Depth variable density reflection point pickup method, electronic equipment, storage medium and device

Abstract

The invention provides a depth variable density reflection point pickup method, electronic equipment, a storage medium and a device, and the method comprises the steps: constructing depth density control pairs based on seismic data, and determining a number range; traversing all the depth density control pairs and sorting the depth density control pairs according to the depth from small to large to obtain sorted depth density control pairs; performing full-depth-range pickup density interpolation on the sorted depth density control pairs by adopting a segmented interpolation algorithm to obtain a pickup density sequence with the same sampling rate and sampling number as the seismic data; and performing reflection point pickup based on the pickup density sequence to obtain a depth variable density reflection point pickup result. The method can improve the pertinence and flexibility of pickup.

Description

Technical Field

[0001] This invention belongs to the field of geophysical exploration technology, and more specifically, relates to a method for picking up depth-variable density reflection points, an electronic device, a storage medium, and a device. Background Technology

[0002] Reflection point picking from subsurface strata is a crucial step in depth-domain tomographic velocity modeling. However, the number of reflection points directly impacts the computational efficiency and accuracy of tomographic inversion. Overly sparse reflection point picking misses detailed information, leading to insufficient accuracy in the final velocity modeling results and affecting the final imaging effect. Overly dense reflection point picking can accurately capture detailed information, but it increases the computational burden of tomographic inversion, resulting in an excessively large matrix, increased ill-conditionedness, and reduced solution accuracy, also leading to unreliable results. Therefore, a suitable density of reflection points is critical to the success of tomographic inversion. However, with the continuous deepening of exploration and the increasing depth of exploration targets, more and more subsurface strata need to be explored. Using high-density reflection point picking for every stratum is impractical, while reducing the reflection point picking density to maintain computational efficiency, thus reducing velocity inversion accuracy, is also undesirable. Therefore, it is essential to adopt different density reflection point picking for different strata. Summary of the Invention

[0003] The purpose of this invention is to provide a method, electronic device, storage medium, and apparatus for picking up reflection points of varying densities in different layers, thereby improving the targeting and flexibility of the picking process.

[0004] To achieve the above objectives, in a first aspect, the present invention provides a method for picking up depth-variable density reflection points, comprising:

[0005] Based on seismic data, depth-density control pairs were constructed, and the range of their quantities was determined.

[0006] Traverse all depth density control pairs and sort them in ascending order of depth to obtain the sorted depth density control pairs;

[0007] A piecewise interpolation algorithm is used to perform full-depth range picking density interpolation on the sorted depth density control pairs to obtain a picking density sequence with the same sampling rate and number of samples as the seismic data.

[0008] Reflection point picking is performed based on the picking density sequence to obtain depth-variable density reflection point picking results.

[0009] Optionally, the traversal of all depth density control pairs and their sorting by depth from smallest to largest takes n(n-1) / 2 times, where n is the number of control pairs.

[0010] Optionally, the step of employing a piecewise interpolation algorithm to perform full-depth range picking density interpolation on the sorted depth-density control pairs includes:

[0011] Based on the nearest neighbor search algorithm, find the depth value and density value of the nearest point in the depth array of the sorted depth density control pair for the full depth sampling point;

[0012] Calculate the weight coefficients of the depth points to be interpolated, and based on the weight coefficients, use a piecewise function to calculate the final picking density sequence corresponding to the full depth sampling points.

[0013] Optionally, the weight coefficients for the interpolation depth points are calculated using the following formula:

[0014]

[0015] Where g is the weighting coefficient. This is the density array for the sorted depth-density control pairs. Let D be the depth array in the sorted depth density control pairs, where i represents the i-th input control pair. ne I is the depth value of the nearest point. ne The density value is the value of the nearest point;

[0016] Optionally, the piecewise function is:

[0017]

[0018] Among them, I f (j) represents the final pick density sequence, D f (j) is an array of full-depth sampling points, where j represents the j-th full-depth sampling point.

[0019] In a second aspect, the present invention provides an electronic device, the electronic device comprising:

[0020] At least one processor; and,

[0021] A memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the depth-variable density reflection point picking method described in the first aspect.

[0023] Thirdly, the present invention provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the depth-variable density reflection point picking method described in the first aspect.

[0024] Fourthly, the present invention provides a depth-variable density reflection point pickup device, comprising:

[0025] The control pair building module is used to construct depth-density control pairs based on seismic data and determine the range of their quantity.

[0026] The control pair sorting module is used to traverse all depth-density control pairs and sort them in ascending order of depth to obtain the sorted depth-density control pairs.

[0027] The picking density sequence construction module is used to perform full-depth range picking density interpolation on the sorted depth density control pairs using a piecewise interpolation algorithm to obtain a picking density sequence with the same sampling rate and number of samples as the seismic data.

[0028] The reflection point picking module is used to pick reflection points based on the picking density sequence to obtain depth-variable density reflection point picking results.

[0029] Optionally, the traversal of all depth density control pairs and their sorting by depth from smallest to largest takes n(n-1) / 2 times, where n is the number of control pairs.

[0030] Optionally, the step of employing a piecewise interpolation algorithm to perform full-depth range picking density interpolation on the sorted depth-density control pairs includes:

[0031] Based on the nearest neighbor search algorithm, find the depth value and density value of the nearest point in the depth array of the sorted depth density control pair for the full depth sampling point;

[0032] Calculate the weight coefficients of the depth points to be interpolated, and based on the weight coefficients, use a piecewise function to calculate the final picking density sequence corresponding to the full depth sampling points.

[0033] The beneficial effects of this invention are as follows: For picking reflection points with varying depth density in seismic data tomography inversion, a method for picking reflection points with varying depth density is provided. First, depth density control pairs are provided to determine the control range. Then, the entire depth density control pair is traversed, and the pairs are reordered from smallest to largest to determine the sorted control pairs. Next, a piecewise interpolation algorithm is used to perform density interpolation across the entire depth range to obtain a picking density sequence that matches the seismic data sampling rate and number of samples. Finally, reflection points are picked according to this sequence to achieve the desired depth-variable density reflection point picking results. This improves the targeting and flexibility of the picking process.

[0034] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0035] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the invention.

[0036] Figure 1 A flowchart of the depth-variable density reflection point picking method in Embodiment 1 of the present invention is shown.

[0037] Figure 2 The depth-density pair provided in Embodiment 2 of the present invention is shown.

[0038] Figure 3 The following is an illustration of depth density pairs sorted from smallest to largest in Embodiment 2 of the present invention.

[0039] Figure 4 The picking results using conventional methods in Embodiment 2 of the present invention are shown.

[0040] Figure 5 This diagram shows an overlay of the picking results using conventional methods and the seismic profile in Embodiment 2 of the present invention.

[0041] Figure 6 The results of the depth-variable density reflection point picking method in Embodiment 2 of the present invention are shown.

[0042] Figure 7 This diagram shows an overlay of the pickup result and the cross-section of the depth-variable density reflection point pickup method used in Embodiment 2 of the present invention. Detailed Implementation

[0043] This invention addresses the issue of depth-variable density reflection point picking in seismic data tomography inversion. It proposes a depth-variable density reflection point picking method. For strata with relatively simple structures and stable layers, relatively low-density reflection point picking can be used, while for complex structural systems or target strata, high-density and high-precision picking can be used to improve picking accuracy and avoid missing detailed information.

[0044] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0045] Example 1

[0046] See Figure 1 This disclosure provides a method for picking up depth-variable-density reflection points. It includes the following steps:

[0047] S1: Based on seismic data, construct depth-density control pairs and determine the range of their quantities;

[0048] S2: Traverse all depth density control pairs and sort them in ascending order of depth to obtain the sorted depth density control pairs;

[0049] In this step, all depth-density control pairs are traversed and sorted by depth from smallest to largest. The number of traversals is n(n-1) / 2, where n is the number of control pairs.

[0050] S3: A piecewise interpolation algorithm is used to perform full-depth range picking density interpolation on the sorted depth density control pairs to obtain a picking density sequence with the same sampling rate and number of samples as the seismic data.

[0051] In this step, the piecewise interpolation algorithm is used to perform full-depth density interpolation on the sorted depth-density control pairs, including:

[0052] Based on the nearest neighbor search algorithm, find the depth value and density value of the nearest point in the depth array of the sorted depth density control pair for the full depth sampling point;

[0053] Calculate the weight coefficients of the depth points to be interpolated, and based on the weight coefficients, use a piecewise function to calculate the final picking density sequence corresponding to the full depth sampling points.

[0054] The weight coefficients for the interpolation depth points are calculated using the formula: g = [I(i) - I ne ] / [D(i)-D ne ];

[0055] Where g is the weight coefficient, I(i) is the density array in the sorted depth density control pairs, D(i) is the depth array in the sorted depth density control pairs, i represents the i-th input control pair, and D... ne I is the depth value of the nearest point. ne The density value is the value of the nearest point;

[0056] The piecewise function is:

[0057]

[0058] Among them, I f (j) represents the final pick density sequence, D f (j) is an array of full-depth sampling points, where j represents the j-th full-depth sampling point.

[0059] S4: Based on the picking density sequence, the reflection point picking is performed to obtain the depth-variable density reflection point picking result.

[0060] Specifically, this method targets depth-variable density reflection point picking in seismic data tomography inversion. First, it provides depth-density control pairs to determine the control range. Next, it iterates through the entire depth-density control pairs, re-sorting them from smallest to largest to determine the sorted control pairs. Then, it uses a piecewise interpolation algorithm to perform density interpolation across the entire depth range, obtaining a picking density sequence that matches the seismic data sampling rate and number of samples. Finally, reflection point picking is performed according to this sequence, thus achieving the desired depth-variable density reflection point picking results. This improves the targeting and flexibility of the picking process.

[0061] Example 2

[0062] This disclosure provides a method for picking up depth-variable-density reflection points. It includes the following steps:

[0063] First, input depth density control pairs D(i) and I(i), where i represents the i-th input control pair, and we take... n represents the number of input control pairs.

[0064] Next, it is necessary to traverse n(n-1) / 2 times to sort the entire depth density control pair in ascending order of depth, and obtain the sorted depth density control pair.

[0065]

[0066] Here, `reorder[··]` represents an ascending sort operation. This represents the depth-density control pairs sorted from smallest to largest.

[0067] Based on this, a piecewise interpolation algorithm is used to establish the picking density at each location across the entire depth range. First, it is necessary to determine the nearest point to the input depth density control pair at each depth. Let D represent the total depth sampling points. f (j), m represents the number of sampling points at the full depth, then:

[0068]

[0069] Where D ne D represents f (j) in array The nearest depth value in the middle, and its corresponding density value is denoted as I. ne Find_nearest[·] represents the nearest neighbor search algorithm.

[0070] Next, the weighting coefficients for the interpolation depth points are calculated using the following method:

[0071]

[0072] Then the full depth sampling point D f(j) corresponds to the final density interpolation result I f (j) can be calculated using the following piecewise function:

[0073]

[0074] This completes the picking of reflection points with varying depth and density.

[0075] Furthermore, this embodiment tests the correctness and effectiveness of the method using actual data.

[0076] Figure 2 The depth-density pair provided in this embodiment is shown, where the first column is the density value in the depth-density pair and the second column is the depth value in the depth-density pair.

[0077] Figure 3 The following diagram shows the depth density pairs sorted from smallest to largest in this embodiment, where the first column is the density value in the depth density pair and the second column is the depth value in the depth density pair.

[0078] Figure 4 The results of the conventional method used in this embodiment are shown. It can be seen that the conventional method picks up the same density in shallow, medium and deep layers, and cannot highlight key layers for targeted and encrypted picking.

[0079] Figure 5 The image shows the overlay display of the picking results using the conventional method in this embodiment and the seismic profile. It can be seen that the conventional method has acceptable picking accuracy and good overlay effect with the profile, but the density of shallow, medium and deep layers is consistent, and depth-variable density picking is not possible.

[0080] Figure 6 The results of the depth-variable density reflection point picking method of this embodiment are shown. It can be seen that the density of shallow, middle and deep layers can be inconsistent after using depth-variable density picking, which improves the targeting and flexibility of picking.

[0081] Figure 7 The image shows the superimposed display of the picking results and the cross-section of the depth-variable density reflection point picking method of this embodiment. It can be seen that after adopting depth-variable density picking, the picking density is higher and the superimposed effect is better for shallow high signal-to-noise ratio areas. For deep low signal-to-noise ratio areas, the picking interval can be appropriately increased and the picking weight reduced to reduce the amount of computation.

[0082] Example 3

[0083] This disclosure provides an electronic device, which includes:

[0084] At least one processor; and,

[0085] A memory communicatively connected to the at least one processor; wherein,

[0086] The memory stores instructions that can be executed by the at least one processor, which enables the at least one processor to perform the depth-variable density reflection point picking method in Embodiment 1 or 2.

[0087] An electronic device according to embodiments of the present disclosure includes a memory and a processor. The memory is used to store non-transitory 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. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0088] The processor may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of this disclosure, the processor is used to execute computer-readable instructions stored in the memory.

[0089] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0090] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0091] Example 4

[0092] This disclosure provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the depth-variable density reflection point picking method in Embodiment 1 or 2.

[0093] A computer-readable storage medium according to embodiments of the present disclosure stores non-transitory computer-readable instructions. When these non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods described in the foregoing embodiments of the present disclosure are performed.

[0094] The aforementioned 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 portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0095] Example 5

[0096] This disclosure provides a depth-variable density reflection point pickup device, including:

[0097] The control pair building module is used to construct depth-density control pairs based on seismic data and determine the range of their quantity.

[0098] The control pair sorting module is used to traverse all depth-density control pairs and sort them in ascending order of depth to obtain the sorted depth-density control pairs.

[0099] The picking density sequence construction module is used to perform full-depth range picking density interpolation on the sorted depth density control pairs using a piecewise interpolation algorithm to obtain a picking density sequence with the same sampling rate and number of samples as the seismic data.

[0100] The reflection point picking module is used to pick reflection points based on the picking density sequence to obtain depth-variable density reflection point picking results.

[0101] Optionally, the traversal of all depth density control pairs and their sorting by depth from smallest to largest takes n(n-1) / 2 times, where n is the number of control pairs.

[0102] Optionally, the step of employing a piecewise interpolation algorithm to perform full-depth range picking density interpolation on the sorted depth-density control pairs includes:

[0103] Based on the nearest neighbor search algorithm, find the depth value and density value of the nearest point in the depth array of the sorted depth density control pair for the full depth sampling point;

[0104] Calculate the weight coefficients of the depth points to be interpolated, and based on the weight coefficients, use a piecewise function to calculate the final picking density sequence corresponding to the full depth sampling points.

[0105] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for picking up depth-variable-density reflection points, characterized in that, include: Based on seismic data, depth-density control pairs were constructed, and the range of their quantities was determined. Traverse all depth density control pairs and sort them in ascending order of depth to obtain the sorted depth density control pairs; A piecewise interpolation algorithm is used to perform full-depth range picking density interpolation on the sorted depth density control pairs to obtain a picking density sequence with the same sampling rate and number of samples as the seismic data. Reflection point picking is performed based on the picking density sequence to obtain depth-variable density reflection point picking results.

2. The depth-variable density reflection point picking method according to claim 1, characterized in that, The process involves traversing all depth-density control pairs and sorting them by depth from smallest to largest, with a traversal count of n(n-1) / 2, where n is the number of control pairs.

3. The depth-variable density reflection point picking method according to claim 1, characterized in that, The step employs a piecewise interpolation algorithm to perform full-depth range density interpolation on the sorted depth-density control pairs, including: Based on the nearest neighbor search algorithm, find the depth value and density value of the nearest point in the depth array of the sorted depth density control pair for the full depth sampling point; Calculate the weight coefficients of the depth points to be interpolated, and based on the weight coefficients, use a piecewise function to calculate the final picking density sequence corresponding to the full depth sampling points.

4. The depth-variable density reflection point picking method according to claim 3, characterized in that, The weight coefficients for the interpolation depth points are calculated using the following formula: Where g is the weighting coefficient. This is the density array for the sorted depth-density control pairs. Let D be the depth array in the sorted depth density control pairs, where i represents the i-th input control pair. ne I is the depth value of the nearest point. ne This is the density value of the nearest point.

5. The depth-variable-density reflection point picking method according to claim 4, characterized in that, The piecewise function is: Among them, I f (j) represents the final pick density sequence, D f (j) is an array of full-depth sampling points, where j represents the j-th full-depth sampling point.

6. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the depth-variable density reflection point picking method according to any one of claims 1-5.

7. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing a computer to perform the depth-variable density reflection point picking method according to any one of claims 1-5.

8. A depth-variable-density reflection point pickup device, characterized in that, include: The control pair building module is used to construct depth-density control pairs based on seismic data and determine the range of their quantity. The control pair sorting module is used to traverse all depth-density control pairs and sort them in ascending order of depth to obtain the sorted depth-density control pairs. The picking density sequence construction module is used to perform full-depth range picking density interpolation on the sorted depth density control pairs using a piecewise interpolation algorithm to obtain a picking density sequence with the same sampling rate and number of samples as the seismic data. The reflection point picking module is used to pick reflection points based on the picking density sequence to obtain depth-variable density reflection point picking results.

9. The depth-variable-density reflection point pickup device according to claim 8, characterized in that, The process involves traversing all depth-density control pairs and sorting them by depth from smallest to largest, with a traversal count of n(n-1) / 2, where n is the number of control pairs.

10. The depth-variable-density reflection point pickup device according to claim 8, characterized in that, The step employs a piecewise interpolation algorithm to perform full-depth range density interpolation on the sorted depth-density control pairs, including: Based on the nearest neighbor search algorithm, find the depth value and density value of the nearest point in the depth array of the sorted depth density control pair for the full depth sampling point; Calculate the weight coefficients of the depth points to be interpolated, and based on the weight coefficients, use a piecewise function to calculate the final picking density sequence corresponding to the full depth sampling points.

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