CN117289343A - Pre-stack gather frequency-increasing method, device and medium based on wavelet cepstrum - Google Patents

Pre-stack gather frequency-increasing method, device and medium based on wavelet cepstrum Download PDF

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CN117289343A
CN117289343A CN202311267483.7A CN202311267483A CN117289343A CN 117289343 A CN117289343 A CN 117289343A CN 202311267483 A CN202311267483 A CN 202311267483A CN 117289343 A CN117289343 A CN 117289343A
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frequency
wavelet
cepstrum
time
spectrum
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刘力辉
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Chengdu Jingshi Petroleum Technology Co ltd
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Chengdu Jingshi Petroleum Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/30—Analysis
    • G01V1/307—Analysis for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
    • G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
    • G01V1/36—Effecting static or dynamic corrections on records, e.g. correcting spread; Correlating seismic signals; Eliminating effects of unwanted energy
    • G01V1/362—Effecting static or dynamic corrections; Stacking
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/50—Corrections or adjustments related to wave propagation
    • G01V2210/51—Migration
    • G01V2210/512—Pre-stack
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V2210/00—Details of seismic processing or analysis
    • G01V2210/60—Analysis
    • G01V2210/62—Physical property of subsurface

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  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Acoustics & Sound (AREA)
  • Environmental & Geological Engineering (AREA)
  • Geology (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Geophysics (AREA)
  • Geophysics And Detection Of Objects (AREA)

Abstract

The invention discloses a pre-stack gather frequency-raising method, equipment and medium based on wavelet cepstrum, which are characterized in that wavelet transformation and cepstrum analysis are comprehensively applied to convert seismic data into wavelet domain to generate multi-scale seismic time spectrums, time-varying wavelets are counted on the seismic time spectrums of all scales, then the cepstrum transformation is utilized to realize single-scale seismic time spectrum frequency-raising, finally inverse wavelet transformation is carried out on the frequency-raising results of the seismic time spectrums of different scales to complete frequency-raising of the single-channel seismic data, the problem of resolution reduction caused by main frequency time-space variation in the seismic data can be effectively recovered by utilizing the time domain and frequency domain information of the seismic data, and the resolution and the frequency bandwidth of the pre-stack gather are improved, so that the problems that the traditional deconvolution method cannot accurately model and process the time-space variation of wavelets when the pre-stack gather frequency-raising are solved, and the performance and the application of the frequency-raising technology are limited.

Description

Pre-stack gather frequency-increasing method, device and medium based on wavelet cepstrum
Technical Field
The invention relates to the technical field of seismic data processing, in particular to a pre-stack gather frequency-boosting method based on wavelet cepstrum.
Background
In seismic data processing, improving seismic resolution is an important task. Deconvolution has been widely focused and studied in depth by researchers at home and abroad as a key means for improving the resolution of seismic data. While many practical deconvolution algorithms have been proposed, these methods are typically only performed within the effective frequency band when broadening the seismic spectrum, and the information that is buried in white noise on both sides of the spectrum cannot be recovered, thus limiting the resolution improvement.
Furthermore, current deconvolution methods are based on conventional deconvolution models, one of which is assumed to be that the wavelet does not change with time and space during subsurface propagation. However, in actual seismic propagation, the wavelet may undergo spatio-temporal variations, which presents a major problem for pre-stack gather frequency-boosting techniques. This means that the traditional deconvolution method cannot accurately model and process the space-time variation of wavelets when the frequency of the prestack gather is increased, and limits the performance and application of the frequency increasing technology.
Disclosure of Invention
Aiming at the problems of the background technology, the invention aims to provide a pre-stack gather frequency-raising method, equipment and medium based on wavelet cepstrum, which are used for converting seismic data into wavelet domain by comprehensively applying wavelet transformation and cepstrum analysis, generating multi-scale seismic time spectrum, counting time-varying wavelets on the seismic time spectrum of each scale, realizing single-scale seismic time spectrum frequency-raising by using cepstrum transformation, and finally carrying out inverse wavelet transformation on the frequency-raising results of the seismic time spectrum frequency-raising of different scales to complete frequency-raising of the single-channel seismic data, thereby effectively recovering the problem of resolution reduction caused by main frequency time-space variation in the seismic data, improving the resolution and the frequency bandwidth of the pre-stack gather, and further solving the problems that the traditional deconvolution method cannot accurately model and process the time-space variation of wavelets when the frequency-raising of the pre-stack gather, and limiting the performance and application of the frequency-raising technology.
The invention is realized by the following technical scheme:
the invention relates to a pre-stack gather frequency-increasing method based on wavelet cepstrum, which comprises the following steps:
acquiring prestack gather data, and transforming the prestack gather data into a wavelet domain by utilizing a wavelet transformation formula to obtain a multi-scale earthquake time spectrum;
the frequency of the multi-scale earthquake time frequency spectrum is developed by adopting a cepstrum frequency raising method, and a multi-scale earthquake time frequency spectrum frequency development result after frequency development is obtained;
and performing inverse wavelet transformation on the frequency spectrum frequency expansion result in the multi-scale earthquake to obtain pre-stack gather data after frequency expansion.
In the technical scheme, the pre-stack gather data is transformed into a wavelet domain for processing by adopting wavelet transformation, and the characteristic that the wavelet can change in time and space in actual seismic propagation is reserved by utilizing wavelet transformation space (time) and frequency local transformation, so that the problem that the traditional deconvolution method cannot accurately model and process the time and space change of the wavelet when the pre-stack gather frequency is increased is solved.
Frequency information of different scales can be obtained by carrying out cepstrum analysis on the frequency spectrum in the seismic channel. Then, the result of the cepstrum analysis is subjected to frequency-up processing in the wavelet domain. Compared with the traditional deconvolution method, the method provided by the invention has the advantages that the problem of resolution reduction caused by main frequency space-time variation in the seismic data can be effectively recovered by carrying out cepstrum and frequency lifting in the wavelet domain, and the resolution and the frequency bandwidth of the prestack gather are improved.
The frequency spectrum frequency expansion result in multi-scale earthquake is subjected to inverse wavelet transformation to obtain frequency expansion pre-stack gather data, the frequency expansion pre-stack gather data can be carried out in an effective frequency band when the earthquake frequency spectrum is expanded, and meanwhile, the information of the two sides of the frequency spectrum submerged in white noise can be recovered, so that the resolution is improved, and the capability and effect of earthquake data processing are improved.
In one possible embodiment, the wavelet transform is expressed as:
wherein, psi is a,τ (t) represents a wavelet basis function, a represents a scale of controlling the wavelet function, and τ and t represent a shift amount and time, respectively.
In one possible embodiment, using a cepstral frequency boost method to frequency-boost the multi-scale seismic time spectrum includes:
transforming each single-scale seismic time spectrum in the multi-scale seismic time spectrum into a cepstrum time frequency domain to obtain a cepstrum signal;
smoothing the cepstrum signal through smooth cepstrum to obtain a time spectrum for estimating wavelet;
and calculating the time spectrum for estimating the wavelet in the wavelet domain to obtain a reflection coefficient time spectrum.
In one possible embodiment, transforming a single-scale seismic-time spectrum of the multi-scale seismic-time spectrum into a cepstral time-frequency domain comprises:
lnG(τ,f)＝lnW(τ,f)+lnR(τ,f)
in the above equation, G (τ, f) represents the time spectrum of the non-stationary seismic record, W (τ, f) represents the time spectrum of the time-varying wavelet, and R (τ, f) represents the reflection coefficient time spectrum.
In one possible embodiment, the time spectrum of the time-varying wavelet is expressed as:
W(τ,f)＝a(τ,f)*ω(f)
in the above equation, a (τ, f) represents the decay function, and ω (f) represents the wavelet spectrum. In one possible embodiment, smoothing the cepstral signal by smoothing the cepstral signal comprises:
|W(τ,f)|≈exp(ployfit(G ln (τ,f)))
in the above, G ln (τ, f) represents the time spectrum of the cepstral non-stationary seismic record, exp () represents the exponential function, ployfit () represents the curve fitting function.
In a possible embodiment, calculating the time spectrum for estimating wavelets in the wavelet domain comprises:
in the above, mu is a parameter for preventing zero value from being introduced in denominator, A max Represents the maximum value of the frequency spectrum |w (τ, f) | at the time of dynamic wavelet. In one possible embodiment, performing an inverse wavelet transform on the multi-scale seismic time spectrum frequency development results comprises:
in the above, C ψ A parameter indicating that the wavelet satisfies the tolerance condition,WT f (a, τ) represents the wavelet transform result of the signal f (t).
The second aspect of the invention provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a wavelet cepstrum-based pre-stack gather frequency boosting method when executing the program.
A third aspect of the present invention provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a wavelet cepstrum-based pre-stack gather frequency-boosting method.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the method has the advantages that the pre-stack gather data is transformed into a wavelet domain for processing by wavelet transformation, and the characteristic that the wavelet can change in time and space in actual seismic propagation is reserved by utilizing wavelet transformation space (time) and frequency local transformation, so that the problem that the traditional deconvolution method cannot accurately model and process the time and space change of the wavelet when the pre-stack gather frequency is increased is solved;
2. frequency information of different scales can be obtained by carrying out cepstrum analysis on the frequency spectrum in the seismic channel. And then frequency-lifting processing is carried out on the result of the cepstrum analysis in the wavelet domain. Compared with the traditional deconvolution method, the method provided by the invention has the advantages that the problem of resolution reduction caused by main frequency space-time variation in the seismic data can be effectively recovered by carrying out cepstrum and frequency lifting in the wavelet domain, and the resolution and the frequency bandwidth of the prestack gather are improved.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the drawings that are needed in the examples will be briefly described below, it being understood that the following drawings only illustrate some examples of the present invention and therefore should not be considered as limiting the scope, and that other related drawings may be obtained from these drawings without inventive effort for a person skilled in the art. In the drawings:
fig. 1 is a schematic flow chart of a pre-stack gather frequency-boosting method based on wavelet cepstrum provided in embodiment 1 of the present invention;
FIG. 2 is a graph showing the comparison of the original gather before frequency boosting and the gather after frequency boosting of the wavelet cepstrum provided in embodiment 1 of the present invention;
FIG. 3 is a comparison of AVO fitting analysis provided in example 1 of the present invention;
FIG. 4 is a diagram showing a comparison of a mid-angle stacked seismic section before frequency boosting and a mid-angle stacked seismic section after frequency boosting by wavelet cepstrum provided in example 1 of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to embodiment 2 of the present invention.
Detailed Description
For the purpose of making apparent the objects, technical solutions and advantages of the present invention, the present invention will be further described in detail with reference to the following examples and the accompanying drawings, wherein the exemplary embodiments of the present invention and the descriptions thereof are for illustrating the present invention only and are not to be construed as limiting the present invention.
Example 1
Fig. 1 is a flow chart of a method for frequency-increasing a pre-stack gather based on a wavelet cepstrum according to embodiment 1 of the present invention, as shown in fig. 1, the method for frequency-increasing a pre-stack gather based on a wavelet cepstrum includes:
s1, acquiring prestack gather data, and transforming the prestack gather data into a wavelet domain by utilizing wavelet transformation to obtain a multi-scale seismic time spectrum.
It should be noted that wavelet transformation is a new transformation analysis method, which inherits and develops the concept of short-time fourier transformation localization, and overcomes the disadvantages that the window size does not change with frequency, and the like, so that a 'time-frequency' window which changes with frequency can be provided, and the wavelet transformation analysis method is an ideal tool for carrying out time-frequency analysis and processing of signals. In the invention, wavelet transformation is adopted to transform the prestack gather data into a wavelet domain for processing, and the characteristic that the wavelet can change in time and space in actual seismic propagation is reserved by utilizing wavelet transformation space (time) and frequency local transformation, so that the problem that the traditional deconvolution method cannot accurately model and process the time and space change of the wavelet when the prestack gather is frequency-increased is solved.
In an alternative embodiment, the wavelet transform is expressed as:
wherein, psi is a,τ (t) represents a wavelet basis function, a represents a scale of controlling the wavelet function, and τ and t represent a shift amount and time, respectively.
S2, performing frequency extension on the multi-scale seismic time spectrum by using a cepstrum frequency-raising method to obtain a frequency extension result of the multi-scale seismic time spectrum after frequency extension.
It should be noted that, cepstrum analysis is a method for performing linear prediction in the frequency domain, and may extract the dominant frequency information of the signal. According to the invention, frequency information of different scales can be obtained by carrying out cepstrum analysis on the frequency spectrum of the seismic channel. Then, the result of the cepstrum analysis is subjected to frequency-up processing in the wavelet domain. Compared with the traditional deconvolution method, the method provided by the invention has the advantages that the problem of resolution reduction caused by main frequency space-time variation in the seismic data can be effectively recovered by carrying out cepstrum and frequency lifting in the wavelet domain, and the resolution and the frequency bandwidth of the prestack gather are improved.
The frequency expansion of the multi-scale seismic time spectrum by using a cepstrum frequency-raising method comprises the following steps:
and S21, transforming each single-scale seismic time spectrum in the multi-scale seismic time spectrum into a cepstrum time frequency domain to obtain a cepstrum signal.
The theory of research on wavelets by Rosa et al (1991) in combination with Ricker (1977) suggests that: the reflection coefficients affect only a detailed portion of the amplitude spectrum of the seismic record, and the seismic wavelet determines the general shape of the amplitude spectrum of the seismic wavelet. Therefore, in the invention, the time spectrum of the non-stationary seismic trace needs to be transformed into a cepstrum time-frequency domain, so that the frequency information of each scale is acquired.
Wherein transforming a single-scale seismic time spectrum of the multi-scale seismic time spectrum to a cepstrum time-frequency domain comprises:
lnG(τ,f)＝lnW(τ,f)+lnR(τ,f)
in the above equation, G (τ, f) represents the time spectrum of the non-stationary seismic record, W (τ, f) represents the time spectrum of the time-varying wavelet, and R (τ, f) represents the reflection coefficient time spectrum.
The time spectrum G (τ, f) of the decaying seismic trace is approximately equal to the wavelet spectrum ω (f), and the product between the decay function a (τ, f) and the reflection coefficient time spectrum R (τ, f) can be expressed as:
|G(τ,f)|≈|ω(f)|·|a(τ,f)|·|R(τ,f)|
further, the time spectrum of the time-varying wavelet is expressed as:
W(τ,f)＝a(τ,f)*ω(f)
in the above equation, a (τ, f) represents the decay function, and ω (f) represents the wavelet spectrum.
Where the decay function a (τ, f) and the wavelet spectrum ω (f) are combined to represent the time spectrum W (τ, f) of the time-varying wavelet, i.e. W (τ, f) =a (τ, f) ×ω (f), so that the time spectrum of the non-stationary seismic record can be represented by the product of the time-varying wavelet amplitude spectrum and the reflection coefficient time spectrum R (τ, f), i.e.:
|G(τ,f)|≈|W(τ,f)|·|R(τ,f)|
and S22, smoothing the cepstrum signal through smoothing cepstrum to obtain a time spectrum for estimating the wavelet. Wherein smoothing the cepstrum signal by smoothing the cepstrum signal comprises:
|W(τ,f)|≈exp(ployfit(G ln (τ,f)))
in the above, G ln (τ, f) represents the time spectrum of the cepstral non-stationary seismic record, exp () represents the exponential function, ployfit () represents the curve fitting function.
Step S23, calculating the time spectrum for estimating the wavelet in the wavelet domain to obtain the reflection coefficient time spectrum.
Wherein calculating the time spectrum for estimating wavelets in the wavelet domain comprises:
in the above, mu is the prevention of denominatorZero-value introduced parameter, A max Represents the maximum value of the frequency spectrum |w (τ, f) | at the time of dynamic wavelet. In addition, according to the deconvolution theory, the reflection coefficient time spectrum R (τ, f) can be obtained as long as the dynamic wavelet time spectrum |w (τ, f) | can be accurately estimated, thereby realizing time-frequency domain deconvolution.
Repeating the steps S21 to S23 can realize frequency expansion of the pre-stack gather data. The resolution of the seismic records can be significantly improved by applying wavelet transforms to multi-scale decomposition and frequency expansion of the seismic data.
And step S3, performing inverse wavelet transformation on the multi-scale seismic time spectrum frequency expansion result to obtain pre-stack gather data after frequency expansion.
Wherein performing an inverse wavelet transform on the multi-scale seismic time-frequency spectrum frequency expansion result comprises:
in the above, C ψ Parameters indicating that wavelet satisfies tolerance conditions, WT f (a, τ) represents the wavelet transform result of the signal f (t). It should be noted that the method is constrained by the signal-to-noise ratio of the original seismic data, and the original data needs to reach a certain signal-to-noise ratio to obviously improve the resolution.
In summary, the wavelet domain cepstrum method pre-stack gather frequency-raising technology combines wavelet transformation and cepstrum analysis, and by performing time-frequency analysis and frequency-raising processing in a wavelet domain, the problem of main frequency space-time variation of pre-stack gather depth layers and far and near channel seismic data can be effectively solved, and the resolution of seismic records is improved.
In order to illustrate the beneficial effects of the pre-stack gather frequency-increasing method based on wavelet cepstrum, practical data of a certain area is taken as an example, and the method is described with reference to an effect diagram. Specifically, fig. 2 is a comparison chart of an original gather before frequency boost and a gather after wavelet cepstrum frequency boost provided in embodiment 1 of the present invention, and fig. 3 is a comparison chart of AVO fitting analysis provided in embodiment 1 of the present invention, as shown in fig. 2 and fig. 3, after the pre-stack gather is processed by the wavelet cepstrum frequency boost method, the following improvement of the results can be observed:
(1) Improving the longitudinal resolution: the wavelet cepstrum frequency-raising method can effectively improve the longitudinal resolution of the gathers, the details of the underground structure and the reflection interface are clearer, and a foundation is laid for the subsequent inversion work;
(2) Maintaining the relative energy relationship: the trace set processed by the wavelet cepstrum frequency-raising method still maintains the relative energy relation of the longitudinal phase axis of the trace set in the longitudinal direction. This means that the energy distribution relation among the various horizons is maintained, so that the optimized result is more accurate and reliable;
(3) Amplitude preservation performance: the transverse AVO rule of the gather is also maintained through wavelet cepstrum frequency boosting, and the method has good amplitude preservation.
In addition, by performing medium-angle superposition on the gather processed by the wavelet cepstrum frequency-raising method, as shown in fig. 4, the following conclusion can be obtained:
(1) Resolution is improved: through superposition of the middle-angle seismic sections, resolution can be effectively improved, so that details of seismic reflection are more obvious, and the underground structure can be accurately identified and explained;
(2) Maintaining relatively low frequency information: by performing spectral analysis on the stacked seismic profile of the target layer, it is known that low frequency information can be maintained without loss.
In conclusion, by the wavelet cepstrum frequency-raising method, the longitudinal resolution of the gather is improved, the relative energy relation of the longitudinal homophase axes of the gather and the AVO rule of the gather in the transverse direction are maintained, and the method has good amplitude preservation. At the same time, the resolution is improved while the relatively low frequency is effectively maintained. The technology fully utilizes the time domain and frequency domain information of the seismic data, can effectively recover the problem of resolution reduction caused by the space-time change of the main frequency in the seismic data, and improves the resolution and the frequency bandwidth of the prestack gather.
Example 2
Fig. 5 is a schematic structural diagram of an electronic device according to embodiment 2 of the present invention, and as shown in fig. 5, the electronic device includes a processor 21, a memory 22, an input device 23 and an output device 24; the number of processors 21 in the computer device may be one or more, one processor 21 being taken as an example in fig. 5; the processor 21, the memory 22, the input means 23 and the output means 24 in the electronic device may be connected by a bus or by other means, in fig. 5 by way of example.
The memory 22 serves as a computer-readable storage medium for storing software programs, computer-executable programs, and modules. The processor 21 executes various functional applications of the electronic device and data processing by running software programs, instructions and modules stored in the memory 22, i.e., implements the wavelet cepstrum-based pre-stack frequency-raising method of embodiment 1.
The memory 22 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for functions; the storage data area may store data created according to the use of the terminal, etc. In addition, the memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, memory 22 may further include memory remotely located relative to processor 21, which may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 23 may be used to receive an id and a password entered by a user, etc. The output device 24 is used for outputting the distribution network page.
Example 3
Embodiment 3 of the present invention also provides a computer-readable storage medium for implementing the wavelet cepstrum-based pre-stack frequency-raising method as provided in embodiment 1 when executed by a computer processor.
The storage medium containing computer executable instructions provided by the embodiments of the present invention is not limited to the method operations provided in embodiment 1, and may also perform the related operations in the pre-stack gather frequency-boosting method based on wavelet cepstrum provided in any embodiment of the present invention.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims (10)

1. The pre-stack channel set frequency-increasing method based on wavelet cepstrum is characterized by comprising the following steps:
acquiring prestack gather data, and transforming the prestack gather data into a wavelet domain by utilizing a wavelet transformation formula to obtain a multi-scale earthquake time spectrum;
the frequency of the multi-scale earthquake time frequency spectrum is developed by adopting a cepstrum frequency raising method, and a multi-scale earthquake time frequency spectrum frequency development result after frequency development is obtained;
and performing inverse wavelet transformation on the frequency spectrum frequency expansion result in the multi-scale earthquake to obtain pre-stack gather data after frequency expansion.
2. The wavelet cepstrum-based prestack gather frequency raising method according to claim 1, wherein the wavelet transform is expressed as:
wherein, psi is a,τ (t) represents a wavelet basis function, a represents a scale of controlling the wavelet function, and τ and t represent a shift amount and time, respectively.
3. The wavelet cepstrum-based pre-stack gather frequency boosting method of claim 1, wherein the frequency boosting of the multi-scale seismic time spectrum by using cepstrum frequency boosting method comprises:
transforming each single-scale seismic time spectrum in the multi-scale seismic time spectrum into a cepstrum time frequency domain to obtain a cepstrum signal;
smoothing the cepstrum signal through smooth cepstrum to obtain a time spectrum for estimating wavelet;
and calculating the time spectrum for estimating the wavelet in the wavelet domain to obtain a reflection coefficient time spectrum.
4. A wavelet cepstrum-based pre-stack frequency enhancement method as claimed in claim 3, wherein transforming a single-scale seismic-time spectrum of said multi-scale seismic-time spectrum to a cepstrum time-frequency domain comprises:
lnG(τ,f)＝lnW(τ,f)+lnR(τ,f)
in the above equation, G (τ, f) represents the time spectrum of the non-stationary seismic record, W (τ, f) represents the time spectrum of the time-varying wavelet, and R (τ, f) represents the reflection coefficient time spectrum.
5. The wavelet cepstrum-based pre-stack frequency enhancement method of claim 4, wherein the time spectrum of the time-varying wavelet is represented by:
W(τ,f)＝a(τ,f)*ω(f)
in the above equation, a (τ, f) represents the decay function, and ω (f) represents the wavelet spectrum.
6. The wavelet cepstrum-based pre-stack frequency enhancement method of claim 4, wherein smoothing the cepstrum signal by smoothing the cepstrum comprises:
|W(τ,f)|≈exp(ployfit(G ln (τ,f)))
in the above, G ln (τ, f) represents the time spectrum of the cepstral non-stationary seismic record, exp () represents the exponential function, ployfit () represents the curve fitting function.
7. The wavelet cepstrum-based pre-stack frequency enhancement method of claim 6, wherein calculating the time spectrum for estimating wavelets in the wavelet domain comprises:
in the above, mu is a parameter for preventing zero value from being introduced in denominator, A max Represents the maximum value of the frequency spectrum |w (τ, f) | at the time of dynamic wavelet.
8. The wavelet cepstrum-based prestack gather frequency boosting method of claim 2, wherein performing an inverse wavelet transform on the multi-scale seismic-time spectrum frequency development results comprises:
in the above, C ψ Parameters indicating that wavelet satisfies tolerance conditions, WT f (a, τ) represents the wavelet transform result of the signal f (t).
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the wavelet cepstrum-based pre-stack frequency-raising method of claims 1 to 8 when the program is executed.
10. A computer readable storage medium having stored thereon a computer program which when executed by a processor implements the wavelet cepstrum-based pre-stack frequency enhancement method of claims 1 to 8.
CN202311267483.7A 2023-09-27 2023-09-27 Pre-stack gather frequency-increasing method, device and medium based on wavelet cepstrum Pending CN117289343A (en)

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