A Near-Surface and Medium-Deep Q-Field Fusion Method, System, Device and Medium Based on a Mask Body

Abstract

The present invention belongs to the technical field of oil exploration information processing, and specifically discloses a method, system, device and medium for fusing near-surface and mid-deep Q fields based on mask bodies. The method includes: generating a near-surface Q field F1 and a mid-deep Q field F2, subtracting the two Q fields after weighting to form a data volume F3, and obtaining the data volume F3 after processing to remove outliers from the data volume F3 ” , for the data volume F3 ” perform mask transformation to respectively obtain mask bodies F 1 / 0 , F 0 / 1 , and the data boundaries where the 0 and 1 values in the mask bodies F 1 / 0 , F 0 / 1 are located are ideal fusion surfaces; multiply the points corresponding to the near-surface Q field F1 and the mid-deep Q field F2 by the mask bodies F 1 / 0 , F 0 / 1 respectively to obtain complementary data volumes F 上 and data volume F 下 , and finally add the data volume F 上 and the data volume F 下 . The present invention can realize intelligent and efficient fusion of near-surface and mid-deep Q fields, with high fusion accuracy and high efficiency. The present invention is applicable to the fusion of near-surface and mid-deep Q fields and the establishment of a full-layer Q field.

Description

Technical Field

[0001] The present invention relates to the technical field of oil exploration information processing, and particularly relates to a method, system, device and medium for fusing near-surface and middle-deep Q fields based on a mask body. Background Art

[0002] In the field of oil exploration, the quality factor Q is an important parameter for describing the absorption and attenuation characteristics of a medium for seismic waves. A reasonable and fine description of the Q field is crucial for improving the resolution of seismic data. At present, a series of Q processing technologies based on "Q modeling, Q compensation, and Q migration" have been widely applied and achieved good results. Especially in basin areas with complex near-surface conditions, such as the Ordos Basin area, due to the severe absorption and attenuation of data by its extremely thick loess tableland, the main frequency of the data is low and the frequency band is narrow, which severely restricts the prediction of thin sand bodies and lithological interpretation. However, the application of Q processing technology can better solve the problems of high-frequency loss, phase dispersion, and wavelet distortion caused by complex near-surface absorption and attenuation in the basin.

[0003] The near-surface Q field and the middle-deep Q field of the Q processing technology are respectively obtained by calculating and fitting micro-logging data and VSP data. And in the current application of the Q processing technology, it has developed from "near-surface Q compensation and middle-deep Q migration" to "whole-layer Q migration". "Near-surface Q compensation and middle-deep Q migration" independently models the two Q fields and applies them to the energy compensation stage and the migration stage respectively; "Whole-layer Q migration" is to fuse the two Q fields in a certain way to construct a whole-layer Q field with a Q value distribution model covering the entire formation (from shallow to deep), and finally conduct overall modeling and evaluation and apply it to the migration stage. Compared with the former, the weak reflections in the profile are clearer in "whole-layer Q migration", and both the main frequency and the frequency bandwidth are further improved.

[0004] There are mainly two existing methods for fusing the near-surface layer Q field and the middle-deep Q field to obtain the whole-layer Q field. One is to fuse the near-surface layer and the middle-deep Q field along the top surface of the high-velocity layer, and the other is to fuse along the zero-difference interface. The method of fusing along the top surface of the high-velocity layer does not require picking up the fusion surface, but the coupling between the two Q fields at the transition position is poor, and large smoothing processing is required after fusion, which is not conducive to the overall fine description and evaluation of the Q field, resulting in low precision of the whole-layer Q migration; the method of fusing along the zero-difference interface has a better coupling effect in the transition zone, but it requires manually picking up the zero-difference interface. The manual picking workload is large and time-consuming, and the picking accuracy varies due to different manual picking experiences. Especially in the case of a large grid density of three-dimensional seismic, the picking workload increases sharply, resulting in a high cost of experimental modeling and it is difficult to meet the industrial production requirements, which is not conducive to the comprehensive promotion of the whole-layer Q field application technology. Summary of the Invention

[0005] To address the above deficiencies in the existing technology, the present invention aims to provide a method, system, device, and medium for fusing the near-surface and mid-deep Q-fields based on a mask body, improving the modeling methods and processes for fusing the two Q-fields, and solving the problems of low accuracy and low efficiency in establishing the full-layer Q-field in the existing technology, thereby achieving the intelligent and efficient fusion of the near-surface and mid-deep Q-fields.

[0006] To achieve the above objective, the technical method adopted by the present invention is as follows: A method for fusing the near-surface and mid-deep Q-fields based on a mask body, comprising the following steps:

[0007] S1. Generate the near-surface Q-field F1 and the mid-deep Q-field F2;

[0008] S2. Subtract the mid-deep Q-field F2 from the near-surface Q-field F1 with weights to form a data volume F3 containing a zero-value interface;

[0009] S3. Process the data volume F3 to remove outliers, obtaining the data volume F3'';

[0010] S4. Perform mask transformation on the data volume F3'' to obtain the near-surface mask body F 1 / 0 and the mid-deep mask body F 0 / 1 respectively;

[0011] S5. Multiply the near-surface Q-field F1 and the mid-deep Q-field F2 by the mask bodies F 1 / 0 and F 0 / 1 respectively, and then add them together to complete the fusion of the two Q-fields.

[0012] As a limitation, the formula for weighted subtraction in S2 is: F3 = F1 - αF2, where the value range of the weight coefficient α is 0.5 to 1.5.

[0013] As a limitation, the method for removing outliers in S3 is the moving average method.

[0014] As a further limitation, the moving average method adopts the five-point moving average method, and the calculation steps of the five-point moving average method are as follows:

[0015] S31. Mark the data at the layer position of the zero-value interface in the data volume F3 as (x, y, Depth / Time), where Depth is the data type in the depth domain and Time is the data type in the time domain;

[0016] S32. Calculate the boundary values excluding the two ends of the data, and the processing formula is as follows:

[0017]

[0018] Among them, A(x, y, z n ) represents the sample value of the zero-value interface in the data volume F3, and A''(x, y, zn represents the zero-value interface sample value in the processed data body F3”; the data length of the sample value is k, where 3 ≤ n ≤ k - 2;

[0019] S33. Calculate the boundary values at both ends of the data, and the processing formula is as follows:

[0020]

[0021] Thus, the unique data body F3” of the zero-value interface on the vertical single trace is obtained.

[0022] As a limitation, in S4, the mask body F 1 / 0 performs a logical judgment on the data body F3” using the logical function GE (>=) or LE (<=), taking numbers greater than 0 as 1 and numbers less than 0 as 0; the mask body F 0 / 1 performs a judgment on it using the logical function LOGICALNOT to obtain the mask body F 1 / 0 complementary to it 0 / 1 .

[0023] As another limitation, the mask body F 0 / 1 performs a logical judgment on the data body F3” using the logical function GE (>=) or LE (<=), taking numbers less than 0 as 1 and numbers greater than 0 as 0.

[0024] As a limitation, the near-surface Q field F1 in S1 is obtained by inverting the near-surface velocity field using the first arrival data of large guns and fitting it with the data of dual-well micro-logging; the mid-deep Q field F2 is obtained using VSP well information and horizon interpolation.

[0025] The present invention also provides a near-surface and mid-deep Q field fusion system based on a mask body, including:

[0026] A Q field data generation module for generating a near-surface Q field F1 and a mid-deep Q field F2;

[0027] A data body F3 acquisition module for acquiring the zero-value interface including the transition region between the near-surface Q field F1 and the mid-deep Q field F2;

[0028] A data body F3 processing module for removing the abnormal values of the zero-value interface on the vertical single trace to make the zero-value interface unique on the vertical single trace, and obtaining the data body F3”;

[0029] A data body F3” mask transformation module for obtaining the mask bodies F 1 / 0 , F 0 / 1 , and the data boundaries where the 0 and 1 values in the mask bodies F 1 / 0 , F 0 / 1 are located are the ideal fusion surfaces;

[0030] The Q-field fusion module is used to fuse two Q-fields on the ideal fusion surface, and the dot product mask bodies F 1 / 0 and F 0 / 1 corresponding to the near-surface Q-field F1 and the mid-deep Q-field F2 respectively, to obtain a data body F 上 and a data body F 下 that only contain the corresponding parts and are complementary along the ideal fusion surface; adding the data body F 上 to the data body F 下 realizes the fusion of the two Q-fields and completes the establishment of the full-layer Q-field.

[0031] The present invention also provides a computer device, including a memory and a processor. The memory stores a computer program, and the processor calls the computer program in the memory to execute any one of the above-mentioned methods for fusing the near-surface and mid-deep Q-fields based on the mask body.

[0032] The present invention also provides a computer-readable storage medium. A computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, it is used to implement any one of the above-mentioned methods for fusing the near-surface and mid-deep Q-fields based on the mask body.

[0033] Due to the adoption of the above technical solutions, compared with the prior art, the beneficial effects obtained by the present invention are as follows:

[0034] In the fusion of the surface Q-field and the mid-deep Q-field in the present invention, the zero-difference interface fusion concept is followed, and the two Q-fields are weighted and subtracted to form a data body F3. The data body F3 contains a zero-value interface corresponding to the manually picked best fusion surface. At this time, the mask transformation technology in the computer field is used to extend the mask concept to the three-dimensional attribute body modeling field of seismic data, and the data body to be picked is transformed to form a mask body. The boundary value of the mask body is consistent with the zero-difference surface to be picked, ensuring good coupling effect in the transition zone for the zero-difference interface fusion method; when fusing the two Q-fields, the two complementary mask bodies are directly fused with the two Q-field data respectively by dot product and then addition. The whole process does not require manual picking of fusion surface data, that is, the traditional idea of fusing the near-surface and mid-deep Q-fields of "Q-field + fusion surface" is transformed into the idea of "Q-field + mask body". The whole fusion process does not involve the "fusion surface", and the "fusion surface" is hidden on the data boundary of the mask body, removing the work process of manual picking of the fusion surface. While avoiding manual picking errors, it minimizes the input of manual picking costs to the greatest extent, which is conducive to production and quality control requirements, and achieves the expected effect of intelligent and efficient Q-field fusion.

[0035] In summary, the present invention is applicable to the intelligent and efficient fusion of the near-surface and mid-deep Q-fields, meeting the fast pace of 3D production and the requirements of fine exploration. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Schematic diagram of the process of a near-surface and mid-deep Q-field fusion method based on a mask body in Embodiment 1 of the present invention;

[0037] Figure 2 Generation result diagram of the near-surface Q-field F1 in step S1 of Embodiment 1 of the present invention;

[0038] Figure 3 Generation result diagram of the mid-deep Q-field F2 in step S1 of Embodiment 1 of the present invention;

[0039] Figure 4 Method flow chart of steps S2 to S5 in Embodiment 1 of the present invention;

[0040] Figure 5 Single-trace display diagram of the near-surface Q-field F1 in a certain seismic trace data in Embodiment 1 of the present invention;

[0041] Figure 6 In Embodiment 1 of the present invention Figure 5 Corresponding single-trace display diagram of the mid-deep Q-field F2 in the seismic trace data;

[0042] Figure 7 Single-trace display diagram of the data volume F3 in Embodiment 1 of the present invention and the data volume F3'' obtained by using the five-point moving average method;

[0043] Figure 8 Morphological schematic diagram of the near-surface Q-field mask body F obtained in step S4 of Embodiment 1 of the present invention 1 / 0 where: (a) is the single-trace schematic diagram of the mask body F 1 / 0 where: (b) is the schematic diagram of one section of the mask body F 1 / 0 where: (c) is the three-dimensional schematic diagram of the mask body F 1 / 0 Three-dimensional schematic diagram;

[0044] Figure 9 Morphological schematic diagram of the mid-deep Q-field mask body F obtained in step S4 of Embodiment 1 of the present invention 0 / 1 where: (a) is the single-trace schematic diagram of the mask body F 0 / 1 where: (b) is the schematic diagram of one section of the mask body F 0 / 1 where: (c) is the schematic diagram of one section of the mask body F 0 / 1 Three-dimensional schematic diagram;

[0045] Figure 10 Three-dimensional schematic diagram of the fused full-layer Q-field in Embodiment 1 of the present invention;

[0046] Figure 11This is the full-stack Q prestack time migration profile in Embodiment 1 of the present invention, where: (a) is the conventional prestack time migration profile (without applying the Q field fusion technology), (b) is the full-stack Q prestack time migration profile obtained by fusing the Q field using the manual picking method, and (c) is the full-stack Q prestack time migration profile obtained by applying the fusion method of the present invention;

[0047] Figure 12 This is the structural block diagram of a near-surface and mid-deep Q field fusion system based on a mask body in Embodiment 2 of the present invention. Specific Embodiments

[0048] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and do not constitute a limitation to the present invention. Embodiment 1

[0049] A near-surface and mid-deep Q field fusion method based on a mask body, as Figure 1 shown in the flow diagram of this method. Specifically, in this embodiment, taking the 3D seismic data processing in a certain block of a certain basin in the central region of China as an example, the area of this work area is about 300 km 2 , the surface type belongs to typical loess tableland mountains, and the near-surface height conditions are complex. The specific process of applying the fusion method of the present invention is as follows:

[0050] S1. Generate a near-surface Q field F1 and a mid-deep Q field F2 respectively according to the seismic data of the work area.

[0051] In this embodiment, the seismic data in the Geo-East seismic data processing system or other existing processing systems is used for data processing. Specifically, as Figure 2 shown, the Q-v relationship fitting of the obtained dual-well micro-logging data is carried out, and the near-surface velocity field is inverted in combination with the first arrival data of large guns, and finally the near-surface Q field F1 is fitted and formed; as Figure 3 shown, the mid-deep Q field F2 is interpolated using the VSP well information and horizon information to complete the data preparation work of the two Q fields. Of course, the generation methods of the near-surface Q field F1 and the mid-deep Q field F2 in this step can also be other methods in the prior art.

[0052] S2. Subtract the near-surface Q field F1 and the mid-deep Q field F2 with weights to form a data volume F3, and the data volume F3 contains the zero-value interface in the transition region between the near-surface Q field F1 and the mid-deep Q field F2.

[0053] The zero-value interface corresponds to the best fusion surface in the existing manual picking method. This interface can be regarded as a horizon data (X, Y, Depth / Time), where Depth is the data type in the depth domain and Time is the data type in the time domain. Depth or Time data can be selected according to needs. Most of the horizon scatter points are unique on the vertical single trace, and a small number of points are not unique. The non-unique positions are the main reasons for the slow speed and poor accuracy of manual picking.

[0054] As Figure 4 shown, it is the specific method flowchart of steps S2 to S5 in this embodiment. The above weighted subtraction formula is: F3 = F1 - αF2, where the value range of the weight coefficient α is 0.5 to 1.5. When the weight coefficient α takes the value of 1, the near-surface Q field F1 and the mid-deep Q field F2 are directly subtracted. In the subsequent fusion process and Q field migration application, the weight coefficient α can be adjusted through the migration result quality control data, so that the zero-value interface of the obtained F3 moves up or down within a certain range in the vertical direction, thereby performing a new round of Q field fusion until the Q field quality control meets the conditions.

[0055] As Figure 5 shown, it is the single-trace display diagram of the near-surface Q field F1 in a certain trace of seismic data in this embodiment. The jump points in the figure are abnormal points, which are abnormal values calculated from the first arrivals of large guns. Figure 6 As shown in Figure 5 is the single-trace display diagram of the mid-deep Q field F2 in a certain trace of seismic data corresponding to Figure 7 . Taking this single-trace data as an example, in this embodiment, α takes the value of 1, and through the processing of F3 = F1 - F2, a single-trace difference of the data volume F3 shown by the black dotted line in Figure 7 is obtained. In

[0056] S3. Process the data volume F3 to remove abnormal values to make the zero-value interface unique on the vertical single trace, and obtain the data volume F3”.

[0057] In this embodiment, the method for removing abnormal values is the moving average method, specifically the five-point moving average method. The calculation steps of the five-point moving average method are as follows:

[0058] S31. Mark the data of the layer where the zero-value interface in the data body F3 is located as (x, y, Depth / Time), where Depth is the data type in the depth domain and Time is the data type in the time domain; select either the depth-domain Depth data or the time-domain Time data according to the type of seismic data. In this embodiment, the Time data is taken as an example.

[0059] S32. Calculate the boundary values excluding the two ends of the data, and the processing formula is as follows:

[0060]

[0061] where A(x, y, z n ) represents the sample point value of the zero-value interface in the data body F3, and A”(x, y, z n ) represents the sample point value of the zero-value interface in the processed data body F3”; the data length of the sample point value is k, and in the formula, 3 ≤ n ≤ k - 2.

[0062] S33. Calculate the boundary values at the two ends of the data, and the processing formula is as follows:

[0063]

[0064] Thus, the unique data body F3” of the zero-value interface on the vertical single trace is obtained.

[0065] In Figure 7 , the gray dotted line is the display diagram of the data body F3” obtained by the five-point moving average method in this single trace in this embodiment. It can be seen that after removing the outliers, the values on the left side of the junction of the data body F3 in this single trace are all above the zero axis.

[0066] S4. Perform mask transformation on the data body F3” to obtain the mask bodies F 1 / 0 , F 0 / 1 , and the data boundaries where the 0 and 1 values in the mask bodies F 1 / 0 , F 0 / 1 are located are the ideal fusion surfaces.

[0067] Mask technology is a technology that selectively filters or modifies data through binary bit operations, logical operations, or specific rules. Its core idea is to extract certain parts of the target data through a “template”. The obtained mask body is an attribute mark of the data.

[0068] In this step, use the logical functions GE(>=) or LE(<=) (GE represents greater than or equal to, LE represents less than or equal to) to perform logical judgment on the data body F3”. For example, in Figure 4 , use the logical function GE to take the numbers greater than 0 as 1 and the numbers less than 0 as 0 to obtain the mask body F 1 / 0 ; in the mask body F0 / 1 In one of the acquisition methods, a logical function LOGICALNOT (logical negation) is used to judge the mask body F 1 / 0 , and then the mask body F 1 / 0 complementary to F 0 / 1 is obtained. In another acquisition method of the mask body F 0 / 1 , a logical function GE (>=) or LE (<=) is used to directly perform a logical judgment on the data body F3”. Numbers less than 0 are taken as 1, and numbers greater than 0 are taken as 0.

[0069] As Figure 8 shown, various schematic diagrams of the near-surface Q-field mask body F 1 / 0 are obtained after mask transformation. Figure 8 (a) is a single-trace schematic diagram of the mask body F 1 / 0 , where the value on the left side of the junction is 1 and the value on the right side of the junction is 0; Figure 8 (b) is a schematic diagram of one of the profiles of the mask body F 1 / 0 ; Figure 8 (c) is a three-dimensional schematic diagram of the mask body F 1 / 0 ; The single-trace data is superimposed to form the mask body shapes of Figure 8 (b) and Figure 8 (c).

[0070] As Figure 9 shown, various schematic diagrams of the mid-depth Q-field mask body F 0 / 1 are obtained after mask transformation. Figure 9 (a) is a single-trace schematic diagram of the mask body F 0 / 1 , where the value on the left side of the junction is 0 and the value on the right side of the junction is 1; Figure 9 (b) is a schematic diagram of one of the profiles of the mask body F 0 / 1 ; Figure 9 (c) is a three-dimensional schematic diagram of the mask body F 0 / 1 ; The single-trace data is superimposed to form the mask body shapes of Figure 9 (b) and Figure 9 (c). The mid-depth Q-field mask body F 0 / 1 is complementary to the near-surface Q-field mask body F 1 / 0 .

[0071] S5. Multiply the near-surface Q-field F1 and the mid-depth Q-field F2 by the mask bodies F 1 / 0 , F 0 / 1 respectively, and then add them together to complete the fusion of the two Q-fields.

[0072] Specifically, the calculation steps of this embodiment are as Figure 4 shown. Multiply the near-surface Q-field F1 by the mask body F 1 / 0 to obtain the data body F 上, multiply the mid - deep Q - field F2 by the mask body F 0 / 1 , to obtain the data body F 下 ; F 上 and F 下 only contain the corresponding parts and are complementary along the ideal fusion surface, and then add the data body F 上 to the data body F 下 . The above - mentioned calculation process adopts the calculation method of "volume multiplication and then addition". Finally, the three - dimensional schematic diagram of the fused full - layer Q - field as shown in Figure 10 is obtained, realizing the fusion of two Q - fields and completing the establishment of the full - layer Q - field.

[0073] In the 3D seismic data processing of a certain block in a certain basin of this embodiment, when directly using the high - speed top - surface fusion method in the Q - field fusion stage, the coupling in the transition area is poor and the accuracy is low. While using the traditional zero - difference surface fusion manual picking method takes a long time and there are manual picking errors. The average time for single - round fusion is 30 hours, and in actual operation, multiple rounds of fusion are often required, and the Q - field fusion process takes up to half a month, which cannot meet the requirements of industrial production. By applying the fusion method of the present invention, the average time for single - round is only 20 minutes. It not only greatly shortens the processing time, but also takes into account the accuracy of zero - difference surface fusion. At the same time, it avoids the errors of horizon picking that vary from person to person, which is beneficial to production and quality control requirements, achieving the expected effect of intelligent and efficient Q - field fusion.

[0074] In the subsequent migration application of the fused full - layer Q - field of this embodiment, the quality control of the Q - field fusion effect can be carried out from multiple dimensions by comparing the quality of the Q - time migration profile with the results of conventional time migration (without applying Q - field fusion technology) as a synchronous means.

[0075] During the quality control process, the weight coefficient α can be adjusted by using the migration result quality control data, so that the zero - value interface of the obtained F3 moves up or down within a certain range in the vertical direction, and thus a new round of Q - field fusion is carried out until the Q - field quality control meets the conditions. This method can be used multiple times and has high operation efficiency in this iterative process. Figure 11This is the full-stack Q prestack time migration profile in Embodiment 1 of the present invention. Among them: (a) is the conventional prestack time migration profile (without applying the Q-field fusion technology), and the migration profile effect at the arrow is poor; (b) is the full-stack Q prestack time migration profile obtained by fusing the Q-field using the manual picking method, and the migration profile effect at the arrow is good; (c) is the full-stack Q prestack time migration profile obtained by applying the fusion method of the present invention, and the migration profile effect at the arrow is good. It can be seen from this figure that the quality of the full-stack Q-field time migration profile fused by the method of the present invention can reach the quality of the migration profile using the manual picking method, but the processing time of this method is greatly shortened, which greatly improves the implementation effect of the full-stack Q-field application technology and meets the industrial production requirements. Embodiment 2

[0076] A near-surface and mid-deep Q-field fusion system based on a mask body, as Figure 12 shown, includes:

[0077] A Q-field data generation module for generating a near-surface Q-field F1 and a mid-deep Q-field F2;

[0078] A data volume F3 acquisition module for acquiring a zero-value interface including the transition region between the near-surface Q-field F1 and the mid-deep Q-field F2;

[0079] A data volume F3 processing module for removing the abnormal values of the zero-value interface on the vertical single trace to make the zero-value interface unique on the vertical single trace, obtaining the data volume F3'';

[0080] A data volume F3'' mask transformation module for obtaining the mask bodies F 1 / 0 、F 0 / 1 ,where the data boundaries of the 0 and 1 values in the mask bodies F 1 / 0 、F 0 / 1 are the ideal fusion surfaces;

[0081] A Q-field fusion module for fusing the two Q-fields on the ideal fusion surface, multiplying the points corresponding to the near-surface Q-field F1 and the mid-deep Q-field F2 by the mask bodies F 1 / 0 、F 0 / 1 respectively, obtaining the data volumes F 上 and the data volume F 下 that only contain the corresponding parts and are complementary along the ideal fusion surface; adding the data volume F 上 and the data volume F 下 to achieve the fusion of the two Q-fields and complete the establishment of the full-stack Q-field. Embodiment 3

[0082] A computer device includes a memory and a processor. The memory stores a computer program, and the processor calls the computer program in the memory to execute the computer program for implementing the method in Embodiment 1. Embodiment 4

[0083] This embodiment provides a computer-readable storage medium. A computer program is stored in the readable storage medium, and when the computer program is executed by a processor, it is used to implement the method in Embodiment 1.

[0084] Among them, the computer-readable storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the computer-readable storage medium is coupled to the processor, so that the processor can read information from the computer-readable storage medium and write information to the computer-readable storage medium. Of course, the computer-readable storage medium can also be a component of the processor. The processor and the computer-readable storage medium can be located in an application-specific integrated circuit (ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the computer-readable storage medium can also exist as discrete components in a communication device. Specifically, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc, etc. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present disclosure, and are not intended to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present disclosure.

Claims

1. A near-surface and mid-deep Q-field fusion method based on a mask body, characterized in that The method includes the following steps: S1. Generate a near-surface Q field F1 and a mid-deep Q field F2; S2. Weighted subtraction of the near-surface Q field F1 and the mid-deep Q field F2 to form a data volume F3 containing the zero-value interface; S3. Process the data body F3 to remove outliers, obtaining the data body F3 ” ; S4. Mask the data volume F3 ” to obtain the near-surface mask volume F 1 / 0 and the mid-deep mask volume F 0 / 1 respectively; S5. Dot multiply the near-surface Q field F1 and the mid-deep Q field F2 with the mask body F respectively 1 / 0 and F 0 / 1 and then add them together to complete the fusion of the two Q fields; The mask body F in S4 1 / 0 performs a logical judgment on the data body F3 using the logical functions GE (>=) or LE (<=) ” and takes the numbers greater than 0 as 1 and the numbers less than 0 as 0; the mask body F 0 / 1 performs a judgment on the mask body F using the logical function LOGICALNOT 1 / 0 to obtain a mask body F 1 / 0 complementary to F 0 / 1 , or the mask body F 0 / 1 performs a logical judgment on the data body F3 using the logical functions GE (>=) or LE (<=) ” and takes the numbers less than 0 as 1 and the numbers greater than 0 as 0.

2. The method for fusing near-surface and mid-deep Q fields based on a mask body according to claim 1, wherein The formula for weighted subtraction in S2 is: F3 = F1 - αF2, where the value range of the weight coefficient α is 0.5 to 1.

5.

3. A near-surface and mid-deep Q-field fusion method based on a mask body according to claim 1, characterized in that The method for removing outliers in S3 is the moving average method.

4. A method for fusing near-surface and mid-deep Q fields based on a mask body according to claim 3, characterized in that The moving average method uses a five-point moving average method, and the calculation steps of the five-point moving average method are as follows: S31. Mark the data of the layer where the zero-value interface in the data volume F3 is located as (x, y, Depth / Time), where Depth is the data type in the depth domain and Time is the data type in the time domain; S32. Calculate and remove the boundary values at both ends of the data, and the processing formula is as follows: Among them, A(x, y, z n ) represents the zero-value interface sample value in the data volume F3, and A ” (x, y, z n ) represents the zero-value interface sample value in the processed data volume F3 ” ; the data length of the sample value is k, where 3 ≤ n ≤ k - 2; S33. Calculate the boundary values at both ends of the data, and the processing formula is as follows: This yields the unique data body F3 of the zero-value interface on the vertical single trace ” .

5. A method for fusing near-surface and mid-deep Q fields based on a mask body according to claim 4, characterized in that The near-surface Q field F1 in S1 is obtained by inverting the near-surface velocity field using the first arrivals of large guns and fitting with the crosshole micro-logging data; the mid-deep Q field F2 is obtained by using the VSP well information and layer interpolation.

6. A near-surface and mid-deep Q-field fusion system based on a mask body, characterized in that, It includes: A Q field data generation module for generating a near-surface Q field F1 and a mid-deep Q field F2; A data volume F3 acquisition module for obtaining the zero-value interface including the transition region between the near-surface Q field F1 and the mid-deep Q field F2; The data volume F3 processing module is used to remove the outliers of the zero-value interface on the vertical single trace, making the zero-value interface unique on the vertical single trace, and obtaining the data volume F3 ” ; Data body F3 ” Mask transformation module, used to obtain the near-surface mask volume F 1 / 0 , medium-deep mask body F 0 / 1 , F 1 / 0 、F 0 / 1 The data boundary where the 0 and 1 values ​​in are located is the ideal fusion surface; the mask body F 1 / 0 It uses the logic function GE (>=) or LE (<=) to perform the operation on the data body F3. ” Perform logical judgment, take the number greater than 0 as 1, and take the number less than 0 as 0; the mask body F 0 / 1 The mask body F is processed by using the logical function LOGICALNOT 1 / 0 Make a judgment and get the same as F 1 / 0 Complementary mask body F 0 / 1 , or mask body F 0 / 1 It uses the logic function GE (>=) or LE (<=) to perform the operation on the data body F3. ” Perform logical judgment, set the number less than 0 to 1, and the number greater than 0 to 0; The Q-field fusion module is used to fuse two Q-fields on the ideal fusion surface, and the points corresponding to the near-surface Q-field F1 and the mid-deep Q-field F2 are respectively dot-multiplied by the near-surface mask body F 1 / 0 , the mid-deep mask body F 0 / 1 , to obtain a data body F 上 and data body F 下 that only contains the corresponding parts and is complementary along the ideal fusion surface; adding the data body F 上 to the data body F 下 realizes the fusion of the two Q-fields and completes the establishment of the full-layer Q-field.

7. A computer device, characterized in that, It includes a memory and a processor. The memory stores a computer program, and the processor calls the computer program in the memory to execute a method for fusing the near-surface and mid-deep Q fields based on a mask body according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, A computer program is stored in the computer-readable storage medium, and when the computer program is executed by the processor, it is used to implement a method for fusing the near-surface and mid-deep Q fields based on a mask body according to any one of claims 1 to 5.

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