Method for accurately extracting seismic structural information

Abstract

The present application provides a kind of seismic structure information accurate extraction method, which comprises the following steps: step 1, according to poststack seismic record, generate time difference data dT and channel difference data dA;Step 2, calculate time difference square data dT2, channel difference square data dA2 and time-channel difference square data dTA;Step 3, calculate smooth time difference square data, smooth channel difference square data and smooth time-channel difference square data;Step 4, according to smooth time difference square data, smooth channel difference square data and smooth time-channel difference square data, construct hessian matrix;Step 5, the eigenvalue T1 of hessian matrix, T2 is solved;Step 6, according to eigenvalue, calculate apparent dip angle.The seismic structure information accurate extraction method can better avoid the influence of seismic noise, fault and seismic amplitude variation, obtain accurate and stable seismic dip angle data body, and extract accurate seismic dip angle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil reservoir geophysics, and particularly to a method for accurately extracting seismic structural information. BACKGROUND

[0002] The seismic dip reflects the inclination degree of the seismic reflection surface along a certain direction. The dip in the direction is the true dip, and the component of the true dip in other directions is the apparent dip along the direction. In a seismic work area, the apparent dips along the inline and crossline directions are usually considered. However, the calculated stratum dip is often not stable due to the influence of seismic noise, faults and seismic amplitude variation in the conventional algorithm of seismic data, and singular points often appear in the data. It is relatively difficult to remove the influence of the dip data in the later use process.

[0003] In the Chinese patent application with the application number CN201710740537.5, a method and device for determining stratum dip are involved. The method includes: calculating the total energy of the to-be-measured seismic data in each of a plurality of preset directions; determining the maximum value of the plurality of total energies and the direction corresponding to the maximum value; and calculating the stratum dip of the direction corresponding to the maximum value, and taking the determined stratum dip as the corresponding stratum dip of the to-be-measured seismic data. In the embodiment of the application, the local dip calculation result with high accuracy is ensured while the calculation efficiency is ensured, thereby improving the performance of the seismic data processing, interpretation and inversion method characterized by data-driven.

[0004] In the Chinese patent application with the application number CN202110074333.9, a method and device for automatically extracting stratum dip information from seismic data are involved. The method includes: acquiring seismic data; performing seismic horizon tracking on the seismic data to generate a seismic stratum body; performing dip moveout analysis on each seismic trace in the seismic data according to the seismic stratum body to generate a dip moveout sequence corresponding to each seismic trace; performing filtering processing on the dip moveout sequence corresponding to each seismic trace according to a pre-set effective range of stratum dip moveout to obtain a filtered dip moveout sequence of each seismic trace; performing interpolation processing on the filtered dip moveout sequence of each seismic trace by taking the start sampling point and the end sampling point of each seismic trace as an interpolation range to obtain an equal-interval dip moveout sequence of each seismic trace; and generating a stratum dip body according to the equal-interval dip moveout sequences of the seismic traces. The application can improve the stability, reliability and controllability of extracting stratum dip information from seismic data.

[0005] In the Chinese patent application with the application number CN201310272811.2, a high-precision stratigraphic dip angle estimation method is disclosed. Firstly, a gradient vector is calculated, and then the vector field is flipped. After the vector field is flipped, the vector set distance is calculated, the vector filtering weight is calculated, and finally the vector weighted filtering processing is performed. This method can maintain the spatial consistency of the stratigraphic dip angle estimation in the single direction extension area of the event, improve the stratigraphic dip angle estimation accuracy of the stratigraphic structure at the fault, angular unconformity and fold shape, and the algorithm content of the technical solution is easy to implement and has high calculation efficiency. Meanwhile, the analysis window size can be flexibly adjusted to meet the needs of different dip angle estimation effects. For seismic data with serious noise interference, a large analysis window can be used to improve the spatial consistency of the dip angle estimation result, and for seismic data with high signal-to-noise ratio, a small analysis window can be used to improve the accuracy of the dip angle estimation result in the fault and angular unconformity area.

[0006] In the Chinese patent application with the application number CN202010861920.8, a seismic identification method for low-order faults under high stratigraphic dip angle conditions is disclosed. The method includes the following steps: performing frequency diffusion filtering processing on the post-stack seismic data; calculating the gradient feature attributes of the processed seismic data to obtain the horizontal, vertical and diagonal gradient data of the seismic data; calculating the dip angle attributes of the seismic data to obtain the dip angle data of the seismic data; determining whether the stratum is inclined and the inclination direction by using the dip angle data, and then replacing the gradient according to different conditions; dividing the seismic image into stable events and non-stable events, and performing gradient correction on the gradient data after gradient replacement according to different conditions to construct the structure tensor of the seismic data; calculating the edge detection factor to identify the low-order faults under high stratigraphic dip angle conditions. The method effectively realizes the seismic identification of low-order faults under high stratigraphic dip angle conditions.

[0007] The above prior art has great differences from the present application and cannot solve the technical problems we want to solve. Therefore, we have invented a new seismic structure information accurate extraction method. SUMMARY

[0008] The purpose of the present application is to provide a seismic structure information accurate extraction method that removes the influence of these data in the dip angle calculation stage to improve the stability of the stratigraphic dip angle.

[0009] The purpose of the present application can be achieved by the following technical measures: a seismic structure information accurate extraction method, which comprises:

[0010] Step 1: generating time difference data dT and trace difference data dA according to post-stack seismic records;

[0011] Step 2, calculating time difference square data dT2, trace difference square data dA2 and time-trace difference square data dTA;

[0012] Step 3, calculating smooth time difference square data smooth trace difference square data and smooth time-trace difference square data

[0013] Step 4, calculating apparent dip angle according to smooth time difference square data smooth trace difference square data smooth time-trace difference square data constructing a Hessian matrix;

[0014] Step 5, calculating eigenvalues T1, T2 of the Hessian matrix;

[0015] Step 6, calculating apparent dip angle according to the eigenvalues.

[0016] The object of the present application can also be achieved by the following technical measures:

[0017] In step 1, the post-stack seismic record refers to actual observed post-stack seismic record or synthetic record established according to a geological model.

[0018] In step 1, according to the post-stack seismic record, the difference between time points of each trace is calculated to generate time difference dT=F(T i+1 ,A j )-F(T i ,A j ). Wherein, F represents the amplitude value of seismic post-stack data, T i represents the time of i point, T i+1 represents the time of i+1 point, A j represents the jth trace seismic data; F(T i ,A j ) represents the amplitude value of the jth trace seismic data, i point of time, F(T i+1 ,A j ) represents the amplitude value of the jth trace seismic data, i+1 point of time.

[0019] In step 1, according to the post-stack seismic record, the difference between time points of each trace is calculated to generate time difference dT=F(T i ,A j+1 )-F(T i ,A j ). Wherein, F represents the amplitude value of seismic post-stack data, T i represents the time of i point, A j represents the jth trace seismic data, A j+1 represents the j+1th trace seismic data; F(T i ,A j) represents the amplitude value of the jth seismic data, the i point of time, F(T i ,A j+1 ) represents the amplitude value of the j+1th seismic data, the i point of time.

[0020] In step 2, the time difference data dT is multiplied to generate time difference square data dT2=dT*dT.

[0021] In step 2, the trace difference data dA is multiplied to generate trace difference square data dA2=dA*dA.

[0022] In step 2, the time difference data dT is multiplied by the trace difference data dA to generate time-trace difference square data dTA=dT*dA.

[0023] In step 3, the time difference square data dT2 is filtered by Gaussian filtering to generate smoothed time difference square data

[0024] In step 3, the trace difference square data dA2 is filtered by Gaussian filtering to generate smoothed trace difference square data

[0025] In step 3, the time-trace difference square data is filtered by Gaussian filtering to generate smoothed time-trace difference square data

[0026] In step 4, the smoothed time difference square data Smoothed trace difference square data Smoothed time-trace difference square data The Hessian matrix is constructed:

[0027]

[0028] In step 5, the eigenvalues T1, T2 of the Hessian matrix are calculated by using the Jacobi iteration algorithm, and T1, T2 are sorted so that T1>T2.

[0029] In step 6, the apparent dip angle D=T2 / T1 is calculated according to the eigenvalues.

[0030] The seismic structure information accurate extraction method in the application meets the requirement of stable calculation of the stratum dip angle, and is mainly used for analyzing the stratum dip angle of the geological horizon and understanding the tendency of the stratum. The method mainly calculates the eigenvalue of the Hessian matrix by improving the Hessian matrix construction method, so as to obtain the stratum dip angle data of the stratum. The method can well avoid the influence of the seismic noise, the fault and the seismic amplitude change, obtain the accurate and stable seismic dip angle data, and accurately extract the seismic dip angle. BRIEF DESCRIPTION OF DRAWINGS

[0031] Figure 1A post-stack seismic record diagram actually observed in a specific embodiment of the present application;

[0032] Figure 2 A stratum dip angle diagram calculated in a specific embodiment of the present application;

[0033] Figure 3 A flow chart of a specific embodiment of the seismic structure information accurate extraction method of the present application. DETAILED DESCRIPTION

[0034] It should be noted that the following detailed description is exemplary in nature and is intended to provide further description of the present application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0035] It is to be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of stated features, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and / or groups thereof.

[0036] As shown in Figure 3 , Figure 3 A flow chart of the seismic structure information accurate extraction method of the present application. The seismic structure information accurate extraction method comprises:

[0037] Step 101, generating time difference and trace difference data according to post-stack seismic record;

[0038] Step 102, calculating time difference square data, trace difference square data and time-trace difference square data;

[0039] Step 103, calculating smoothed time difference square data, smoothed trace difference square data and smoothed time-trace difference square data;

[0040] Step 104, constructing Hessian matrix according to smoothed time difference square data, smoothed trace difference square data and smoothed time-trace difference square data;

[0041] Step 105, calculating eigenvalues T1 and T2 of Hessian matrix;

[0042] Step 106, calculating apparent dip angle according to eigenvalues.

[0043] The present application is a method for accurately extracting seismic dip angle by improving Hessian matrix construction algorithm, which can avoid the influence of seismic noise, fault and seismic amplitude variation, and obtain accurate and stable seismic dip angle data body.

[0044] The following are several specific embodiments of the present application

[0045] Embodiment 1

[0046] In a specific embodiment 1 of the present application, the seismic structure information accurate extraction method comprises the following steps:

[0047] 1) Calculate the difference between time points of each trace of post-stack seismic record, generate time difference dT=F(T i+1 ,A j )-F(T i ,A j ); the observed post-stack seismic record refers to the actual observed post-stack seismic record or the synthetic record established according to the geological model, as shown in Figure 1 ;

[0048] 2) Calculate the difference between amplitudes of each time point of each trace of post-stack seismic record, generate trace difference data dA=F(T i ,A j+1 )-F(T i ,A j ); the observed post-stack seismic record refers to the actual observed post-stack seismic record or the synthetic record established according to the geological model, as shown in Figure 1 ;

[0049] 3) Multiply the time difference data dT, generate time difference square data dT2=dT*dT;

[0050] 4) Multiply the trace difference data dA, generate trace difference square data dA2=dA*dA;

[0051] 5) Multiply the time difference data dT and the trace difference data dA, generate time-trace difference square data dTA=dT*dA;

[0052] 6) Filter the time difference square data dT2 by using Gaussian filter (5x5), generate smoothed time difference square data

[0053] 7) Filter the trace difference square data dA2 by using Gaussian filter (5x5), generate smoothed trace difference square data

[0054] 8) Filter the time-trace difference square data by using Gaussian filter (5x5), generate smoothed time-trace difference square data

[0055] 9) According to the smoothed time difference square data the smoothed trace difference square data the smoothed time-trace difference square data , construct the Hessian matrix:

[0056]

[0057] 10) Using Jacobi iterative algorithm, eigenvalues T1, T2 of Hessian matrix are calculated, and T1, T2 are sorted so that T1>T2;

[0058] 11) According to the eigenvalues, the apparent dip angle D=T2 / T1 is calculated. The stratum dip angle represented by the seismic event is shown as follows. Figure 2

[0059] Embodiment 2

[0060] In the specific embodiment 2 of the present application, the seismic structure information accurate extraction method comprises the following steps:

[0061] 1) The time difference dT=F(T i+1 ,A j )-F(T i ,A j ) between each trace time point of the post-stack seismic record is calculated to generate the time difference data dT; the observed post-stack seismic record refers to the actual observed post-stack seismic record or the synthetic record established according to the geological model, as shown in Figure 1

[0062] 2) The amplitude difference dA=F(T i ,A j+1 )-F(T i ,A j ) between each trace time point of each line of the post-stack seismic record is calculated to generate the trace difference data dA; the observed post-stack seismic record refers to the actual observed post-stack seismic record or the synthetic record established according to the geological model, as shown in Figure 1

[0063] 3) The time difference data dT is multiplied to generate the time difference square data dT2=dT*dT;

[0064] 4) The trace difference data dA is multiplied to generate the trace difference square data dA2=dA*dA;

[0065] 5) The time difference data dT is multiplied by the trace difference data dA to generate the time-trace difference square data dTA=dT*dA;

[0066] 6) The time difference square data dT2 is filtered by using Gaussian filter (7x7) to generate the smoothed time difference square data

[0067] 7) The trace difference square data dA2 is filtered by using Gaussian filter (7x7) to generate the smoothed trace difference square data

[0068] 8) The time-trace difference square data dTA is filtered by using Gaussian filter (7x7) to generate the smoothed time-trace difference square data ​​​

[0069] 9) According to the smooth time difference data Smooth trace difference data Smooth time trace difference data Constructing the Hessian matrix:

[0070]

[0071] 10) Using the Jacobi iterative algorithm, the eigenvalues T1, T2 of the Hessian matrix are solved, and T1, T2 are sorted so that T1>T2;

[0072] 11) According to the eigenvalues, the apparent dip angle D=T2 / T1 of the stratum represented by the seismic event is calculated.

[0073] Embodiment 3

[0074] In the specific embodiment 3 of the application, the seismic structure information accurate extraction method comprises the following steps:

[0075] 1) Calculate the difference between time points of each trace of the post-stack seismic record to generate time difference data dT=F(T i+1 ,A j )-F(T i ,A j ); the observed post-stack seismic record refers to the actual observed post-stack seismic record or the synthetic record established according to the geological model, as shown in Figure 1 ;

[0076] 2) Calculate the difference between amplitudes of each time point of each trace of each line of the post-stack seismic record to generate trace difference data dA=F(T i ,A j+1 )-F(T i ,A j ); the observed post-stack seismic record refers to the actual observed post-stack seismic record or the synthetic record established according to the geological model, as shown in Figure 1 ;

[0077] 3) Multiply the time difference data dT to generate time difference square data dT2=dT*dT;

[0078] 4) Multiply the trace difference data dA to generate trace difference square data dA2=dA*dA;

[0079] 5) Multiply the time difference data dT by the trace difference data dA to generate time trace difference square data dTA=dT*dA;

[0080] 6) Filter the time difference square data dT2 using Gaussian filter (3x3) to generate smooth time difference square data

[0081] 7) Filter the trace difference square data dA2 with Gaussian filter (3x3) to generate smooth trace difference square data

[0082] 8) Filter the time difference square data with Gaussian filter (3x3) to generate smooth time difference square data

[0083] 9) Calculate the apparent dip angle D = T2 / T1 according to the smooth time difference square data Smooth trace difference square data Smooth time difference square data Construct the Hessian matrix:

[0084]

[0085] 10) Calculate the eigenvalues T1, T2 of the Hessian matrix with Jacobi iterative algorithm, and sort T1, T2 so that T1 > T2;

[0086] 11) Calculate the apparent dip angle D = T2 / T1 according to the eigenvalues, which represents the dip angle of the stratum represented by the seismic event.

[0087] Finally, it should be noted that the above only for the preferred embodiments of the present application, and is not intended to limit the present application, although the foregoing detailed description of the present application has been made with reference to the foregoing embodiments, for those skilled in the art, it still can be modified, or part of the technical features of the equivalent replacement. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application, should be included within the scope of the present application.

[0088] In addition to the technical features described in the specification, are known to those skilled in the art.

Claims

1. A method for accurately extracting seismic structure information, characterized by, The method for accurately extracting the seismic structural information comprises the following steps: Step 1: generating time difference data dT and trace difference data dA according to the post-stack seismic record; Step 2: calculating time difference square data dT2, trace difference square data dA2 and time-trace difference square data dTA; Step 3, compute smoothed time difference data Smoothed trace difference data And smoothed time trace difference data Step 4, smooth time difference data Smoothed trace difference data Smoothed time trace difference data Constructing the Hessian matrix Step 5: calculating eigenvalues T1 and T2 of the Hessian matrix; Step 6: calculating apparent dip angle D according to the eigenvalues; In step 1, according to the post-stack seismic record, the amplitude difference between time points of each trace is calculated to generate time difference data dT=F(T i+1 ,A j )-F(T i ,A j ); wherein, F represents the amplitude value of the post-stack seismic data, T i represents the time of the i point, T i+1 represents the time of the i+1 point, A j represents the jth seismic data; F(T i ,A j ) represents the amplitude value of the jth seismic data at the i point, F(T i+1 ,A j ) represents the amplitude value of the jth seismic data at the i+1 point; In step 1, according to the post-stack seismic record, the difference of the amplitude of each time point between each trace of each line is calculated to generate the trace difference data dA=F(T i ,A j+1 )-F(T i ,A j ); wherein, F represents the amplitude value of the seismic post-stack data, T i represents the time of the i point, A j represents the j trace seismic data, A j+1 represents the j+1 trace seismic data; F(T i ,A j ) represents the amplitude value of the j trace seismic data at the i point, and F(T i ,A j+1 ) represents the amplitude value of the j+1 trace seismic data at the i point. In step 2, the time difference data dT is multiplied to generate the time difference square data dT2=dT*dT; In step 2, the trace difference data dA is multiplied to generate the trace difference square data dA2=dA*dA; In step 2, the time difference data dT is multiplied by the trace difference data dA to generate the time-trace difference square data dTA=dT*dA; At step 4, the smoothed time difference data is used to construct the matrix H Smoothed trace difference data Smoothed time trace difference data Constructing the Hessian matrix H:

2. The method of claim 1, wherein, In step 1, the post-stack seismic record refers to the actually observed post-stack seismic record or the synthetic record established according to the geological model.

3. The method of claim 1, wherein, In step 3, the smoothed time difference squared data dT2 is generated by filtering the time difference squared data dT2 with a Gaussian filter 4. The method of claim 1, wherein, At step 3, the smoothed cross-dip data dA2 is generated by filtering the cross-dip data dA2 with a Gaussian filter 5. The method of claim 1, wherein, In step 3, the time channel difference square data is filtered by using Gaussian filter to generate smooth time channel difference square data 6. The method of claim 1, wherein, In step 5, the eigenvalues T1 and T2 of the Hessian matrix are calculated by using the Jacobi iteration algorithm, and T1 and T2 are sorted so that T1>T2.

7. The method of claim 6, wherein, In step 6, the apparent dip angle D is calculated according to the eigenvalues, i.e. D=T2 / T1.

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