Method for calculating distribution and influence strength of near-surface igneous rocks

Abstract

The invention provides a method for solving near-surface igneous rock distribution and influence intensity. The method comprises the following steps: S101, collecting original seismic data; s103, performing linear dynamic correction on the collected original seismic data to obtain data after dynamic correction; s105, carrying out superposition on the data after dynamic correction to obtain superposition imaging data; and S107, carrying out signal-to-noise ratio analysis on the superposition imaging data to obtain signal-to-noise ratio data capable of reflecting the distribution intensity and the influence range of the igneous rock. According to the method, superposition imaging is carried out for multiple times of refraction, correlation analysis is carried out on superposition imaging, the near-surface igneous rock distribution and the influence intensity thereof are effectively obtained, the prediction effect is good, the cost is low, and operation is convenient.

Description

Technical Field

[0001] The invention belongs to the field of petroleum exploration, and in particular, relates to a method for obtaining the distribution of near-surface igneous rocks and their influence strength. Background Art

[0002] Near-surface igneous rocks seriously affect the excitation effect in seismic acquisition. Clarifying the distribution range and influence intensity of igneous rocks in the seismic acquisition area can enable targeted measures to be taken during new acquisition to improve the acquisition effect. Currently, micro-well logging and static penetration are usually used for near-surface structural surveys. These technologies are not only costly, but also point surveys, and cannot fully reflect the igneous rock structure of the entire acquisition area. Summary of the invention

[0003] The embodiment of the present application provides a method for obtaining the distribution and influence intensity of near-surface igneous rocks, which effectively analyzes the distribution range and influence intensity of igneous rocks in the seismic acquisition area through near-surface refraction wave imaging technology.

[0004] The present application embodiment provides a method for obtaining the distribution and influence strength of near-surface igneous rocks, including:

[0005] S101, collecting raw seismic data;

[0006] S103, performing linear dynamic correction on the collected original seismic data to obtain data after dynamic correction;

[0007] S105, superimposing the data after dynamic calibration to obtain superimposed imaging data;

[0008] S107, performing signal-to-noise ratio analysis on the stacked imaging data to obtain signal-to-noise ratio data that can reflect the distribution intensity and impact range of the igneous rock.

[0009] In some embodiments, in step S101, raw seismic data is collected, and the raw seismic data seismic shot Calculate the linear propagation velocity v of multiple shallow refractions hcy ,

[0010] v hcy =Δx / Δt

[0011] Among them, Δx is the propagation distance and Δt is the propagation time.

[0012] In some embodiments, in step S103, the original seismic data is seismic shot Perform linear dynamic calibration to obtain the seismic data after dynamic calibration LMO , the linear dynamic correction formula is:

[0013]

[0014] Among them, t is the actual wave field travel time, t0 is the wave field travel time at zero deviation position, Δt LMO is the linear dynamic correction time difference, and x is the distance between the shot point and the receiver point.

[0015] In some embodiments, in step S105, the seismic LMO Superimpose and get seismic stack ;

[0016]

[0017] Among them, i represents the sampling point in the time direction, j represents the offset number, and k represents the common center point gather CMP.

[0018] In some embodiments, in step S107, the superimposed imaging data is seismic stack By performing signal-to-noise ratio analysis, we can finally obtain signal-to-noise ratio data that can reflect the distribution intensity and impact range of igneous rocks. The signal-to-noise ratio formula is as follows:

[0019]

[0020] Where S is the energy spectrum of the signal, N is the energy spectrum of the noise, and f is the frequency.

[0021] The method for obtaining the distribution of near-surface igneous rocks and their influence strength in the embodiment of the present application has the following beneficial effects:

[0022] This application is based on existing seismic data and uses near-surface refraction wave imaging technology to effectively analyze the distribution range and impact intensity of igneous rocks in the seismic acquisition area. It has good prediction effect, low cost and easy operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic diagram of a method for obtaining the distribution of near-surface igneous rocks and their influence on strength according to an embodiment of the present application;

[0024] Figure 2 Another schematic flow chart of the method for obtaining the distribution of near-surface igneous rocks and their influence on strength according to an embodiment of the present application;

[0025] Figure 3 A schematic diagram for obtaining linear velocity in this application;

[0026] Figure 4 This is a comparison diagram before and after the dynamic calibration of igneous rock velocity for a single shot in this application;

[0027] Figure 5 It is a multiple stacking imaging of refraction in the igneous rock development area in this application;

[0028] Figure 6 This is a diagram of the distribution and impact intensity of near-surface igneous rocks in this application. DETAILED DESCRIPTION

[0029] The present application is further described below in conjunction with the accompanying drawings and embodiments.

[0030] In the following introduction, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance. The following introduction provides multiple embodiments of the present invention, and different embodiments can be replaced or combined, so this application can also be considered to include all possible combinations of the same and / or different embodiments recorded. Therefore, if one embodiment includes features A, B, and C, and another embodiment includes features B and D, then this application should also be considered to include embodiments containing one or more of all other possible combinations of features A, B, C, and D, even though the embodiment may not be clearly recorded in the following text.

[0031] like Figure 1 As shown, the method for obtaining the distribution and influence intensity of near-surface igneous rocks in the present application includes: S101, collecting original seismic data; S103, performing linear dynamic correction on the collected original seismic data to obtain the data after dynamic correction; S105, superimposing the data after dynamic correction to obtain superimposed imaging data; S107, performing signal-to-noise ratio analysis on the superimposed imaging data to obtain signal-to-noise ratio data that can reflect the distribution intensity and influence range of igneous rocks. The purpose of the present application is to effectively analyze the distribution range and influence intensity of igneous rocks in the seismic acquisition area through near-surface refraction wave imaging technology based on existing seismic data. Each step is introduced below.

[0032] In areas where igneous rocks are developed near the surface, shallow refraction is usually more developed. The greater the impact of igneous rocks, the stronger the refraction. Therefore, stacking images of refraction and performing correlation analysis on the stacked images can effectively determine the distribution of igneous rocks near the surface and their impact intensity. Figure 1-2 As shown, the method for obtaining the distribution of near-surface igneous rocks and their influence strength in this application includes:

[0033] Step 1: Figure 3 As shown in the figure, the existing original seismic data is collected and the original seismic data is used to shot Calculate the linear propagation velocity v of multiple shallow refractions hcy , usually the speed of igneous rocks is around 3500-6000;

[0034] v hcy =Δx / Δt

[0035] Among them, Δx is the propagation distance and Δt is the propagation time.

[0036] Step 2: Use the linear propagation velocity v hcy The original seismic data shot Perform linear dynamic calibration to obtain the seismic data after dynamic calibration LMO , the linear dynamic correction formula is as follows:

[0037]

[0038] Among them, t is the actual wave field travel time, t0 is the wave field travel time at zero deviation position, Δt LMO is the linear dynamic correction time difference, and x is the distance between the shot point and the receiver point.

[0039] Step 3: Seismic calibration of the data LMO Superimpose and get seismic stack ;

[0040]

[0041] Among them, i represents the sampling point in the time direction, j represents the offset number, and k represents CMP.

[0042] Step 4: Seismic analysis of stacked imaging data stack A shallow signal-to-noise ratio analysis (200ms-800ms) was performed, and finally the signal-to-noise ratio data that can reflect the distribution intensity and impact range of igneous rocks were obtained. The signal-to-noise ratio formula is as follows:

[0043]

[0044] Among them, S is the energy spectrum of the signal, N is the energy spectrum of the noise, and f is the frequency.

[0045] Figure 4 The comparison of single shots before and after linear dynamic correction is shown. (a) is the original single shot, and (b) is the single shot after linear dynamic correction using the igneous rock velocity. It can be seen from the figure that the shallow refraction affected by the igneous rock has been flattened many times. Figure 5 The cross-section is displayed based on the superimposed imaging of the data after dynamic correction and flattening. From the cross-section, it can be seen that the distribution intensity and influence range of igneous rocks are different. Figure 6 It shows that the data of the entire work area were refracted and stacked multiple times to form images, and then the signal-to-noise ratio analysis of the stacked imaging data was performed to obtain the distribution and impact intensity information of near-surface igneous rocks. From the figure, it can be seen that the distribution and impact intensity information of near-surface igneous rocks is consistent with the actual impact range and intensity of igneous rocks.

[0046] The present application adopts a method of multiple refraction stacking imaging and a signal-to-noise ratio analysis to obtain the distribution and impact intensity of near-surface igneous rocks, which has a novel idea, good prediction effect, low cost and easy operation.

[0047] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for obtaining the distribution and influence strength of near-surface igneous rocks, characterized in that: include: S101, collecting raw seismic data; S103, performing linear dynamic correction on the collected original seismic data to obtain data after dynamic correction; S105, superimposing the data after dynamic calibration to obtain superimposed imaging data; S107, performing signal-to-noise ratio analysis on the stacked imaging data to obtain signal-to-noise ratio data that can reflect the distribution intensity and impact range of the igneous rock.

2. The method for obtaining the distribution and influence strength of near-surface igneous rocks according to claim 1, characterized in that: In step S101, the original seismic data is collected and the original seismic data is used to shot Calculate the linear propagation velocity v of multiple shallow refractions hcy , v hcy =Δx / Δt Among them, Δx is the propagation distance and Δt is the propagation time.

3. The method for obtaining the distribution and influence strength of near-surface igneous rocks according to claim 1 or 2, characterized in that: In step S103, the original seismic data is seismic shot Perform linear dynamic calibration to obtain the seismic data after dynamic calibration LMO , the linear dynamic correction formula is: Among them, t is the actual wave field travel time, t0 is the wave field travel time at zero deviation position, Δt LMO is the linear dynamic correction time difference, and x is the distance between the shot point and the receiver point.

4. The method for obtaining the distribution and influence strength of near-surface igneous rocks according to claim 1 or 2, characterized in that: In step S105, the seismic LMO Superimpose and get seismic stack ; Among them, i represents the sampling point in the time direction, j represents the offset number, and k represents the common center point gather CMP.

5. The method for obtaining the distribution and influence strength of near-surface igneous rocks according to claim 1 or 2, characterized in that: In step S107, the superimposed imaging data is seismic stack By performing signal-to-noise ratio analysis, we can finally obtain signal-to-noise ratio data that can reflect the distribution intensity and impact range of igneous rocks. The signal-to-noise ratio formula is as follows: Where S is the energy spectrum of the signal, N is the energy spectrum of the noise, and f is the frequency.

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