Two-dimensional seismic horizon automatic tracking method and device

Abstract

The invention discloses a two-dimensional seismic horizon automatic tracking method and device. The method comprises the following steps: acquiring N seed points of a two-dimensional seismic horizon of a research work area; calculating the score of each seed point based on a preset scoring criterion; selecting B seed points from the N seed points to construct a global two-dimensional horizon initial value according to the position relationship between the scores and the seed points; and performing two-dimensional horizon automatic tracking based on the two-dimensional horizon initial value and the A seed points.

Description

Technical Field

[0001] The present invention relates to the field of seismic exploration technology, and in particular to a two-dimensional seismic layer automatic tracking method and device. Background Art

[0002] Automatic seismic layer tracking is of great significance for improving the efficiency of seismic data interpretation. Compared with the algorithm that tracks layers according to a specific path, the automatic seismic layer tracking algorithm based on the global optimization algorithm usually has better stability and higher tracking efficiency in structurally complex areas. Therefore, the global seismic layer tracking algorithm has become one of the important application technologies of current seismic interpretation.

[0003] However, compared with the traditional layer tracking algorithm along a specific path, the global seismic layer tracking algorithm is more sensitive to the number of manually picked seismic layer seed points: when the number of seed points is too large, the calculation time required to construct the initial value of the layer increases significantly, which greatly affects the efficiency of global seismic layer automatic tracking; but when the number of seed points is insufficient, the increase in the number of optimization iterations in the global seismic layer automatic tracking process reduces the efficiency of the algorithm, and the accuracy of the results will also be reduced due to the insufficient number of seed points. In addition, according to actual application tests, since the consistency of the seismic phases corresponding to the manually picked seed points is not strictly uniform, the participation of some seed points not only reduces the efficiency of global seismic layer automatic tracking, but also has a certain negative impact on the accuracy of the final result.

[0004] Therefore, realizing a new two-dimensional seismic layer automatic tracking method is an urgent problem to be solved. Summary of the invention

[0005] The inventors found that:

[0006] (1) The global 2D seismic layer tracing method needs to construct the 2D layer initial value using manually picked seed points. If the number of seed points is too small in this step, the accuracy of the calculated layer initial value will be low, which will affect the convergence speed and convergence accuracy of the subsequent 2D layer tracing algorithm. However, if the number of seed points is too large, the calculation time of the layer initial value will be greatly increased, which will reduce the overall efficiency of the global 2D seismic layer automatic tracing.

[0007] (2) Among the manually picked seed points, some are critical to the construction of the initial values ​​of the 2D horizon, but the contribution of a small number of seed points can be basically ignored. Therefore, quantitative evaluation of seed points can be carried out to construct the initial values ​​of the horizon for some key seed points, thereby improving the efficiency of global 2D seismic horizon tracking.

[0008] (3) Some of the manually picked seed points may have a certain phase deviation from the target layer. Such seed points will affect the accuracy of the overall results in the global two-dimensional seismic layer automatic tracking. Therefore, seed point scoring is performed to select some seed points with high comprehensive rankings for layer tracking and discard some seed points with low rankings, thereby improving the accuracy of global two-dimensional seismic layer automatic tracking and seismic interpretation.

[0009] Based on the above findings, the present application provides a two-dimensional seismic layer automatic tracking method and device. This method can improve the efficiency of global two-dimensional layer tracking by selecting seed points with high comprehensive ranking to construct initial values ​​of two-dimensional seismic layers; and eliminate some seed points with low ranking through comprehensive ranking results, thereby improving the accuracy of global two-dimensional layer automatic tracking results.

[0010] In a first aspect, the present application provides a two-dimensional seismic layer automatic tracking method, characterized in that the method comprises:

[0011] Obtain N seed points of the 2D seismic horizon in the study area;

[0012] Calculate the score of each seed point based on the preset scoring criteria;

[0013] According to the positional relationship between the score and the seed point, B seed points are selected from the N seed points to construct a global two-dimensional layer initial value;

[0014] Automatic two-dimensional layer tracking is performed based on the two-dimensional layer initial value and A seed points.

[0015] In a second aspect, an embodiment of the present invention further provides a two-dimensional seismic layer automatic tracking device, the device comprising: a memory and a processor; the memory is used to store a program for automatic tracking of two-dimensional seismic layers, and the processor is used to read and execute the program for automatic tracking of two-dimensional seismic layers, and execute any one of the methods described in the above embodiments.

[0016] In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a data processing program is stored, and the data processing program is executed by a processor according to any one of the two-dimensional seismic layer automatic tracking methods described in the above embodiments.

[0017] Compared with the related art, the present application provides a two-dimensional seismic layer automatic tracking method and device, the method comprising: obtaining N seed points of the two-dimensional seismic layer of the research area; calculating the score of each seed point based on a preset scoring criterion; selecting B seed points from the N seed points to construct the global two-dimensional layer initial value according to the positional relationship between the score and the seed point; and performing two-dimensional layer automatic tracking based on the two-dimensional layer initial value and A seed points. The present application can improve the efficiency of global two-dimensional layer tracking by selecting seed points with high comprehensive ranking to construct the two-dimensional seismic layer initial value; and can improve the accuracy of the global two-dimensional layer automatic tracking result by eliminating some seed points with low ranking through the comprehensive ranking result, which has important guiding significance for high-precision layer automatic tracking and seismic interpretation.

[0018] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by implementing the present application. Other advantages of the present application can be realized and obtained by the schemes described in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings are used to provide an understanding of the technical solution of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application and do not constitute a limitation on the technical solution of the present application.

[0020] Figure 1 This is a flow chart of the two-dimensional seismic layer automatic tracking method according to an embodiment of the present application;

[0021] Figure 2 A schematic diagram of a two-dimensional seismic layer automatic tracking device according to an embodiment of the present application;

[0022] Figure 3 A schematic cross-sectional diagram of the results of global two-dimensional seismic layer automatic tracking interpretation based on different seed points in some exemplary embodiments;

[0023] Figure 4 A schematic diagram of amplitude variance comparison of automatic tracing layer results in some exemplary embodiments;

[0024] Figure 5 A schematic diagram of 10 seed points of a two-dimensional seismic horizon based on manual picking in some exemplary embodiments;

[0025] Figure 6 A schematic diagram of the ratio of the vertical and horizontal distances between each seed point and other seed points in some exemplary embodiments;

[0026] Figure 7 is a schematic diagram of a first sequence of seed points in some exemplary embodiments;

[0027] Figure 8 is a schematic diagram of a second sequence of seed points in some exemplary embodiments;

[0028] Fig. 9 A cross-sectional diagram of global two-dimensional seismic horizon automatic tracking interpretation result constrained by selecting first three, first four and first five seed points according to the second sequence in some exemplary embodiments;

[0029] Fig.10 A comparative analysis diagram of amplitude variance results corresponding to the automatic tracking interpretation results using the first 3, first 4, and first 5 seed points in some exemplary embodiments. DETAILED DESCRIPTION

[0030] The present application describes multiple embodiments, but the description is exemplary rather than restrictive, and it is obvious to those skilled in the art that there may be more embodiments and implementations within the scope of the embodiments described in the present application. Although many possible feature combinations are shown in the drawings and discussed in the specific embodiments, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with any other feature or element in any other embodiment, or may replace any other feature or element in any other embodiment.

[0031] The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements disclosed in the present application may also be combined with any conventional features or elements to form a unique invention scheme defined by the claims. Any features or elements of any embodiment may also be combined with features or elements from other invention schemes to form another unique invention scheme defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in the present application may be implemented individually or in any appropriate combination. Therefore, except for the limitations made according to the attached claims and their equivalents, the embodiments are not subject to other restrictions. In addition, various modifications and changes may be made within the scope of protection of the attached claims.

[0032] In addition, when describing representative embodiments, the specification may have presented the method and / or process as a specific sequence of steps. However, to the extent that the method or process does not rely on the specific order of the steps described herein, the method or process should not be limited to the steps of the specific order described. As will be understood by those of ordinary skill in the art, other sequences of steps are also possible. Therefore, the specific sequence of the steps set forth in the specification should not be interpreted as a limitation to the claims. In addition, the claims for the method and / or process should not be limited to the steps of performing them in the order written, and those skilled in the art can easily understand that these sequences can be changed and still remain within the spirit and scope of the embodiments of the present application.

[0033] The embodiment of the present invention provides a two-dimensional seismic layer automatic tracking method, such as Figure 1 As shown, the method includes steps S100-S130:

[0034] S100: Obtain N seed points of the 2D seismic horizon of the study area;

[0035] S110: Calculate the score of each seed point based on a preset scoring criterion;

[0036] S120: selecting B seed points from the N seed points according to the positional relationship between the score and the seed point to construct a global two-dimensional layer initial value;

[0037] S130: Automatically track the two-dimensional layer based on the two-dimensional layer initial value and A seed points.

[0038] In an exemplary embodiment, obtaining N seed points of a two-dimensional seismic horizon in a research area includes:

[0039] Step 1, obtain a two-dimensional seismic profile of the study area;

[0040] In this step, the two-dimensional seismic profile of the study area is post-stack seismic data, which is the data obtained after a series of seismic data processing operations are performed on the original seismic data collected; the seismic data processing operations include but are not limited to: static correction, denoising, amplitude compensation, velocity analysis, dynamic correction, offset, etc. The final processed post-stack seismic data is equivalent to the collected data under self-excitation and self-collection conditions, which can be recorded as s(t,x), where t represents the two-way travel time of the seismic wave and x is the seismic channel number.

[0041] Step 2, combining geophysical data, cores, logging and geological information of the work area, determining the two-dimensional seismic horizon to be automatically tracked;

[0042] Step 3, pick N seed points of the 2D seismic horizon. Figure 5The two-dimensional seismic horizon shown is based on N=10 seed points picked manually, which are numbered 1-10 from left to right.

[0043] In this step, the seed points of the two-dimensional seismic horizon are manually picked up and recorded as seed(t1,x1), seed(t2,x2), ..., seed(t N ,x N ), where (t1,x1), (t2,x2), ..., (t N ,x N ) represent the two-way travel time and lateral coordinate position of these N seed points on the two-dimensional seismic profile.

[0044] In an exemplary embodiment, the score of each seed point is calculated based on a preset scoring criterion, including:

[0045] Step 1, corresponding to any seed point seed(t i ,x i )(i=1,2,...,N), first calculate its relationship with any other seed point seed(t j ,x j )(j≠i,j=1,2,...,N) longitudinal and lateral distances;

[0046] The horizontal distance is:

[0047]

[0048] in, is the horizontal distance between the i-th seed point and the j-th seed point, L grid is the distance between seismic traces, abs(.) means to find the absolute value, x i Indicates the trace number corresponding to the i-th seed point on the two-dimensional seismic profile, x j Indicates the trace number corresponding to the jth seed point on the two-dimensional seismic profile.

[0049] The vertical distance is:

[0050]

[0051] in, is the longitudinal distance between the ith seed point and the jth seed point, sp is the seismic sampling time interval, vp represents the longitudinal wave velocity of the formation, t i represents the two-way travel time corresponding to the i-th seed point on the two-dimensional seismic profile, t j It represents the two-way travel time corresponding to the j-th seed point on the two-dimensional seismic profile. From the above formula, it can be seen that the vertical distance between seed points is half of the product of the two-way travel time difference and the formation P-wave velocity.

[0052] Step 2, establishing a seed point symmetric matrix according to the aspect ratio of each seed point;

[0053] The aspect ratio is:

[0054]

[0055] Among them, Ratio (i,j) is the ratio of the vertical and horizontal distances between the i-th seed point and the j-th seed point. Figure 6 As shown, a schematic diagram of the calculated vertical and horizontal distance ratios of each seed point to other seed points.

[0056] Set Ratio (i,j) = 0 when i = j; it can be seen that for all manually picked seed points, Ratio is a symmetric matrix with zero diagonal elements, as shown below:

[0057]

[0058] Among them, r (i,j) is the element corresponding to Ratio at position (i, j), r (i,j) =r (j,i) .

[0059] Step 3, calculating the sum of the i-th row or i-th column of the symmetric matrix of each seed point, and using the sum as the score of each seed point.

[0060] For any manually picked seed point seed(t i ,x i )(i=1,2,...,N), find all the aspect ratios r related to it (i,j) The sum sum(t i ,x i )(i=1,2,...,N):

[0061]

[0062] From the above formula, we can see that sum(t i ,x i ) is the sum of the ith row or ith column of the symmetric matrix Ratio. When the seed point is located at a complex structural location such as a fault, it usually has a larger aspect ratio with other seed points; on the contrary, in a simple structural area, the seed point is usually located on a continuous horizontal seismic axis, and its corresponding aspect ratio is very close to zero. Therefore, the manually picked seed points can be simply ranked by quantitative scoring based on the aspect ratio. The larger sum(t,x) is, the higher the score is.

[0063] In an exemplary embodiment, according to the positional relationship between the score and the seed point, B seed points are selected from the N seed points to construct the global two-dimensional layer initial value, including:

[0064] Step 1, constructing a first sequence of seed points by sorting them according to the score of each seed point, and determining M key seed points from the first sequence;

[0065] like Figure 7 As shown, based on Figure 6 The sum of the vertical and horizontal distance ratios of each seed point is a schematic diagram of the score of each seed point. The first sequence of seed points is constructed by sorting according to the score, and M = 2 key seed points are selected from the first sequence, such as Figure 7 As shown, the key seed points are 4 and 5.

[0066] Step 2, constructing a second sequence of seed points by sorting the NM seed points according to the positional relationship between the NM seed points and the M key seed points, and selecting B seed points from the second sequence, specifically includes:

[0067] Step 21, classify the NM seed points into categories of key seed points that are consistent with the positional relationship;

[0068] Step 22, sorting the multiple seed points in each class according to the scores;

[0069] Step 23, based on the score ranking results of each category, a comprehensive ranking is performed according to the category to construct a second sequence of seed points; Figure 8 As shown, Figure 8 is based on Figure 6 The results and the comprehensive ranking results obtained by taking the 4th and 5th seed points with the highest scores as the key seed points are taken into account. Figure 6 The scoring results in the 2D seismic layer automatic tracking are compared with the relative positions of various sub-points and key seed points, which avoids the problem of uneven distribution of seed point scores on both sides of the key seed point affecting the accuracy and stability of the global 2D seismic layer automatic tracking results.

[0070] Step 24: Select B seed points from the second sequence.

[0071] like Figure 8 As shown, according to Figure 8 For the second sequence in , B = 4 seed points (4, 5, 1, 6) or B = 5 seed points (4, 5, 1, 6, 2) can be selected according to the specific work area conditions.

[0072] Step 3: construct a global two-dimensional layer initial value based on the B seed points.

[0073] This step can use an interpolation algorithm to construct the initial value of the global two-dimensional layer. The interpolation algorithm can use spline interpolation. This type of algorithm can obtain an interpolation effect that is relatively close to the actual layer under the condition of sufficient seed points, thereby reducing the number of subsequent iterations to improve the accuracy and efficiency of global two-dimensional seismic layer automatic tracking. However, when there are many seed point data, the efficiency of spline interpolation is greatly reduced, which greatly affects the efficiency of layer tracking. For this reason, the seed point sorting optimization is carried out and the initial value of the layer is constructed on this basis, so that the global two-dimensional seismic layer automatic tracking can maximize the operating efficiency while ensuring accuracy.

[0074] In an exemplary embodiment, two-dimensional layer automatic tracking is performed based on the two-dimensional layer initial value and A seed points; in this embodiment, on the basis of the completion of the construction of the two-dimensional layer initial value, most of the seed points with high comprehensive ranking are selected to carry out global two-dimensional seismic layer automatic tracking. In this process, some seed points near the end of the ranking can be eliminated: first, most of the seed points with low ranking are located in the work area with relatively simple structure. Eliminating some seed points at this position has basically no effect on the final global two-dimensional seismic layer automatic tracking result, and can also improve the operation efficiency of the global two-dimensional seismic layer automatic tracking algorithm. Secondly, since the phase consistency of the manually picked seed points does not strictly meet the consistency requirements, the tracking results of the automatic layer tracking algorithm in the simple structure area usually have good phase consistency; for this reason, eliminating some seed points with low comprehensive ranking can reduce the adverse effects of seed point phase inconsistency on the final result in most cases, thereby improving the accuracy of the result of global two-dimensional seismic layer automatic tracking. Specific examples, such as Fig. 9 As shown, Fig. 9 Figure (a) is a cross-sectional diagram of the global 2D seismic layer automatic tracking interpretation result constrained by the first three seed points selected in the second sequence. Fig. 9 Figure (b) is a cross-sectional diagram of the global 2D seismic layer automatic tracking interpretation result constrained by the first 4 seed points selected in the second sequence. Fig. 9 Figure (c) in the figure is a cross-section of the global 2D seismic layer automatic tracking interpretation result constrained by the first 5 seed points selected in the second sequence. For the interpretation result diagram obtained by the above automatic tracking, the corresponding amplitude variance is calculated and compared, and we can get Fig.10 The comparison diagram shown is from Fig.10 The comparative analysis shows that the amplitude variance corresponding to the global 2D seismic layer automatic tracking result based on a small number of seed points with the highest comprehensive ranking is much smaller than Figure 3Corresponding amplitude variance; secondly, after comprehensive sorting, with the increase of high-scoring seed points, the amplitude variance of the layer tracking result gradually decreases, indicating that the accuracy of the result is gradually improved. Therefore, selecting some seed points with high comprehensive ranking to carry out global two-dimensional seismic layer automatic tracking can meet the stability of layer tracking and reduce the influence of some seed points with poor phase consistency in the lower ranking on the accuracy of the final result. At the same time, it also greatly improves the computational efficiency of global two-dimensional seismic layer automatic tracking, which has important guiding significance for high-precision seismic interpretation.

[0075] The present invention adopts the above technical solution, which has the following advantages:

[0076] 1. This technical solution uses a specific scoring criterion to carry out quantitative evaluation on multiple seed points of global two-dimensional seismic horizon automatic tracking, selects multiple key seed points with the highest ranking to construct the initial value of the two-dimensional horizon, and greatly improves the efficiency of global two-dimensional seismic horizon automatic tracking;

[0077] 2. This technical solution takes into account the mutual position relationship of each seed point, and conducts comprehensive sorting based on the scoring results and the above position relationship, so as to further improve the accuracy and efficiency of global two-dimensional seismic layer automatic tracking;

[0078] 3. The algorithm of this technical solution is simple and easy to implement, with high operating efficiency, and it is easy to form software function modules for promotion and application.

[0079] An embodiment of the present invention also provides a two-dimensional seismic layer automatic tracking device, which includes: a memory 210 and a processor 220; the memory is used to store a program for automatic tracking of two-dimensional seismic layers, and the processor is used to read and execute the program for automatic tracking of two-dimensional seismic layers, and execute any one of the methods described in the above embodiments.

[0080] An embodiment of the present invention further provides a computer-readable storage medium, on which a data processing program is stored. The data processing program is executed by a processor to perform the two-dimensional seismic layer automatic tracking method described in any one of the above embodiments.

[0081] Example 1

[0082] This example shows the automatic tracking method of 2D seismic horizons based on the selected seed points. The specific process is as follows:

[0083] Step a. Collecting post-stack seismic data;

[0084] Step b. Manually picking 2D seismic horizon seed points based on the geophysical data and geological knowledge of the work area;

[0085] Step c. Calculate the score of each seed point based on the preset scoring criteria, and sort the seed points from large to small according to the score results to obtain a first sequence of seed points;

[0086] Step d. Determine M key seed points from the first sequence, and sort the remaining seed points again according to their relative position relationship with the key seed points and the score results to construct a second sequence of seed points; in this step, after determining M key seed points based on the first sequence, it is necessary to further sort the remaining seed points again according to their relative position relationship with the key seed points and the score results to construct a second sequence of seed points. An important reason for carrying out this step is that the top-ranked seed points evaluated by the above-mentioned scoring results may be unevenly distributed on both sides of the key seed points, thereby affecting the accuracy and stability of the global two-dimensional seismic layer automatic tracking results. Figure 3 As shown, Figure 3 Figure (a) is the final interpretation result profile of the global 2D seismic layer automatic tracking based on four seed points. Figure 3 Figure (b) is the final interpretation result profile of the global 2D seismic layer automatic tracking based on the two middle seed points. Figure 3 Figure (c) is a profile of the final interpretation result of automatic tracking of global two-dimensional seismic layers based on two seed points on the edge. Figure 4 for Figure 3 A schematic diagram of the amplitude variance comparison of the three automatic tracking layer results. Figure 4 The comparative analysis shows that: 1) The smaller the amplitude variance, the better the seismic phase consistency of the global two-dimensional seismic layer automatic tracking, and the higher the two-dimensional seismic layer tracking accuracy. 2) For the global two-dimensional seismic layer automatic tracking, the more seed points picked manually, the better. Some key seed points have a much greater guiding role in the automatic layer tracking than most other seed points. Figure 3 (a) Figure 4 The amplitude variance corresponding to the global 2D seismic layer automatic tracking result constrained by seed points is greater than Figure 3 The amplitude variance of the result constrained by the two seed points in the middle of Figure (b) is the error caused by the phase inconsistency problem of manually picking seed points. Figure 3 The amplitude variance of the result constrained by the two seed points in the middle of Figure (b) is Figure 3 The comparison of the amplitude variance of the results constrained by the two seed points in the middle of Figure (c) shows that the seed points at different positions picked manually have different effects on the global 2D seismic layer automatic tracking results. The contribution and influence of the two seed points in the middle on the accuracy and stability of the 2D seismic layer automatically picked by the global 2D seismic layer are much greater than those of the two seed points on the edge. The above comparative analysis shows that the position relationship of the seed points affects the accuracy and stability of the global 2D seismic layer automatic tracking results.

[0087] Step e. Selecting B seed points from the second sequence to construct a global two-dimensional layer initial value;

[0088] Step f. Based on the above constructed two-dimensional layer initial value and most of the top seed points, global two-dimensional layer automatic tracking is carried out. In this step, most of the top seed points can be selected according to the specific situation, such as selecting the top 70%-80% of the seed points, that is, 20-30% of the seed points at the back need to be excluded for global two-dimensional layer automatic tracking.

[0089] The method implemented in this example has the following technical effects:

[0090] By selecting seed points with high comprehensive ranking to construct the initial values ​​of 2D seismic horizons, the efficiency of global 2D horizon tracking can be improved; and by eliminating some seed points with low ranking through comprehensive ranking results, the accuracy of global 2D horizon automatic tracking results can be improved, which has important guiding significance for high-precision horizon automatic tracking and seismic interpretation.

[0091] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

Claims

1. A two-dimensional seismic layer automatic tracking method, characterized in that: The method comprises: Obtain N seed points of the 2D seismic horizon in the study area; Calculate the score of each seed point based on the preset scoring criteria; According to the positional relationship between the score and the seed point, B seed points are selected from the N seed points to construct a global two-dimensional layer initial value; Automatically tracking the two-dimensional layer based on the two-dimensional layer initial value and A seed points; Among them, N is greater than A, A is greater than B, and N, A, and B are all positive integers.

2. The two-dimensional seismic layer automatic tracking method according to claim 1, characterized in that: The step of obtaining N seed points of the two-dimensional seismic horizon of the research area includes: Obtain a 2D seismic profile of the study area; Combine the geophysical data, core information, logging information and geological information of the work area to determine the 2D seismic horizon to be automatically tracked; Pick N seed points of the 2D seismic horizon.

3. The two-dimensional seismic layer automatic tracking method according to claim 1, characterized in that: The score of each seed point is calculated based on the preset scoring criteria, including: Calculate the horizontal and vertical distances between each seed point and other seed points; Establish a seed point symmetric matrix according to the aspect ratio of each seed point; The sum of the i-th row or i-th column of the symmetric matrix of each seed point is calculated, and the sum is used as the score of each seed point.

4. The two-dimensional seismic layer automatic tracking method according to claim 1, characterized in that: The step of selecting B seed points from the N seed points to construct a global two-dimensional layer initial value according to the positional relationship between the score and the seed point includes: Sorting the scores of each seed point to construct a first sequence of seed points, and determining M key seed points from the first sequence; Sorting the NM seed points according to the positional relationship between the NM seed points and the M key seed points to construct a second sequence of seed points, and selecting B seed points from the second sequence; A global two-dimensional layer initial value is constructed according to the B seed points.

5. The two-dimensional seismic layer automatic tracking method according to claim 3 is characterized in that: The lateral distance is: in, is the horizontal distance between the i-th seed point and the j-th seed point, x i Indicates the trace number corresponding to the i-th seed point on the two-dimensional seismic profile, x j Indicates the trace number corresponding to the jth seed point on the 2D seismic profile, L grid is the distance between seismic traces, and abs(.) means finding the absolute value.

6. The two-dimensional seismic layer automatic tracking method according to claim 5, characterized in that: The longitudinal distance is: in, is the longitudinal distance between the ith seed point and the jth seed point, sp is the seismic sampling time interval, vp represents the longitudinal wave velocity of the formation, t i represents the two-way travel time corresponding to the i-th seed point on the two-dimensional seismic profile, t j Represents the two-way travel time corresponding to the j-th seed point on the two-dimensional seismic profile.

7. The two-dimensional seismic layer automatic tracking method according to claim 6, characterized in that: The aspect ratio is: Among them, Ratio (i,j) is the ratio of the vertical and horizontal distances between the i-th seed point and the j-th seed point.

8. The two-dimensional seismic layer automatic tracking method according to claim 3 is characterized in that: The seed point symmetric matrix is: Among them, r (i,j) is the element corresponding to Ratio at position (i, j), r (i,j) =r (j,i) .

9. The two-dimensional seismic layer automatic tracking method according to claim 3, characterized in that: The score of the seed point is: Among them, sum(t i ,x i ) is the sum of the ith row or ith column of the symmetric matrix, r (i,j) is the element corresponding to Ratio at position (i,j), i=1,2,...,N.

10. The two-dimensional seismic layer automatic tracking method according to claim 4, characterized in that: The step of constructing a second sequence of seed points by sorting the NM seed points according to the positional relationship between the NM seed points and the M key seed points, and selecting B seed points from the second sequence includes: Divide the NM seed points into categories of key seed points that are consistent with their positional relationships; sorting the plurality of seed points in each class according to the scores; According to the ranking results of the scores of each category, a comprehensive ranking is performed according to the categories to construct a second sequence of seed points; B seed points are selected from the second sequence.

11. A two-dimensional seismic layer automatic tracking device, characterized in that: The device includes: a memory and a processor; the memory is used to store a program for automatic tracking of two-dimensional seismic layers, and the processor is used to read and execute the program for automatic tracking of two-dimensional seismic layers, and execute the method described in any one of claims 1-10.

12. A computer-readable storage medium having a data processing program stored thereon, wherein the data processing program is executed by a processor to implement the two-dimensional seismic layer automatic tracking method according to any one of claims 1 to 10.

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