CN109738953B - Complete multiple suppression method based on wavelet domain frequency division energy compensation - Google Patents
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Abstract
The invention relates to a complete multiple suppression method based on wavelet domain frequency division energy compensation, which comprises the following steps: determining a coefficient of wavelet matching according to the seismic record and the predicted multiples data, performing wavelet matching, and primarily correcting and predicting the amplitude and phase of the multiples; selecting a wavelet basis function, and performing wavelet domain frequency band decomposition on the predicted multiples after wavelet matching and the seismic records under the same parameters to obtain data of i frequency bands in one-to-one correspondence; predicting the characteristics of multi-time wave data and seismic records according to different frequency bands, determining the frequency band of energy compensation, and performing spectral whitening processing in a frequency domain; determining an amplitude matching window and a matching coefficient, and performing accurate amplitude matching; carrying out data reconstruction on the result after the amplitude matching; and according to the least square principle, subtracting the matched predicted multi-time wave data from the original seismic record to obtain a suppression result. The complete multiple suppression method based on wavelet domain frequency division energy compensation can realize effective suppression of multiples.
Description
Technical Field
The invention relates to the technical field of processing and explaining of geophysical exploration seismic data, in particular to a complete multiple suppression method in a seismic data processing process, and particularly relates to a complete multiple suppression method based on wavelet domain frequency division energy compensation.
Background
Imaging studies of subsurface geological formations are a necessary process for locating and obtaining oil and gas resources stored underground. In general, in seismic exploration, a seismic source is placed near the surface of the earth, and detectors are buried at a depth below the surface of the earth to receive information about the reflected wave field from the earth. The purpose of seismic imaging is to perform reverse homing on reflected wave information from a complex underground structure so as to return the reflected wave information to a generated underground reflection point, and then the reflected wave information of the underground structure is obtained. In seismic imaging calculations, it is generally assumed that all scattered energy from the subsurface is reflected once. However, in actual seismic exploration, the underground structure information has no difference between the information of the down-going wave field from the earth surface and the information of the reflected up-going wave field, that is, the down-going reflected energy occurs again when the seismic waves pass through some uneven stratum in the shallow layer in the up-going process, so that the multiple wave reflections are formed.
In modern seismic exploration technologies mainly based on reflected wave imaging, multiple suppression has been a hot problem of research. Especially in marine seismic exploration, the presence of free surface multiples is quite severe since sea level is a strong reflecting interface. The occurrence of multiples makes offset imaging unreal, thereby affecting the authenticity and reliability of seismic imaging, as well as interfering with geological structure interpretation. At present, in actual production, many earlier filtering methods are still used to suppress multiples, such as predictive deconvolution, F-K domain filtering, Radon transform, τ -p domain deconvolution, horizontal superposition, and the like, and most of these methods perform multiple suppression based on the physical property differences such as periodicity, velocity, and the like between primary waves and multiples. These filtering methods may achieve the objective of suppressing multiples when the parameters are properly selected, but may not be effective or effective when the difference between the primary and the multiples is not obvious or the parameters are not properly selected, or may even damage the effective signals.
With the development of exploration situations and the increase of exploration difficulty, when the assumed conditions of multiple generation and attenuation cannot be met, the traditional filtering method loses the function, and the prediction subtraction method based on the wave equation theory is generated. The method is based on the fluctuation theory, does not need model assumption, directly utilizes the measured seismic data to predict the multiple waves, and after the multiple waves are predicted, the multiple waves are matched and subtracted from the seismic record, so that the purpose of attenuating the multiple waves is achieved. It does not require prior information of the subsurface structure and therefore can adapt to complex subsurface conditions.
The separation of the effective wave and the multiple waves based on the wave equation theory mainly comprises two steps: a multiple prediction stage and a multiple and effective wave separation stage. In the second phase, measures are taken to compensate for the dynamic and kinematic errors of the predicted multiples signal. The subtraction process of the predicted multiples seems to be simple, but in actual processing, the multiples predicted by different methods are different; moreover, under the influence of exploration environment, a complete seismic wave field cannot be acquired under a complex geophysical environment, and inaccurate multiple signal prediction can be caused; errors in shot and geophone points due to time and depth changes can also result in large errors in the predicted multiples.
Currently, the most widely used multiple matching subtraction methods are the least squares methods proposed by Verschuur and Berkhout. The method can reduce the errors of the predicted multiples and the multiples in the real seismic record on the travel time, the amplitude and the phase to a certain extent, but the actual output always makes a way between the retention of the primary waves and the suppression degree of the multiples, namely when the primary waves are completely retained, the multiples are more remained.
Disclosure of Invention
The present invention aims to provide a complete multiple wave suppression method based on wavelet domain frequency division energy compensation, which solves the problems of multiple wave energy damage prediction caused by multi-pass convolution in the multiple wave prediction process and low matching accuracy of the traditional least square matching subtraction method.
The purpose of the invention is realized by the following technical scheme:
a complete multiple suppression method based on wavelet domain frequency division energy compensation comprises the following steps:
A. according to original exploration seismic records of a target work area and multiple wave data obtained by predicting the work area data based on the wave equation theory, determining wavelet matching coefficients corresponding to the original exploration seismic records and the multiple wave data, performing wavelet matching, and primarily correcting and predicting the amplitude and phase of the multiple waves. The method specifically comprises the following steps: using a global filter to seek a global inverse wavelet for each shot record, minimizing energy loss after the subtraction of the original shot record and the predicted multiples, performing deconvolution on the predicted multiples and the inverse wavelet filter, and preliminarily correcting the information of amplitude, phase and the like of the predicted multiples to a degree which is very close to the original shot record;
B. selecting wavelet basis functions used for wavelet domain frequency band decomposition according to predicted multi-time wave data after wavelet matching and target work area original seismic records, and performing corresponding wavelet domain frequency band decomposition on the predicted multi-time waves after wavelet matching and the original seismic records under the same parameters to obtain data of i frequency bands in one-to-one correspondence;
C. according to the characteristics of the multi-wave data and the original seismic record predicted by different frequency bands, determining the frequency band of the multi-wave data to be predicted, which needs energy compensation, and performing spectral whitening processing on the frequency band in a frequency domain to compensate the energy of the multi-wave data;
D. and aiming at the predicted multi-order data and the original seismic record of each frequency band, determining an optimum amplitude matching window and matching coefficients of the predicted multi-order data and the original seismic record, and performing accurate amplitude matching in a targeted manner. And selecting time-space windows and filtering operators with different sizes according to the predicted multiples and the original seismic records of different frequency bands. When the next window is selected, the window and the previous window are overlapped in time and space, and the final result of the frequency band amplitude matching is formed by performing local self-adaptive processing, namely performing slope processing on the result at the edge of each window and integrating the multiples obtained by different windows together.
E. Carrying out data reconstruction on the prediction multiple wave data after amplitude matching to obtain well-matched full-band prediction multiple wave data, and carrying out same processing on the original seismic records;
F. and according to the original seismic record of the target work area and the matched predicted multi-time wave data, subtracting the matched predicted multi-time wave data from the original seismic record by utilizing a least square principle, namely a principle that the residual energy of the pressed multi-time wave is minimum in a time domain, so as to obtain a final pressing result.
And step A, the target work area is a marine exploration work area or a land exploration work area.
Compared with the prior art, the invention has the beneficial effects that: the complete multiple pressing method based on wavelet domain frequency division energy compensation can compensate predicted multiple energy damage caused by multi-channel convolution to a certain extent, carries out targeted processing on data of different frequency bands, has no redundant step in an algorithm, cannot generate an overlarge data matrix in actual operation to cause slow calculation, has no step back on the calculation efficiency and the calculation time, meets the actual production requirement of the current industry on high efficiency, realizes the multiple matching with higher precision on the basis, can realize the quick and effective pressing of multiple, and has better use and popularization values.
Drawings
FIG. 1 is a flow chart of a complete multiple suppression method based on wavelet domain frequency division energy compensation;
FIG. 2 is a raw seismic record of a work area as described in an embodiment of the present application;
FIG. 3 shows multiple data predicted based on wave equation theory for the work area in the embodiment of the present application;
FIG. 4 shows predicted multi-wave data after matching of the work area wavelets in the embodiment of the present application;
FIG. 5 is a diagram illustrating a wavelet domain decomposition of frequency bands in an embodiment of the present application;
FIG. 6 is a graph of the 'db 10' wavelet basis function selected for use in the embodiments of the present application;
FIG. 7a is a first band raw seismic record based on a db10 wavelet decomposition in an embodiment of the present application;
FIG. 7b is a second band raw seismic record based on the db10 wavelet decomposition in the present embodiment;
FIG. 7c is a third band raw seismic record based on the db10 wavelet decomposition in the present embodiment;
FIG. 7d is a fourth band raw seismic record based on the db10 wavelet decomposition in the present embodiment;
FIG. 7e is a logarithmic amplitude spectrum of the original data of four frequency bands obtained based on the db10 wavelet decomposition in the embodiment of the present application;
FIG. 7f is a graph of linear amplitude spectra of four bands of raw data obtained by a db10 wavelet decomposition according to an embodiment of the present application;
FIG. 8a is a diagram illustrating a first frequency band multiple prediction based on db10 wavelet decomposition in an embodiment of the present application;
FIG. 8b is a diagram illustrating a second band multiple prediction based on db10 wavelet decomposition in an embodiment of the present application;
FIG. 8c is a diagram illustrating a third frequency band multiple prediction based on db10 wavelet decomposition according to an embodiment of the present application;
FIG. 8d is a diagram illustrating a fourth band multiple prediction based on db10 wavelet decomposition in the present embodiment;
FIG. 8e is a logarithmic amplitude spectrum of the four frequency band prediction multiples obtained based on the db10 wavelet decomposition in the embodiment of the present application;
FIG. 8f is a graph of the linear amplitude spectrum of the four frequency band prediction multiples obtained in the present embodiment based on the db10 wavelet decomposition;
FIG. 9a is a diagram of a first band prediction multi-pass data after spectral whitening in an embodiment of the present application;
FIG. 9b is a logarithmic amplitude spectrum of a predicted multiple for four frequency bands after spectral whitening in an embodiment of the present application;
FIG. 9c is a linear amplitude spectrum of the predicted multiples for four frequency bands after spectral whitening in the embodiment of the present application;
FIG. 10a is a diagram illustrating a first frequency band amplitude matched predicted multiples in an embodiment of the present application;
FIG. 10b shows the second band amplitude matched multiples in the present embodiment;
FIG. 10c is a graph of the third band amplitude matched multiples in the present embodiment;
FIG. 10d is a graph of the fourth band amplitude matched multiples in the present embodiment;
FIG. 10e is a logarithmic amplitude spectrum of the predicted multiples for four frequency bands after amplitude matching in the embodiment of the present application;
FIG. 10f is a linear amplitude spectrum of a predicted multiple for four frequency bands after amplitude matching in the embodiment of the present application;
FIG. 11 shows the multiple compression results in the examples of the present application.
Detailed Description
The embodiment of the application provides a complete multiple suppression method based on wavelet domain frequency division energy compensation.
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The following embodiments are only used for illustrating the present invention, and the present invention selects db10 wavelet as the wavelet basis function, and any other wavelet basis function is changed on the basis of the technical solution of the present invention, which belongs to the equivalent mathematical transformation without innovation, and should not be excluded from the protection scope of the present invention.
The embodiment of the application provides a complete multiple suppression method in seismic exploration data processing. The multiple suppression method provides original seismic records of a target work area and multiple data obtained by predicting the seismic records of the work area based on a wave equation theory.
In this embodiment, the target work area may be an offshore exploration work area or a land exploration work area. The target work area has geological conditions that generate multiples.
The embodiment of the application performs multiple suppression according to the flow chart shown in fig. 1. FIG. 2 is a diagram of an actual seismic record of a certain offshore seismic exploration work area, which has a geological condition of generating strong energy multiples due to the existence of a strong wave impedance interface. FIG. 3 is a diagram of multiple data predicted from the seismic record of FIG. 2 based on wave equation theory. The data shown in the figure is data obtained by resampling original seismic records, specifically, resampling is carried out at a sampling time interval of 4ms to be a sampling time interval of 8ms, the ordinate in the figure represents sampling time, and the abscissa in the figure represents the number of detectors.
As shown in fig. 1, a complete multiple suppression method based on wavelet domain frequency division energy compensation includes the following steps:
A. determining wavelet matching coefficients according to original exploration seismic records of an offshore work area and multiple wave data obtained by predicting the work area seismic records based on a wave equation theory, and performing wavelet matching. In this embodiment, a global filter is used to find a global inverse wavelet for each shot record, so that the energy loss after the original shot record is subtracted from the predicted multiples is minimized, the predicted multiples are deconvoluted with the inverse wavelet filter, and the amplitude and phase information of the predicted multiples are preliminarily corrected. FIG. 4 is the predicted multiples data after wavelet matching in the present embodiment, where the ordinate represents the sampling time and the abscissa represents the detector count.
B. According to the predicted multi-wave data after wavelet matching and the original seismic record of the target work area, the 'db 10' wavelet is selected as a wavelet basis function used for wavelet domain frequency band decomposition, and fig. 5 is a schematic diagram of a 'db 10' wavelet basis function curve. Performing wavelet domain frequency band decomposition shown in fig. 6 on the predicted multiples after wavelet matching and the original seismic record, wherein a represents an approximate sequence extraction function, D represents a detail sequence extraction function, and 4 frequency band data corresponding to each other one by one are obtained, fig. 7a to 7f are the original seismic records of four frequency bands obtained based on db10 wavelet decomposition in the embodiment of the present application, and fig. 8a to 8f are the predicted multiples obtained after matching the four frequency band wavelets obtained based on db10 wavelet decomposition in the embodiment of the present application.
C. In the embodiment of the present application, the predicted multi-pass data of the 1 st frequency band has significant energy loss, so that the spectral whitening processing is performed on the data in the frequency domain, which is equivalent to compensating the energy of the high frequency part of the data, and the result after the spectral whitening is shown in fig. 9a to 9 c.
D. And aiming at the predicted multi-order data and the original seismic record of each frequency band, determining an optimum amplitude matching window and matching coefficients of the predicted multi-order data and the original seismic record, and performing accurate amplitude matching in a targeted manner. And selecting time-space windows and filtering operators with different sizes according to the predicted multiples and the original seismic records of different frequency bands. When the next window is selected, the window overlaps with the previous window in terms of time and space, and after local adaptive processing, that is, the result at the edge of each window is subjected to ramp processing, and multiples obtained from different windows are integrated together to form the final result of amplitude matching of the frequency band, and fig. 10 a-10 f are the results of amplitude matching of the four-frequency-band predicted multiple data.
E. Performing data reconstruction on the predicted multiple wave data after amplitude matching shown in the figures 10 a-10 f to obtain well-matched full-frequency-band predicted multiple wave data, and performing same processing on the original seismic records;
F. according to the original seismic record of the target work area and the matched predicted multi-wave data, in the time domain, by using the least square principle, the matched predicted multi-wave data is subtracted from the original seismic record, so that the pressing result shown in fig. 11 is obtained. The ordinate in fig. 11 represents the sampling time, and the abscissa in the figure represents the detector number. The method effectively overcomes the boundary effect and waveform distortion easily caused by the conventional least square matching, and more effectively suppresses multiples than F-K domain filtering and tau-p domain deconvolution methods conventionally used in the industry, more completely retains primary waves and improves the precision of a suppression result.
In addition, the invention has program packages under Matlab and L inux environments, and geophysical data processing and interpreters can perform multiple wave compression by means of the program packages, so that the invention has better use and popularization values.
Claims (3)
1. A complete multiple suppression method based on wavelet domain frequency division energy compensation is characterized by comprising the following steps:
A. determining wavelet matching coefficients corresponding to original exploration seismic records of a target work area and multiple wave data obtained by predicting the work area data based on a wave equation theory, performing wavelet matching, and primarily correcting and predicting the amplitude and phase of the multiple waves;
B. selecting wavelet basis functions used for wavelet domain frequency band decomposition according to predicted multi-time wave data after wavelet matching and target work area original seismic records, and performing corresponding wavelet domain frequency band decomposition on the predicted multi-time waves after wavelet matching and the original seismic records under the same parameters to obtain data of i frequency bands in one-to-one correspondence;
C. according to the characteristics of the multi-wave data and the original seismic record predicted by different frequency bands, determining the frequency band of the multi-wave data to be predicted, which needs energy compensation, and performing spectral whitening processing on the frequency band in a frequency domain to compensate the energy of the multi-wave data;
D. determining the most suitable amplitude matching window and matching coefficient of the predicted multi-time wave data and the original seismic record of each frequency band, and performing accurate amplitude matching with pertinence; the method specifically comprises the following steps: designing a local filter, estimating a filtering operator in each window by a method of opening a time-space window, acting the operator on the predicted multiples, selecting the time-space windows and the filtering operators with different sizes aiming at the predicted multiples and original seismic records of different frequency bands, overlapping the window and the previous window in time and space when selecting the next window, and performing local self-adaptive processing, namely performing slope processing on results at the edges of each window, and integrating the multiples obtained by different windows together to form a final result of amplitude matching of the frequency band;
E. carrying out data reconstruction on the prediction multiple wave data after amplitude matching to obtain well-matched full-band prediction multiple wave data, and carrying out same processing on the original seismic records;
F. and according to the original seismic record of the target work area and the matched predicted multi-time wave data, subtracting the matched predicted multi-time wave data from the original seismic record by utilizing a least square principle, namely a principle that the residual energy of the pressed multi-time wave is minimum in a time domain, so as to obtain a final pressing result.
2. The wavelet domain frequency division energy compensation-based complete multiple suppression method according to claim 1, wherein the step A specifically comprises: a global inverse wavelet is sought for each shot record using a global filter to minimize energy loss by subtracting the predicted multiples from the original shot record, the predicted multiples are deconvoluted with the inverse wavelet filter, and their amplitude and phase information are initially corrected.
3. The complete multiple suppression method based on wavelet domain frequency division energy compensation as claimed in claim 1, wherein: and step A, the target work area is a marine exploration work area or a land exploration work area.
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