Method and device for enhancing seismic coherence attribute and storage medium

Abstract

The invention relates to a method for enhancing seismic coherence attributes. Two-dimensional scalar seismic coherence attributes can be obtained. Extracting fracture seed points according to the spatial similarity of the two-dimensional scalar seismic coherence attributes, and constructing a fracture skeleton according to the fracture seed points; calculating an inclination angle of a fault where each fracture seed point is located, and picking up a local optimal fracture path with maximum similarity according to the fracture seed points and the inclination angles of the faults; extracting a fault attribute value corresponding to each local optimal fracture path, and obtaining a local optimal fracture path score according to the fault attribute value; and integrating the local optimal fracture path scores into a global optimal fracture score result, and performing normalization processing on the global optimal fracture score result to obtain enhanced seismic coherence attributes. According to the technical scheme, the problem of poor continuity of partial fracture space in the seismic coherence attribute is solved, the stable enhanced seismic coherence attribute can be obtained, and the requirement of modern oil-gas exploration for fracture prediction is met.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic exploration, and in particular to a method, a device and a storage medium for enhancing seismic coherence attributes. Background Art

[0002] Fractures in underground strata are storage spaces and migration channels for oil and gas. Reliable fracture prediction results are important for oil and gas exploration and development. Seismic coherence attributes are a widely used method for predicting underground fractures. High-quality seismic coherence attributes play a vital role in the reliability of underground fracture prediction.

[0003] At present, the first-generation coherence technology based on three-channel cross-correlation, the second-generation coherence technology based on multi-channel similarity, the third-generation coherence technology based on intrinsic structure and the structural tensor are widely used in earthquake fracture prediction. These technologies mainly identify fractures based on the spatial discontinuity of seismic data, which leads to the discontinuity of the coherence attributes calculated by such methods in actual data applications and cannot describe the macroscopic morphology of fractures. In some structurally complex areas, the fidelity of seismic data is difficult to guarantee, and the extracted seismic coherence attributes will also have coherence anomalies in incoherent noise and some weak reflection continuous interfaces. In addition, when the fault displacement is approximately equal to the dominant period (or wavelength) of the reflector, the fracture response in the seismic coherence attribute is weak or disappears, resulting in a decrease in the spatial continuity of some coherence attributes.

[0004] Therefore, the seismic coherence attributes in current oil and gas seismic exploration are easily affected by noise in identifying discontinuous structures, and the spatial morphology of some fractures predicted by them has poor continuity. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide a method, device and storage medium for enhancing seismic coherence attributes to solve the problem that the existing seismic coherence attribute technology is easily affected by noise in identifying discontinuous structures and the predicted spatial morphology of some fractures has poor continuity.

[0006] According to a first aspect of an embodiment of the present invention, a method for enhancing seismic coherence attributes is provided, comprising:

[0007] Obtain two-dimensional scalar seismic coherence attributes;

[0008] Extracting fracture seed points according to the spatial similarity of two-dimensional scalar seismic coherence attributes, and constructing a fracture skeleton according to the fracture seed points;

[0009] Calculate the inclination angle of the fault where each fracture seed point is located, and pick the local optimal fracture path with maximum similarity according to the fracture seed point and the inclination angle of the fault;

[0010] Extracting the fault attribute value corresponding to each local optimal fracture path, and obtaining the local optimal fracture path score according to the fault attribute value;

[0011] The local optimal fracture path scores are integrated into global optimal fracture score results, and the global optimal fracture score results are normalized to obtain enhanced seismic coherence attributes.

[0012] Preferably, extracting fracture seed points according to the spatial similarity of two-dimensional scalar seismic coherence attributes and constructing a fracture skeleton according to the fracture seed points comprises:

[0013] Extracting sample points whose coherence attribute values ​​are less than a preset threshold from the scalar seismic coherence attributes as candidate fracture seed points;

[0014] Marking the location value of the smallest attribute data in the scalar seismic coherent attribute as an initial fracture seed point;

[0015] Taking the initial fault seed point as the center, obtain the similarity weight of each scalar seismic coherent attribute around it to the initial fault seed point; search for the next fault seed point in space according to the similarity weight; take the newly searched fault seed point as the initial fault seed point, repeat this step to find the next fault seed point, until the number of searches meets the preset number, and obtain all the qualified fault seed points in the scalar fault attribute;

[0016] Construct a fracture skeleton based on all fracture seed points.

[0017] Preferably, the calculating the dip angle of the fault where each fracture seed point is located includes:

[0018] The directional scanning method is used to calculate the inclination of the fault where each fault seed point is located, and the pth fault seed point S is calculated using the following formula: p The confidence level Q in each inclination angle θ p (θ):

[0019]

[0020] Where H is the range of seismic coherent attributes in the scanning direction θ; <·> means that the attribute value is processed along the scanning direction using a Gaussian function;

[0021] The fracture seed point S p The dip angle of the fault is expressed as: θ p =argmin(Q(θ)).

[0022] Preferably, picking the local optimal fracture path with maximum similarity according to the fracture seed point and the inclination angle of the fault includes:

[0023] For all the searched fault seed points and their corresponding fault inclination angles, set the window length lx in the x direction and the window length lt in the t direction;

[0024] With the pth (p=0,1,…,ns)th fault seed point as the center, with window length lx and window length lt, along the fault dip direction θ p Extract the corresponding local scalar seismic coherence attribute T p ;

[0025] The center point of the local scalar seismic coherence attribute is taken as the initial path point and marked as

[0026] The local scalar seismic coherence attribute is transferred to the initial path point (t i ,x j ) is expressed as:

[0027]

[0028] Among them, β is the path similarity coefficient constraint weight, α is the maximum dip angle of the local fault; l represents the order of the norm, l = 1 or 2; D is the similarity weight matrix of lt×lx;

[0029] The next fault path point found in the local scalar seismic coherence attribute is It is expressed as:

[0030]

[0031] in,

[0032] The newly searched fault path point is used as the initial fault path point, and the above path search steps are repeated until the number of searches meets nl, and the local optimal fault path L representing the fault in the local scalar earthquake fault attribute corresponding to the pth fault seed point is obtained. p (nl); pick up the optimal fracture path in the local scalar seismic coherence attribute corresponding to ns fracture seeds, and obtain the local optimal fracture path L corresponding to all seed points ns .

[0033] Preferably, the step of obtaining a local optimal fracture path score according to the fault attribute value comprises:

[0034] The local optimal fracture path score g is calculated by the following formula p :

[0035] g p (nl)=<1-T(L p (nl))>

[0036] Where p represents the pth fracture seed point, T(L p (nl)) represents the attribute value on the path, and <·> represents the attribute value processed by the Gaussian function along the scanning direction.

[0037] Preferably, the local optimal fracture path scores are integrated into global optimal fracture score results, and the global optimal fracture score results are normalized to obtain enhanced seismic coherence attributes, including:

[0038] All local optimal fracture paths L ns Score ns Integrate into the global optimal fracture score result M:

[0039]

[0040] The global optimal fracture score result M is normalized to obtain the enhanced seismic coherence attribute T en :

[0041]

[0042] Among them, M min is the minimum value of the cumulative score result, M max It is the maximum value of the cumulative score results.

[0043] According to a second aspect of an embodiment of the present invention, there is provided a device for enhancing seismic coherence attributes, comprising:

[0044] A main controller, and a memory connected to the main controller;

[0045] a memory in which program instructions are stored;

[0046] The main controller is used to execute program instructions stored in the memory to perform any of the above methods.

[0047] According to a third aspect of an embodiment of the present invention, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the method described in any one of the above is implemented.

[0048] The technical solution provided by the embodiments of the present invention may have the following beneficial effects:

[0049] It can be understood that the technical solution shown in the present invention can obtain two-dimensional scalar seismic coherence attributes; extract fracture seed points according to the spatial similarity of the two-dimensional scalar seismic coherence attributes, and construct a fracture skeleton according to the fracture seed points; calculate the inclination of the fault where each fracture seed point is located, and pick up the local optimal fracture path with the maximum similarity according to the fracture seed point and the inclination of the fault; extract the fault attribute value corresponding to each local optimal fracture path, and obtain the local optimal fracture path score according to the fault attribute value; integrate the local optimal fracture path score into the global optimal fracture score result, and normalize the global optimal fracture score result to obtain enhanced seismic coherence attributes. The technical solution shown in the present invention solves the problem of poor spatial continuity of some fractures in seismic coherence attributes, and thus can obtain stable enhanced seismic coherence attributes to meet the needs of modern oil and gas exploration for fracture prediction.

[0050] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0052] Figure 1 is a schematic diagram of steps of a method for enhancing seismic coherence attributes according to an exemplary embodiment;

[0053] Figure 2 is a schematic diagram of a basic form of a broken skeleton according to an exemplary embodiment;

[0054] Figure 3 is a schematic diagram of seismic data according to an exemplary embodiment;

[0055] Figure 4 It is a schematic diagram of enhanced earthquake coherent fracture attribute results according to an exemplary embodiment. DETAILED DESCRIPTION

[0056] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0057] In one embodiment, Figure 1 is a schematic diagram of steps of a method for enhancing seismic coherence attributes according to an exemplary embodiment, see Figure 1 , a method for enhancing seismic coherence attributes is provided, comprising:

[0058] Step S11, obtaining two-dimensional scalar seismic coherence attributes.

[0059] In practice, the input time sampling interval is dt, and the two-dimensional seismic coherence attribute T (nt, nx) is used, where dt is a constant in seconds; nt is the number of time sampling points; and nx is the number of traces in the x direction. Figure 3 .

[0060] Taking a specific actual scenario as an example, for example, the input time sampling interval is 0.003s for the two-dimensional seismic coherent fracture attribute T (nt, nx); the number of time sampling points nt = 151; the number of traces in the x direction nx = 101.

[0061] Step S12: extracting fracture seed points according to the spatial similarity of the two-dimensional scalar seismic coherence attributes, and constructing a fracture skeleton according to the fracture seed points.

[0062] It should be noted that this step includes:

[0063] Step S121: extracting sample points whose coherence attribute values ​​are less than a preset threshold from the scalar seismic coherence attributes as candidate fracture seed points.

[0064] In order to improve the calculation efficiency and reliability of subsequent calculations, all sample points with coherent attribute values ​​less than the threshold λ are first collected, thereby filtering out points with large attribute values ​​that are unlikely to belong to faults. The remaining sample points are potential fracture seed candidate points C(nt,nx).

[0065] Taking a specific actual scenario as an example, the threshold λ=0.7.

[0066] Step S122: The smallest attribute data among the scalar seismic coherent attributes The location value is marked as the initial fracture seed point S1:

[0067] S1={t i ,x j}

[0068] Step S123: Taking the initial fault seed point as the center, obtain each scalar seismic coherence attribute C around it. t,x A similarity weight D to the initial fracture seed point;

[0069]

[0070] in, l represents the order of the norm (l=1 or 2), and D is a similarity weight matrix of nt×nx, the smaller the value, the stronger the similarity.

[0071] The next fracture seed point S2 searched in the space according to the similarity weight can be expressed as:

[0072]

[0073] S2={t m ,x n}

[0074] Among them, S2≠S, and satisfies and That is, the next fracture seed point is within a certain spatial distance δ, and the search cannot be repeated.

[0075] The newly searched fracture seed point is used as the initial fracture seed point, and this step is repeated to find the next fracture seed point until the search times meet the preset times ns, and all the fracture seed points S(ns) that meet the conditions in the scalar fracture attribute are obtained.

[0076] Step S124: construct a fracture skeleton based on all fracture seed points. The basic form of the fracture skeleton is as follows: Figure 2 shown.

[0077] Step S13: Calculate the inclination angle of the fault where each fracture seed point is located, and pick up the local optimal fracture path with maximum similarity according to the fracture seed point and the inclination angle of the fault.

[0078] Faults are not necessarily nearly vertical. Before picking the optimal fault path, it is necessary to estimate the fault direction of each seed point, so that data can be selected along the fault direction for calculation, ensuring that the fault in the local window is nearly vertical when calculating the optimal fault path. Therefore, it should be noted that step S13 includes:

[0079] The directional scanning method is used to calculate the inclination of the fault where each fault seed point is located, and the pth fault seed point S is calculated using the following formula: p The confidence Q in each scanning direction θ p (θ):

[0080]

[0081] Where H is the range of seismic coherent attributes in the scanning direction θ; <·> means that the attribute value is processed along the scanning direction using a Gaussian function;

[0082] The fracture seed point S p The dip angle of the fault is expressed as: θ p =argmin(Q(θ)).

[0083] Step S14: extracting the fault attribute value corresponding to each local optimal fracture path, and obtaining the local optimal fracture path score according to the fault attribute value.

[0084] It should be noted that step S14 includes:

[0085] Step S141: for all the searched fracture seed points and their corresponding fracture inclination angles, set the window length lx in the x direction and the window length lt in the t direction.

[0086] Set the window length and half window length in the x direction to hlx and lx respectively. The window length lx can be expressed by the half window length hlx as: lx = 2hlx + 1. Both hlx and lx are positive integers. The range of hlx is The range of lx is 3≤lx≤nx; the window length and half window length in the t direction are set to hlt and lt respectively. The window length lt can be expressed by the half window length hlt as: lt=2hlt+1. Both hlt and lt are positive integers. The range of hlt is The range of lt is 3≤lt≤nt.

[0087] Step S142: With the pth (p=0, 1, ..., ns)th fault seed point as the center, with the window lengths lx and lt, along the dip direction θ of the fault p Extract the corresponding local scalar seismic coherence attribute T p .

[0088] Step S143: Use the local scalar seismic coherence attribute center point as the initial path point and mark it as This step can ensure that the path passes through the fracture seed point S p .

[0089] Step S144: local scalar seismic coherence attributes to the initial path point (t i ,x j ) is expressed as:

[0090]

[0091] Among them, β is the path similarity coefficient constraint weight, α is the maximum inclination angle of the local fault, that is, when searching for the next path point, the direction inclination angle cannot be less than α, thereby further ensuring that the local optimal fault path is picked up along the maximum similarity direction of the fault. l represents the order of the norm, l=1 or 2; D is a similarity weight matrix of lt×lx, the smaller the value, the stronger the similarity.

[0092] Step S145: search for the next fault path point in the local scalar seismic coherence attribute It is expressed as:

[0093]

[0094] in,

[0095] Step S146: Use the newly searched fracture path point as the initial fracture path point, repeat the above path search steps until the number of searches meets nl, and obtain the local optimal fracture path L representing the fracture in the local scalar earthquake fracture attribute corresponding to the pth fracture seed point. p (nl); Pick up the optimal fracture path in the local scalar seismic coherence attribute corresponding to ns fracture seeds, and obtain the local optimal fracture path L corresponding to all seed points ns .

[0096] For the pth seed point, we obtain an optimal fracture path L passing through the seed point and along the global minimum fault attribute value p (nl). We define these selected optimal fracture path points as voters, and the fault attribute values ​​extracted along the paths of these voters are used to define the fracture path scores.

[0097] It should be noted that, in step S14, the local optimal fracture path score is obtained according to the fault attribute value, including:

[0098] The local optimal fracture path score g is calculated by the following formula p :

[0099] g p (nl)=<1-T(L p (nl))>

[0100] Where p represents the pth fracture seed point, T(L p (nl)) represents the attribute value on the path, and <·> represents the attribute value processed by the Gaussian function along the scanning direction.

[0101] Step S15: Integrate the local optimal fracture path scores into global optimal fracture score results, normalize the score results, and obtain enhanced seismic coherence attributes.

[0102] It should be noted that step S15 includes:

[0103] All local optimal fracture paths L ns Score ns Integrate into the global optimal fracture score result M:

[0104]

[0105] The fracture paths that are traversed many times will have higher values ​​in the cumulative score map. These paths are more likely to represent real faults, which are strengthened in the global cumulative score results. On the contrary, since the noise paths are traversed less times and have lower scores, they are suppressed in the global cumulative score results.

[0106] In order to make the scores of different regions more comparable and highlight the high-scoring regions (real fault features) and low-scoring regions (noise), the global optimal fault score result M is normalized to obtain the enhanced seismic coherence attribute T en :

[0107]

[0108] Among them, M min is the minimum value of the cumulative score result, M max It is the maximum value of the cumulative score results.

[0109] See the schematic diagram of the enhanced earthquake coherent fracture attribute results for Figure 4 .

[0110] It can be understood that the technical solution shown in the present invention can obtain two-dimensional scalar seismic coherence attributes; extract fracture seed points according to the spatial similarity of the two-dimensional scalar seismic coherence attributes, and construct a fracture skeleton according to the fracture seed points; calculate the inclination of the fault where each fracture seed point is located, and pick up the local optimal fracture path with the maximum similarity according to the fracture seed point and the inclination of the fault; extract the fault attribute value corresponding to each local optimal fracture path, and obtain the local optimal fracture path score according to the fault attribute value; integrate the local optimal fracture path score into the global optimal fracture score result, and normalize the global optimal fracture score result to obtain enhanced seismic coherence attributes. The technical solution shown in the present invention solves the problem of poor spatial continuity of some fractures in seismic coherence attributes, and thus can obtain stable enhanced seismic coherence attributes to meet the needs of modern oil and gas exploration for fracture prediction.

[0111] The method first constructs a fracture skeleton based on the spatial similarity of coherent attributes. For each fracture seed point on the fracture skeleton, the local optimal fracture path is picked along the direction of maximum fracture similarity on the local coherent attribute centered on it. These optimal fracture paths are regarded as voters and given fracture scores, and all local fracture path scores are collected to generate a cumulative score result. Finally, the cumulative score result is normalized to make the characteristics of the fault layer in the coherent attribute clearer and the spatial morphology more continuous, thereby enhancing the coherent attribute.

[0112] According to a second aspect of an embodiment of the present invention, there is provided a device for enhancing seismic coherence attributes, comprising:

[0113] A main controller, and a memory connected to the main controller;

[0114] a memory in which program instructions are stored;

[0115] The main controller is used to execute program instructions stored in the memory to perform any of the above methods.

[0116] According to a third aspect of an embodiment of the present invention, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the method described in any one of the above is implemented.

[0117] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0118] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0119] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0120] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0121] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0122] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0123] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0124] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0125] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for enhancing seismic coherence attributes, characterized in that: include: Obtain two-dimensional scalar seismic coherence attributes; Extracting fracture seed points according to the spatial similarity of two-dimensional scalar seismic coherence attributes, and constructing a fracture skeleton according to the fracture seed points; Calculate the inclination angle of the fault where each fracture seed point is located, and pick the local optimal fracture path with maximum similarity according to the fracture seed point and the inclination angle of the fault; Extracting the fault attribute value corresponding to each local optimal fracture path, and obtaining the local optimal fracture path score according to the fault attribute value; The local optimal fracture path scores are integrated into global optimal fracture score results, and the global optimal fracture score results are normalized to obtain enhanced seismic coherence attributes.

2. The method according to claim 1, characterized in that: The method of extracting fracture seed points according to the spatial similarity of the two-dimensional scalar seismic coherence attributes and constructing a fracture skeleton according to the fracture seed points includes: Extracting sample points whose coherence attribute values ​​are less than a preset threshold from the scalar seismic coherence attributes as candidate fracture seed points; Marking the location value of the smallest attribute data in the scalar seismic coherent attribute as an initial fracture seed point; Taking the initial fault seed point as the center, obtain the similarity weight of each scalar seismic coherent attribute around it to the initial fault seed point; search for the next fault seed point in space according to the similarity weight; take the newly searched fault seed point as the initial fault seed point, repeat this step to find the next fault seed point, until the number of searches meets the preset number, and obtain all the qualified fault seed points in the scalar fault attribute; Construct a fracture skeleton based on all fracture seed points.

3. The method according to claim 2, characterized in that The calculating the dip angle of the fault where each fault seed point is located includes: The directional scanning method is used to calculate the inclination of the fault where each fault seed point is located, and the pth fault seed point S is calculated using the following formula: p The confidence level Q in each inclination angle θ p (θ): Where H is the range of seismic coherent attributes in the scanning direction θ; <·> means that the attribute value is processed along the scanning direction using a Gaussian function; The fracture seed point S p The inclination angle of the fault is expressed as: θ p =argmin(Q(θ)).

4. The method according to claim 3, characterized in that According to the fracture seed point and the inclination angle of the fault, the local optimal fracture path is picked with maximum similarity, including: For all the searched fault seed points and their corresponding fault inclination angles, set the window length lx in the x direction and the window length lt in the t direction; With the pth (p=0,1,…,ns)th fault seed point as the center, with window length lx and window length lt, along the fault dip direction θ p Extract the corresponding local scalar seismic coherence attribute T p ; The center point of the local scalar seismic coherence attribute is taken as the initial path point and marked as The local scalar seismic coherence attribute is transferred to the initial path point (t i ,x j ) is expressed as: Among them, β is the path similarity coefficient constraint weight, α is the maximum dip angle of the local fault; l represents the order of the norm, l = 1 or 2; D is the similarity weight matrix of lt×lx; The next fault path point found in the local scalar seismic coherence attribute is It is expressed as: in, The newly searched fault path point is used as the initial fault path point, and the above path search steps are repeated until the number of searches meets nl, and the local optimal fault path L representing the fault in the local scalar earthquake fault attribute corresponding to the pth fault seed point is obtained. p (nl); pick up the optimal fracture path in the local scalar seismic coherence attribute corresponding to ns fracture seeds, and obtain the local optimal fracture path L corresponding to all seed points ns .

5. The method according to claim 4, characterized in that Determining the local optimal fracture path score according to the fault attribute value includes: The local optimal fracture path score g is calculated by the following formula p : g p (nl)=<1-T(L p (nl))> Where p represents the pth fracture seed point, T(L p (nl)) represents the attribute value on the path, and <·> represents the attribute value processed by the Gaussian function along the scanning direction.

6. The method according to claim 5, characterized in that The local optimal fracture path scores are integrated into global optimal fracture score results, and the global optimal fracture score results are normalized to obtain enhanced seismic coherence attributes, including: All local optimal fracture paths L ns Score ns Integrate into the global optimal fracture score result M: The global optimal fracture score result M is normalized to obtain the enhanced seismic coherence attribute T en : Among them, M min is the minimum value of the cumulative score result, M max It is the maximum value of the cumulative score results.

7. A device for enhancing seismic coherence attributes, characterized in that: include: A main controller, and a memory connected to the main controller; a memory in which program instructions are stored; The main controller is used to execute program instructions stored in the memory and execute the method according to any one of claims 1 to 6.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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