CN104237945A - Seismic data self-adaptive high-resolution processing method - Google Patents
Seismic data self-adaptive high-resolution processing method Download PDFInfo
- Publication number
- CN104237945A CN104237945A CN201410480293.8A CN201410480293A CN104237945A CN 104237945 A CN104237945 A CN 104237945A CN 201410480293 A CN201410480293 A CN 201410480293A CN 104237945 A CN104237945 A CN 104237945A
- Authority
- CN
- China
- Prior art keywords
- data
- seismic data
- seismic
- resolution processing
- resolution
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention relates to a seismic data self-adaptive high-resolution processing method. The method includes the steps that data are collected and processed, and a stacked or skewed trace gather is obtained; the effective bandwidth range of the seismic data is selected; a partial spectrum sequence of reflection coefficients is obtained by dividing the frequency spectrum of a single seismic record by the frequency spectrum of wavelets within the effective bandwidth range; self-adaptive filters are designed and used for filtering the partial spectrum sequence; a reflection range corresponding to a selected time position is estimated; a finally-obtained full reflection coefficient sequence is estimated; in combination with logging information and well bypass processing, the application effect of a section is evaluated, and then high-fidelity and high-resolution processing results of the whole seismic data are obtained; based on the obtained trace gather with the wider frequency band, construction and explanation and evaluation on lithology and micro-crack development are further conducted, and beneficial regions for shale gas exploration and development are found; in combination with existing data of an exploratory well, geology and other aspects, a new well site design basis is provided; the method can be used for explaining and evaluating a finer shale gas reservoir.
Description
Technical field
The invention belongs to seismic data disposal route, a kind of theoretical based on nonparametric Power estimation, by simulating the statistical nature of interference relatively, design sef-adapting filter group is suppressed it, thus carry out stable estimating exactly to the reflection wave amplitude of different time position, thus improve geological data section resolution, with high fidelity widen the high resolution processing technique of geological data frequency band.
Background technology
China's marine facies shale exploratory area reservoir has the obvious characteristic such as multilayer system, strong transformation, high maturity, and be mainly distributed in southern mountain area, top layer, work area and complex geologic conditions, relative to conventional gas and oil, shale gas exploratory development difficulty is larger.Shale reservoir distribution relative complex, although mud shale stratum is very thick, can reach km on hundreds of, reaches only have tens even several meters of effective shale gas reservoir standard.The change of organic carbon content can cause the change of density of earth formations, speed, but amplitude is very little.So, have higher requirement in quality, particularly resolution to seismic data during detecting and identifying to shale gas reservoir and fidelity aspect.For the feature of shale gas reservoir, need to carry out to have Hi-Fily to propose high-resolution seismic data processing technology research.
Conventional raising seismic data resolution method mainly considers the identification to thin layer, take deconvolution as representative (Huang Xude, 1992), mostly based on convolution model (Robinson and Treitel of the single track of seismologic record, 1980), product (the Castagna that seismic trace frequency spectrum is wavelet and reflectivity spectrum is then shown as in frequency field, 2004), main consideration improves the vision addressability (Porsani and Ursin, 1998) of seismologic record by inverse filtering.Impact due to noise only can recover the partial frequency spectrum of effective free transmission range reflection coefficient, and seismic data resolution still determined by frequency band range, there is contradiction (Levy and Fullagar, 1981) between resolution characteristic and signal to noise ratio (S/N ratio).Along with inversion theory progress of research, sparse deconvolution (Zhu Zhenyu and Liu Hong, 2005) and inversion method (Zhang Fanchang, Liu Jie, print Xing Yao etc., 2008) also become the important means identifying thickness of thin layer and bottom boundary position, top.Openness constraint inversion technique is in searching strong reflection, and antinoise aspect shows larger advantage (Liu Xiwu, Ning Junrui, Zhang Gailan, 2009).
Improving seismic data resolution method is extract certain approach of geologic body reflectance signature.Based on different mathematical models, the method improving seismic data resolution also shows as different feature (Wiggins, 1985; Velis, 2008), Inverse Problem Thoery is applied to improving (Wang Jiaying in resolution method more and more, 2002), inversion result depends in selected forward model and mates the distribution of approximate error and selection (Zhang Hongbing, the Shang Zuoping of corresponding interpretational criteria in observation data accordingly, Yang Changchun etc., 2005), ignore the concrete form of systematic error and go merely the way of " coupling " to be (Parker, 1977) that there is " risk ".In addition, often its " sensingization " feature is too obvious in the foundation of constraint condition, namely under different constraint condition, inversion result can show different features, the model parameter estimation result causing inverting to obtain is unpredictable, and be very unstable (Sacchi, Velis and Cominguez, 1992).From theory, priori conditions is people to one of institute's inverse model parameter attribute initial conjecture, and this initial conjecture should be similar to true solution, namely should be generally realistic physics law.If these conditions too " sensingization ", the result obtained like this and truth have (Ulrych, 2001) of very large deviation often.
In sum, existing geological data high resolution data processing methods often sacrifices much useful earthquake information while acquisition high resolution processing result, in fact these information are present among the subtle change of seismic trace waveform, the subtle change of existing geological data High Resolution Method particularly inverting class algorithm to lithology is insensitive, and the seismic data after high resolution processing lost much useful reservoir information after obtaining the visual high-resolution of geological data.Particularly for multilayer system feature and the lithological change feature of shale reservoir, this large class high resolution data processing methods is also inapplicable.
2002, Vetterli proposes sampling and the reconstruction theory of limited turnover rate signal, the possibility that in this theoretical explanation finite bandwidth situation, reflection coefficient is rebuild.Vetterli (2002) is method used serial of methods just in parametrization analysis of spectrum when rebuilding pulse sequence signal, such as Prony method (Kay and Marple, 1981), subspace method (Kung etc., 1983; Maravi, 2004) etc.Estimated performance based on the parameter class methods of model all extremely depends on the mathematical model of hypothesis and the matching degree of real process, usually can obtain the estimated result of failure when model is not inconsistent.In fact, be directed to the spectral model feature of seismic trace reflection coefficient, imparametrization method table reveals the characteristic (Stoica and Moses, 1997) of anti-noise more.First maximum likelihood (Capon) method of estimation (Capon proposed, 1969) be initially mainly used in the research of the propagation characteristic of seismic event in geological data Array Signal Processing, be first interpreted as a kind of Power estimation method based on maximum likelihood.Afterwards, this method is used to estimate its amplitude and phase place respectively to the sinusoidal signal of the different frequency of limited sampling length, the covariance of first noise and relative interference in simulated data during estimation, then design the interference suppressing again noise and other frequency sine while corresponding sef-adapting filter can nondestructively filter specific sinusoidal signal as much as possible, thus obtain accurate maximal possibility estimation result.Experiment shows that Capon method of estimation is while having higher estimation stability, its sinusoidal signal component close to frequency has very high resolution characteristic, and the method can regulate between statistics stability and frequency resolution in some sense, but problem is that its estimated result has deviation (having the rough simulation that deviating cause is interference covariance statistical nature).1996, Li and Stoica proposed amplitude and phase estimation method, and it is widely used in target detection and synthetic-aperture radar (SAR) imaging, by carrying out estimating target to the board design sef-adapting filter group of interference covariance.Have estimation of deviation characteristic relative to Capon method, amplitude and phase estimation method are that a kind of nearly bias free is estimated, and to disturbing, the simulation of covariance is more accurate.
Therefore, this thought is applied to the spectral model of reflection coefficient by us, the reflection amplitudes of underground is rationally estimated, when not adding artificial prior imformation, by designing adaptive bank of filters compacting interference relatively, the estimated result of high-resolution reflectance magnitude can be obtained.Section after process or three-dimensional road set information are while showing as high-resolution broad frequency band width, show as the Amplitude Estimation of reflection coefficient more accurately simultaneously, provide abundanter amplitude and phase information, for the further explanation for shale gas reservoir characteristic and appraisal are given information guarantee.
Summary of the invention
Improve resolution method for existing geological data and widen Problems existing in effect and data fidelity at frequency band, the present invention is to obtain high fidelity and high-resolution seismic channel set for target, use for reference and make use of statistic line loss rate method advanced in the world, based on adaptive filtering theory, high resolution processing being carried out to seismic data.Under Hi-Fi requirement, process obtains high-resolution data volume, and frequency ranges of data is widened, and comprises the earthquake information of more high frequency more details.On this basis, carry out high-resolution attributes extraction and explanation, carry out the identification of shale gas reservoir distribution and the prediction and evaluation of reservoir geology condition, to form a whole set of, for shale gas reservoir, contain workflow and the technical system of the geophysical method of shale reservoir data.
The very little weak reflectance signature brought of amplitude of variation for shale reservoir density, speed, self-adaptation high resolution data processing methods is theoretical based on self-adaptation statistical filtering, design corresponding sef-adapting filter group, under the prerequisite keeping original seismic data information to greatest extent, seismic channel set is processed, estimates subsurface reflective amplitude.
Within the scope of the effective band of seismologic record, the partial frequency spectrum of the reflection coefficient that can obtain divided by the frequency spectrum of seismic wavelet with the frequency spectrum of seismologic record, and according to convolution model, it is just the sinusoidal signal of the different frequency of limited sampling length, the wherein time location of the corresponding reflection coefficient of each sinusoidal signal frequency, and the corresponding reflection amplitudes of sinusoidal amplitude.Therefore, algorithm is mainly for this feature of the partial frequency spectrum model of reflection coefficient, utilize non-parametric spectrum analysis theory method, choose different time location (frequency of the sine in corresponding part frequency spectrum) offset of sinusoidal amplitudes (namely changing the reflection amplitudes of time location) to estimate, algorithm is by the statistical nature of simulation interference relatively (comprising the noise existed in other reflections and data), design sef-adapting filter is suppressed relatively disturbing, thus realizes accurately estimating the stable of reflection amplitudes of different time position.Estimated result shows as high-resolution features on section, and data frequency band is widened, and effectively maintains small geological information in original data, obtains high fidelity and high-resolution seismic channel set.On this basis, can carry out a series of process and interpretation work, such as profile construction and layer position are explained, three-dimensional properties is extracted and geologic body is portrayed.Especially for the exploration of unconventional shale gas reservoir, widening by frequency span, abundant amplitude is more suitable for phase information portrays the relevant rock physics information of shale gas reservoir, such as organic carbon content, fragility etc., more fine description crack and microfracture can grow behavior, the final prediction for shale gas exploratory development range of profitability (" dessert ") provides abundant data, for well location and horizontal well design provide more reliable foundation simultaneously.Overall method and technology process description is as follows:
1) conventional processing and skew are carried out to the seismic data that shale exploratory area collects, obtain poststack or skew rear road collection;
2) for two dimension or three-dimensional road collection, choose destination layer position (shale bed) and extract wavelet, and calculate the frequency spectrum of wavelet, and choose seismic data effective bandwidth scope according to actual conditions (data characteristic, signal to noise ratio (S/N ratio) etc.);
3) extract single-channel seismic record, calculate its frequency spectrum, within the scope of effective bandwidth, obtain the partial spectrum sequence of reflection coefficient divided by the frequency spectrum of wavelet;
4) based on the partial spectrum sequence of reflection coefficient and the corresponding relation of time domain reflected impulse, selected position sometime, the statistical nature (relatively disturb and be made up of sine corresponding to other times position reflected impulse in partial spectrum and noise) that simulation is disturbed relatively, thus design sef-adapting filter, design criteria is as far as possible sinusoidal close to the frequency field that institute seclected time is corresponding for making its filtering export, the interference relatively of compacting simultaneously, then applies designed wave filter and carries out filtering to partial spectrum sequence;
5) estimate its amplitude to the near sinusoidal sequence obtained after filtering (corresponding to selected time location), according to the corresponding relation of itself and time domain reflected impulse, it estimates that the reflection amplitudes being corresponding selected time location is estimated;
6) select different time locations, namely design corresponding different sef-adapting filter estimate finally to obtain whole reflection coefficient sequences for different time locations;
7) in conjunction with well-log information, the process of well lie, the effect of section is evaluated, thus adjusting and optimizing effect is carried out to the correlation parameter of bank of filters, finally carry out step 3-6 by road and can obtain high-fidelity to whole geological data and high resolution processing result;
8) on the basis of the more wide band road collection obtained, further construct, lithology, microfracture growth etc. explanation and appraisal, find shale gas exploratory development range of profitability;
9) combine existing prospect pit, geology etc. each side data, provides new well location design considerations.
In addition, in actual applications, for the data compared with high s/n ratio, method also may be used for the process of prestack road collection, and can carry out more high-precision prestack AVO inverting based on this, the work such as prestack attribute extraction.It should be noted that the method is estimate phase information when estimation reflection coefficient simultaneously in addition, namely it is plural number to the estimated result of reflected amplitudes.So the result that we obtain comprises the multiple geological data section of estimated result real part and imaginary part composition, the data information after its process, not only in frequency span, also shows as more abundant information in phase place.
The effect of invention
Method is under the prerequisite keeping original seismic data information to greatest extent, and process obtains high fidelity and high-resolution seismic channel set.Algorithm has self-adaptive features, do not introduce artificial " directive property " constraint, effectively widen data frequency band, enriched amplitude and phase information, utilize the slight change of amplitude and phase place to understand and explain the change of lithology, meticulousr shale gas RESERVOIR INTERPRETATION and evaluation can be carried out.
Accompanying drawing explanation
Fig. 1: the main technical flows of self-adaptation high resolution data processing methods
Fig. 2: aWedge model synthesis synthesis road collection and b each road frequency spectrum
Fig. 3: aWedge model composite traces process experimental result (noiseless) and b spectrum recovery effect
Fig. 4: aWedge model composite traces process experimental result (Noise) and b spectrum recovery effect
Fig. 5: well lie composite traces High-resolution Processing comparison of test results
B High-resolution Processing result c 35Hz wavelet synthesis road, a 25Hz wavelet synthesis road
Fig. 6: a real well lie result and b composite traces of logging well contrasts
Fig. 7: real data self-adaptation high resolution processing algorithm application example
Section after section b High-resolution Processing before a process
Fig. 8: spectral contrast before and after real data High-resolution Processing
Fig. 9: survey region base map and former three-dimensional poststack road collection
Figure 10: the wavelet of destination layer position and extraction and wavelet frequency band
Figure 11: three-dimensional data high resolution processing result
Figure 12: the synthesis well lie of different dominant frequency wavelet and the well lie of process front and back seismologic record
Figure 13: meticulous well shake coupling is carried out to the seismic channel set that High-resolution Processing obtains
Figure 14: the crack association attributes along destination layer position on High-resolution Processing basis is explained
Specific embodiment mode
Fig. 1 is the main technical flows that self-adaptation high resolution data processing methods is applied to seismic trace High-resolution Processing;
The wedge-shaped body Model composite traces (Wedge model) of the model test application that Fig. 2 carries out for investigation method effect and each road frequency spectrum thereof, wherein synthesizing wavelet is 25Hz Ricker wavelet, and seismic channel set effective bandwidth scope is about 10-50Hz;
Fig. 3 is that under noise-free case, method is to the treatment effect of Wedge model trace collection, and result resolution is very high, and frequency information has efficient recovery;
Fig. 4 has the treatment effect to Wedge model trace collection under noise situations, and improve the resolution of seismic channel set to a certain extent, frequency band is widened.
Fig. 5 synthesizes well lie for utilizing real logging data, high-resolution process experiment is carried out to it, wherein left figure a is the Prof. Du Yucang Jing Pangdaoji by 25Hz wavelet and logging well reflection coefficient, middle figure b carries out the result after high resolution processing to Zuo Tuzhong road collection, right figure c is the Prof. Du Yucang road collection of 35Hz wavelet and logging well reflection coefficient, it is consistent that result resolution characteristics and 35Hz wavelet synthesize road collection, and illustration method effectively improves resolution, and has high fidelity;
Fig. 6 is that real well lie High-resolution Processing result contrasts with well logging composite traces, process before seismic trace near well corresponding with the composite traces of 25Hz wavelet and practical logging reflection coefficient, and process after seismic trace near well and have better corresponding relation with the composite traces of 33Hz wavelet and practical logging reflection coefficient;
Fig. 7 is the treatment effect for section application process a certain in the actual seismic data of somewhere, and the seismic section resolution after process significantly improves;
Fig. 8 is the front frequency band comparison diagram with processing rear sectional data of process in Fig. 7, and the data effective band after process is obviously widened.
Below with the High-resolution Processing in certain shale gas exploratory area and be interpreted as example, brief description is carried out to high resolution processing technique:
Step 1) conventional migration before stack is carried out to certain shale gas exploratory area data, obtain road collection after three-D migration; (see Fig. 9)
Step 2) zero-phase wavelet is extracted to destination layer Using statistics correlation method, and calculate the frequency spectrum of wavelet, thus choose effective bandwidth scope; (see Figure 10)
Step 3)-6) each road seismologic record to three-dimensional data, use auto adapted filtering high resolution algorithm in frequency field, finally obtain high-resolution three-dimensional road collection; (see Figure 11)
Step 7) according to the spectral change before and after High-resolution Processing, in conjunction with well-log information (well logging acoustic impedance), apply the wavelet synthesis well lie of corresponding dominant frequency, the effect of evaluation method, carry out meticulousr well shake coupling; (see Figure 12,13)
Step 8)-9) on the basis of wide band seismic channel set, further construct, lithology, the seismic interpretations such as microfracture growth and appraisal (here for fracture distribution that is relevant and curvature attributes target of prediction layer), find shale gas exploratory development range of profitability, final combination has prospect pit, geology etc. each side data, provides new well location design considerations.(see Figure 14)
Claims (1)
1. a seismic data self-adaptation high resolution processing method, is characterized in that:
Method comprises the steps:
1) conventional processing and skew are carried out to the seismic data that shale exploratory area collects, obtain poststack or skew rear road collection;
2) for two dimension or three-dimensional road collection, choose layer position, page object rock stratum, extract wavelet, and calculate the frequency spectrum of wavelet, and according to data characteristic, signal to noise ratio (S/N ratio) chooses seismic data effective bandwidth scope;
3) extract single-channel seismic record, calculate its frequency spectrum, within the scope of effective bandwidth, obtain the partial spectrum sequence of reflection coefficient divided by the frequency spectrum of wavelet;
4) based on the partial spectrum sequence of reflection coefficient and the corresponding relation of time domain reflected impulse, selected position sometime, the statistical nature that simulation is disturbed relatively, relative interference is made up of sine corresponding to other times position reflected impulse in partial spectrum and noise, thus design sef-adapting filter, design criteria is as far as possible sinusoidal close to the frequency field that institute seclected time is corresponding for making its filtering export, and the interference relatively of compacting simultaneously, then applies designed wave filter and carry out filtering to partial spectrum sequence;
5) namely correspond to selected time location to the near sinusoidal sequence obtained after filtering and estimate its amplitude, according to its corresponding relation with time domain reflected impulse, it estimates the reflection amplitudes estimation being corresponding selected time location;
6) select different time locations, namely design corresponding different sef-adapting filter estimate finally to obtain whole reflection coefficient sequences for different time locations;
7) in conjunction with well-log information, the process of well lie, the effect of section is evaluated, thus adjusting and optimizing effect is carried out to the correlation parameter of bank of filters, finally carry out step 3-6 by road and can obtain high-fidelity to whole geological data and high resolution processing result;
8) on the basis of the more wide band road collection obtained, further construct, lithology, microfracture is grown and is explained and appraisal, finds shale gas exploratory development range of profitability;
9) combine existing prospect pit, geology each side data, provides new well location design considerations.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410480293.8A CN104237945B (en) | 2014-09-18 | 2014-09-18 | A kind of seismic data self adaptation high resolution processing method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410480293.8A CN104237945B (en) | 2014-09-18 | 2014-09-18 | A kind of seismic data self adaptation high resolution processing method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104237945A true CN104237945A (en) | 2014-12-24 |
| CN104237945B CN104237945B (en) | 2016-09-07 |
Family
ID=52226389
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410480293.8A Active CN104237945B (en) | 2014-09-18 | 2014-09-18 | A kind of seismic data self adaptation high resolution processing method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104237945B (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104569344A (en) * | 2014-12-31 | 2015-04-29 | 长江大学 | Shale reservoir brittle mineral earthquake quantitative characterization method |
| CN106054245A (en) * | 2016-06-29 | 2016-10-26 | 中国石油化工股份有限公司 | Earthquake data high-resolution processing quantitative evaluation method |
| CN106199715A (en) * | 2015-05-30 | 2016-12-07 | 中国石油化工股份有限公司 | Strong reflection separation method based on model and device |
| CN106772579A (en) * | 2016-12-07 | 2017-05-31 | 中国矿业大学(北京) | Earthquake prestack inversion method and apparatus in a kind of girdle |
| CN109946740A (en) * | 2019-03-01 | 2019-06-28 | 成都理工大学 | A kind of seismic resolution enhancing technology based on wide flat spectrum seismic wavelet shaping |
| CN110263763A (en) * | 2019-07-09 | 2019-09-20 | 兰州大学 | Method based on lithology midpoint Sine Interpolation model analysis High-resolution Cyclostratigraphy |
| CN111610562A (en) * | 2019-02-22 | 2020-09-01 | 中国石油天然气集团有限公司 | Method and device for separating strong reflection signals in seismic data |
| CN113050162A (en) * | 2021-04-16 | 2021-06-29 | 中南大学 | Viscoelastic medium seismic inversion method based on Zoeppritz equation |
| CN113882853A (en) * | 2020-07-03 | 2022-01-04 | 中国石油化工股份有限公司 | Method for transmitting near-bit logging while drilling data |
| CN114076990A (en) * | 2020-08-14 | 2022-02-22 | 中国石油化工股份有限公司 | Method and system for determining oil shale reflection energy, storage medium and electronic equipment |
| CN114428291A (en) * | 2020-09-22 | 2022-05-03 | 中国石油化工股份有限公司 | Multichannel reflection coefficient pulse determination method, storage medium, and electronic device |
| CN115267902A (en) * | 2021-04-30 | 2022-11-01 | 中国石油化工股份有限公司 | Computer program product and method for estimating spatially varying wavelets |
| CN117434604A (en) * | 2023-02-20 | 2024-01-23 | 中国石油化工股份有限公司 | Seismic data processing method and device, storage medium and electronic equipment |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4797668A (en) * | 1986-12-12 | 1989-01-10 | Halliburton Company | Acoustic well logging system having multiplexed filter digitizing |
| CN102193108B (en) * | 2010-03-19 | 2013-07-03 | 中国石油天然气集团公司 | Method for improving SNR (signal-to-noise ratio) of oil exploration data processing |
| CN103293552B (en) * | 2013-05-24 | 2015-10-28 | 中国石油天然气集团公司 | A kind of inversion method of Prestack seismic data and system |
-
2014
- 2014-09-18 CN CN201410480293.8A patent/CN104237945B/en active Active
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104569344A (en) * | 2014-12-31 | 2015-04-29 | 长江大学 | Shale reservoir brittle mineral earthquake quantitative characterization method |
| CN106199715A (en) * | 2015-05-30 | 2016-12-07 | 中国石油化工股份有限公司 | Strong reflection separation method based on model and device |
| CN106054245A (en) * | 2016-06-29 | 2016-10-26 | 中国石油化工股份有限公司 | Earthquake data high-resolution processing quantitative evaluation method |
| CN106054245B (en) * | 2016-06-29 | 2018-03-09 | 中国石油化工股份有限公司 | High resolution seismic data handles quantitative evaluation method |
| CN106772579A (en) * | 2016-12-07 | 2017-05-31 | 中国矿业大学(北京) | Earthquake prestack inversion method and apparatus in a kind of girdle |
| CN111610562A (en) * | 2019-02-22 | 2020-09-01 | 中国石油天然气集团有限公司 | Method and device for separating strong reflection signals in seismic data |
| CN111610562B (en) * | 2019-02-22 | 2023-10-27 | 中国石油天然气集团有限公司 | Method and device for separating strong reflection signals in seismic data |
| CN109946740B (en) * | 2019-03-01 | 2020-06-30 | 成都理工大学 | Seismic resolution enhancement method based on wide flat spectrum seismic wavelet shaping |
| CN109946740A (en) * | 2019-03-01 | 2019-06-28 | 成都理工大学 | A kind of seismic resolution enhancing technology based on wide flat spectrum seismic wavelet shaping |
| CN110263763B (en) * | 2019-07-09 | 2021-06-29 | 兰州大学 | Method for analyzing gyrus stratum based on lithology midpoint sine interpolation model |
| CN110263763A (en) * | 2019-07-09 | 2019-09-20 | 兰州大学 | Method based on lithology midpoint Sine Interpolation model analysis High-resolution Cyclostratigraphy |
| CN113882853B (en) * | 2020-07-03 | 2024-06-04 | 中国石油化工股份有限公司 | Method for transmitting near-bit logging while drilling data |
| CN113882853A (en) * | 2020-07-03 | 2022-01-04 | 中国石油化工股份有限公司 | Method for transmitting near-bit logging while drilling data |
| CN114076990A (en) * | 2020-08-14 | 2022-02-22 | 中国石油化工股份有限公司 | Method and system for determining oil shale reflection energy, storage medium and electronic equipment |
| CN114076990B (en) * | 2020-08-14 | 2024-04-09 | 中国石油化工股份有限公司 | Oil shale reflected energy determination method, system, storage medium and electronic equipment |
| CN114428291A (en) * | 2020-09-22 | 2022-05-03 | 中国石油化工股份有限公司 | Multichannel reflection coefficient pulse determination method, storage medium, and electronic device |
| CN113050162A (en) * | 2021-04-16 | 2021-06-29 | 中南大学 | Viscoelastic medium seismic inversion method based on Zoeppritz equation |
| CN115267902A (en) * | 2021-04-30 | 2022-11-01 | 中国石油化工股份有限公司 | Computer program product and method for estimating spatially varying wavelets |
| CN117434604A (en) * | 2023-02-20 | 2024-01-23 | 中国石油化工股份有限公司 | Seismic data processing method and device, storage medium and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104237945B (en) | 2016-09-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104237945B (en) | A kind of seismic data self adaptation high resolution processing method | |
| CN108802812B (en) | Well-seismic fusion stratum lithology inversion method | |
| CN102109613B (en) | Method for determining effective thickness of target reservoir under complex geological conditions | |
| CN104570067B (en) | Phased seismic inversion method in a kind of geophysical exploration | |
| CN104516018A (en) | Porosity inversion method under lithological constraint in geophysical exploration | |
| CN103954992B (en) | Deconvolution method and device | |
| Górszczyk et al. | Graph‐space optimal transport concept for time‐domain full‐waveform inversion of ocean‐bottom seismometer data: Nankai trough velocity structure reconstructed from a 1D model | |
| CN102109616A (en) | Wave impedance inversion method for deposition cycle restriction | |
| Schmelzbach et al. | Efficient deconvolution of ground-penetrating radar data | |
| CN105089652A (en) | Pseudo-acoustic curve rebuilding and sparse pulse joint inversion method | |
| CN111722284B (en) | Method for establishing speed depth model based on gather data | |
| Zeng et al. | Recent progress in analysis of seismically thin beds | |
| CN102385066B (en) | Pre-stack earthquake quantitative imaging method | |
| Bouchaala et al. | Azimuthal Investigation of a Fractured Carbonate Reservoir | |
| von Ketelhodt et al. | Post-stack denoising of legacy reflection seismic data: implications for coalbed methane exploration, Kalahari Karoo Basin, Botswana | |
| CN105093291A (en) | Method for recovering seismic reflection characteristics of oil and gas reservoir | |
| Okpoli et al. | Integration of Well logs and seismic attribute analysis in reservoir identification on PGS field onshore Niger Delta, Nigeria | |
| Zhang et al. | Interval Q inversion based on zero-offset VSP data and applications | |
| Sirazhiev | Seismic attribute analysis of the mississippian chert at the wellington field, south-central kansas | |
| Banerjee et al. | Mapping of reservoir properties using model-based seismic inversion and neural network architecture in raniganj basin, India | |
| CN113589365B (en) | Reservoir pinch-out line description method based on time-frequency domain information | |
| Ningkai et al. | Stepped and detailed seismic prediction of shallow-thin reservoirs in Chunfeng oilfield of Junggar Basin, NW China | |
| CN111694055B (en) | Method and device for extracting and analyzing AVO attribute under strong reflection shielding | |
| CN106353796A (en) | Surface seismic data resolution ratio increasing method | |
| Rossi et al. | Traveltime and attenuation tomography of CO2 plume at Sleipner |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |