assume that the initial azimuth angle θ 0 =0°, the corresponding orthogonal azimuth pairs are (0°, 90°), (30°, 120°) and (60°, 150°); Assuming the initial azimuth angle θ 0 =15°, the corresponding orthogonal orientation pairs are (15°, 105°), (45°, 135°) and (75°, 165°).

[0066] Taking N=5 as an example, 10 azimuth stacking data can be selected. Assume that the initial azimuth angle is θ 0 =0°, the corresponding orthogonal azimuth pairs are (0°, 90°), (18°, 108°), (36°, 126°), (54°, 144°) and (72°, 162°); Assuming the initial azimuth angle θ 0=15°, the corresponding orthogonal orientation pairs are (15°, 105°), (33°, 123°), (51°, 141°), (69°, 159°) and (87°, 177°).

[0067] It should be noted that the inventors found that the larger the value of N, the more orthogonal azimuth pairs are divided, and the more consistent the parallelism and perpendicularity of one of the orthogonal azimuth pairs with the actual fault direction, the more likely it is to find the maximum azimuth difference. However, the increase in orthogonal azimuth pairs also leads to a decrease in the number of seismic traces during stacking, which in turn affects the signal-to-noise ratio of stacked data in each orientation, which is not conducive to the practical application of the method. Therefore, in practice, the value of N needs to take into account both aspects, namely the number of orthogonal azimuth pairs and the signal-to-noise ratio of azimuth stacking data.

[0068] In an optional embodiment, the initial azimuth angle may also be determined based on a priori values ​​of the fracture azimuth. 0 There is no special requirement for the determination of , usually it can be set to 0°. In practical applications, if the main development orientation of the fault has been determined through other data With a priori knowledge, the initial azimuth angle is determined according to the a priori value of the fault azimuth. For example, the initial azimuth angle θ can be determined by formula (2): 0 , to optimize the partitioning of orthogonal orientation pairs.

[0069]

[0070] in, Indicates taking the maximum value of parameter k. For example, according to formulas (1) and (2), when N=3, the corresponding orthogonal orientation pairs are (5°, 95°), (35°, 125°) and (65°, 155°); when N=5, the corresponding orthogonal orientation pairs are (17°, 107°), (35°, 125°), (53°, 143°), (71°, 161°) and (89°, 179°).

[0071] Step S212: sorting the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the multiple groups of orthogonal azimuth pairs and the seismic traces to obtain seismic pre-stack gather data pairs with different azimuths.

[0072] This step is to sort out the seismic pre-stack gather data pairs with different orientations according to the multiple groups of orthogonal orientation pairs determined in step S211 and the orientation information of the seismic traces, so as to facilitate the analysis and processing of the seismic pre-stack gather data pairs.

[0073] Step S22: stacking the pre-stack seismic gather data pairs to obtain multiple groups of azimuth stack data pairs.

[0074] This step is to stack the multiple groups of seismic pre-stack gather data with different azimuths determined in the above step S21 to obtain multiple groups of azimuth stacking data. The process of the above stacking processing in the embodiment of the present invention can be: according to the gather data azimuth corresponding to the seismic trace information and the preset stacking parameters, as well as the set target layer parameters and the preset calculation method, multiple gather points of the target layer are selected for stacking. Of course, the embodiment of the present invention is not limited to the above stacking method.

[0075] Step S23: Perform discontinuity detection on the multiple sets of azimuth superposition data pairs to determine multiple sets of discontinuity detection data volume pairs.

[0076] This step is consistent with the above step S12. In this embodiment, at least one of the following detection methods can be used to detect the orientation superposition data: a coherence volume detection algorithm, a curvature volume detection algorithm, an ant volume detection algorithm, and a variance volume detection algorithm.

[0077] For example, the above step S22 obtains multiple groups (N groups) of azimuth superposition data as follows: The discontinuities in the seismic data are calculated respectively. This discontinuity is essentially a specific expression of the fault characteristics implicit in the seismic data. In this way, N discontinuity detection data volumes can be obtained. Due to the different orientations of the data bodies, according to the propagation characteristics of seismic waves, the discontinuity detection body There will be differences between them, and this difference reflects the impact of underground fault characteristics on seismic waves propagating in different directions.

[0078] Step S24: performing discontinuity difference analysis on the multiple groups of discontinuity detection data volumes respectively to determine multiple groups of discontinuity difference volumes.

[0079] This step is consistent with the above step S13. In this embodiment of the present invention, for each orthogonal orientation pair discontinuity detection result, the absolute value of the difference D is calculated. k To highlight the fracture characteristics, as shown in formula (3):

[0080]

[0081] Among them, D k The difference between discontinuous data bodies in different directions.

[0082] The inventors found that for underground media, when there are no faults or cracks, the anisotropic characteristics of seismic wave propagation are relatively unobvious. At this time, no matter from which direction the analysis is performed, the discontinuity characteristics are relatively similar, so the difference is small, resulting in a smaller value of formula (3); under the influence of faults or cracks, the discontinuity characteristics of seismic waves in different directions will be different. At this time, the difference comparison achieved through formula (3) can further highlight this difference.

[0083] Step S25, fusing multiple groups of discontinuity difference volumes to determine the fracture data in the seismic azimuth prestack gather data.

[0084] This step is consistent with the above step S14. The embodiment of the present invention is based on the fact that under the influence of the fault, there will be differences between the discontinuities of each orthogonal azimuth pair. However, due to the influence of the propagation azimuth of the seismic wave, the size of the difference between each orthogonal pair in formula (3) will be different. Among the many orthogonal azimuth pairs, the greatest difference will be shown when the seismic wave propagates parallel and perpendicular to the fault respectively. Therefore, for the discontinuity difference volume D of multiple orthogonal azimuth pairs k (k=0,1,2,…,N-1), select the maximum value among them and fuse them into the final discontinuity difference body, so as to achieve the best detection of fracture features, as shown in formula (4):

[0085] D(i,j,l)=Max{D 0 (i,j,l),D 1 (i,j,l),D 2 (i,j,l),…,D N-1 (i,j,l)} Formula (4)

[0086] Among them, (i, j, l) represents the coordinates of the sample point in the data volume.

[0087] This method is applied to fracture detection in 3D seismic data and compared with conventional methods. Figure 4 The planar results of coherent detection based on full stack data are shown, where dark colors represent fractures. Due to the low resolution, only the outline features of large fractures can be depicted. Figure 5 The plane result of the fracture detection based on the difference of azimuthal discontinuity has a significantly improved resolution compared with the conventional coherent detection result, and the edge and interior features of the fracture have been clearly depicted. At the same time, some small fracture features in the blank area that cannot be detected in the conventional results are also clearly depicted, reflecting the advantage of this method in small fracture detection. With the help of azimuthal seismic data, the present invention can improve the detection effect of the fracture edge and interior based on the difference characteristics of the discontinuity of seismic wave propagation in different azimuths, thereby improving the detection ability of small-scale fractures.

[0088] Based on the same inventive concept, Embodiment 1 of the present invention also provides a fracture detection device based on azimuth discontinuity difference, referring to Figure 6 As shown, the device may include: a sorting module 11, a detection module 12, an analysis module 13 and a fusion module 14, and its working principle is as follows:

[0089] The sorting module 11 is used to sort the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic trace, and to stack the sorted multiple groups of seismic pre-stack gather data pairs with different azimuths to obtain multiple groups of azimuth stacked data pairs. Specifically, the sorting module 11 may include a sorting subunit and a stacking subunit; the sorting subunit 111 is used to sort the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic trace, and determine multiple groups of seismic pre-stack gather data pairs with different azimuths; the stacking subunit 112 is used to stack the seismic pre-stack gather data pairs to obtain multiple groups of azimuth stacked data pairs.

[0090] The detection module 12 is used to perform discontinuity detection on multiple groups of azimuth superposition data pairs to determine multiple groups of discontinuous detection data volume pairs.

[0091] The analysis module 13 is used to perform discontinuity difference analysis on multiple groups of discontinuity detection data volume pairs respectively to determine multiple groups of discontinuity difference volumes.

[0092] The fusion module 14 is used to fuse multiple groups of discontinuity difference bodies to determine the fracture data in the seismic azimuth pre-stack gather data.

[0093] In an optional embodiment, the sorting subunit 111 is specifically used to determine multiple groups of orthogonal azimuth pairs in the survey area; and sort the seismic azimuth pre-stack gather data in the survey area according to the multiple groups of orthogonal azimuth pairs and the azimuth information of the seismic traces. More specifically, the sorting subunit 111 determines the azimuths of the multiple groups of orthogonal azimuth pairs according to the initial azimuths and the number of orthogonal azimuth pairs.

[0094] In another optional embodiment, the detection module 12 detects the orientation superposition data using at least one of the following detection methods: a coherence volume detection algorithm, a curvature volume detection algorithm, an ant volume detection algorithm, and a variance volume detection algorithm.

[0095] Based on the same inventive concept, embodiment 1 of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned fracture detection method based on azimuthal discontinuity difference is implemented.

[0096] Based on the same inventive concept, embodiment 1 of the present invention also 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 implements the above-mentioned fracture detection method based on orientation discontinuity difference when executing the program.

[0097] It should be noted that since the principles of the problems solved by these devices, computer-readable storage media and computer equipment are similar to the aforementioned fracture detection method based on azimuthal discontinuity differences, the implementation of the device, computer-readable storage medium and computer equipment can refer to the implementation of the aforementioned method. Therefore, regarding the fracture detection device based on azimuthal discontinuity differences in the above embodiment, the specific manner in which each module performs operations has also been described in detail in the embodiment of the method, and will not be elaborated here.

[0098] Example 2

[0099] Embodiment 2 of the present invention provides a reservoir distribution prediction method, which comprises: predicting reservoir distribution based on fracture data obtained by the fracture detection method based on azimuthal discontinuity difference described in Embodiment 1.

[0100] The above reservoir distribution prediction method in the embodiment of the present invention uses the fracture data detected in the above embodiment 1 as reference data for reservoir distribution prediction to perform reservoir distribution prediction. Specific examples thereof will not be repeated here.

[0101] Based on the same inventive concept, embodiment 2 of the present invention further provides a reservoir distribution prediction device, which may include: a prediction module and a fracture detection device based on azimuthal discontinuity difference in embodiment 1;

[0102] A prediction module is used to predict reservoir distribution according to the fracture data obtained by the fracture detection device based on azimuthal discontinuity difference.

[0103] Based on the same inventive concept, Embodiment 2 of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned reservoir distribution prediction method is implemented.

[0104] Based on the same inventive concept, Embodiment 2 of the present invention also 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 implements the above-mentioned reservoir distribution prediction method when executing the program.

[0105] It should be noted that since the principles of solving the problems solved by these devices, computer-readable storage media and computer equipment are similar to those of the aforementioned reservoir distribution prediction method, the implementation of the device, computer-readable storage medium and computer equipment can refer to the implementation of the aforementioned method, and the specific manner in which each module in the reservoir distribution prediction device performs operations has also been described in detail in the embodiments of the method, and will not be elaborated here.

[0106] Example 3

[0107] Embodiment 3 of the present invention provides a method for analyzing oil reservoir migration, the method comprising: analyzing oil reservoir migration according to the fracture data obtained by the fracture detection method based on azimuthal discontinuity difference described in Embodiment 1.

[0108] The above-mentioned reservoir distribution prediction method in the embodiment of the present invention uses the fracture data detected in the above-mentioned embodiment 1 as reference data for reservoir migration analysis to predict reservoir distribution. The specific examples thereof are not repeated here.

[0109] Based on the same inventive concept, embodiment 3 of the present invention further provides an oil reservoir migration analysis device, which may include: a migration analysis module and a fracture detection device based on azimuthal discontinuity difference in embodiment 1;

[0110] The migration analysis module is used to analyze the migration of the oil reservoir according to the fracture data obtained by the fracture detection device based on the difference in azimuthal discontinuity.

[0111] Based on the same inventive concept, embodiment 3 of the present invention further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned reservoir migration analysis method is implemented.

[0112] Based on the same inventive concept, Embodiment 3 of the present invention also 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 implements the above-mentioned reservoir migration analysis method when executing the program.

[0113] It should be noted that since the principles of solving the problems solved by these devices, computer-readable storage media and computer equipment are similar to those of the aforementioned reservoir migration analysis method, the implementation of the device, computer-readable storage medium and computer equipment can refer to the implementation of the aforementioned method, and the specific manner in which each module in the reservoir migration analysis device performs operations has also been described in detail in the embodiments of the migration analysis method, and will not be elaborated here.

[0114] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0115] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0116] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0117] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0118] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A fracture detection method based on azimuthal discontinuity differences, It is characterized in that include: The seismic azimuth pre-stack gather data in the survey area are sorted according to the azimuth information of the seismic traces, and a plurality of groups of seismic pre-stack gather data pairs with different azimuths are stacked to obtain a plurality of groups of azimuth stack data pairs; Performing discontinuity detection on the plurality of groups of azimuth stacking data pairs to determine a plurality of groups of discontinuous detection data volume pairs; Performing discontinuity difference analysis on the plurality of groups of discontinuity detection data volume pairs respectively to determine a plurality of groups of discontinuity difference volumes; A plurality of groups of discontinuity difference bodies are fused to determine the fracture data in the seismic azimuth prestack gather data.

2. The method according to claim 1, It is characterized in that The seismic azimuth pre-stack gather data in the survey area are sorted according to the azimuth information of the seismic traces, and a plurality of groups of sorted seismic pre-stack gather data with different azimuths are stacked to obtain a plurality of groups of azimuth stack data pairs, including: Separate the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic traces to determine multiple groups of seismic pre-stack gather data pairs with different azimuths; The seismic pre-stack gather data pairs are stacked to obtain multiple groups of azimuth stack data pairs.

3. The method according to claim 2, It is characterized in that The method of sorting the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic traces includes: Determine multiple sets of orthogonal azimuth pairs within the survey area; The seismic azimuth pre-stack gather data in the survey area are sorted according to the azimuth information of the multiple groups of orthogonal azimuth pairs and seismic traces.

4. The method according to claim 3, It is characterized in that The step of determining a plurality of orthogonal orientation pairs within the survey area comprises: The azimuth angles of multiple groups of orthogonal azimuth pairs are determined according to the initial azimuth angle and the number of orthogonal azimuth pairs.

5. The method according to claim 4, It is characterized in that Also includes: The initial azimuth is determined according to the priori value of the azimuth of the fracture.

6. The method according to any one of claims 1 to 5, It is characterized in that The performing discontinuity detection on the plurality of groups of azimuth stacking data pairs comprises: The azimuth superposition data is detected using at least one of the following detection methods: a coherence volume detection algorithm, a curvature volume detection algorithm, an ant volume detection algorithm, and a variance volume detection algorithm.

7. A fracture detection device based on azimuthal discontinuity differences, It is characterized in that include: A sorting module is used to sort the seismic azimuth pre-stack gather data in the survey area according to the azimuth information of the seismic trace, and to stack the sorted multiple groups of seismic pre-stack gather data pairs with different azimuths to obtain multiple groups of azimuth stack data pairs; A detection module, used for performing discontinuity detection on the plurality of groups of azimuth superposition data pairs, and determining a plurality of groups of discontinuous detection data volume pairs; An analysis module, used for performing discontinuity difference analysis on the plurality of groups of discontinuity detection data volume pairs respectively, to determine a plurality of groups of discontinuity difference volumes; A fusion module is used to fuse multiple groups of discontinuity difference bodies to determine the fracture data in the seismic azimuth pre-stack gather data.

8. A reservoir distribution prediction method, It is characterized in that include: The reservoir distribution is predicted by the fracture data obtained by the fracture detection method based on azimuthal discontinuity difference according to any one of claims 1 to 6.

9. A reservoir distribution prediction device, It is characterized in that include: A prediction module and a fracture detection device based on azimuthal discontinuity difference as claimed in claim 7; The prediction module is used to predict reservoir distribution based on the fracture data obtained by the fracture detection device based on azimuthal discontinuity difference.

10. A method for analyzing oil reservoir migration, It is characterized in that The reservoir migration is analyzed using the fracture data obtained by the fracture detection method based on azimuthal discontinuity difference according to any one of claims 1 to 6.

11. An oil reservoir migration analysis device, It is characterized in that include: A migration analysis module and a fracture detection device based on azimuthal discontinuity differences as claimed in claim 7; The migration analysis module is used to analyze reservoir migration based on the fracture data obtained by the fracture detection device based on azimuthal discontinuity difference.

12. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the program is executed by a processor, it implements the fracture detection method based on azimuthal discontinuity difference as described in any one of claims 1 to 6, or implements the reservoir distribution prediction method as described in claim 8, or implements the oil reservoir migration analysis method as described in claim 10.

13. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the program, the fracture detection method based on azimuthal discontinuity difference as described in any one of claims 1 to 6 is implemented, or the reservoir distribution prediction method as described in claim 8 is implemented, or the oil reservoir migration analysis method as described in claim 10 is implemented.

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