Automatic horizon tracking method and device driven by seismic waveform feature points and medium

Abstract

The invention belongs to the technical field of seismic data geological interpretation, and particularly discloses an automatic horizon tracking method and device driven by seismic waveform feature points and a medium. And recursive search is carried out in the X direction and the Y direction according to local waveform similarity, and the layer crossing phenomenon is reduced through horizon closure discrimination, so that the problems of large calculation amount, large sample learning and training workload, insufficient tracking result precision and stability and the like of the existing horizon automatic tracking method are solved. The apparatus and medium of the present invention can store and execute a computer program based on the method. The method is suitable for the horizon interpretation technology.

Description

Technical Field

[0001] The invention belongs to the technical field of geological interpretation of seismic data, and relates to automatic layer tracking, in particular to a method, device and medium for automatic layer tracking driven by seismic waveform characteristic points. Background Art

[0002] In the geological interpretation of seismic data, accurate stratigraphic information obtained from stratigraphic interpretation is not only an important basis for reservoir prediction, but is also widely used in seismic processing methods such as velocity analysis and tomography. As a key link in stratigraphic interpretation, stratigraphic tracing has a direct impact on the rationality of the final geological interpretation. However, the current manual stratigraphic tracing technology is time-consuming, wastes manpower costs, and the results are easily affected by subjective factors.

[0003] Therefore, developing an efficient and stable automatic layer tracking technology is crucial to improving the effectiveness of seismic data processing and interpretation.

[0004] There are three main types of existing automatic layer tracking methods: the first type is the automatic layer tracking method based on waveform similarity, which is mainly based on the waveform cross-correlation algorithm and uses the correlation between traces to track the phase axis. The results obtained by this method have good noise resistance and stability, but the calculation amount is large, and when there are similar waveforms in adjacent layers, it is easy to have a layer-by-layer phenomenon, which reduces the reliability of the results; the second type is the automatic layer tracking method based on artificial neural network, which has a good layer tracking effect, but requires a large number of sample learning and training. Not only is the workload large, but also due to the different characteristics of seismic data in different work areas, the learning and training results cannot be shared between work areas; the third type is the automatic layer tracking method based on image, which applies structural tensors to fault and layer identification, uses a series of directional filters to extract characteristic directions, and then obtains the main direction of layer development. Although this type of method has high calculation efficiency, when the layer morphology is more complex, it will affect the accuracy and stability of the tracking results. Summary of the invention

[0005] One purpose of the present invention is to provide a layer automatic tracking method driven by seismic waveform feature points, which uses the coordinates of the waveform feature points at the seed point to determine the search range of adjacent recording tracks in the Z direction, and performs recursive search in the X direction and Y direction based on local waveform similarity, and also reduces the layer stringing phenomenon by layer closure discrimination, thereby solving the problems of large calculation amount, large sample learning and training workload, insufficient tracking result accuracy and stability, etc. in the existing layer automatic tracking method;

[0006] Another object of the present invention is to provide equipment and medium for the automatic layer tracking method driven by the above-mentioned seismic waveform characteristic points.

[0007] To achieve the above object, the present invention provides a method for automatic layer tracking driven by seismic waveform characteristic points, the method comprising the following steps performed in sequence:

[0008] S1. Correct the manually interpreted seed point to the characteristic point of the waveform of the recording track in the Z direction to obtain the corrected seed point;

[0009] S2. Sort the correction seed points with the same X coordinate from small to large according to the Y coordinate to obtain sequence A;

[0010] For the correction seed points at both ends of sequence A, the layers are tracked to the corresponding boundaries according to the similarity of the local waveforms of the adjacent traces; for the waveforms within the range formed by the remaining two adjacent correction seed points in sequence A, the layers are tracked and the closure is judged according to the similarity of the local waveforms of the adjacent traces, and the intermediate results of the layer tracking of sequence A are obtained;

[0011] S3. Sort the correction seed points with the same Y coordinate from small to large according to the X coordinate to obtain sequence B;

[0012] For the correction seed points at both ends of sequence B, the layers are tracked to the corresponding boundaries according to the similarity of the local waveforms of the adjacent traces; for the waveforms within the range of the remaining two adjacent correction seed points in sequence B, the layers are tracked and the closure is judged according to the similarity of the local waveforms of the adjacent traces, and the intermediate results of the layer tracking of sequence B are obtained;

[0013] S4. Perform closure judgment on the intermediate results of layer tracking of sequence A and the intermediate results of layer tracking of sequence B to obtain the automatic tracking result of the current layer;

[0014] S5. Using the current layer automatic tracking result as the correction seed point, repeat steps S2-S4 to obtain the layer automatic tracking result.

[0015] As a limitation of the present invention, in step S1, the correction seed point is obtained by performing the following steps in sequence:

[0016] S11. Determine the Z-direction distribution range of the current layer according to the depth distribution range of the manually interpreted seed point coordinates in the Z-direction;

[0017] S12. Identify waveform feature points of the seismic record waveform within the Z-direction distribution range of the current layer;

[0018] S13. The waveform feature points of each recording track are identified to obtain waveform feature points of each recording track;

[0019] S14. Correcting the manually interpreted seed point to the corresponding waveform feature point of the recording track according to the shortest distance criterion to obtain a corrected seed point;

[0020] As a second limitation of the present invention, in step S11, the distribution range of the current layer in the Z direction is determined by extending the depth distribution range of the manually interpreted seed point in the Z direction upward and downward by a fixed number of samples.

[0021] As a further limitation of the present invention, the waveform characteristic points are waveform positive extreme value points and waveform negative extreme value points.

[0022] As a third limitation of the present invention, the local waveform similarity of adjacent tracks is:

[0023] Taking the waveform feature point corresponding to the current correction seed point as the center, determine the current waveform within the local window length;

[0024] Determine the waveform feature points of the same type as the current calibration seed point within the same local window length range in the adjacent traces of the current calibration seed point, and determine the waveform of the adjacent traces within the same local window length range with the waveform feature points of the same type as the center;

[0025] The cross-correlation coefficient between the current waveform and the adjacent waveform is calculated. If the cross-correlation coefficient is greater than a set threshold, the layer tracking is continued; otherwise, the layer tracking is interrupted.

[0026] As a fourth limitation of the present invention, the layer closure determination refers to selecting the tracking result with a larger waveform correlation coefficient when the layer tracking results between two adjacent correction seed points are inconsistent.

[0027] The present invention also provides an electronic device for automatic layer tracking driven by seismic waveform feature points, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned automatic layer tracking method driven by seismic waveform feature points when executing the computer program.

[0028] The present invention also provides a computer-readable storage medium, which stores a computer program for executing the above-mentioned automatic layer tracking method driven by seismic waveform feature points.

[0029] Due to the adoption of the above scheme, the present invention has the following beneficial effects compared with the prior art:

[0030] The present invention uses the position of the waveform feature point at the artificial interpretation seed point to determine the Z-direction search range of the adjacent traces, and recursively searches in the X and Y directions based on the local waveform similarity, thereby overcoming the defects of the conventional automatic layer tracking method based on waveform similarity, such as large amount of calculation, many layer stringing phenomena, and difficult closure, and realizes efficient layer automatic interpretation driven by three-dimensional data with artificial interpretation as the sample.

[0031] The present invention is applicable to the layer interpretation technology, and reduces the layer cross-talk phenomenon by judging the layer closure, thereby solving the problems of large calculation amount, large sample learning and training workload, insufficient tracking result accuracy and stability, etc. in the existing layer automatic tracking method. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] Figure 1 This is a waveform feature point recognition result diagram in Example 1 of the present invention;

[0034] Figure 2 The result diagram of the correction to the corresponding recording track waveform feature points in Example 1 of the present invention;

[0035] Figure 3 The result diagram of the cross section corresponding to the manually interpreted seed point after correction in Example 1 of the present invention;

[0036] Figure 4 A three-dimensional spatial display diagram of a cross section corresponding to a manually interpreted seed point after correction in Example 1 of the present invention;

[0037] Figure 5 This is the intermediate result diagram of the sequence A layer tracing in Example 1 of the present invention;

[0038] Figure 6 A three-dimensional spatial display diagram of the intermediate result of the sequence A layer tracing in Example 1 of the present invention;

[0039] Figure 7 This is an intermediate result diagram of the sequence B layer tracing in Example 1 of the present invention;

[0040] Figure 8 A three-dimensional spatial display diagram of the intermediate result of the sequence B layer tracing in Example 1 of the present invention;

[0041] Fig. 9 A three-dimensional spatial display diagram of the automatic tracking result of the current layer in Example 1 of the present invention;

[0042] Fig.10 A three-dimensional spatial display diagram of the layer automatic tracking result in Example 1 of the present invention;

[0043] Fig.11 This is a comparison chart of the site fusion display results of Example 1 of the present invention and Comparative Example 1. Fig.11 (a) is a diagram showing the layer site fusion result obtained by the method of comparative example 1 of the present invention, Fig.11 (b) is a diagram showing the layer site fusion results obtained by the method of Example 1 of the present invention. DETAILED DESCRIPTION

[0044] The present invention is further described below in conjunction with embodiments, but those skilled in the art should understand that the present invention is not limited to the following embodiments, and any improvements and equivalent changes made based on the specific embodiments of the present invention are within the scope of protection of the claims of the present invention.

[0045] Example 1: Automatic layer tracking method driven by earthquake waveform feature points

[0046] This embodiment is a method for automatic layer tracking driven by seismic waveform feature points, which includes the following steps performed in sequence:

[0047] S1. Correct the manually interpreted seed point to the characteristic point of the waveform of the recording track in the Z direction to obtain the corrected seed point. The specific method is:

[0048] S11. The depth distribution range in the Z direction of all manually interpreted seed points in the work area is expanded upward and downward by 200 fixed sampling numbers to determine the distribution range in the Z direction of the current layer.

[0049] S12. For the seismic record waveform in the Z-direction distribution range of the current layer, waveform feature point recognition is performed to identify two types of waveform feature points: waveform positive extreme value points (i.e., wave crests) and waveform negative extreme value points (i.e., wave troughs);

[0050] Figure 1 This is the waveform feature point identification result diagram. The curve in the figure is the earthquake record waveform, the dots are the positive extreme points of the waveform, and the asterisks are the positive extreme points of the waveform.

[0051] S13. Perform waveform feature point identification of step S12 on each recording channel within the Z-direction distribution range of the current layer in the entire work area to obtain waveform feature points of each recording channel.

[0052] S14. Correcting the manually interpreted seed point to the corresponding waveform feature point of the recording track according to the shortest distance criterion to obtain the corrected seed point;

[0053] Figure 2 This is the result of correction to the corresponding waveform feature point of the recording track. The white point in the figure is the original seed point position; the gray point in the figure is the seed point position after correction to the waveform feature point position;

[0054] After correction, the profile results corresponding to the correction seed points are as follows: Figure 3 As shown, its three-dimensional space is displayed as Figure 4 .

[0055] S2. Sort the correction seed points with the same X coordinate from small to large according to the Y coordinate to obtain sequence A;

[0056] (I) For the corrected seed points at both ends of sequence A, the layers are tracked to the corresponding boundaries according to the local waveform similarity of adjacent traces:

[0057] Among them, sequence A has 6 calibration seed points with the same X coordinates and increasing Y coordinates, and the calibration seed points at both ends are the first seed point and the sixth seed point.

[0058] Layer tracking is performed based on the similarity of local waveforms of adjacent traces, specifically:

[0059] (1) Determine the current waveform: When the current calibration seed point is the first seed point, set the local window length to 20. Then, with the waveform feature point corresponding to the current calibration seed point as the center, the local window length range is a Y coordinate range of 10-30, that is, the current waveform is a waveform within the range of 10-30 of the current channel.

[0060] (2) Determine the waveform of the adjacent trace: Determine the waveform feature point in the adjacent trace whose Y coordinate is within the range of 10-30 (i.e., the local window length range) and is a trough (of the same type) as the first seed point (i.e., the current calibration seed point). With the trough as the center, determine the waveform of the adjacent trace within the range of 10-30 Y coordinate.

[0061] (3) Calculate the cross-correlation coefficient between the current waveform and the adjacent waveform. If the two cross-correlation coefficients are greater than the set threshold, continue layer tracking; otherwise, interrupt layer tracking.

[0062] For the correction seed points at both ends, trace the layers to the corresponding boundaries using the above method.

[0063] (II) For the waveforms within the range formed by the remaining two adjacent correction seed points in sequence A, the layer tracking and closure judgment are performed according to the similarity of the local waveforms of the adjacent traces, and the intermediate result of the layer tracking of sequence A is obtained:

[0064] Among them, the range formed by the remaining two adjacent correction seed points includes: the range formed by the first seed point to the second seed point, the range formed by the second seed point to the third seed point, the range formed by the third seed point to the fourth seed point, the range formed by the fourth seed point to the fifth seed point, and the range formed by the fifth seed point to the sixth seed point.

[0065] The same method is used for layer tracking and correction seed points at both ends. When the layer tracking results between two adjacent artificial interpretation seed points are inconsistent, the tracking result with a larger waveform correlation coefficient is selected to obtain the intermediate layer tracking result of sequence A, such as Figure 5 As shown, the three-dimensional space display of the intermediate results of sequence A layer tracking is as follows Figure 6 ;

[0066] The present invention ensures a single layer tracking result through the layer tracking and closure determination.

[0067] S3. Sort the correction seed points with the same Y coordinate from small to large according to the X coordinate to obtain sequence B;

[0068] For the correction seed points at both ends of sequence B, the layer tracking is performed to the corresponding boundary according to the local waveform similarity method of adjacent traces in step S2; for the waveforms within the range of the remaining two adjacent correction seed points in sequence B, the layer tracking and closure judgment are performed according to the local waveform similarity of adjacent traces, and the intermediate layer tracking result of sequence B is obtained, such as Figure 7 As shown, the three-dimensional space display of the intermediate results of sequence B layer tracking is as follows Figure 8 .

[0069] S4. Perform closure judgment on the intermediate results of sequence A layer tracking and sequence B layer tracking, and obtain the current layer automatic tracking result, whose three-dimensional space display is as follows: Fig. 9 .

[0070] S5. Using the current layer automatic tracking result as the correction seed point, repeat steps S2-S4 to obtain the layer automatic tracking result, which is displayed in three-dimensional space as follows Fig.10 .

[0071] In steps S2 and S3, X and Y are processed in the horizontal direction; S1 is the vertical depth direction. The layer depth range is determined only in S1 according to the depth range of all seed points, without determining waveform feature points at all depths, thus significantly improving efficiency.

[0072] Comparative Example 1 A conventional layer automatic tracking method based on waveform envelope similarity

[0073] This comparative example is a conventional layer automatic tracking method based on waveform envelope similarity, which is a well-known technical means in the art. By this method, the layer automatic tracking is performed on the same work area as in Example 1 to obtain a conventional layer automatic tracking result based on waveform envelope similarity.

[0074] The seismic waveform image is fused with the layer position obtained by the conventional layer automatic tracking result based on the similarity of the waveform envelope. The result is as follows: Fig.11 (a) The seismic waveform diagram is fused with the layer position obtained from the layer position automatic tracking result in Example 1, and the result is as follows: Fig.11 (b) Comparing the rectangular framed area in the figure, it can be seen that the layer site fusion display result obtained by the conventional layer automatic tracking method based on waveform envelope similarity has obvious layer-to-layer phenomenon, while the layer sites obtained by the method of Example 1 of the present invention are well fused and are relatively in the same layer without layer-to-layer phenomenon.

[0075] The above results show that the automatic tracking method of the present invention overcomes the defects of the conventional layer automatic tracking method based on waveform envelope similarity, such as large amount of calculation, many layer stringing phenomena, and difficult closure, and the tracking results are more reasonable.

[0076] Embodiment 2 A computer device

[0077] This embodiment provides a computer device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, so as to implement the automatic layer tracking method driven by seismic waveform feature points of Embodiment 1.

[0078] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0079] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capability and / or instruction execution capability, and may control other components in the electronic device to perform desired functions. The processor is used to run the computer-readable instructions stored in the memory.

[0080] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0081] For detailed description of this embodiment, please refer to the corresponding description in the above-mentioned embodiment, which will not be repeated here.

[0082] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the automatic layer tracking method driven by seismic waveform feature points of Example 1 is implemented.

[0083] The computer-readable storage medium stores non-transitory computer-readable instructions. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of various embodiments are executed.

[0084] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0085] It should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of protection of the claims of the present invention.

Claims

1. A method for automatic layer tracking driven by seismic waveform feature points, characterized in that: The method comprises the following steps performed in sequence: S1. Correct the manually interpreted seed point to the characteristic point of the waveform of the recording track in the Z direction to obtain the corrected seed point; S2. Sort the calibration seed points with the same X coordinate from small to large according to the Y coordinate to obtain sequence A; For the correction seed points at both ends of sequence A, the layers are tracked to the corresponding boundaries according to the similarity of the local waveforms of the adjacent traces; for the waveforms within the range formed by the remaining two adjacent correction seed points in sequence A, the layers are tracked and the closure is judged according to the similarity of the local waveforms of the adjacent traces, and the intermediate results of the layer tracking of sequence A are obtained; S3. Sort the correction seed points with the same Y coordinate from small to large according to the X coordinate to obtain sequence B; For the correction seed points at both ends of sequence B, the layers are tracked to the corresponding boundaries according to the similarity of the local waveforms of the adjacent traces; for the waveforms within the range of the remaining two adjacent correction seed points in sequence B, the layers are tracked and the closure is judged according to the similarity of the local waveforms of the adjacent traces, and the intermediate results of the layer tracking of sequence B are obtained; S4. Perform closure judgment on the intermediate results of layer tracking of sequence A and the intermediate results of layer tracking of sequence B to obtain the automatic tracking result of the current layer; S5. Using the current layer automatic tracking result as the correction seed point, repeat steps S2-S4 to obtain the layer automatic tracking result.

2. The automatic layer tracking method driven by seismic waveform feature points according to claim 1 is characterized in that: In step S1, the correction seed point is obtained by performing the following steps in sequence: S11. Determine the Z-direction distribution range of the current layer according to the depth distribution range of the manually interpreted seed point coordinates in the Z-direction; S12. Identify waveform feature points of the seismic waveform recorded within the Z direction distribution range of the current layer; S13. The waveform feature points of each recording channel are identified to obtain waveform feature points of the recording channels respectively; S14. Correct the manually interpreted seed point to the corresponding waveform feature point of the recording track according to the shortest distance criterion to obtain the corrected seed point.

3. The automatic layer tracking method driven by earthquake waveform characteristic points according to claim 2 is characterized in that: In step S11, the Z-direction distribution range of the current layer is determined by extending the depth distribution range of the manually interpreted seed point in the Z direction upward and downward by a fixed number of samples.

4. The automatic layer tracking method driven by earthquake waveform characteristic points according to claim 3 is characterized in that: The waveform characteristic points are the waveform positive extreme value points and the waveform negative extreme value points.

5. The automatic layer tracking method driven by seismic waveform feature points according to claim 1, characterized in that: The local waveform similarity of adjacent tracks is: Taking the waveform feature point corresponding to the current correction seed point as the center, determine the current waveform within the local window length; Determine a waveform feature point of the same type as the current calibration seed point within a local window length range in an adjacent trace, and determine the waveform of the adjacent trace within the same local window length range with the waveform feature point of the same type as the center; The cross-correlation coefficient between the current waveform and the adjacent waveform is calculated. If the cross-correlation coefficient is greater than a set threshold, the layer tracking is continued; otherwise, the layer tracking is interrupted.

6. The automatic layer tracking method driven by earthquake waveform characteristic points according to any one of claims 1 to 5, characterized in that: The layer closure determination refers to selecting the tracking result with the larger waveform correlation coefficient when the layer tracking results between two adjacent correction seed points are inconsistent.

7. An electronic device for automatic layer tracking driven by earthquake waveform characteristic points, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the automatic layer tracking method driven by seismic waveform feature points described in any one of claims 1-6 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program for executing the automatic layer tracking method driven by seismic waveform feature points according to any one of claims 1 to 6.

Images