CN103954994B - Seismic signal Enhancement Method and device based on continuous wavelet transform - Google Patents
Seismic signal Enhancement Method and device based on continuous wavelet transform Download PDFInfo
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Abstract
The invention provides a kind of seismic signal Enhancement Method and device based on continuous wavelet transform, this method includes seismic signal being decomposed into multiple dimensioned characteristic of field signal；The principal dimensions in the multiple dimensioned characteristic of field signal is selected as benchmark；Correlation computations are carried out to the multiple dimensioned characteristic of field signal using the benchmark, to establish the correction factor of small echo weight coefficient；The seismic signal is reconstructed according to the correction factor of the small echo weight coefficient.Continuous wavelet transform used is a kind of analysis method of time scale in seismic signal Enhancement Method of the invention based on continuous wavelet transform, it has higher frequency resolution in low frequency part, there is higher temporal resolution in HFS, all there is the ability for characterizing signal local feature in time, the domain of yardstick two, so as to reconstruct wavelet coefficient by correlation, the selectively seismic signal of reconstruct different scale, interference ripple thus can be effectively eliminated, realizes the feature extraction and enhancing of useful signal.
Description
Technical Field
The invention relates to a digital processing method of seismic data for petroleum geophysical exploration, in particular to a seismic signal enhancement method and device based on continuous wavelet transform.
Background
In the digital processing of seismic data for oil geophysical exploration, short-time Fourier transform is commonly used. The short-time Fourier transform is a signal analysis method with single resolution, and the idea is as follows: selecting a time-frequency localized window function, and assuming that the analysis window function g (t) is stable (pseudo-stable) in a short time interval, moving the window function so that f (t) g (t) is stable signals in different finite time widths, thereby calculating the power spectrum at different moments. The short-time fourier transform uses a fixed window function, whose shape is not changed once determined, and whose resolution is determined. If the resolution is to be changed, the window function needs to be reselected. Short-time fourier transform is used to analyze piecewise stationary signals or near stationary signals, but for non-stationary signals, when the signal changes drastically, a window function is required to have a higher time resolution; when the waveform changes more slowly, mainly a low-frequency signal, the window function is required to have higher frequency resolution. Therefore, the short-time fourier transform cannot compromise the frequency and time resolution requirements. The short-time Fourier transform window function is limited by a W.Heisenberg uncertainty criterion, and the area of a time-frequency window is not less than 2. This illustrates, from the other side, that the time and frequency resolution of the short-time fourier transform window functions cannot be optimized simultaneously.
However, the seismic signals are usually quite complex, and sometimes the energy of the effective signals is weak, so that the existing seismic signal analysis method based on short-time fourier transform cannot extract the effective signals with weak energy from the complex seismic signals.
Disclosure of Invention
The invention aims to provide a seismic signal enhancement method and a seismic signal enhancement device based on continuous wavelet transform, so as to extract effective signals with weak energy from complex seismic signals.
In order to achieve the above object, one aspect of the present invention provides a method for enhancing seismic signals based on continuous wavelet transform, comprising the steps of:
decomposing the seismic signals into multi-scale domain characteristic signals;
selecting a main scale in the multi-scale domain characteristic signal as a reference scale;
performing correlation calculation on the multi-scale domain characteristic signal by using the reference scale to establish a correction coefficient of a wavelet weight coefficient;
and reconstructing the seismic signals according to the correction coefficient of the wavelet weight coefficient.
The method for enhancing the seismic signals based on the continuous wavelet transform, disclosed by the invention, comprises the following steps of decomposing the seismic signals into multi-scale domain characteristic signals:
the signal multi-scale domain decomposition technology based on the Morie complex value wavelet decomposes the seismic signals into multi-scale domain characteristic signals.
The seismic signal enhancement method based on continuous wavelet transform, provided by the invention, is characterized in that the multi-scale domain characteristic signals are subjected to correlation calculation by utilizing the reference scale so as to establish a correction coefficient of a wavelet weight coefficient, and the method specifically comprises the following steps:
(1) selecting a reference scale as a wavelet and comparing the wavelet with a scale domain characteristic signal at an analysis time interval;
(2) calculating a continuous wavelet transform coefficient at a certain moment;
(3) adjusting a time translation factor, and then repeating the steps (1) to (2) until the analysis time period covers the whole support area of the scale domain characteristic signal;
(4) and (4) adjusting the scale expansion factor, and then repeating the steps (1) to (3) until all scales of continuous wavelet transform coefficients in the multi-scale domain characteristic signal are completed.
The seismic signal enhancement method based on continuous wavelet transform, which is disclosed by the invention, reconstructs the seismic signal according to the correction coefficient of the wavelet weight coefficient, and specifically comprises the following steps:
according to the formulaReconstructing the seismic signal, wherein CψFor continuous wavelet transform coefficients, Wψf (a, b) is the wavelet spectrum,. psia,b(x) Is a wavelet function anda is a scale factor and b is a time shift factor.
In still another aspect, the present invention further provides a seismic signal enhancement apparatus based on continuous wavelet transform, including:
the scale decomposition module is used for decomposing the seismic signals into multi-scale domain characteristic signals;
the reference selection module is used for selecting a main scale in the multi-scale domain characteristic signal as a reference scale;
the coefficient correction module is used for performing correlation calculation on the multi-scale domain characteristic signals by using the reference scale so as to establish a correction coefficient of a wavelet weight coefficient;
and the signal reconstruction module is used for reconstructing the seismic signals according to the correction coefficient of the wavelet weight coefficient.
The invention relates to a seismic signal enhancement device based on continuous wavelet transform, which decomposes seismic signals into multi-scale domain characteristic signals and specifically comprises the following steps:
the signal multi-scale domain decomposition technology based on the Morie complex value wavelet decomposes the seismic signals into multi-scale domain characteristic signals.
The invention relates to a seismic signal enhancement device based on continuous wavelet transform, wherein a coefficient correction module performs scale domain multi-channel signal correlation calculation by using the reference scale so as to establish a correction coefficient of a wavelet weight coefficient, and the device specifically comprises the following steps:
(1) selecting a reference scale as a wavelet and comparing the wavelet with a scale domain characteristic signal at an analysis time interval;
(2) calculating a continuous wavelet transform coefficient at a certain moment;
(3) adjusting a time translation factor, and then repeating the steps (1) to (2) until the analysis time period covers the whole support area of the scale domain characteristic signal;
(4) and (4) adjusting the scale expansion factor, and then repeating the steps (1) to (3) until all scales of continuous wavelet transform coefficients in the multi-scale domain characteristic signal are completed.
The invention relates to a seismic signal enhancement device based on continuous wavelet transform, wherein a signal reconstruction module reconstructs a seismic signal according to a correction coefficient of a wavelet weight coefficient, and the device specifically comprises:
according to the formulaReconstructing the seismic signal, wherein CψFor continuous wavelet transform coefficients, Wψf (a, b) is the wavelet spectrum,. psia,b(x) Is a wavelet function anda is a scale factor and b is a time shift factor.
The invention relates to a seismic signal enhancement method based on continuous wavelet transform, which comprises the steps of firstly decomposing a seismic signal into multi-scale domain characteristic signals; then selecting a main scale in the multi-scale domain characteristic signal as a reference scale; secondly, performing correlation calculation on the multi-scale domain characteristic signals by using a reference scale to establish a correction coefficient of the wavelet weight coefficient; finally, reconstructing the seismic signals according to the correction coefficient of the wavelet weight coefficient; therefore, the continuous wavelet transform used by the invention is a time-scale analysis method, which has higher frequency resolution in a low-frequency part and higher time resolution in a high-frequency part, namely has the capability of representing the local characteristics of signals in both time domain and scale domain, thereby selectively reconstructing the seismic signals of different scales through related reconstructed wavelet coefficients, effectively eliminating interference waves and realizing the characteristic extraction and enhancement of effective signals.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart of a method for seismic signal enhancement based on continuous wavelet transform according to an embodiment of the present invention;
FIG. 2 is a block diagram of a seismic signal enhancement apparatus based on continuous wavelet transform according to an embodiment of the present invention;
FIG. 3 is a cross-sectional view of an original single shot seismic signal recording in an example of use of the present invention;
FIG. 4 is a cross-sectional view of a decomposed low-frequency component scale feature signal in an embodiment of the present invention;
FIG. 5 is a cross-sectional view of a decomposed intermediate frequency component scale signature in an exemplary embodiment of the present invention;
FIG. 6 is a cross-sectional view of a decomposed principal frequency component scale feature signal in an embodiment of the present invention;
FIG. 7 is a signal profile and spectrum diagram of a weak signal before enhancement according to an embodiment of the present invention;
FIG. 8 is a signal profile and a spectrum diagram of a weak signal after enhancement according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the following embodiments and the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
Referring to fig. 1, a seismic signal enhancement method based on continuous wavelet transform according to an embodiment of the present invention includes the following steps:
and S101, acquiring seismic signals.
And S102, decomposing the seismic signals into multi-scale domain characteristic signals. In particular, the seismic signals may be decomposed into multi-scale domain signature signals based on a signal multi-scale domain decomposition technique of a Morlet complex wavelet (i.e., a Morlet complex wavelet). Since the multi-scale domain decomposition technique of continuous wavelet transform belongs to the prior art, it is not described herein.
And S103, selecting a main scale in the multi-scale domain characteristic signal as a reference scale. In order to detect some specific signals, wavelets with similar waveforms should be selected for analysis, and usually the dominant scale in the multi-scale domain feature signal is closer to the waveform of the multi-scale domain feature signal, so the dominant scale in the multi-scale domain feature signal is selected as the reference scale.
And step S104, performing correlation calculation on the multi-scale domain characteristic signal by using the reference scale to establish a correction coefficient of the wavelet weight coefficient. The method comprises the following specific steps:
(1) selecting a reference scale as a wavelet and comparing the wavelet with a scale domain characteristic signal at an analysis time interval;
(2) calculating a continuous wavelet transform coefficient at a certain moment;
(3) adjusting the time translation factor, and then repeating the steps (1) to (2) until the analysis time period covers the whole support area of the scale domain characteristic signal;
(4) and (4) adjusting the scale expansion factor, and then repeating the steps (1) to (3) until all scales of continuous wavelet transform coefficients in the multi-scale domain characteristic signal are completed.
And S105, reconstructing the seismic signals according to the correction coefficient of the wavelet weight coefficient. Specifically, the method comprises the following steps:
according to the formulaReconstructing the seismic signal, wherein CψRepresenting the similarity of the wavelet to the scale domain characteristic signal in the analysis period, W, for continuous wavelet transform coefficientψf (a, b) is the wavelet spectrum,. psia,b(x) Is a wavelet function anda is a rulerDegree scaling factor, representing the frequency dependent scaling, b is the time shift factor.
The continuous wavelet transform used in the seismic signal enhancement method based on the continuous wavelet transform is a time-scale analysis method, and has higher frequency resolution in a low-frequency part and higher time resolution in a high-frequency part, namely, the continuous wavelet transform has the capacity of representing the local characteristics of signals in both time and scale domains, so that the seismic signals with different scales are selectively reconstructed by related reconstructed wavelet coefficients, interference waves can be effectively eliminated, and the characteristic extraction and enhancement of effective signals are realized.
Referring to fig. 2, the seismic signal enhancement apparatus based on continuous wavelet transform according to the embodiment of the present invention includes:
and the scale decomposition module 21 is used for decomposing the seismic signals into multi-scale domain characteristic signals. In particular, the seismic signals may be decomposed into multi-scale domain signature signals based on a signal multi-scale domain decomposition technique of a Morlet complex wavelet (i.e., a Morlet complex wavelet).
And the reference selection module 22 is used for selecting the main scale in the multi-scale domain characteristic signal as the reference scale. In order to detect some specific signals, wavelets with similar waveforms should be selected for analysis, and usually the dominant scale in the multi-scale domain feature signal is closer to the waveform of the multi-scale domain feature signal, so the dominant scale in the multi-scale domain feature signal is selected as the reference scale.
The coefficient correction module 23 is configured to perform correlation calculation on the multi-scale domain feature signal by using the reference scale to establish a correction coefficient of the wavelet weight coefficient, and the specific implementation of the coefficient correction module includes the following steps:
(1) selecting a reference scale as a wavelet and comparing the wavelet with a scale domain characteristic signal at an analysis time interval;
(2) calculating a continuous wavelet transform coefficient at a certain moment;
(3) adjusting the time translation factor, and then repeating the steps (1) to (2) until the analysis time period covers the whole support area of the scale domain characteristic signal;
(4) and (4) adjusting the scale expansion factor, and then repeating the steps (1) to (3) until all scales of continuous wavelet transform coefficients in the multi-scale domain characteristic signal are completed.
And the signal reconstruction module 24 is used for reconstructing the seismic signals according to the correction coefficient of the wavelet weight coefficient. Specifically, the method comprises the following steps:
according to the formulaReconstructing the seismic signal, wherein CψRepresenting the similarity of the wavelet to the scale domain characteristic signal in the analysis period, W, for continuous wavelet transform coefficientψf (a, b) is the wavelet spectrum,. psia,b(x) Is a wavelet function anda is a scale factor, representing the frequency dependent scaling, and b is a time shift factor.
The continuous wavelet transform used in the seismic signal enhancement device based on the continuous wavelet transform is a time-scale analysis means, and has higher frequency resolution in a low-frequency part and higher time resolution in a high-frequency part, namely, the continuous wavelet transform has the capacity of representing the local characteristics of signals in both time domain and scale domain, so that the seismic signals with different scales are selectively reconstructed by related reconstructed wavelet coefficients, interference waves can be effectively eliminated, and the characteristic extraction and enhancement of effective signals are realized.
The following is an example of the weak signal enhancement of the pre-stack seismic data, which is specifically as follows:
in seismic exploration carried out in western China, surface waves and interference waves are developed due to the fact that the complex earth surface condition is often met, in this example, the seismic signal enhancement method based on continuous wavelet transformation is utilized to carry out surface wave suppression, and effective signal energy is improved. In the signal enhancement process, firstly, the original single-shot seismic signals (as shown in fig. 3) are decomposed into multi-scale domain characteristic signals (as shown in fig. 4 to 6) by using continuous wavelet transform, wherein fig. 4 is low-frequency scale signals, fig. 5 is medium-frequency scale signals, and fig. 6 is main-frequency scale signals. As shown in fig. 7, the wave energy is stronger before treatment. And referring to fig. 8, after treatment, the surface wave is better suppressed, thereby enhancing the energy of the effective wave.
Those of skill would further appreciate that the various illustrative logical blocks, units, and steps described in connection with the embodiments disclosed herein may be implemented as hardware, software, or combinations of both. Whether implemented in hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.
The various illustrative logical blocks, or elements, described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be located in a user terminal. In the alternative, the processor and the storage medium may reside in different components in a user terminal.
In one or more exemplary designs, the functions described above in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such discs (disk) and disks (disc) include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (4)
1. A seismic signal enhancement method based on continuous wavelet transform is characterized by comprising the following steps:
decomposing the seismic signals into multi-scale domain characteristic signals;
selecting a main scale in the multi-scale domain characteristic signal as a reference scale;
performing correlation calculation on the multi-scale domain characteristic signal by using the reference scale to establish a correction coefficient of a wavelet weight coefficient;
reconstructing the seismic signals according to the correction coefficient of the wavelet weight coefficient; wherein,
the method for performing correlation calculation on the multi-scale domain characteristic signal by using the reference scale to establish a correction coefficient of a wavelet weight coefficient specifically comprises the following steps:
(1) selecting a reference scale as a wavelet and comparing the wavelet with a scale domain characteristic signal at an analysis time interval;
(2) calculating a continuous wavelet transform coefficient at a certain moment;
(3) adjusting a time translation factor, and then repeating the steps (1) to (2) until the analysis time period covers the whole support area of the scale domain characteristic signal;
(4) adjusting scale expansion factors, and then repeating the steps (1) to (3) until all scales of continuous wavelet transform coefficients in the multi-scale domain characteristic signal are completed;
the reconstructing the seismic signal according to the correction coefficient of the wavelet weight coefficient specifically includes:
according to the formulaReconstructing the seismic signal, wherein CψFor continuous wavelet transform coefficients, Wψf (a, b) is the wavelet spectrum,. psia,b(x) Is a wavelet function anda is a scale expansion factor, b is a time translation factor, and R is a space of continuous wavelet transform.
2. The method for enhancing seismic signals based on continuous wavelet transform as claimed in claim 1, wherein said decomposing seismic signals into multi-scale domain signature specifically comprises:
the signal multi-scale domain decomposition technology based on the Morie complex value wavelet decomposes the seismic signals into multi-scale domain characteristic signals.
3. A seismic signal enhancement device based on continuous wavelet transform, comprising:
the scale decomposition module is used for decomposing the seismic signals into multi-scale domain characteristic signals;
the reference selection module is used for selecting a main scale in the multi-scale domain characteristic signal as a reference scale;
the coefficient correction module is used for performing correlation calculation on the multi-scale domain characteristic signals by using the reference scale so as to establish a correction coefficient of a wavelet weight coefficient;
the signal reconstruction module is used for reconstructing the seismic signals according to the correction coefficient of the wavelet weight coefficient; wherein,
the coefficient correction module performs scale domain multi-channel signal correlation calculation by using the reference scale to establish a correction coefficient of the wavelet weight coefficient, and specifically comprises the following steps:
(1) selecting a reference scale as a wavelet and comparing the wavelet with a scale domain characteristic signal at an analysis time interval;
(2) calculating a continuous wavelet transform coefficient at a certain moment;
(3) adjusting a time translation factor, and then repeating the steps (1) to (2) until the analysis time period covers the whole support area of the scale domain characteristic signal;
(4) adjusting scale expansion factors, and then repeating the steps (1) to (3) until all scales of continuous wavelet transform coefficients in the multi-scale domain characteristic signal are completed;
the signal reconstruction module reconstructs the seismic signal according to the correction coefficient of the wavelet weight coefficient, and specifically comprises:
according to the formulaReconstructing the seismic signal, wherein CψFor continuous wavelet transform coefficients, Wψf (a, b) is the wavelet spectrum,. psia,b(x) Is a wavelet function anda is a scale expansion factor, b is a time translation factor, and R is a space of continuous wavelet transform.
4. The apparatus for enhancing seismic signals based on continuous wavelet transform as claimed in claim 3, wherein said decomposing the seismic signals into multi-scale domain feature signals specifically comprises:
the signal multi-scale domain decomposition technology based on the Morie complex value wavelet decomposes the seismic signals into multi-scale domain characteristic signals.
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