CN109669212B - Seismic data processing method, stratum quality factor estimation method and device - Google Patents
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Abstract
The invention relates to a seismic data processing method, a stratum quality factor estimation method and a stratum quality factor estimation device, which are used for carrying out static correction, spherical diffusion compensation, prestack noise attenuation and earth surface consistency amplitude compensation on initial seismic data, extracting seismic wavelets by a high-order statistic method after stacking, obtaining an initial quality factor by a spectral ratio method, then removing interference of the initial quality factor in a main measuring line direction and a connecting line direction by a high-density attribute filtering method, finally obtaining an optimized quality factor, and carrying out inverse Q filtering by using the quality factor to obtain finally processed seismic data. The method can obtain an accurate quality factor Q value according to the existing seismic data under the condition of lacking surface layer survey information and VSP data, carries out inverse Q filtering processing, recovers seismic data amplitude information, and provides a reliable basis for seismic inversion through the seismic data processed by inverse Q filtering and fidelity and amplitude preservation.
Description
Technical Field
The invention belongs to the technical field of petroleum exploration seismic data processing, and particularly relates to a seismic data processing method, a stratum quality factor estimation method and a stratum quality factor estimation device.
Background
In seismic data, seismic waves undergo energy attenuation and velocity dispersion as they propagate through an incompletely elastic subsurface medium. Energy attenuation causes the energy of deep stratum seismic waves to be weaker, and influences the signal-to-noise ratio and resolution of seismic data. The inverse Q filtering is an effective method for compensating the absorption effect of the earth, can compensate the amplitude attenuation and frequency loss of seismic waves, enhances the energy of weak reflected waves, and further improves the signal-to-noise ratio and resolution of seismic data.
The Chinese patent with publication number 106646601 discloses a shallow, middle and deep three-dimensional Q value establishing method with multi-information joint constraint, which utilizes surface layer survey information to carry out constraint through surface layer Q value measurement data and establishes a relation curve of the Q value and a speed value at a measurement point position; under the constraint of the velocity value, obtaining a shallow three-dimensional velocity model through high-precision constraint chromatography inversion; obtaining a shallow three-dimensional Q value of a depth domain by utilizing a shallow three-dimensional speed model and a relation curve of the Q value and the speed value at the position of a measuring point; establishing a three-dimensional velocity model of a middle and deep layer by using seismic data; under the constraint of the three-dimensional speed model, solving a three-dimensional Q value of a middle and deep layer; and performing time-depth or deep-time conversion, converting the shallow three-dimensional Q value and the middle-deep three-dimensional Q value into one domain, effectively fusing the shallow three-dimensional Q value and the middle-deep three-dimensional Q value by utilizing a sine-cosine matching constraint three-dimensional fusion technology, establishing the shallow middle-deep three-dimensional Q value containing near-surface factors, and effectively solving the problem of the fracture of the shallow Q value and the middle-deep Q value.
Chinese patent publication No. 103913770 provides a method for processing seismic data based on VSP data, which compensates amplitude of seismic data by using reference VSP data to obtain amplitude-compensated seismic data; taking a down-going longitudinal wave of the VSP data as a target wavelet, and shaping the seismic data after amplitude compensation by referring to the target wavelet to obtain shaped seismic data; estimating the Q values of different layers by utilizing VSP data, and counting the Q values of the different layers to obtain a global Q value; and performing inverse Q filtering on the shaped seismic data by using the global Q value to obtain the filtered seismic data.
The existing Seismic data processing method utilizes surface multi-information joint constraint, Vertical Seismic Profiling (VSP) data or interwell data for processing, and can solve reliable quality factors to a certain extent and effectively improve the precision of inverse Q filtering.
Disclosure of Invention
The invention aims to provide a seismic data processing method, a stratum quality factor estimation method and a stratum quality factor estimation device, which are used for solving the problems that when surface survey information or VSP (vertical seismic profiling) data are lacked in seismic data processing, an accurate quality factor is obtained and the accuracy of inverse Q filtering is improved.
In order to solve the above technical problem, the present invention provides a seismic data processing method, which includes the following steps:
1) acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; then reducing abnormal amplitude in the seismic data by adopting a prestack noise attenuation method;
2) eliminating the energy difference of seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume;
3) extracting seismic wavelets from the superimposed pure wave data volume, and solving the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets; and performing inverse Q filtering on the prestack gather data by using the quality factor Q value to obtain filtered seismic data.
Performing inverse Q filtering on the prestack gather data by using the optimized quality factor Q value, wherein the optimization method comprises the following steps:
performing spectrum analysis on the quality factor Q value obtained in the step 3) to determine an interference frequency band, and removing the interference in the interference frequency band in the main measuring line direction and the connecting line direction selected by the Q value to obtain an optimized quality factor Q value.
And 3) extracting seismic wavelets from the stacked pure wave data volume by adopting a high-order statistical method.
The high-order statistical method is a cumulant matching method, and the cumulant matching method for extracting the seismic wavelet comprises the following steps:
and dividing the superposition pure wave data volume into different time windows, performing Fourier transform on the input seismic channel in each time window to obtain a phase spectrum of fourth-order cumulant, performing phase expansion by using the phase spectrum of the fourth-order cumulant to obtain a phase spectrum of the seismic wavelet, and further solving the seismic wavelet in a time domain.
In order to solve the above technical problem, the present invention further provides a formation quality factor estimation method, comprising the following steps:
1) acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; then reducing abnormal amplitude in the seismic data by adopting a prestack noise attenuation method;
2) eliminating the energy difference of seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume;
3) and extracting seismic wavelets from the superimposed pure wave data volume, and calculating the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets.
Performing inverse Q filtering on the prestack gather data by using the optimized quality factor Q value, wherein the optimization method comprises the following steps:
performing spectrum analysis on the quality factor Q value obtained in the step 3) to determine an interference frequency band, and removing the interference in the interference frequency band in the main measuring line direction and the connecting line direction selected by the Q value to obtain an optimized quality factor Q value.
And 3) extracting seismic wavelets from the stacked pure wave data volume by adopting a high-order statistical method.
The high-order statistical method is a cumulant matching method, and the cumulant matching method for extracting the seismic wavelet comprises the following steps:
and dividing the superposition pure wave data volume into different time windows, performing Fourier transform on the input seismic channel in each time window to obtain a phase spectrum of fourth-order cumulant, performing phase expansion by using the phase spectrum of the fourth-order cumulant to obtain a phase spectrum of the seismic wavelet, and further solving the seismic wavelet in a time domain.
To solve the above technical problem, the present invention further provides a formation quality factor estimation apparatus, including a processor for executing instructions to implement the following method:
1) acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; then reducing abnormal amplitude in the seismic data by adopting a prestack noise attenuation method;
2) eliminating the energy difference of seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume;
3) and extracting seismic wavelets from the superimposed pure wave data volume, and calculating the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets.
Performing inverse Q filtering on the prestack gather data by using the optimized quality factor Q value, wherein the optimization method comprises the following steps:
performing spectrum analysis on the quality factor Q value obtained in the step 3) to determine an interference frequency band, and removing the interference in the interference frequency band in the main measuring line direction and the connecting line direction selected by the Q value to obtain an optimized quality factor Q value.
The invention has the beneficial effects that: the method comprises the steps of carrying out a series of processing on initial seismic data, wherein the processing comprises static correction, spherical surface diffusion compensation, pre-stack noise attenuation and earth surface consistency amplitude compensation, extracting seismic wavelets from the stacked data by a high-order statistic method, obtaining initial quality factors by a spectral ratio method, removing interference of the initial quality factors in the main measuring line direction and the connecting line direction by a high-density attribute filtering method, obtaining optimized quality factors finally, and carrying out inverse Q filtering by using the quality factors to obtain the finally processed seismic data. The method can obtain an accurate quality factor Q value according to the existing seismic data under the condition of lacking surface layer survey information and VSP data, carries out inverse Q filtering processing, recovers seismic data amplitude information, and provides a reliable basis for seismic inversion through the seismic data processed by inverse Q filtering and fidelity and amplitude preservation.
Drawings
FIG. 1 is a seismic data processing flow diagram of the present invention;
FIG. 2 is a schematic diagram of wavelets extracted from a post-stack data volume using a fourth order cumulant method;
FIG. 3 is a diagram showing Q values obtained by the spectral ratio method;
FIG. 4 is a schematic diagram of the Q value obtained by the spectral ratio method after editing and smoothing;
FIG. 5-a is a schematic diagram of the cross-sectional effect of the pre-Q filter stack;
fig. 5-b is a schematic diagram of the superimposed cross-sectional effect after inverse Q filtering.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings.
The embodiment of the invention provides a seismic data processing method which can recover seismic amplitude information and is independent of surface survey information and VSP data constraint and high-precision inverse Q filtering, and is realized by the following specific steps:
1. and acquiring prestack gather data and a superposition pure wave data volume.
1.1, performing static correction processing on the seismic data of the target area to solve the static correction problem of seismic data; compensating the loss energy of the seismic data spherical diffusion in the time direction after the static correction processing by using the spherical diffusion compensation; reducing abnormal amplitude in the seismic data by adopting a prestack noise attenuation method, and improving the signal-to-noise ratio of the seismic data; after abnormal amplitude is processed, the energy of the seismic data is compensated in the space direction by using a ground surface consistency amplitude compensation method, and the difference of the energy of the seismic data between the cannons and the tracks is eliminated. And obtaining pre-stack gather data after the processing.
And 1.2, overlapping the pre-stack gather data to obtain an overlapped pure wave data volume.
2. Seismic wavelets are extracted from the stacked data volume obtained in step 1.2 by a fourth-order cumulant matching method, as shown in fig. 2. The fourth order cumulant matching method is used as one of the high order statistical methods, and is an estimation method for non-minimum phase wavelets of seismic signals, wherein wavelets are extracted by utilizing the phase information characteristics of signals contained in the high order statistics based on the fourth order cumulant of the signals and a fourth order spectrum of the signals. The high-order statistical method is the prior art, and is specifically referred to in journal of petroleum geophysical prospecting, volume 43, pages 123-128 of phase 1, and article entitled "summary of seismic wavelet extraction method" by Yangbeijie.
2.1, firstly, dividing the stacked data volume obtained in the step 1.2 into different time windows, and performing Fourier transform on the input seismic channels in each time window to obtain a phase spectrum of the fourth-order cumulant.
2.2, performing phase expansion on the phase spectrum of the fourth-order cumulant obtained in the step 2.1 by adopting a least squares method to obtain the phase spectrum of the seismic wavelet, and performing stabilization and smoothing treatment on the phase spectrum to obtain the accurate phase spectrum of the seismic wavelet.
2.3, after the wavelet phase spectrum of the step 2.2 is obtained more accurately, the seismic wavelets in the time domain are obtained by utilizing a linear equation system.
3. The wavelet obtained in step 2.3 is input as a reference signal, the superimposed pure wave data volume obtained in step 1.2 is divided into time windows in the longitudinal direction, and the ratio of the amplitude spectrum of the reference signal to the amplitude spectrum of each downward overlapping time window is logarithmized by adopting a spectrum ratio method to calculate the Q value, as shown in fig. 3. The principle is as follows:
considering the absorption of the formation, the seismic amplitude spectrum can be approximated as follows:
where f is the frequency and B (f, t) is the seismic amplitude spectrum of the seismic travel time t. Q is the quality factor of the medium, B (f, t)0) Is seismic travel time t0Seismic amplitude spectra of (a). A (t) is a frequency independent factor at t1And t2The time is as follows:
taking logarithm of the ratio of the two formulas to obtain;
wherein, C ═ In (a (t)2)/A(t1) F and B are unknown, where we assume that Q is independent of frequency, and for each frequency value we use the equation (3.4) to obtain a log spectral ratio, which is the frequency with a slope of-pi (t)2-t1) The function of/Q, each slope obtains a Q value, we can estimate the Q value from the prestack shot gather, for a plurality of strata, the principle of equivalent Q values can be used, the stratum is assumed to be composed of n layers, and the quality factor of each layer is Q1、Q2、…、QnThe travel time of the seismic waves through the adjacent strata is t1、t2、…、tnEquivalent Q value of each layer1eff、Q2eff、…、QneffCan be estimated from the above formula. For the estimation of the Q value of each layer, there are two methods: one method is that the Q value of the nth layer is related to the propagation time of seismic waves on each layer, the Q value of each layer and the equivalent Q value of the nth layer, and the formula is as follows:
wherein, tnFor travel time of seismic waves through the nth formation, QnIs the quality factor of the n-th layer, QneffIs the equivalent Q value of the n-th layer, tiFor the travel time of seismic waves through the i-th stratum, i-n-1, QiIs the quality factor of the ith layer.
4. And (4) optimizing the Q value obtained in the step (3) to obtain an optimized Q value, which is shown in FIG. 4.
4.1 carrying out spectrum analysis on the Q value obtained in the step 3 and determining the frequency band range of the low-frequency interference so as to eliminate the low-frequency noise in the Q value.
4.2 the Q value obtained in the step 3 is selected to the direction of the main measuring line, and the low-frequency interference in the direction of the main measuring line is removed by filtering in the wave number domain by applying the frequency band range of the low-frequency interference obtained by analyzing in the step 4.1 by adopting a high-density attribute filtering method.
4.3 the Q value filtered by the main line measuring direction in the step 4.2 is selected to be in the line measuring direction of the connecting line, a geological filtering method is adopted, the frequency band range of the low-frequency interference obtained by analyzing in the step 4.1 is applied to filtering in a wave number domain, the low-frequency interference in the direction of the connecting line is removed, and the optimized Q value is obtained.
5. And (4) applying the step 4.3 to obtain an optimized Q value, and performing inverse Q filtering on the pre-stack gather data obtained in the step 1.1, as shown in FIG. 5.
The method can obtain an accurate quality factor Q value according to the existing seismic data under the condition of lacking surface layer survey information and VSP data, carries out inverse Q filtering processing, recovers seismic data amplitude information, and provides a reliable basis for seismic inversion through the seismic data processed by inverse Q filtering and fidelity and amplitude preservation.
The invention also provides a stratum quality factor estimation method, which comprises the following steps:
acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; a prestack noise attenuation method is then employed to reduce anomalous amplitudes in the seismic data.
And eliminating the energy difference of the seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume. And extracting seismic wavelets from the superimposed pure wave data volume, and calculating the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets.
And performing spectrum analysis on the quality factor Q value to determine an interference frequency band, and removing the interference in the interference frequency band in the main measuring line direction and the connecting line direction from the Q value by adopting a high-density attribute filtering method to obtain an optimized quality factor Q value.
Since the description of the formation quality factor estimation method in one embodiment of the formation quality factor estimation method is sufficiently clear and complete, the formation quality factor estimation method will not be described in detail.
The invention also provides a formation quality factor estimation device, which comprises a processor, wherein the processor is used for executing the instructions for realizing the following method:
acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; a prestack noise attenuation method is then employed to reduce anomalous amplitudes in the seismic data.
And eliminating the energy difference of the seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume. And extracting seismic wavelets from the superimposed pure wave data volume, and calculating the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets.
The formation quality factor estimation device is a computer solution based on the formation quality factor estimation method of the invention, namely a software framework, which can be applied to a computer, and the description of the method is clear and complete enough, so the detailed description is not needed.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (7)
1. A seismic data processing method, comprising the steps of:
1) acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; then reducing abnormal amplitude in the seismic data by adopting a prestack noise attenuation method;
2) eliminating the energy difference of seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume;
3) extracting seismic wavelets from the superimposed pure wave data volume, and solving the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets; performing inverse Q filtering on the prestack gather data by using a quality factor Q value to obtain filtered seismic data;
performing inverse Q filtering on the prestack gather data by using the optimized quality factor Q value, wherein the optimization method comprises the following steps:
performing spectrum analysis on the quality factor Q value obtained in the step 3) to determine an interference frequency band, and removing the interference in the interference frequency band in the main measuring line direction and the connecting line direction selected by the Q value to obtain an optimized quality factor Q value.
2. A method of seismic data processing according to claim 1, wherein the seismic wavelets are extracted from the stacked pure wave data volume in step 3) using higher order statistical methods.
3. The seismic data processing method of claim 2, wherein the higher order statistical method is cumulant matching, and the cumulant matching method for extracting seismic wavelets comprises the steps of:
and dividing the superposition pure wave data volume into different time windows, performing Fourier transform on the input seismic channel in each time window to obtain a phase spectrum of fourth-order cumulant, performing phase expansion by using the phase spectrum of the fourth-order cumulant to obtain a phase spectrum of the seismic wavelet, and further solving the seismic wavelet in a time domain.
4. A formation quality factor estimation method, comprising the steps of:
1) acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; then reducing abnormal amplitude in the seismic data by adopting a prestack noise attenuation method;
2) eliminating the energy difference of seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume;
3) extracting seismic wavelets from the superimposed pure wave data volume, and solving the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets;
performing inverse Q filtering on the prestack gather data by using the optimized quality factor Q value, wherein the optimization method comprises the following steps:
performing spectrum analysis on the quality factor Q value obtained in the step 3) to determine an interference frequency band, and removing the interference in the interference frequency band in the main measuring line direction and the connecting line direction selected by the Q value to obtain an optimized quality factor Q value.
5. The method of claim 4, wherein the seismic wavelets in step 3) are extracted from the stacked pure wave data volume using higher order statistics.
6. The method of estimating a formation quality factor according to claim 5, wherein the higher-order statistical method is cumulant matching, and the cumulant matching method for extracting seismic wavelets comprises the steps of:
and dividing the superposition pure wave data volume into different time windows, performing Fourier transform on the input seismic channel in each time window to obtain a phase spectrum of fourth-order cumulant, performing phase expansion by using the phase spectrum of the fourth-order cumulant to obtain a phase spectrum of the seismic wavelet, and further solving the seismic wavelet in a time domain.
7. A formation quality factor estimation apparatus comprising a processor for executing instructions that implement a method comprising:
1) acquiring seismic data of a stratum, and after statically correcting the seismic data, compensating energy lost by spherical diffusion in the time direction by adopting a geometric diffusion compensation method; then reducing abnormal amplitude in the seismic data by adopting a prestack noise attenuation method;
2) eliminating the energy difference of seismic data between shots and between tracks by adopting a ground surface consistency compensation method to obtain pre-stack gather data, and stacking the pre-stack gather data to obtain a stacked pure wave data volume;
3) extracting seismic wavelets from the superimposed pure wave data volume, and solving the quality factor Q value of the stratum by adopting a spectral ratio method for the seismic wavelets;
performing inverse Q filtering on the prestack gather data by using the optimized quality factor Q value, wherein the optimization method comprises the following steps:
performing spectrum analysis on the quality factor Q value obtained in the step 3) to determine an interference frequency band, and removing the interference in the interference frequency band in the main measuring line direction and the connecting line direction selected by the Q value to obtain an optimized quality factor Q value.
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| CN112764095B (en) * | 2019-10-21 | 2023-03-14 | 中国石油化工股份有限公司 | VSP data Q value calculation method and system based on generalized energy ratio |
| CN112711074B (en) * | 2019-10-24 | 2024-03-26 | 中国石油化工股份有限公司 | Denoising method and device for seismic first arrival wave |
| CN113138419B (en) * | 2020-01-20 | 2022-05-10 | 中国石油天然气集团有限公司 | Method and device for extracting downlink wavelet and attenuation parameters |
| CN111781646B (en) * | 2020-06-29 | 2022-04-15 | 广州海洋地质调查局 | Amplitude-preserving and fidelity-preserving linear coherent noise suppression method and processing terminal |
| CN111880218A (en) * | 2020-07-13 | 2020-11-03 | 西南石油大学 | Inversion wavelet dictionary construction method based on quality factor |
| CN114252910A (en) * | 2020-09-25 | 2022-03-29 | 中国石油天然气股份有限公司 | Seismic quality factor determination method and device |
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| US20100097886A1 (en) * | 2008-10-20 | 2010-04-22 | Anthony James Day | Method for determining formation quality factor from dual-sensor marine seismic signals |
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| US10466378B2 (en) * | 2014-09-03 | 2019-11-05 | Pgs Geophysical As | Impact assessment of marine seismic surveys |
| CN104360382B (en) * | 2014-10-31 | 2018-12-11 | 中国石油化工股份有限公司 | A method of oil and gas detection is carried out using post-stack seismic data |
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