Method for evaluating anticlinal oil-gas possibility

Abstract

The invention discloses a method for evaluating the anticlinal oil-gas possibility, and the method comprises the steps: carrying out the abundance time difference calculation through the data of each sampling CDP point on a designed related evaluation measuring line, and obtaining the abundance time difference data of oil-gas; performing discrete coefficient calculation on the abundance time difference data to obtain an abundance coefficient value about evaluation of the whole measuring line; and calculating a reservoir evaluation coefficient by using the abundance coefficient data value on each evaluation measuring line, so that the reservoir evaluation coefficient can be used for evaluating the oil-gas possibility of the whole anticline. Furthermore, the well position of the exploration well can be determined according to the abundance time difference data on the specified survey line. Compared with a traditional conventional reservoir prediction result, the reservoir prediction method has higher accuracy and higher evaluation rapidness, the oil-gas property distribution condition, the oil-gas enrichment degree and the like of a target stratum on the anticline structure can be rapidly recognized, relevant exploration well position arrangement is guided, and powerful technical support and well spacing basis can be provided for oil-gas exploration.

Description

Technical Field

[0001] The invention belongs to the field of oil and gas exploration, specifically to the technical field of seismic data interpretation in geophysical exploration, and relates to a method for evaluating reservoir coefficients of anticline oil and gas properties based on abundance time difference and abundance coefficient calculation. Background Art

[0002] In the field of geophysical exploration, after obtaining seismic data through conventional methods, it is necessary to interpret the seismic data, and generally carry out the corresponding reservoir prediction and evaluation process. In the conventional reservoir interpretation process, it is necessary to analyze the relevant logging data, extract and invert the relevant attributes of the seismic data, and then use the original seismic data, logging data, and extracted or inverted attribute data to conduct qualitative and quantitative analysis to identify the development areas and layers of the reservoir, thereby completing the oil and gas evaluation work. These reservoir prediction technologies often require a large amount of technical data and software to support them.

[0003] A large amount of exploration data shows that when the core of the anticline contains oil and gas, seismic data can be used to identify it. In seismic reflection, the reflection pull-down phenomenon at the bottom of the reservoir is often caused. The appearance of this phenomenon is different from the reflection characteristics caused by normal stratigraphic deposition. Therefore, it can be identified through relevant technical means to determine the oil and gas content of the anticline core. In early oil and gas exploration activities, it is often very important to determine the anticline closure. This is mainly because during the migration of oil and gas, they often gather in the anticline. Therefore, a large number of early oil and gas exploration wells often drilled anticline high points. However, there are also many examples of such failures, mainly due to the incomplete evaluation technology of the oil and gas content of the anticline, which leads to some exploration wells encountering no reservoirs, poor reservoirs, etc. Summary of the invention

[0004] The present invention aims to overcome the above and other shortcomings of the conventional technology and accurately identify the oil and gas content of the anticline. To this end, the present invention provides a method for evaluating the oil and gas content of the anticline by calculating the reservoir evaluation coefficient based on the abundance time difference and the abundance coefficient.

[0005] Technical solution:

[0006] A method for evaluating the oil and gas content of anticlines, specifically comprising:

[0007] S1. Conduct stratigraphic interpretation on the bottom of the target layer and the reference layer that need to be evaluated on the anticline structure, and determine the evaluation survey line, sampling point interval and extraction of relevant stratigraphic data pairs.

[0008] a. Perform stratigraphic interpretation on the bottom of the target layer and the reference layer that need to be evaluated in the anticline structure. The main operation is to use the results of three-dimensional seismic data body, well seismic calibration, etc. to determine the two-way reflection time position of the bottom of the target layer and the two-way reflection time position of the reference layer, and perform stratigraphic interpretation. Through automatic stratigraphic tracking or manual interpretation, the stratigraphic data of the bottom of the target layer and the reference layer are obtained. The reference layer mainly refers to the layer with stable sedimentation in this area, with good reflection continuity and easy tracking. In general, the reference layer refers to the sedimentation caused by large-scale water intrusion or deep water environment, with relatively simple physical properties and stable sedimentation. If the reference layer cannot be found in the anticline area, then a reference layer can be established through manual interpretation-established in the upper strata of the target layer. The establishment of the artificial reference layer is to draw a relatively smooth curved surface with reference to the reflection occurrence of the strata at the bottom of the target layer on both wings of the anticline; the artificial reference layer in the core of the anticline can be drawn with reference to the occurrence of the reflection layer of the strata at the top of the target layer. In this way, a reference layer can be established manually.

[0009] b. Determine the position of the survey line for oil and gas evaluation, and extract the data pairs of the bottom of the target layer and the reference layer on the survey line. Among them, the position of the survey line can be determined according to the relevant evaluation requirements and expert experience. Generally, the line direction or the track direction, or both directions can be used. If multiple survey lines are to be used for oil and gas evaluation in the anticline area, it is necessary to extract data pairs separately for relevant calculation and post-evaluation. In addition, extracting the relevant layer data pairs on the survey line refers to determining the two-way reflection time Ti0 and relative distance Xi of the relevant target layer of each sampling CDP point on the survey line. The relative distance refers to the distance of each sampling CDP point relative to the minimum or maximum sampling CDP point number, which is an integer multiple of the track distance.

[0010] c. The establishment of sampling CDP points on the survey line mainly involves setting the sampling interval and number. In general, the sampling interval is set to an integer multiple of the track spacing, which can be determined by the anticline range, the accuracy of exploration evaluation, and other conditions. The smaller the sampling interval, the higher the evaluation accuracy; conversely, the evaluation accuracy decreases. In actual work, a sampling interval of 5 track spacing lengths can be used, which reduces the workload and does not reduce the evaluation accuracy.

[0011] Preferably, the number of sampling points on each survey line should be consistent, and the relevant sampling points should cover the core and wing of the anticline. In principle, the number of sampling points in the core is required to be roughly consistent with the number of sampling points in the wing. The number of relevant sampling points can be determined based on actual seismic data, expert experience, exploration evaluation accuracy, etc.

[0012] S2. Calculate the abundance time difference of the evaluation survey line and related horizon data to obtain the abundance time difference data of each sampling point on the evaluation survey line.

[0013] S2-1. First, extract the two-way reflection time of the bottom of the target layer and the reference layer at the same sampling CDP point on a certain evaluation line to calculate and determine the abundance time difference data of the CDP point. The calculation formula of the abundance time difference data is as follows:

[0014]

[0015] In formula (1), K i is the abundance time difference data of the i-th sampling CDP point on the survey line, is the two-way reflection time data of the target layer bottom at the i-th sampling CDP point on the survey line, It is the two-way reflection time data of the reference layer at the i-th sampling CDP point on the survey line.

[0016] S2-2. According to the calculation of relative distance, the relative distance of each sampling CDP point is obtained. The specific implementation is to determine a reference point on the survey line and calculate the relative distance between each sampling CDP point on the survey line and the reference point. In general, the reference point can be the position of the largest or smallest sampling CDP point on the survey line. Each evaluation survey line must have a reference point. The relative distance calculation formula is as follows:

[0017] L i =ΔX* (A i -A O ) (2)

[0018] In formula (2), L i is the relative distance data of the i-th sampling CDP point on the survey line, A i is the point number of the i-th sampling CDP point on the survey line, A O is the point number of the reference point on the survey line, and ΔX is the track distance.

[0019] S2-3, establish the data pair (K i , L i ). The specific implementation is to obtain the abundance time difference data and relative distance data of each sampling CDP point through the above calculation, and then establish a data set of these two data for each sampling CDP point. Using the data pair (K i , L i ) Establish a two-dimensional coordinate system and test or optimize the relevant reference layers and methods. The relevant steps are as follows:

[0020] a. If in the reference layer and abundance time difference calculation test, in the two-dimensional coordinate system, the abundance time difference data on both sides of the anticline are relatively stable, and the difference between the maximum data and the minimum data does not exceed 10% of the maximum data, then the reference layer can be used for abundance time difference calculation.

[0021] b. If in the reference layer and abundance time difference calculation test, the abundance time difference data on the two wings of the anticline in the two-dimensional coordinates rise or fall relatively toward the outside of the wings, and the difference between the maximum data and the minimum data is greater than 10% of the maximum data, the following two methods can be used to perform abundance time difference correction calculations.

[0022] 1. The reference layer can be re-interpreted manually until the abundance time difference on both wings is relatively stable and does not exceed 10% of the maximum data. The reference layer data can be used to calculate the abundance time difference in the next step.

[0023] 2. Dimensionality reduction processing technology can be used to correct the relevant abundance time difference data. The relevant dimensionality reduction processing steps are as follows:

[0024] (1) Extract the data pair (K) of each sampling CDP point on the survey line i , L i ), and use the two-dimensional coordinate system to intersect to obtain an intersection diagram, and find the oblique straight line that can determine the general direction of these data points from the intersection diagram.

[0025] (2) Rotate the coordinates using the angle θ between the oblique straight line and the horizontal axis in the original coordinate system as the rotation angle, and transform the original coordinate system into a new coordinate system. If the horizontal axis in the new coordinate system is parallel to the oblique straight line, the vertical axis in the new coordinate system is parallel to the normal direction of the oblique straight line; if the vertical axis in the new coordinate system is parallel to the oblique straight line, the horizontal axis in the new coordinate system is parallel to the normal direction of the oblique straight line. The transformation of the original coordinate system into the new coordinate system is achieved by using calculation formulas (3) and (4):

[0026] X / =Xcosθ+Ysinθ (3)

[0027] Y / =Ycosθ-Xsinθ (4)

[0028] Where X and Y are the horizontal and vertical coordinates in the original coordinate system; X / , Y / are the horizontal and vertical coordinates in the new coordinate system, and θ is the angle between the oblique line and the horizontal axis in the original coordinate system. In general, the X axis is set as distance and the Y axis is the abundance time difference.

[0029] (3) Use the function formula (dimensionality reduction calculation formula) (3) or (4) to perform dimensionality reduction processing on the two attribute data bodies to obtain a reduced-dimensional data body. When the oblique straight line in the new coordinate system is parallel to the horizontal axis, the formula (3) is used for dimensionality reduction processing; if the oblique straight line in the new coordinate system is parallel to the vertical axis, the formula (4) is used for dimensionality reduction processing. In general, the dimensionality reduction processing is mainly performed on the abundance time difference data.

[0030] (4) Perform dimensionality reduction processing on the abundance time difference data of each sampling CDP point to obtain a reduced-dimensionality data value. The reduced-dimensionality value is the corrected abundance time difference data.

[0031] Preferably, the dimension reduction data processing technology is used, and the reference layer does not need to be modified again, and the relevant data can be directly used for correction. For the above two relative abundance time difference data with an error greater than 10%, one of the methods should be selected according to the actual specific situation.

[0032] Preferably, the abundance time difference is calculated for the evaluation survey line and the relevant layer data to obtain the abundance time difference data of each sampling point on the evaluation survey line. In principle, corresponding adjustments should be made according to the conditions of the reference layer and the test conditions of the abundance time difference to optimize the calculation of the abundance time difference.

[0033] Preferably, the abundance time difference calculation is performed on the evaluation survey line and the relevant horizon data, mainly to establish a two-dimensional coordinate system and perform relevant evaluation work to determine the abundance time difference data involved in the subsequent calculation steps.

[0034] S3. Calculate the dispersion coefficient using the abundance time difference data on the evaluation survey line, and use the dispersion coefficient as the abundance coefficient data to calculate the reservoir evaluation coefficient, so as to obtain the reservoir evaluation coefficient for oil and gas evaluation.

[0035] S3-1. Calculate the dispersion coefficient using the abundance time difference data values ​​of each sampling CDP point on the survey line to obtain the abundance coefficient for oil and gas evaluation. The specific operation is to extract the abundance time difference data values ​​on the survey line. Calculate the dispersion coefficient. The dispersion coefficient can be used as the abundance coefficient value of the survey line. The dispersion coefficient calculation formula is as follows:

[0036]

[0037] In formula (5) to (7) Represents the dispersion coefficient value on the hth survey line, that is, the abundance coefficient value, represents the standard deviation of the hth measurement line, represents the arithmetic mean of the abundance time difference data of the sampling points in the anticline wing area of ​​the survey line, ji represents the abundance time difference data value of the ith sampling CDP point of the survey line, and k is the number of CDP points on the survey line involved in calculating the dispersion coefficient data.

[0038] S3-2. According to the above calculation method, the abundance coefficient calculation of each evaluation survey line is completed, and the obtained abundance coefficient data is weighted and averaged to obtain the reservoir evaluation coefficient, so as to relatively accurately evaluate the oil and gas content of the anticline. In general, the larger the reservoir evaluation coefficient, the greater the possibility that the anticline contains oil and gas; conversely, the anticline may not contain oil and gas. In addition, the abundance time difference data on each survey line can also be used to draw contour lines - the data is interpolated and smoothed to obtain a contour plane map. The oil and gas content of the core of the anticline is evaluated through the abundance time difference contour map and the reservoir evaluation coefficient. Among them, the calculation method of the reservoir evaluation coefficient of the anticline structure is as follows:

[0039]

[0040] Where A represents the reservoir evaluation coefficient of the anticline structure, Fi represents the abundance coefficient calculated by the i-th survey line, and p is the number of evaluation survey lines on the anticline structure.

[0041] S4. Use reservoir evaluation coefficients and abundance time difference data to evaluate the oil and gas content of a target layer in the core of the anticline.

[0042] Preferably, an electronic device is also provided in an example of the present invention, which includes: a memory storing executable instructions; a processor, which runs the executable instructions in the memory to implement the method of evaluating the oil and gas content of a target layer segment of an anticline structure.

[0043] Preferably, the embodiment of the present disclosure also provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, it implements the method of evaluating the oil and gas content of a certain target layer segment of anticline structure.

[0044] Beneficial Effects of the Invention

[0045] By determining the data of relevant evaluation survey lines and sampling points (or CDP points), the abundance time difference data is calculated; the abundance time difference data on the evaluation survey line is used to calculate the discrete coefficient to obtain the abundance coefficient; the reservoir evaluation coefficient calculated by the abundance coefficient of each evaluation survey line and the abundance time difference data are used to evaluate the oil and gas content of a certain target layer section of the anticline. Through the implementation of the present invention, the evaluation accuracy of the oil and gas content in the core of the anticline is significantly improved, the exploration risk is effectively reduced, and the exploration economic benefits of the anticline area can be greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the technical process of this invention. DETAILED DESCRIPTION

[0047] The present invention will be further described below in conjunction with embodiments, but the protection scope of the present invention is not limited thereto:

[0048] Example 1

[0049] According to the technical process of this invention ( Figure 1 ), formulate work procedures, and take the example of evaluating the oil and gas content of the second segment of the anticline core in a certain three-dimensional work area.

[0050] In step ①, according to the characteristics of the fault anticline in the study area, the relevant interpretation horizons are established. By introducing relevant exploration horizons from the outside area, the interpretation of the bottom of the Xu 2 reservoir is implemented to obtain its interpretation horizon. Secondly, by comparing the artificially established reference surface and the reference surface of stable deposition. It is believed that the reference surface of stable deposition is relatively far away from the reflection layer at the bottom of the reservoir, which may cause some errors. Therefore, in actual operation, the artificially established reference surface is mainly used. In this step, according to the characteristics of the fault anticline, a total of 6 evaluation survey lines in three line directions and three track directions are established to evaluate the oil and gas content of the Xu 2 segment of the fault anticline. The interval between the sampling CDP points on the survey line is 4 track distances. According to the interpreted relevant stratum data, a data pair is established to implement the next step.

[0051] In step ②, the enrichment time difference calculation is performed on the 6 evaluation lines using the data pairs of each sampling CDP on each line, and the abundance time difference data and relative distance data of the target layer at the sampling CDP points on each evaluation line are obtained. From the abundance time difference data of the target layer, the abundance time difference on the two wings of the anticline is relatively stable, with little change, and tends to increase toward the core of the anticline. Therefore, the dimensionality reduction processing technology can be used to correct the abundance time difference data. In actual exploration, the abundance time difference calculation formula is used to complete the processing of the abundance time difference of each sampling CDP point on the 6 evaluation lines. From this step, it can also be seen that the oil and gas content of the reservoir in the core of the anticline affects the abundance time difference data. The abundance time difference value in the core area is relatively large, while the abundance time difference in the wing area of ​​the anticline is relatively small. The larger the abundance time difference value, the higher the possibility of inferring oil and gas.

[0052] In step ③, the abundance time difference data is used to calculate the dispersion coefficient for each evaluation survey line, and the abundance coefficients (i.e., dispersion coefficients) on the six survey lines are used to calculate the reservoir evaluation coefficient, thereby obtaining a reservoir evaluation coefficient for evaluating the oil and gas content of the second section of the anticline core. In the example, the abundance time difference data at each sampling point of the designed six survey lines are used to calculate the dispersion coefficient, and 6 abundance coefficient data values ​​about the oil and gas content of the anticline in the study area are obtained; and the reservoir evaluation coefficient is calculated based on the 6 abundance coefficient data values. The reservoir evaluation coefficient is compared with the reservoir evaluation coefficient of the second section of the anticline structure in other study areas that is known to be free of oil and gas. It is found that the reservoir evaluation coefficient of this structure is higher than the reservoir evaluation coefficient of the anticline structure that is known to be free of oil and gas, and the data difference can reach 4.5 times. Therefore, it can be determined that the anticline structure is relatively rich in oil and gas, and a structural high point is selected on the No. 3 survey line with the largest abundance coefficient (the abundance time difference value of a sampling CDP point on this survey line is also large) to deploy an exploration well. Subsequent drilling data in the study area have verified that the well has drilled a high-yield oil and gas flow in the Xu 2 reservoir.

[0053] Example 2

[0054] The present invention discloses an electronic device, which includes: a memory storing executable instructions; a processor running the executable instructions in the memory to implement the above-mentioned method for evaluating the oil and gas content of a target layer section on the anticline structure.

[0055] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0056] 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.

[0057] The processor may be a central processing unit (CPU) or other forms of processing units having 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 the present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0058] 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.

[0059] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0060] Example 3

[0061] The embodiment of the present disclosure provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for evaluating the oil and gas content of a target layer segment on an anticline structure.

[0062] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of each embodiment of the present disclosure are executed.

[0063] 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).

[0064] The specific embodiments described herein are merely examples of the spirit of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in similar ways, but they will not deviate from the spirit of the present invention or exceed the scope defined by the appended claims.

Claims

1. A method for evaluating the oil and gas content of anticlines, characterized in that It includes the following steps: S1. Conduct stratigraphic interpretation on the bottom of the target layer and the reference layer to be evaluated on the anticline structure, determine the survey line position, sampling point interval and extract relevant stratigraphic data pairs for oil and gas evaluation; S2, performing abundance time difference calculation on the evaluation survey line and related horizon data pairs to obtain abundance time difference data of each sampling point on the evaluation survey line; S3, calculating the dispersion coefficient of the abundance time difference data on the evaluation line to obtain the abundance coefficient value, and calculating the reservoir evaluation coefficient according to the abundance coefficient data value of the relevant evaluation line; S4. Use reservoir evaluation coefficients and abundance time difference data to evaluate the oil and gas content of a target layer in the core of the anticline.

2. The method according to claim 1, characterized in that In step S1, the bottom of the target layer to be evaluated on the anticline structure and the reference layer are interpreted, specifically: Using 3D seismic data and well-seismic calibration results, determine the two-way reflection time position of the bottom of the target layer and the two-way reflection time position of the reference layer, and perform layer interpretation; obtain the layer data of the bottom of the target layer and the reference layer through automatic layer tracking or manual interpretation; The reference layer refers to the layer with stable sedimentation in the area, good reflection continuity and easy tracking; the reference layer refers to the sedimentation caused by large-scale water invasion or deep water environment, with relatively simple physical properties and stable sedimentation; If no reference layer can be found in the anticline area, a reference layer is established through manual interpretation: it is established in the upper strata of the target layer.

3. The method according to claim 2, characterized in that The establishment of the artificial reference layer is as follows: a relatively smooth curved surface is drawn with reference to the reflection dip of the strata at the bottom of the target layer on both wings of the anticline; the artificial reference layer is drawn in the core of the anticline with reference to the dip of the reflection layer at the top of the target layer.

4. The method according to claim 1, characterized in that In step S1, the survey line position, sampling point interval and relevant stratum data pairs for oil and gas evaluation are determined, specifically: The location of the survey line is determined based on relevant evaluation requirements and expert experience, and the line direction or track direction, or both directions can be used; By establishing sampling CDP points on the survey line, the interval and number of sampling points are set; the sampling points should cover the core and wing of the anticline, and the number of sampling points in the core is consistent with the number of sampling points in the wing; Extracting relevant layer data pairs on the survey line refers to determining the two-way reflection time Ti0 and relative distance Xi of the relevant target layer of each sampling CDP point on the survey line. The relative distance refers to the distance of each sampling CDP point relative to the minimum or maximum sampling CDP point number, which is an integer multiple of the track distance.

5. The method according to claim 1, characterized in that Step S2 specifically includes: S2-1. First, extract the two-way reflection time of the bottom of the target layer and the reference layer of the same sampling CDP point on a certain evaluation line for calculation, and determine the abundance time difference data of the CDP point by the following formula: Among them, K i is the abundance time difference data of the i-th sampling CDP point on the survey line, T j i is the two-way reflection time data of the target layer bottom at the i-th sampling CDP point on the survey line, is the two-way reflection time data of the reference layer at the i-th sampling CDP point on the survey line; S2-2. The relative distance of each sampling CDP point is obtained by the following formula: L i =ΔX*(A i -A O ) Among them, L i is the relative distance data of the i-th sampling CDP point on the survey line, A i is the point number of the i-th sampling CDP point on the survey line, A O is the point number of the reference point on the survey line, ΔX is the track distance; S2-3, establish the data pair (K) of each sampling CDP point on the survey line i , L i ), using the data of each sampling CDP point (K i , L i ) Establish a two-dimensional coordinate system, and test or optimize the relevant reference layers and methods; determine the final abundance time difference data.

6. The method according to claim 5, characterized in that The test or optimization steps of step S2-3 are specifically: ① If in the reference layer and abundance time difference calculation test, in the two-dimensional coordinate system, the abundance time difference data on both sides of the anticline are relatively stable, and the difference between the maximum data and the minimum data does not exceed 10% of the maximum data, then the reference layer can be used for abundance time difference calculation; ②. If in the reference layer and abundance time difference calculation test, the abundance time difference data of the two wings of the anticline in the two-dimensional coordinates rise or fall relatively toward the outside of the wing, and the difference between the maximum data and the minimum data is greater than 10% of the maximum data, then it is necessary to perform a correction calculation of the abundance time difference data, and the correction calculation of the abundance time difference data is: Solution 1: Re-interpret the reference layer manually until the abundance time difference on its two wings is relatively stable and does not exceed 10% of the maximum data, and use the reference layer data to calculate the abundance time difference in the next step; or Option 2: Use dimensionality reduction technology to correct the relevant abundance time difference data.

7. The method according to claim 6, characterized in that In the second scheme, the specific steps of dimensionality reduction processing are as follows: (1) Extract the data pair (K) of each sampling CDP point on the survey line i , L i ), and use the two-dimensional coordinate system to intersect to obtain an intersection diagram, and find the oblique straight line that can determine the general direction of these data points from the intersection diagram; (2) The coordinates are rotated with the angle θ between the oblique straight line and the horizontal axis in the original coordinate system as the rotation angle, and the original coordinate system is converted into a new coordinate system, such as the horizontal axis in the new coordinate system is parallel to the oblique straight line, and the vertical axis in the new coordinate system is parallel to the normal direction of the oblique straight line; such as the vertical axis in the new coordinate system is parallel to the oblique straight line, and the horizontal axis in the new coordinate system is parallel to the normal direction of the oblique straight line; the conversion of the original coordinate system into the new coordinate system is realized by using calculation formula (3) and formula (4): X / =Xcosθ+Ysinθ (3) Y / =Ycosθ-Xsinθ (4) Where X and Y are the horizontal and vertical coordinates in the original coordinate system; X / , Y / are the horizontal and vertical coordinates in the new coordinate system, and θ is the angle between the oblique line and the horizontal axis in the original coordinate system; (3) Using formula (3) or formula (4) to perform dimensionality reduction processing on the two attribute data bodies, a reduced-dimensional data body is obtained; when the oblique straight line in the new coordinate system is parallel to the horizontal axis, the dimensionality reduction processing is performed using formula (3); if the oblique straight line in the new coordinate system is parallel to the vertical axis, the dimensionality reduction processing is performed using formula (4); (4) Perform dimensionality reduction processing on the abundance time difference data of each sampling CDP point to obtain a reduced-dimensionality data value. The reduced-dimensionality value is the corrected abundance time difference data.

8. The method according to claim 6, characterized in that Step S3 specifically includes: S3-1. The dispersion coefficient is calculated using the abundance time difference data values ​​of each sampling CDP point on the survey line to obtain the abundance coefficient for oil and gas evaluation. The dispersion coefficient calculation formula is as follows: In the formula, represents the dispersion coefficient value on the hth line, as the abundance coefficient value, represents the standard deviation of the hth line, represents the arithmetic mean of the abundance time difference data of the sampling points in the anticline wing area of ​​the survey line, j i represents the abundance time difference data value of the i-th sampling CDP point on the survey line, and k is the number of CDP points involved in calculating the dispersion coefficient data on the survey line; S3-2. The calculation method of reservoir evaluation coefficient is as follows: Where A represents the reservoir evaluation coefficient of the anticline structure, F i represents the abundance coefficient calculated for the ith survey line, and p is the number of evaluation survey lines on the anticline structure.

9. An electronic device, comprising: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement a method for evaluating the oil and gas content of anticlines as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements a method for evaluating the oil and gas content of anticlines as claimed in any one of claims 1 to 8.

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