CN111505719B - Diffracted multiple suppression method based on wave field decomposition - Google Patents

Diffracted multiple suppression method based on wave field decomposition Download PDF

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CN111505719B
CN111505719B CN202010459278.0A CN202010459278A CN111505719B CN 111505719 B CN111505719 B CN 111505719B CN 202010459278 A CN202010459278 A CN 202010459278A CN 111505719 B CN111505719 B CN 111505719B
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谢玉洪
李�列
欧阳敏
张迎朝
袁全社
李林
盖永浩
王大为
杨文博
邓聪
吴涛
邱宇
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    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
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Abstract

The invention relates to a diffracted multiples suppression method based on wave field decomposition, which rearranges seismic data into a common shot gather form and carries out linear radon transform, re-extracts and arranges a data matrix according to p sections to obtain plane wave data incident at different angles, separates a reflected wave field and a diffracted wave field in each extracted section by using an fx-EMD algorithm according to the difference of reflection and diffraction homophase axis forms when plane waves are incident, rearranges the extracted sections into the common shot gather form and carries out anti-radon transform to obtain separated diffracted wave field data and reflected wave field data, and subtracts the separated data in a graded multiples prediction mode to obtain seismic data irrelevant to multiples. The method does not need to require the types of the multiples in the original data, can effectively distinguish the multiples of different types, greatly improves the graded multiple prediction result, improves the robustness of the multiple pressing result, and reduces the complexity of a prediction model and the difficulty of subtracting the subsequent multiples.

Description

Diffracted multiple suppression method based on wave field decomposition
Technical Field
The invention belongs to the technical field of geophysical signal processing, particularly relates to a multiple suppression method, and particularly relates to a diffraction multiple suppression method based on wave field decomposition.
Background
In recent years, marine oil and gas exploration is rapidly developed, seismic exploration is the main method of marine oil and gas exploration, and the multiple wave problem is always the first big problem of marine seismic exploration. The multiples in the seismic data are regular interference waves, and when the multiples and the effective waves occur at the same travel position, especially in deep water data, the multiples with strong energy even cover the effective waves in deep layers and interfere with the effective waves. The intersecting of the same phase axes seriously affects the quality of the seismic section, so that the deep structure is difficult to identify, and subsequent processing, such as velocity picking and migration interpretation, is difficult to perform. Therefore, the research on the multiple suppression technology has important significance in improving the resolution of seismic data.
One standard method of removing multiples currently used in the industry is the data-driven surface multiple attenuation technique (SRME) proposed by Verschuur et al (1992) and Berkhout and Verschuur (1997), which divides the suppression of multiples into two steps, prediction and subtraction. SRME is more efficient than those simple conventional filtering-like multiple suppression methods when there is a complex topography, a large number of surface multiples develop, and the primary and multiples have little or no differentiation in velocity. However, the diffraction waves develop sufficiently under rugged sea floor conditions so that the multiple waves formed by diffraction develop sufficiently. This results in the first place that conventional prediction methods cannot accurately predict a multiple model suitable for a complex seafloor. Second, the subtraction process is very complicated due to the fact that these diffracted multiples are interleaved with the ordinary reflected multiples.
Disclosure of Invention
The invention aims to provide a diffracted multiple wave pressing method based on wave field decomposition, which overcomes the defects that a multiple wave model cannot be accurately predicted and the subtracting process is abnormal and complicated in the multiple wave pressing process by improving the conventional SRME method.
The purpose of the invention is realized by the following technical scheme:
a method for suppressing diffracted multiples based on wave field decomposition comprises the following steps:
a. arranging original seismic data into a data matrix of common shot record;
b. performing linear radon transform on each common shot point record;
c. rearranging by taking the reflection coefficient as a standard to obtain plane wave data (common p section) incident at different angles, wherein in the common p section, the reflected wave is approximately linearly continuous, and the diffracted wave is approximately in a hyperbolic shape;
d. according to the time window with proper size, mapping the seismic data of the extracted section to an f-x domain (frequency domain) through Fast Fourier Transform (FFT) to obtain a real part and an imaginary part of a signal of the f-x domain;
e. for each frequency slice;
e1, performing EMD on the real part data, extracting proper IMF components, generally the first two IMF components, reconstructing the IMF components as a diffraction wave field real part, and using the rest as a reflection wave field real part, wherein the EMD is frequency domain empirical mode decomposition, and the IMF components can be obtained by calculating the difference between the signals and the upper and lower envelope averages formed by the cubic spline connecting line of the local maximum value point and the cubic spline connecting line of the local minimum value point;
e2, performing EMD on the imaginary part data, extracting appropriate IMF components, generally the first two IMF components, reconstructing the IMF components as the imaginary part of the diffraction wave field, and using the residual part as the imaginary part of the reflection wave field;
e3, reconstructing the decomposed real part data and imaginary part data into complex data;
f. generating two groups of data of a diffraction wave field and a reflection wave field by performing inverse Fourier transform (IFFT) on the reconstructed data to a t-x domain (time domain);
g. sliding the time window, and repeating the operations on the next time window until all data are finished;
h. rearranging the decomposed reflected and diffracted wave fields of the common p-section into plane wave data;
i. making reverse drawing winter transformationAlternatively, the plane wave data is transformed into a reflected wave field P in the form of a common shot gatherrAnd diffracted wave field data Ps；
j. The decomposed reflected wave field PrAnd diffracted wave field data PsCarrying out hierarchical multiple prediction to obtain a prediction model;
Figure BDA0002510375030000021
expanding reflection mode multiples, diffraction mode multiples and mixed mode multiples models;
Figure BDA0002510375030000031
(reflection mode multiple)
Figure BDA0002510375030000032
(diffraction mode multiples)
Figure BDA0002510375030000033
(reflection-diffraction mixed multiples)
Figure BDA0002510375030000034
(diffraction-reflection mixed multiples)
k. And comparing the curvatures of the diffracted multiples and the four multiple prediction models, and selecting the model with the highest similarity for prediction and subtraction.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, a diffracted multiple decomposition technology is introduced into a multiple pressing process, aiming at the problem that reflection and diffracted multiple aliasing caused by diffracted wave development in marine seismic exploration cause difficulty in prediction, different expression forms of reflected waves and diffracted waves are obtained through radon transformation and extraction of a common p section, two groups of data of a diffracted wave field and a reflected wave field are accurately calculated through fx-EMD decomposition and anti-radon transformation, then, a graded multiple prediction is carried out to obtain an accurate model, a proper prediction model is selected for prediction and subtraction by taking the similarity of wave field curvatures as a standard, and the robustness of marine seismic data multiple pressing is improved.
The invention has the following advantages:
1. the method for suppressing the diffracted multiples based on wave field decomposition does not need to require the types of the multiples in the original data;
2. the method solves the problem that the seismic model is difficult to predict due to the existence of diffracted multiples in the multiple pressing process, can effectively distinguish different types of multiples, can predict graded multiples, greatly improves the model prediction result compared with the conventional method, and improves the robustness of the multiple pressing result;
3. the method reduces the complexity of a prediction model and the difficulty of subsequent multiple subtraction by a hierarchical prediction method.
Drawings
FIG. 1 is a schematic drawing of a common p-section;
FIG. 2 is a flow chart of the EMD algorithm;
FIG. 3 practical data example; FIG. 3a wavefield decomposition results, FIG. 3b hierarchical multiple prediction results based on wavefield decomposition, FIG. 3c conventional SRME suppress multiples results compared to hierarchical multiple prediction suppress results.
FIG. 4 is a flow chart of a method for wavefield decomposition based diffraction multiple suppression according to the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and examples.
As shown in fig. 1, firstly, original seismic data are rearranged into a common shot gather form and subjected to linear radon transform, and linear radon domain data are rearranged with a reflection coefficient as a criterion to obtain plane wave data (common p sections) with different angles of incidence, a fx-EMD algorithm is used according to the difference of reflection and diffraction homophase axis forms when plane waves are incident to decompose a reflection wave field and a diffraction wave field in each common p section, then the decomposed data are rearranged into a common shot gather form and subjected to inverse linear radon transform, so that diffraction and reflection wave field data can be respectively obtained, and finally, the seismic data irrelevant to multiples can be obtained only by performing multiple suppression in a hierarchical multiple prediction mode.
The method comprises the following steps of obtaining a component to be solved by calculating the difference between an upper envelope average value and a lower envelope average value formed by a signal, a cubic spline connecting line of a local maximum value point and a local minimum value point connecting line according to the difference of reflection and diffraction homophase axis forms when plane waves are incident by using an fx-EMD algorithm, namely frequency domain empirical mode decomposition, and judging whether the component meets the following requirements: when the envelope mean value is 0, the difference between the extreme point and the zero-crossing point is less than or equal to one; if the component is not satisfied, the average value of the upper and lower envelopes in the process is repeatedly subtracted with the component as new signal data until the condition is satisfied. And finally, determining a first value meeting the condition as the first component, then, making a difference between the selected signal and the component, taking the obtained data as original data, repeating the above steps to obtain a second component, wherein the obtained component is the IMF component.
Specifically, the diffraction multiple suppression method based on wave field decomposition comprises the following steps:
a. arranging original seismic data into a data matrix of common shot record;
b. performing linear radon transform on each common shot point record;
c. rearranging the plane wave data (common p section) by taking the reflection coefficient as a standard to obtain plane wave data (common p section) incident at different angles, wherein in the common p section, the reflected wave is approximately linearly continuous, and the diffracted wave is approximately in a hyperbolic shape;
d. according to the time window with proper size, mapping the seismic data of the extracted section to an f-x domain through Fast Fourier Transform (FFT), and obtaining a real part and an imaginary part of a signal of the f-x domain;
e. for each frequency slice, as shown in fig. 2;
e1, performing EMD on the real part data, extracting proper IMF components, generally the first two IMF components, reconstructing the IMF components as a diffraction wave field real part, and using the rest as a reflection wave field real part, wherein the EMD is frequency domain empirical mode decomposition, and the IMF components can be obtained by calculating the difference between the signals and the upper and lower envelope averages formed by the cubic spline connecting line of the local maximum value point and the cubic spline connecting line of the local minimum value point;
e2, performing EMD on the imaginary part data, extracting appropriate IMF components, generally the first two IMF components, reconstructing to be used as a diffraction wave field imaginary part, and using the rest part as a reflection wave field imaginary part;
e3, reconstructing the decomposed real part data and imaginary part data into complex data;
f. mapping the reconstructed data to a t-x domain through inverse Fourier transform (IFFT) to generate two groups of data of a diffraction wave field and a reflection wave field;
g. sliding the time window, and repeating the operations on the next time window until all data are finished;
h. rearranging the decomposed reflected wave field and diffracted wave field of the common p-section into plane wave data;
i. making inverse radon transform to change the plane wave data into the reflected wave field P in the form of common shot gatherrAnd diffracted wave field data Ps；
j. The decomposed reflected wave field PrAnd diffracted wave field data PsCarrying out hierarchical multiple prediction to obtain a prediction model;
Figure BDA0002510375030000051
unfolding we will obtain four causal prediction models: reflection mode multiples, diffraction mode multiples, mixed mode multiples (reflection-diffraction, diffraction-reflection)
Figure BDA0002510375030000052
(reflection mode multiple)
Figure BDA0002510375030000053
(winding around)Radio mode multiple wave)
Figure BDA0002510375030000054
(reflection-diffraction mixed multiples)
Figure BDA0002510375030000055
(diffraction-reflection mixing multiples)
k. The curvatures of the diffracted multiples and the wave fields of the four multiple prediction models are compared, and the model with the highest similarity is selected for prediction and subtraction, so that the purpose of removing the interference of the diffracted multiples is achieved.
Examples
a. The original seismic data is measured data of a certain area, wherein the measured data comprises 600 cannon data, 480 cannons, 2000 sampling points and 2ms sampling interval; arranging original seismic data into a data matrix of common shot record;
b. performing linear radon transform on each common shot point data record;
c. rearranging the plane wave data (common p section) by taking the reflection coefficient as a standard to obtain plane wave data (common p section) incident at different angles, wherein in the common p section, the reflected wave is approximately linearly continuous, and the diffracted wave is approximately in a hyperbolic shape;
d. selecting a time window of suitable size, the size of the time window being related to the data dimension, typically 10% -50% of the data dimension, 500 x 50 in this example; mapping the seismic data of the extracted section to an f-x domain through Fast Fourier Transform (FFT), and obtaining a real part and an imaginary part of a signal of the f-x domain;
e. for each frequency slice;
e1, performing EMD on the real part data, extracting proper IMF components, generally the first two IMF components, reconstructing the IMF components as a diffraction wave field real part, and using the rest as a reflection wave field real part, wherein the EMD is frequency domain empirical mode decomposition, and the IMF components can be obtained by calculating the difference between the signals and the upper and lower envelope averages formed by the cubic spline connecting line of the local maximum value point and the cubic spline connecting line of the local minimum value point;
e2, performing EMD on the imaginary part data, extracting appropriate IMF components, generally the first two IMF components, reconstructing to be used as a diffraction wave field imaginary part, and using the rest part as a reflection wave field imaginary part;
e3, reconstructing the decomposed real part data and imaginary part data into complex data;
f. mapping the reconstructed data to a t-x domain through inverse Fourier transform (IFFT) to generate two groups of data of a diffraction wave field and a reflection wave field;
g. sliding the time window, and repeating the operations on the next time window until all data are finished;
h. rearranging the decomposed reflected and diffracted wave fields of the common p-section into plane wave data, as shown in FIG. 3a, wherein the left side is the reflected wave field and the right side is the diffracted wave field;
i. making inverse radon transform to change the plane wave data into the reflected wave field P in the form of common shot gatherrAnd diffracted wave field data Ps；
j. The decomposed reflected wave field PrAnd diffracted wave field data PsPerforming a fractional multiple prediction to obtain a prediction model, as shown in fig. 3b, where left 1 is a reflection mode multiple, left 2 is a diffraction mode multiple, right 2 is a mixed mode multiple (reflection-diffraction), and right 1 is a mixed mode multiple (diffraction-reflection);
Figure BDA0002510375030000071
unfolding we will obtain four causal prediction models: reflection mode multiples, diffraction mode multiples, mixed mode multiples (reflection-diffraction, diffraction-reflection)
Figure BDA0002510375030000072
(reflection mode multiple)
Figure BDA0002510375030000073
(diffraction mode multiples)
Figure BDA0002510375030000074
(reflection-diffraction mixed multiples)
Figure BDA0002510375030000075
(diffraction-reflection mixed multiples)
k. The curvatures of the diffracted multiples and the four multiples prediction model wave fields are compared, and the model with the highest similarity is selected for prediction and subtraction, so that the purpose of removing the interference of the diffracted multiples is achieved, as shown in fig. 3 c.
The invention uses the difference of reflection and diffraction homophase axis shape when plane wave is incident, carries on linear radon transform to the earthquake data and extracts and arranges the two different forms again by taking the reflection coefficient in the data matrix as the standard, selects the proper time window to carry on FFT transform to the f-x domain comparing the shape character of the point earthquake focus, then carries on IFFT transform by EMD decomposition to obtain the decomposed field data of the two, then carries on data rearrangement and anti-radon transform to obtain the decomposed wave field diffraction and reflection wave field, then carries on the two by the classification forecasting mode to obtain the accurate forecasting model, finally carries on the suppression by the proper filter to obtain the earthquake data of the suppressed multiple wave.

Claims (1)

1. A method for suppressing diffracted multiples based on wave field decomposition, comprising the steps of:
a. arranging original seismic data into a data matrix of common shot record;
b. performing linear radon transform on each common shot point record;
c. rearranging the reflection coefficients to obtain plane wave data of a common p-section of different angles of incidence, wherein in the common p-section, reflected waves are approximately linearly continuous, and diffracted waves are approximately in a hyperbolic shape;
d. according to the selection of a time window with a proper size, mapping the seismic data of the extracted section to an f-x domain through fast Fourier transform to obtain a real part and an imaginary part of a signal of the f-x domain;
e. for each frequency slice;
e1, performing EMD on the real part data, extracting proper IMF components as the first two IMF components, reconstructing the IMF components as a diffraction wave field real part, and using the rest as a reflection wave field real part, wherein the EMD is frequency domain empirical mode decomposition, and the IMF components can be obtained by calculating the difference between the signals and the upper and lower envelope averages formed by the cubic spline connection of the local maximum value point and the local minimum value point connection;
e2, performing EMD on the imaginary part data, extracting appropriate IMF components to serve as the first two IMF components, reconstructing the IMF components to serve as a diffraction wave field imaginary part, and using the residual part as a reflection wave field imaginary part;
e3, reconstructing the decomposed real part data and imaginary part data into complex data;
f. transforming the reconstructed data into a t-x domain through inverse Fourier transform to generate two groups of data of a diffraction wave field and a reflection wave field;
g. sliding the time window, and repeating the operations on the next time window until all data are finished;
h. rearranging the decomposed reflected and diffracted wave fields of the common p-section into plane wave data;
i. making inverse radon transform to change the plane wave data into the reflected wave field P in the form of common shot gatherrAnd diffracted wave field data Ps；
j. The decomposed reflected wave field PrAnd diffracted wave field data PsCarrying out hierarchical multiple prediction to obtain a prediction model;
Figure FDA0003498246770000011
expanding reflection mode multiples, diffraction mode multiples and mixed mode multiples models;
Figure FDA0003498246770000021
Figure FDA0003498246770000022
Figure FDA0003498246770000023
Figure FDA0003498246770000024
k. and comparing the curvatures of the diffracted multiples and the four multiple prediction models, and selecting the model with the highest similarity for prediction and subtraction.
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