A method, device and storage medium for enhancing earthquake coherence attributes

Abstract

The present invention relates to a method for enhancing seismic coherence attributes, which can obtain two-dimensional scalar seismic coherence attributes; extract fracture seed points based on the spatial similarity of the two-dimensional scalar seismic coherence attributes, and construct a fracture skeleton based on the fracture seed points; calculate the inclination of the fault where each fracture seed point is located, and pick a local optimal fracture path with maximum similarity based on the inclination of the fracture seed point and the fault; extract the fault attribute value corresponding to each local optimal fracture path, and obtain a local optimal fracture path score based on the fault attribute value; integrate the local optimal fracture path score into a 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, thereby obtaining stable enhanced seismic coherence attributes, meeting the needs of modern oil and gas exploration for fracture prediction.

Description

Technical Field

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

[0002] Fractures in underground formations serve as reservoirs and migration pathways for oil and gas. Reliable fracture prediction is crucial for oil and gas exploration and development. Seismic coherence attributes are a widely used method for predicting underground fractures, and high-quality seismic coherence attributes play a crucial role in the reliability of underground fracture prediction.

[0003] Currently, coherent attribute calculation methods such as 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. As a result, the coherent attributes calculated by such methods in actual data applications show discontinuous characteristics and cannot characterize the macroscopic morphology of fractures. In some structurally complex areas, the fidelity of seismic data is difficult to guarantee, and the extracted seismic coherent attributes will also show coherent 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 coherent attributes is weak or disappears, resulting in a decrease in the spatial continuity of some coherent 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 predicted faults 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 when 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 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 based on 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 calculating the local optimal fracture path score according to the fault attribute value;

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

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

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

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

[0015] Taking the initial fracture seed point as the center, obtain the similarity weight of each scalar seismic coherent attribute around it to the initial fracture seed point; search for the next fracture seed point in space based on the similarity weight; use the newly searched fracture seed point as the initial fracture seed point, and repeat this step to find the next fracture seed point until the number of searches meets the preset number, thereby obtaining all fracture seed points that meet the conditions in the scalar fracture 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 direction scanning method is used to calculate the inclination angle 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 inclination angle θ p (θ):

[0019]

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

[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) 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 attributes are transferred to the initial path points (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 Expressed as:

[0030]

[0031] in,

[0032] The newly searched fracture path point is used as the initial fracture path point, and the above path search steps are repeated until the number of searches meets nl, and the local optimal fracture path L representing the fracture in the local scalar earthquake fracture genus corresponding to the p-th fracture seed point is obtained. p (nl); Pick the optimal fracture path in the local scalar seismic coherence attributes 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 includes:

[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] Among them, p represents the pth fracture seed point, T(L p (nl)) represents the attribute value on the path, and <·> represents processing the attribute value along the scanning direction using a Gaussian function.

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

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

[0039]

[0040] Normalize the global optimal fracture score result M 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 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 and 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, wherein when the computer program is executed by a processor, any of the above methods is implemented.

[0048] The technical solutions 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 based on the spatial similarity of the two-dimensional scalar seismic coherence attributes, and construct a fracture skeleton based on the fracture seed points; calculate the inclination of the fault where each fracture seed point is located, and pick the local optimal fracture path with maximum similarity based on the inclination of the fracture seed point and the fault; extract the fault attribute value corresponding to each local optimal fracture path, and calculate the local optimal fracture path score based on the fault attribute value; integrate the local optimal fracture path scores into a 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, meeting 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 showing steps of a method for enhancing seismic coherence attributes according to an exemplary embodiment;

[0053] Figure 2 is a schematic diagram showing the 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 showing 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 illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0057] In one embodiment, Figure 1 is a schematic diagram of a method for enhancing earthquake coherence attributes according to an exemplary embodiment. Figure 1 , providing a method for enhancing seismic coherence attributes, including:

[0058] Step S11: Acquire two-dimensional scalar seismic coherence attributes.

[0059] In practice, the input is the two-dimensional seismic coherence attribute T(nt,nx) with a time sampling interval of dt, 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, and the two-dimensional seismic coherent fracture attribute T (nt, nx); the number of time sampling points nt = 151; and the number of traces in the x direction nx = 101.

[0061] Step S12: extracting fracture seed points based on the spatial similarity of the two-dimensional scalar seismic coherence attributes, and constructing a fracture skeleton based on 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] To improve computational efficiency and subsequent reliability, we first collect all sample points whose coherent attribute values are less than a threshold λ, thereby filtering out points with larger attribute values that are unlikely to belong to a fault. The remaining sample points are potential candidate fault seed 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 earthquake 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 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 the similarity weight matrix of nt×nx, where 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 genus 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 the local optimal fracture path with maximum similarity based on 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. This allows data to 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 direction scanning method is used to calculate the inclination angle 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; <·> indicates that the attribute values are processed using a Gaussian function along the scanning direction;

[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 calculating 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 as the half window length hlx: 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 fault dip direction θ p Extract the corresponding local scalar seismic coherence attribute T p .

[0088] Step S143: The center point of the local scalar seismic coherence attribute is used as the initial path point and marked as This step can ensure that the path passes through the fracture seed point S p .

[0089] Step S144: local scalar earthquake 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 dip angle of the local fault, that is, when searching for the next path point, the direction dip angle cannot be less than α, thereby further ensuring that the local optimal fault path is picked along the maximum similarity direction of the fault. l represents the order of the norm, l = 1 or 2; D is the similarity weight matrix of lt×lx, the smaller the value, the stronger the similarity.

[0092] Step S145: The next fault path point found in the local scalar earthquake coherence attribute is Expressed as:

[0093]

[0094] in,

[0095] Step S146: Use the newly searched fracture path point as the initial fracture path point and 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 p-th fracture seed point. p (nl); Pick up the optimal fracture path in the local scalar seismic coherence attributes 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 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] Among them, p represents the pth fracture seed point, T(L p (nl)) represents the attribute value on the path, and <·> represents processing the attribute value along the scanning direction using a Gaussian function.

[0101] Step S15: Integrate the local optimal fracture path scores into a global optimal fracture score result, and perform normalization processing on the score result to obtain enhanced seismic coherence attributes.

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

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

[0104]

[0105] The fault paths that are traversed multiple times will have higher values in the cumulative score graph. These paths are more likely to represent real faults and are enhanced 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 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 based on the spatial similarity of the two-dimensional scalar seismic coherence attributes, and construct a fracture skeleton based on the fracture seed points; calculate the inclination of the fault where each fracture seed point is located, and pick the local optimal fracture path with maximum similarity based on the inclination of the fracture seed point and the fault; extract the fault attribute value corresponding to each local optimal fracture path, and calculate the local optimal fracture path score based on the fault attribute value; integrate the local optimal fracture path scores into a 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, meeting the needs of modern oil and gas exploration for fracture prediction.

[0111] This method first constructs a fracture skeleton based on spatial similarity of coherent attributes. For each fracture seed point on the fracture skeleton, the optimal local fracture path is selected along the direction of maximum fracture similarity along the local coherent attributes centered on it. These optimal fracture paths are treated as voters and assigned fracture scores. The scores of all local fracture paths are then combined to generate a cumulative score. Finally, the cumulative score is normalized to enhance the coherent attributes, making the fracture features clearer and the spatial morphology more continuous, thereby strengthening the coherent attributes.

[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 and 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, wherein when the computer program is executed by a processor, any of the above methods 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 used for descriptive purposes only and should not be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" is 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 comprising 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 be performed out of 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 pertain.

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

[0121] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0122] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing module, or each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they 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] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

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

Claims

1. A method for enhancing earthquake coherence attributes, characterized in that: include: Obtain two-dimensional scalar seismic coherence attributes; extracting fracture seed points according to 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 based on the fracture seed point and the inclination angle of the fault; Extracting the fault attribute value corresponding to each local optimal fracture path, and calculating the local optimal fracture path score according to the fault attribute value; Integrating the local optimal fracture path scores into a global optimal fracture score result, and normalizing the global optimal fracture score result to obtain enhanced seismic coherence attributes; The calculation of the dip angle of the fault where each fault seed point is located includes: The direction scanning method is used to calculate the inclination angle 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 inclination angle θ p (θ): Where H is the range of seismic coherent attributes in the scanning direction θ; <·> indicates that the attribute values are processed using a Gaussian function along the scanning direction; The fracture seed point S p The dip angle of the fault is expressed as: θ p =argmin(Q(θ)); 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) 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 attributes are transferred to the initial path points (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 Expressed as: in, The newly searched fracture path point is used as the initial fracture path point, and the above path search steps are repeated until the number of searches meets nl, and the local optimal fracture path L representing the fracture in the local scalar earthquake fracture genus corresponding to the p-th fracture seed point is obtained. p (nl); Pick the optimal fracture path in the local scalar seismic coherence attributes corresponding to ns fracture seeds, and obtain the local optimal fracture path L corresponding to all seed points ns .

2. The method according to claim 1, characterized in that The method of extracting fracture seed points based on the spatial similarity of two-dimensional scalar seismic coherence attributes and constructing a fracture skeleton based on 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 fault seed points; Marking the location value of the minimum attribute data in the scalar seismic coherent attribute as the initial fracture seed point; Taking the initial fracture seed point as the center, obtain the similarity weight of each scalar seismic coherent attribute around it to the initial fracture seed point; search for the next fracture seed point in space based on the similarity weight; use the newly searched fracture seed point as the initial fracture seed point, and repeat this step to find the next fracture seed point until the number of searches meets the preset number, thereby obtaining all fracture seed points that meet the conditions in the scalar fracture attribute; Construct a fracture skeleton based on all fracture seed points.

3. The method according to claim 2, 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))> Among them, p represents the pth fracture seed point, T(L p (nl)) represents the attribute value on the path, and <·> represents processing the attribute value along the scanning direction using a Gaussian function.

4. The method according to claim 3, characterized in that The local optimal fracture path scores are integrated into a global optimal fracture score result, and the global optimal fracture score result is normalized to obtain enhanced seismic coherence attributes, including: All local optimal fracture paths L ns Score g ns Integrate into the global optimal fracture score result M: Normalize the global optimal fracture score result M to obtain the enhanced seismic coherence attribute T en : Among them, M min is the minimum value of the cumulative score result, M max is the maximum value of the cumulative score results.

5. A device for enhancing earthquake 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 perform the method according to any one of claims 1 to 4.

6. 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 4 is implemented.

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