CN105092343B - Remove the method and the method for the thin reservoir of identification prediction and gas-bearing formation of thin layer tuning effect - Google Patents
Remove the method and the method for the thin reservoir of identification prediction and gas-bearing formation of thin layer tuning effect Download PDFInfo
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Abstract
The invention discloses a kind of method for removing thin layer tuning effect, and the method for a kind of thin reservoir of identification prediction and gas-bearing formation.The method for removing thin layer tuning effect comprises the following steps：The data of the prestack seismic gather in target work area is pre-processed to correct the signal to noise ratio of lineups and/or raising Prestack seismic data；The frequency spectrum progress wavelet scale of pretreated Prestack seismic data is decomposed to obtain some small echos with different scale, analyzes and determines wavelet scale to be pressed；The small echo of the different scale is reconstructed by building dimensional constraints item, to weaken wavelet scale information to be pressed；De-tuned seismic channel set is formed using the small echo after reconstruct and Prestack seismic data convolution.The present invention proposes to decompose the specific aim method for removing thin layer tuning effect based on wavelet scale, by suppressing seismic data large scale information, recover the true AVO features caused by thin reservoir physical parameter, to improve the accuracy rate of thin reservoir (or thin oil and gas zone) earthquake prediction.
Description
Technical field
The present invention relates to oil gas technical field of physical geography, in particulars relate to a kind of based on prestack trace gather removal thin layer tuning
Method, and a kind of using the method identification that thin layer tuning is removed based on prestack trace gather and predict the side of thin reservoir and gas-bearing formation
Method.
Background technology
How lithology subtle pool as one of highest priority of China's oil-gas exploration at this stage, effectively utilizes earthquake
Data carries out the prediction of thin reservoir into the task of top priority.
Predicted for thin sand, numerous scholars had carried out some new researchs and attempted in recent years.In poststack earthquake prediction side
Face, Xu Liying etc. (2006, the phase of geophysical prospecting for oil the 3rd, thin reservoir prediction is carried out using Spectral Decomposition Technique), Yang Guixiang etc.
(2006, the phase of petroleum exploration the 3rd, the high-resolution inversion technology based on tuned frequency and scaling down processing), Castagna etc.
(phases of 2003, The Leading Edge the 2nd, Detection of low-frequency shadows associated
With hydrocarbon), Liu Wei etc. (2012, the phase of scientific observation the 5th, utilize Spectral Decomposition Technique to identify true and false oil-gas reservoir) application
Spectral Decomposition Technique has carried out the research of thin reservoir prediction.
In terms of pre-stack seismic prediction, and Zhao Wei etc. (2006, the phase of petroleum exploration the 6th, shadow of the thin reservoir tuning effect to AVO
Ring) it is assumed that when thickness of thin layer is more than 1/8 wavelength, thin layer tuning effect can make seismic reflection amplitude is relative to become big or diminish, but
AVO (Amplitude Versus Offset, amplitude with offset distance change) changing rule it is consistent, when thickness of thin layer is small
When 1/16 wavelength, thin layer tuning effect can cause AVO changing rules to invert.Pavilion justice China etc. (2010, petroleum geophysics
Explored for the 1st phase, application of the frequency dividing AVO technologies in the analysis of Zhujiangkou Basin Fanyu natural gas province gas-bearing property) take with different frequencies
Seismic amplitude difference caused by the absorption and decay of rate scope is starting point, using frequency dividing AVO technologies in Zhujiangkou Basin Fanyu
Certain effect is obtained in the gas-bearing property analysis of natural gas province.In addition, Zhao Wanjin etc. (2012, the phase of geophysical prospecting for oil the 3rd, one
Kind frequency domain AVO gas-oil detecting methods) a kind of thin reservoir hydrocarbons detection methods of frequency domain AVO are proposed, it will by time-frequency convert
Geological data is transformed into frequency domain, then interval of interest seismic amplitude (energy) is carried out with frequency and the situation of change of geophone offset
Research, so as to carry out the prediction of thin reservoir hydrocarbons and detection, including the porosity of rock stratum, density, lithology and fluid content.
Oil-gas reservoir velocity of longitudinal wave, density information are not only contained in AVO information, further comprises the important shear wave letter of oil-gas reservoir
Breath, to reducing seismic prospecting multi-solution, it is significant to effectively improve reservoir fluid accuracy of identification.However, into lithology
The oilfield prospecting developing middle and later periods, usual target reservoir is relatively thin, and buried depth is larger.When seismic data dominant frequency is relatively low, can cause
Certain tuning effect, cause thin reservoir AVO feature unobvious, so as to bring difficulty to reservoir and oil and gas prediction.
Due to prior art in thin reservoir sub-band forecast still based on Fourier Transform Technique, it is difficult to ensure prediction essence
Degree.In addition, being directed to post-stack seismic data application for the frequency splitting technology of thin layer tuning effect development, adjusted in a small number of prestack trace gathers more
In humorous effect analysis, mechanism caused by thin layer tuning effect is not systematically discussed, it is simply tentative to be opened using conventional frequency splitting technology
The primary analysis of thin layer tuning effect is opened up, without the specific aim solution for clearly proposing prestack trace gather removal tuning effect.
Therefore, in the prior art, it is no for thin reservoir prediction effectively to remove tuning effect to reach accurate
Really predict the ways and means of thin reservoir characteristic.
The content of the invention
The present invention is directed to above-mentioned technical problem, there is provided the method for removing thin layer tuning effect based on prestack trace gather,
This method comprises the following steps：
S101, the data to the prestack seismic gather in target work area are pre-processed to correct lineups and/or improve folded
The signal to noise ratio of preceding seismic data；
S102, wavelet scale carried out to the frequency spectrum of pretreated Prestack seismic data decompose to obtain some there are different chis
The small echo of degree, analyze and determine wavelet scale to be pressed；
S103, by building dimensional constraints item the small echo of the different scale is reconstructed, it is to be pressed to weaken
Wavelet scale information；
S104, de-tuned seismic channel set is formed using the small echo after reconstruct and Prestack seismic data convolution.
According to one embodiment of present invention, in step S101, using Residual moveout correction come to prestack seismic gather
Data pre-processed.
According to one embodiment of present invention, in step S101, using advantage domain τ-p conversion filtering come to pre-stack seismic
The data of trace gather is pre-processed, by spectrum sigtral response, the Attenuating Random Noise in the τ-p of advantage domain.
According to one embodiment of present invention, in step s 102, will be described pretreated in certain frequency band range
Prestack seismic data is decomposed into the small echo of several different scales, finds the pass between the small echo of each yardstick and corresponding dominant frequency
It is and is counted, so that it is determined that goes out to produce the large scale Wavelet Component of tuning effect.
According to one embodiment of present invention, it is based further on determining the Thickness Analysis of destination layer and the result of test
Produce the large scale wavelet information of tuning effect.
According to one embodiment of present invention, in step s 103, it is further comprising the steps of：
S103a, the matrix form for being added the spectral factorization of seismic channel set data amplitudes for different scale Wavelet-Weighted；
S103b, the coefficient entry to the matrix are estimated；
S103c, the coefficient entry obtained using estimation are weighted superposition to the small echo of the different scale, obtain being superimposed chi
The small echo of degree；
S103d, the coefficient entry is adjusted to build dimensional constraints item to weaken wavelet information to be pressed, wherein to be pressed
Wavelet scale information be large scale wavelet information.
According to one embodiment of present invention, in step S103b, by least-squares algorithm come to the matrix system
It is several to be estimated.
According to one embodiment of present invention, in step S103d, the small echo of the superposition yardstick after adjustment is carried out smooth
Amplitude spectrum of its enveloping surface as reconstruct small echo is obtained, so that in time-domain, reconstructs obtained small echo narrowly distributing, secondary lobe phase
To smaller；In frequency domain, wavelet low frequency composition is pressed, and frequency band range is wider.
According to another aspect of the present invention, a kind of identification that thin reservoir and gas-bearing formation are carried out based on prestack trace gather is additionally provided
With the method for prediction, it includes obtaining de-tuned seismic channel set using the method as described above for removing thin layer tuning effect,
Then AVO attributive analysises are carried out to the seismic channel set to identify and predict thin reservoir and gas-bearing formation.
According to one embodiment of present invention, AVO attributive analysises include intercept attributive analysis and gradient attribute is analyzed.
Present invention offers following beneficial effect：
By studying the mechanism of production of prestack seismic gather tuning effect, fundamentally propose a set of based on wavelet scale point
Solution removes the specific aim method of thin layer tuning effect, by suppressing seismic data large scale information, recovers thin reservoir physical parameter
Caused true AVO features, to improve the accuracy rate of thin reservoir (or thin oil and gas zone) earthquake prediction.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
Obtain it is clear that or being understood by implementing the present invention.The purpose of the present invention and other advantages can be by specification, rights
Specifically noted structure is realized and obtained in claim and accompanying drawing.
Brief description of the drawings
Fig. 1 a and Fig. 1 b are to remove thin layer based on the prestack trace gather that wavelet scale decomposes according to one embodiment of present invention
The method flow diagram of tuning effect；
Fig. 2 a are the schematic diagram datas of the model used according to one embodiment of present invention, wherein, from the left side of figure to
The right represents velocity of longitudinal wave, shear wave velocity and density successively；
Fig. 2 b are the poststack schematic diagrames for the seismic channel set for being synthesized 30Hz Ricker wavelets using forward modeling；
Fig. 3 a show the spectrogram of model geological data and using the frequency spectrum after Scale Decomposition reconstruct with different lines
Figure；
Fig. 3 b, which are shown, carries out the small echo after yardstick reconstruct using the method for the present invention；
Fig. 4 shows the seismic spectrum comparison diagram before and after dimensional constraints；
Fig. 5 a-5f contrasts show the de-tuned front and rear AVO signature analysis schematic diagrames of Scale Decomposition；
Fig. 6 a-6b show that log data picks up the AVO abnormal conditions at big 40 well box, 1 section thin gas-bearing formation bottom；
Fig. 7 a-7b contrasts show the de-tuned AVO abnormal conditions before and after the processing of the 897th survey line；And
Fig. 8 a-8b contrasts show the de-tuned P*G attributive analysis situations before and after the processing of the 897th survey line.
Embodiment
Embodiments of the present invention are described in detail below with reference to drawings and Examples, and how the present invention is applied whereby
Technological means solves technical problem, and the implementation process for reaching technique effect can fully understand and implement according to this.Need to illustrate
As long as not forming conflict, each embodiment in the present invention and each feature in each embodiment can be combined with each other,
The technical scheme formed is within protection scope of the present invention.
In addition, the flow of accompanying drawing can be in the computer system of such as one group computer executable instructions the step of illustrating
Middle execution, although also, show logical order in flow charts, in some cases, can be with different from herein
Order performs shown or described step.
One of core content of wavelet analysis-multiscale analysis is theoretical-is formed at 20 th century laters.With Fourier transformation
Compare, wavelet transformation has the characteristic of self-adapting window size, by signal decomposition to different scale space, different scale space pair
Answer different frequency bands.Therefore, signal is finer, more conducively handles.The technology is in well logging, gravity anomaly analysis, oil gas
The fields such as water boundaries identification are applied, and using less in thin reservoir seismic prediction.
The present invention attempts to suppress large scale component using the technology in thin reservoir prediction, weakens the shadow of tuning effect
Ring.Because seismic signal is that the small magnitude signal of the large scale signal and the thin reservoir of reflection by reflecting underground background information weights
It is formed by stacking.The AVO features of prestack seismic gather reflecting interface are influenceed by two factors：1st, single interface both sides physical property change shadow
Ring, using Zoeppritz equations as theoretical foundation；2nd, the influence of time thickness change, i.e. tuning effect.Specify the tuning of prestack trace gather
Effect mechanism of production is, with the increase of geophone offset, reflecting interface is compressed in a smaller window scope thin layer up and down,
This just increases the interference effect of upper and lower reflecting layer back wave, so as to enhance tuning effect.
Tuning effect is strong and weak relevant with the frequency of wavelet, and when time thickness is less than half-wavelength, tuning effect is to amplitude
Changing rule has an impact, therefore wavelet frequency is lower, and the scope by tuning effects is bigger.Therefore, the present invention passes through
Wavelet transformation carries out Scale Decomposition, suppresses the large scale composition of seismic data to a certain extent, weakens the interference of background information,
The purpose for weakening tuning effect is realized, so as to highlight contribution of the thin reservoir to seismic signal, improves thin reservoir (thin oil and gas zone)
Accuracy of identification.
The application of this method in the present invention is described in detail below.
As seen in figure la and lb, which show the prestack decomposed according to one embodiment of present invention based on wavelet scale
Trace gather removes the method flow diagram of thin layer tuning effect.This method starts from step S101, in this step, to target work area
The signal to noise ratio that the data of prestack seismic gather is pre-processed to correct lineups and improve Prestack seismic data.Preferably,
The data of prestack seismic gather is pre-processed using Residual moveout correction.Certain present invention can also use other quiet schools
Correction method corrects lineups, including but not limited to elevation calculation, model ing static correction, refraction static correction, tomographic statics etc..
In addition, the present invention further converts filtering to be pre-processed to the data of prestack seismic gather using advantage domain τ-p, pass through frequency
Spectral characteristics analysis, the Attenuating Random Noise in the τ p of advantage domain.The method of Attenuating Random Noise has many kinds, of the invention and unlimited
In this.
As shown in Figure 1a, in step s 102, wavelet scale point is carried out to the frequency spectrum of pretreated Prestack seismic data
Solution obtains some small echos with different scale, analyzes and determines wavelet scale to be pressed.
Specifically, the thought of wavelet scale decomposition is primarily based on, target work area prestack seismic gather frequency spectrum is analyzed,
In certain frequency band range, such as 5-120Hz scopes, pretreated Prestack seismic data is decomposed into several different chis
The small echo of degree, find the relation between the small echo of each yardstick and corresponding dominant frequency and counted, so that it is determined that going out to produce tune
The large scale Wavelet Component of humorous effect.According to an embodiment of the invention, scale parameter border is corresponded into dominant frequency to come out, its purpose
It is in order to which subsequently pointedly compacting mainly produces the large scale component of thin layer tuning effect.Then, actual work area target is passed through
Layer Thickness Analysis and testing research determined yardstick to be pressed later.
Wherein, the small echo quantity decomposed can be for example 20, and the invention is not restricted to this specific number, and the number should
It can be adjusted according to actual seismic situation.Said frequencies scope is also in this way, can be adjusted according to actual seismic situation
It is whole.
In step s 103, the small echo of the different scale is reconstructed by building dimensional constraints item, with reduction
Wavelet scale information to be pressed.In one embodiment, the wavelet reconstruction step is further realized by following sub-step,
As shown in Figure 1 b.
It is what different scale Wavelet-Weighted was added by the seismic channel set data amplitudes spectral factorization of model in step S103a
Matrix form；
In step S103b, the coefficient entry of matrix is estimated, usually, can by least-squares algorithm come pair
The coefficient entry of the matrix is estimated；
In S103c, the coefficient entry obtained using estimation is weighted superposition to the small echo of different scale, obtains being superimposed chi
The small echo of degree,
In step S103d, above-mentioned coefficient entry is adjusted to build dimensional constraints item to weaken wavelet information to be pressed, its
In wavelet scale information to be pressed be the large scale wavelet information determined before.
In step S103d, it is small as reconstructing that the small echo of the superposition yardstick after adjustment is smoothly obtained into its enveloping surface
The amplitude spectrum of ripple, so that in time-domain, obtained small echo narrowly distributing is reconstructed, secondary lobe is relatively small；It is low in frequency domain, small echo
Frequency composition is pressed, and frequency band range is wider.
Further, as shown in Figure 1a, in step S104, using the small echo after reconstruct and Prestack seismic data convolution come
Form de-tuned seismic channel set.
The present invention also provides a kind of method for identification and the prediction that thin reservoir and gas-bearing formation are carried out based on prestack trace gather, and it is used
The method of above-mentioned removal thin layer tuning effect obtains de-tuned seismic channel set, then to the seismic channel of the removal tuning effect
Collection carries out AVO attributive analysises to identify and predict thin reservoir and gas-bearing formation.Generally, AVO attributive analysises include intercept attributive analysis and
Gradient attribute is analyzed.Carry out the identification and prediction of thin reservoir and gas-bearing formation by application intercept and gradient attribute.
As shown in Figure 2 a, which show the model data that the present invention uses, wherein, from the left side of figure to the right successively table
Show velocity of longitudinal wave, shear wave velocity and density.30Hz Ricker wavelets Synthetic seismic gather such as Fig. 2 b institutes that forward modeling obtains
Show.Fig. 2 b are that the trace gather after forward modeling is shown, because being theoretical model trace gather, therefore do not pre-process and (pre-process only to reality
Border trace gather is done), de-tuned analysis directly is done to the model trace gather.The model trace gather ordinate is equivalent to time shaft, abscissa phase
When in offset distance.Model trace gather time shaft corresponds to the longitudinal axis of model, and modelling is relative to reference to follow-up real well target gas
The feature of thin gas-bearing formation, equivalent to low speed, low close, low-impedance gas-bearing formation section between longitudinal axis 60-90, exist between longitudinal axis 80-100
One obvious impedance interface by low value to high level, known by earthquake convolution theory, the 30HZ's of model and positive polarity
A strong wave peak can be produced in the interface after Ricker convolutions, the strong axle represents gas-bearing formation bottom circle, and trough thereon represents gas-bearing formation
Boundary is pushed up, the de-tuned AVO analyses of following model trace gather are directed to the two interfaces.Meanwhile the two interface features and actual number
According to similar, contrast verification can be done with actual data analysis very well.
Fig. 3 a show that seismic spectrum closes the comparison diagram of reconstruct yardstick frequency spectrum.Wherein, solid line represents model geological data frequency
Spectrum, and dotted line is the spectrum curve of Scale Decomposition reconstruct.It can thus be seen that yardstick reconstructed spectrum is similar to model geological data
Spectrum envelope face.Fig. 3 b show the multi-scale wavelet reconstructed using yardstick reconstructed spectrum.
Fig. 4 shows that seismic channel spectral contrast is analyzed before and after dimensional constraints, and solid line is seismic spectrum before dimensional constraints, dotted line
For seismic spectrum after dimensional constraints.As can be seen that earthquake record dominant frequency band frequency content is basically unchanged after dimensional constraints, low frequency
Composition is suppressed.
Fig. 5 a-5f compared for influence of the Scale Decomposition to thin bed seismic response AVO features, anti-to Synthetic seismic gather target
Penetrate a layer improvement for AVO features.Wherein, Fig. 5 a, 5c, 5e show the impulse response AVO features on thin layer top, 30Hz wavelets synthetically
The situation after recording and being de-tuned is shaken, and Fig. 5 b, 5d, 5f show that the impulse response AVO features at thin layer bottom, 30Hz wavelets are closed
Into earthquake record and it is de-tuned after situation.
The present invention is tested in certain gas field.As shown in figure 6 a and 6b, big 40 well box, 1 section thin gas-bearing formation bottom is carried out
AVO forward modelings are analyzed.Fig. 6 a show big 40 well Synthetic seismic gather, and AVO is abnormal with showing thin gas-bearing formation bottom by Fig. 6 b.Extract excessive
897th survey line of 40 wells has done following AVO analyses.Picked up by can be seen that original Jing Pangdaoji with big 40 well comparative analysis
Thin gas-bearing formation bottom AVO it is abnormal and the AVO anomalous variation trend of corresponding well opening position is completely contradicted (Fig. 7 a).Gone using Scale Decomposition
The method of tuning, remote geophone offset tuning effect is eliminated (shown in Fig. 7 b), the AVO features after de-tuned processing can be more preferable with well
Coincide.Meanwhile on P*G attribute sections, the attribute abnormal at thin gas-bearing formation bottom highlights (Fig. 8 a and figure after de-tuned processing
8b)。
The present invention (adjusts for influenceing factor-time thickness change of the true AVO features of prestack seismic gather reflecting interface
Humorous effect), it specify that prestack trace gather tuning effect mechanism of production.On this basis, the think of that the present invention is decomposed based on wavelet scale
Think, seismic channel set is decomposed into different scale, build dimensional constraints item, then each yardstick weighted superposition obtained reconstructing yardstick small
Ripple, large scale low frequency component (not being to filter out completely) is suppressed in restructuring procedure, weaken the interference of background information, realized to weaken and adjust
The purpose of humorous effect, so as to highlight contribution of the thin reservoir to seismic signal, improve thin reservoir (thin oil and gas zone) AVO identification essences
Degree.Due to what is developed the present invention be directed to lithological reservoir exploration exploitation, therefore its oil-gas field development to thin reservoir development
With high industrial utility value and popularizing application prospect.
Although disclosed herein embodiment as above, described content only to facilitate understand the present invention and adopt
Embodiment, it is not limited to the present invention.Any those skilled in the art to which this invention pertains, this is not being departed from
On the premise of the disclosed spirit and scope of invention, any modification and change can be made in the implementing form and in details,
But the scope of patent protection of the present invention, still should be subject to the scope of the claims as defined in the appended claims.
Claims (10)
- A kind of 1. method for removing thin layer tuning effect, it is characterised in that the described method comprises the following steps：S101, the data to the prestack seismic gather in target work area are pre-processed with correcting lineups and/or raising prestack The signal to noise ratio of shake data；S102, the frequency spectrum of pretreated Prestack seismic data is carried out wavelet scale decompose to obtain it is some with different scale Small echo, analyze and determine wavelet scale to be pressed；S103, by building dimensional constraints item the small echo of the different scale is reconstructed, to weaken small echo to be pressed Dimensional information；S104, de-tuned seismic channel set is formed using the small echo after reconstruct and Prestack seismic data convolution.
- 2. the method as described in claim 1, it is characterised in that in step S101, using Residual moveout correction come to prestack The data of seismic channel set is pre-processed.
- 3. the method as described in claim 1, it is characterised in that in step S101, using advantage domain τ-p convert filtering come pair The data of prestack seismic gather is pre-processed, by spectrum sigtral response, the Attenuating Random Noise in the τ-p of advantage domain.
- 4. the method as described in claim 1, it is characterised in that in step s 102, will be described pre- in certain frequency band range Treated Prestack seismic data is decomposed into the small echo of several different scales, finds the small echo of each yardstick and corresponding dominant frequency Between relation and counted, so that it is determined that going out to produce the large scale Wavelet Component of tuning effect.
- 5. method as claimed in claim 4, it is characterised in that be based further on the Thickness Analysis to destination layer and the knot of test Fruit come determine produce tuning effect large scale wavelet information.
- 6. such as the method any one of claim 1-5, it is characterised in that in step s 103, in addition to following step Suddenly：S103a, the matrix form for being added the spectral factorization of seismic channel set data amplitudes for different scale Wavelet-Weighted；S103b, the coefficient entry to the matrix are estimated；S103c, the coefficient entry obtained using estimation are weighted superposition to the small echo of the different scale, obtain being superimposed yardstick Small echo；S103d, the coefficient entry is adjusted to build dimensional constraints item to weaken wavelet information to be pressed, wherein to be pressed is small Ripple dimensional information is large scale wavelet information.
- 7. method as claimed in claim 6, it is characterised in that in step S103b, by least-squares algorithm come to described The coefficient entry of matrix is estimated.
- 8. method as claimed in claim 6, it is characterised in that in step S103d, by the small echo of the superposition yardstick after adjustment Amplitude spectrum of its enveloping surface as reconstruct small echo is smoothly obtained, so that in time-domain, reconstructs obtained small echo distribution Narrow, secondary lobe is relatively small；In frequency domain, wavelet low frequency composition is pressed, and frequency band range is wider.
- 9. the method for a kind of thin reservoir of identification prediction and gas-bearing formation, it is characterised in that including using as any in claim 1-8 The method of removal thin layer tuning effect described in obtains de-tuned seismic channel set, then carries out AVO to the seismic channel set Attributive analysis is to identify and predict thin reservoir and gas-bearing formation.
- 10. method as claimed in claim 9, it is characterised in that AVO attributive analysises include intercept attributive analysis and gradient attribute Analysis.
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| CN106033125B (en) * | 2016-06-29 | 2018-06-19 | 中国石油化工股份有限公司 | The trace gather interference of compacting prestack wide-angle carries frequency method |
| CN106405647B (en) * | 2016-12-22 | 2018-04-13 | 成都晶石石油科技有限公司 | A kind of tuning inversion method on sedimentary formation thickness |
| CN109613615B (en) * | 2018-12-07 | 2020-05-19 | 成都北方石油勘探开发技术有限公司 | Geologic body scale quantitative estimation method based on pre-stack seismic response analysis |
| CN112346116B (en) * | 2019-08-09 | 2024-10-29 | 中国石油天然气集团有限公司 | Reservoir prediction method and device |
| CN112946746B (en) * | 2019-12-11 | 2022-11-01 | 中国石油天然气股份有限公司 | Method and device for improving AVO inversion accuracy of thin coal seam |
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