CN102830432A - Method for identifying weak reflection reservoir under cover of coal series strong earthquake reflection characteristics - Google Patents
Method for identifying weak reflection reservoir under cover of coal series strong earthquake reflection characteristics Download PDFInfo
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Abstract
The invention provides a method for identifying a weak reflection reservoir under the cover of coal series strong earthquake reflection characteristics, belonging to the field of seismic exploration reservoir prediction. The method comprises the steps of firstly analyzing an after-stack amplitude maintaining three-dimensional seismic data body, determining a thin layer spectrum resolving calculation range and a spectrum resolving calculation range of the whole data body to obtain a thin layer tuning three-dimensional data body through thin layer spectrum resolving calculation; secondly obtaining tuning three-dimensional data bodies of all sampling points in the after-stack amplitude maintaining three-dimensional seismic data body through a moving time window; subsequently generating a co-frequency component three-dimensional data body or a single frequency component three-dimensional data body through separation; obtaining a time-maximum amplitude frequency data body through comparison; and finally identifying the weak reflection reservoir under the cover of coal series strong earthquake reflection characteristics by using the frequency difference between the sand and the coal series reservoir. With the adoption of the method, a spatial distribution trend of the weak reflection reservoir under the cover of coal series strong earthquake reflection characteristics is reflected in profile and space-time mode visually.
Description
Technical field
The invention belongs to seismic prospecting reservoir prediction field, be specifically related to a kind of coal measures and shake the recognition methods that reflectance signature is covered down weak reflection reservoir doughtily.
Background technology
Spectral Decomposition Technique is the characteristic reservoir description technique that decomposes based on frequency spectrum that development in recent years is got up.Spectral Decomposition Technique transforms to frequency field with geological data from time domain, can obtain abundanter seismic wave field dynamics and kinematics information.The common FREQUENCY SPECTRUM DECOMPOSITION TECHNIQUE of petroclastic rock sandstone reservoir prediction has Fourier transform, wavelet transformation, maximum entropy, Amoco company Spectral Decomposition Technique etc. at present.
These technological characteristics are following: the basis function of Fourier transform has of overall importance, on time domain, does not have time resolution characteristics, on frequency domain, can localize, but can not portray the Seismic reflection character on the local stratum of time domain; Maximum entropy spectrum is decomposed can obtain better frequency resolution, but receives window limit access time, and temporal resolution is not high; Wavelet transformation uses scale parameter control; The width of time frequency window is with the signal adaptive transformation, and high frequency window constantly narrows down automatically, and low frequency window constantly broadens automatically; But with frequency parameter can not be directly corresponding; Geological meaning is clear and definite inadequately, and the wavelet transformation after the improvement can assigned frequency band number and frequency distribution density, can extract the effective frequency information with geological Significance relevant with the frequency response characteristic of objective body; Amoco company Spectral Decomposition Technique is the FREQUENCY SPECTRUM DECOMPOSITION TECHNIQUE to zone of interest; Considered the thin layer tuning characteristic; Can reflect spectrum signature in the thin layer; Present application mainly is the tuning 3-D data volume that calculates to thin zone of interest, and shows the frequency characteristic of thin zone of interest with the form of frequency spectrum section.
Above-mentioned several kinds of FREQUENCY SPECTRUM DECOMPOSITION TECHNIQUE have all been considered frequecy characteristic, but relative merits are respectively arranged.The result of their spectral decomposition is the spectrum signature with the research zone of interest of sliced form demonstration mostly.
Gas field, big ox ground, the basin, Erdos of China belongs to low hole, hypotonic, dense form is main lithologic deposit with the river channel sand.The gas field is main with the Taiyuan group sandstone reservoir of following stone box group, Shanxi group and the Carboniferous system of the Permian system mainly, and the distribution of trap is controlled by the sand body development degree.Grow in Shanxi group and group coal seam, Taiyuan, and coal seam and country rock resistance difference are big, the seismic reflection energy is strong and continuous.3 sections main stem sand bodies of following stone box group box are big ox ground vapour owner of farmland power payzone, and sand body is thin and stacked in length and breadth, phase transformation is frequent, nonuniformity is strong, sand body and country rock wave impedance difference are little, reflected energy a little less than.The strong coal in gas field, big ox ground is the reflectance signature that the 3 sections reservoir-sand bodies of box that are positioned at its top have often been covered in the stratum reflection.
In the reservoir prediction of petroclastic rock stratum, extract the information relevant and remain present sand body identification method relatively more commonly used with amplitude.But, coal measure strata approaches the complicated and changeable of reservoir because shaking the interference and the weak reflection of river channel sand of reflectance signature doughtily; Make directly the precision that the limited seismic data of resolution carries out Sand-body Prediction to be restricted with conventional method, can't the thin gas-bearing sandstone reservoir internal reflection characteristic of meticulous depiction.The response of frequency-amplitude can obtain than time-abundanter, the meticulousr amplitude information of amplitude response.
Though the frequency slice display mode that generally adopts at present can obtain zone of interest interference image in the plane, the personnel that also need explain discern the structure and the pattern of the geologic sedimentation of representative by rule of thumb.Only the spectrum signature with sliced form reflects that the space spread rule of sand body is comprehensive inadequately.
The thin layer Spectral Decomposition Technique is a speciality with research stratum internal reflection changing features; On behalf of the horizontal reflectance signature in local stratum, the single-frequency section that the tuning 3-D data volume that is calculated by single thin layer (representative zone of interest) generates can change, but can not reflect bigger depth range, more comprehensive information.
Summary of the invention
The objective of the invention is to solve a difficult problem that exists in the above-mentioned prior art; Provide a kind of coal measures to shake the recognition methods that reflectance signature is covered down weak reflection reservoir doughtily; Utilize the thin layer Spectral Decomposition Technique, advantage shows different features at " tuning " frequency place to take into account thin layer tuning characteristic and different lithology, rerum natura rock, is obtaining to be total on the basis of frequency component data volume; Consider the frequecy characteristic difference of coal measure strata and sandstone reservoir; Outstanding thin reflectance signature and the spread rule of sand body on section, and then the space spread trend of prediction sand body improve the sandstone reservoir precision of prediction.
The present invention realizes through following technical scheme:
A kind of coal measures shakes the recognition methods that reflectance signature is covered down weak reflection reservoir doughtily; Said method is at first analyzed poststack and is protected width of cloth 3-d seismic data set; Confirm the spectral factorization computer capacity of thin layer spectral factorization computer capacity and whole data volume, utilize the thin layer spectral factorization to calculate the thin layer tuning 3-D data volume; Window when passing through to move then obtains the tuning 3-D data volume that poststack is protected all sampled points in the width of cloth 3-d seismic data set; Generate frequency component 3-D data volume or single-frequency component 3-D data volume altogether through sorting again; Through relatively obtain time-peak swing frequency data body; Utilize the frequency difference of sand body and coal measure strata to identify coal measures at last and shake the weak reflection reservoir of reflectance signature under covering doughtily.
Said method comprising the steps of:
(1) analyzes poststack and protect width of cloth 3-d seismic data set
Poststack is protected width of cloth 3-d seismic data set carry out spectrum analysis, understand sand body and coal seam spectrum signature, confirm the computer capacity of thin layer spectral factorization computer capacity and whole data volume;
(2) single thin layer spectral factorization is calculated
(1) definite thin layer spectral factorization computer capacity is protected from poststack and is extracted the thin layer data the width of cloth 3-d seismic data set set by step, carries out spectral factorization and calculates, and obtains the thin layer tuning 3-D data volume;
(3) whole data volume spectral factorization is calculated;
Window when moving through pointwise is protected each the sampled point repeating step (2) in the width of cloth 3-d seismic data set to poststack, through calculating the corresponding thin layer tuning 3-D data volume of all sampled points;
(4) divide the one group of frequency component data volume altogether of hanking
The thin layer tuning 3-D data volume of all sampled points that step (3) is obtained carries out sorting, forms one group of frequency component time-amplitude data body altogether, but simultaneously also sorting generate the single-frequency component time-amplitude section and section;
(5) extract peak swing frequency data body
The result of calculation that step (4) is obtained compares, the extraction time-peak swing frequency data body; The rise time-peak swing frequency data body section and section;
(6) with the result of section or section step display (5), the sandstone reservoir space spread characteristic under the strong amplitude reflectance signature of outstanding demonstration is covered is carried out sand body space prediction of spread; Wherein, the thin sand dominant frequency is about 40Hz, and the coal measure strata dominant frequency is about 20Hz.
Compared with prior art, the invention has the beneficial effects as follows:
(1) the present invention obtains a plurality of frequency component data volumes altogether, can show the unifrequency amplitude section;
(2) the present invention extract time-peak swing frequency data body can intuitively be reflected in the space spread trend that reflects sandstone reservoir a little less than the strong amplitude reflectance signature of coal measures is covered down on section and space;
(3) the present invention provides a kind of directly perceived, practical method for the thin RESERVOIR RECOGNITION in petroclastic rock stratum with prediction.
Description of drawings
Fig. 1 is the principle schematic of the employed thin layer spectrum of the inventive method imaging.
Fig. 2 is the implementation step block diagram of the inventive method.
Fig. 3-the 1st, the original section in the embodiment of the invention.
Fig. 3-the 2nd, the 20Hz amplitude section of using the inventive method to obtain in the embodiment of the invention, wherein dark strong amplitude zone is the coal measure strata reflectance signature.
Fig. 3-the 3rd, use in the embodiment of the invention that the inventive method obtains the 40Hz amplitude section, wherein dark strong amplitude zone is the coal measure strata reflectance signature.
Fig. 3-the 4th, the peak swing frequency section that uses the inventive method to obtain in the embodiment of the invention, wherein dark-background is a low frequency, and light color is high frequency, and white is the 40Hz frequency, leucoplast reflection sand body spread trend.
Embodiment
Below in conjunction with accompanying drawing the present invention is described in further detail:
(1) ultimate principle
The thin layer Spectral Decomposition Technique is based on the technology of the seismic data volume time-frequency conversion of discrete fourier transform.
The discrete fourier transform formula is:
X wherein
nBe Finite Discrete seismic signal, X
mBe its frequency spectrum, N is a sampling number.
X
mCan be write as the expression formula that contains real part and imaginary part:
X
m=U
m+iV
m
Spectral amplitude A then
mBe expressed as:
Frequency representation is:
Wherein, Δ is a sampling rate, and m is the frequency number, and N is a sampling number.
The theoretical foundation of thin layer Spectral Decomposition Technique is that the thin bed reflections system can produce complicated tuned reflective (shown in accompanying drawing 1).But thin strate is reflected in unique feature representation variation in thickness instruction time in the frequency field.The thin layer spectral factorization calculates the thin layer tuning 3-D data volume.The spectral amplitude that is obtained by thin layer tuning reflection can confirm to constitute the relation between the acoustic wave character on single stratum of reflection, and spectral amplitude falls into frequently curve and confirms the thin strate situation of change through composing.It is relevant with the variation of local rock mass (like local geology, fluid, sedimentology etc.) that spectrum falls into the frequency curve.Spectral amplitude falls into the thin layer time variation in thickness of characteristic reflection frequently, and the complex formation spectral change of caving in can disclose the inner lithology cross direction profiles of thin strate characteristic.
After confirming based on the tuning 3-D data volume of thin layer, can be when moving window obtain the tuning 3-D data volume of The whole calculations data volume, generate frequency component data volume and single-frequency component data body altogether through gather again.
Because the coal seam is different with the dominant frequency of non-coal seam sand body, and all belongs to thin layer, the different frequency amplitude response characteristic that can directly obtain with the thin layer Spectral Decomposition Technique is distinguished.Under the situation of coal measure strata coexistence, even obtain the single-frequency section, but on the single-frequency section outstanding show remain the coal measure strata characteristic, weak reflection sandstone features can not get fine embodiment (shown in accompanying drawing 3-2 and accompanying drawing 3-3).Utilize the frequency difference of sand body and coal measure strata can make the weak reflection sandbody features of the strong amplitude of coal measure strata under covering represented (shown in accompanying drawing 3-4).
(2) step of the inventive method
The realization flow of the inventive method is shown in accompanying drawing 2, and is specific as follows:
(1) analyzes poststack and protect width of cloth 3-d seismic data set
Poststack is protected width of cloth 3-d seismic data set carry out spectrum analysis, understand sand body and coal seam spectrum signature, confirm the spectral factorization computer capacity of thin layer spectral factorization computer capacity and whole data volume;
(2) single thin layer spectral factorization is calculated
(1) definite thin layer spectral factorization computer capacity is protected from poststack and is extracted the thin layer data the width of cloth 3-d seismic data set set by step, carries out spectral factorization and calculates, and obtains the thin layer tuning 3-D data volume;
(3) whole data volume spectral factorization is calculated;
Window when moving through pointwise is protected each the sampled point repeating step (2) in the width of cloth 3-d seismic data set to poststack, through calculating the corresponding thin layer tuning 3-D data volume of all sampled points;
(4) divide the one group of frequency component data volume altogether of hanking
The thin layer tuning 3-D data volume of all sampled points that step (3) is obtained carries out sorting, forms one group of frequency component time-amplitude data body altogether, but simultaneously also sorting generate the single-frequency component time-amplitude section and section;
(5) extract peak swing frequency data body
The result of calculation that step (4) is obtained compares, the extraction time-peak swing frequency data body; The rise time-peak swing frequency data body section and section;
(6) with the result of section or section step display (5), the sandstone reservoir space spread characteristic under the strong amplitude reflectance signature of outstanding demonstration is covered is carried out sand body space prediction of spread; Wherein, the thin sand dominant frequency is about 40Hz, and the coal measure strata dominant frequency is about 20Hz.
Accompanying drawing 3-1 is that a poststack is protected width of cloth seismic section; Strong amplitude reflectance signature is the reflection (seeing the coal measure strata B among the accompanying drawing 3-1) of Shanxi group and layer position, Taiyuan group coal measure strata place on the section; This coal measure strata B goes up square box 2+3 section main stem sand body and is this district main force payzone (seeing the reservoir A among the accompanying drawing 3-1), and it is not obvious that this sand body accompanying drawing 3-1 goes up reservoir A characteristic.
Accompanying drawing 3-2 and accompanying drawing 3-3 are respectively on 20Hz and the 40Hz amplitude section, shake reflectance signature doughtily and still concentrate on coal measure strata (seeing the coal measure strata B among accompanying drawing 3-2 and the accompanying drawing 3-3), and the characteristic of reservoir A is not obvious.
The characteristic that accompanying drawing 3-4 goes up reservoir A is obvious, and horizontal expansion scope and the relative thickness of reservoir A are also high-visible, and actual well drilled confirms that the D place sand body of reservoir A is thicker than E place sand body, and the D place obtains high yield gas, and the E place obtains than high yield gas.The C layer is 1 section ultra-thin sand body of box (not obvious on accompanying drawing 3-1~accompanying drawing 3-3), and the sand body enrichment degree is better than the D place to the C layer at the E place.
Technique scheme is one embodiment of the present invention; For those skilled in the art; On the basis that the invention discloses application process and principle, be easy to make various types of improvement or distortion, and be not limited only to the described method of the above-mentioned embodiment of the present invention; Therefore the mode of front description is just preferred, and does not have restrictive meaning.
Claims (2)
1. a coal measures shakes the recognition methods that reflectance signature is covered down weak reflection reservoir doughtily; It is characterized in that: said method is at first analyzed poststack and is protected width of cloth 3-d seismic data set; Confirm the spectral factorization computer capacity of thin layer spectral factorization computer capacity and whole data volume, utilize the thin layer spectral factorization to calculate the thin layer tuning 3-D data volume; Window when passing through to move then obtains the tuning 3-D data volume that poststack is protected all sampled points in the width of cloth 3-d seismic data set; Generate frequency component 3-D data volume or single-frequency component 3-D data volume altogether through sorting again; Through relatively obtain time-peak swing frequency data body; Utilize the frequency difference of sand body and coal measure strata to identify coal measures at last and shake the weak reflection reservoir of reflectance signature under covering doughtily.
2. coal measures according to claim 1 shakes the recognition methods that reflectance signature is covered down weak reflection reservoir doughtily, it is characterized in that: said method comprising the steps of:
(1) analyzes poststack and protect width of cloth 3-d seismic data set
Poststack is protected width of cloth 3-d seismic data set carry out spectrum analysis, understand sand body and coal seam spectrum signature, confirm the spectral factorization computer capacity of thin layer spectral factorization computer capacity and whole data volume;
(2) single thin layer spectral factorization is calculated
(1) definite thin layer spectral factorization computer capacity is protected from poststack and is extracted the thin layer data the width of cloth 3-d seismic data set set by step, carries out spectral factorization and calculates, and obtains the thin layer tuning 3-D data volume;
(3) whole data volume spectral factorization is calculated;
Window when moving through pointwise is protected each the sampled point repeating step (2) in the width of cloth 3-d seismic data set to poststack, through calculating the corresponding thin layer tuning 3-D data volume of all sampled points;
(4) divide the one group of frequency component data volume altogether of hanking
The thin layer tuning 3-D data volume of all sampled points that step (3) is obtained carries out sorting, forms one group of frequency component time-amplitude data body altogether, but simultaneously also sorting generate the single-frequency component time-amplitude section and section;
(5) extract peak swing frequency data body
The result of calculation that step (4) is obtained compares, the extraction time-peak swing frequency data body; The rise time-peak swing frequency data body section and section;
(6) with the result of section or section step display (5), the sandstone reservoir space spread characteristic under the strong amplitude reflectance signature of outstanding demonstration is covered is carried out sand body space prediction of spread; Wherein, the thin sand dominant frequency is about 40Hz, and the coal measure strata dominant frequency is about 20Hz.
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Cited By (4)
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CN103048678A (en) * | 2012-12-27 | 2013-04-17 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Method for predicting reservoir |
CN107831541A (en) * | 2017-11-17 | 2018-03-23 | 中国石油天然气集团公司 | Thin strate recognition methods and device based on high density VSP data |
CN111045079A (en) * | 2019-12-20 | 2020-04-21 | 核工业北京地质研究院 | Data processing method for enhancing seismic reflection characteristics |
CN113126155A (en) * | 2021-04-01 | 2021-07-16 | 中国石油化工股份有限公司 | Sandstone reservoir prediction method for strong reflection influence distributed among coal rocks |
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Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103048678A (en) * | 2012-12-27 | 2013-04-17 | 中国石油集团川庆钻探工程有限公司地球物理勘探公司 | Method for predicting reservoir |
CN107831541A (en) * | 2017-11-17 | 2018-03-23 | 中国石油天然气集团公司 | Thin strate recognition methods and device based on high density VSP data |
CN111045079A (en) * | 2019-12-20 | 2020-04-21 | 核工业北京地质研究院 | Data processing method for enhancing seismic reflection characteristics |
CN113126155A (en) * | 2021-04-01 | 2021-07-16 | 中国石油化工股份有限公司 | Sandstone reservoir prediction method for strong reflection influence distributed among coal rocks |
CN113126155B (en) * | 2021-04-01 | 2024-03-01 | 中国石油化工股份有限公司 | Sandstone reservoir prediction method aiming at strong reflection influence distributed among coal rocks |
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