CN107797141A - A kind of method of inverting Cracks character - Google Patents
A kind of method of inverting Cracks character Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 33
- 239000012530 fluid Substances 0.000 claims abstract description 31
- 230000002068 genetic effect Effects 0.000 claims description 22
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- 238000005315 distribution function Methods 0.000 abstract description 3
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V1/00—Seismology; Seismic or acoustic prospecting or detecting
- G01V1/28—Processing seismic data, e.g. for interpretation or for event detection
- G01V1/30—Analysis
- G01V1/306—Analysis for determining physical properties of the subsurface, e.g. impedance, porosity or attenuation profiles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6161—Seismic or acoustic, e.g. land or sea measurements
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/61—Analysis by combining or comparing a seismic data set with other data
- G01V2210/616—Data from specific type of measurement
- G01V2210/6169—Data from specific type of measurement using well-logging
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V2210/00—Details of seismic processing or analysis
- G01V2210/60—Analysis
- G01V2210/62—Physical property of subsurface
- G01V2210/622—Velocity, density or impedance
- G01V2210/6224—Density
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Abstract
The present invention proposes a kind of method of inverting Cracks character, comprises the following steps：AVAZ features are become based on frequency and establish inversion objective function；Establish the likelihood function of fracture parameters respectively according to the solving result of inversion objective function；The prior distribution of fracture parameters is combined with the likelihood function of fracture parameters, calculates the Posterior probability distribution function of fracture parameters；Inversion result is intuitively shown using the method for statistics.The present invention new method than existing method in terms of medium supposed premise closer to truth；More Cracks characters can be predicted in result and carry out fluid identification；Realize effective balanced geology, well logging and the reasonable fusion process of earthquake information.
Description
Technical field
The present invention relates to oil gas technical field of physical geography, in particular it relates to a kind of method of inverting Cracks character.
Background technology
With the utilization of oil-gas resource, conventional Porous Reservoir reserves are increasingly reduced, development difficulty by
Cumulative big, oil and gas exploration trend gradually turns to deep by superficial part, turns to special oil and gas pools by conventional oil gas reservoir, especially
It is crack elimination (tight sand, carbonate rock and shale reservoir etc.).The research of FRACTURE PREDICTION is significant.
Nearly all oil-gas reservoir can all be influenceed by intrinsic fracture to a certain extent.The crack of underground development is often
Oil gas storage important place, and crack as a kind of universal phenomenon universally present in all kinds of lithostratigraphies.In carbonate
In rock reservoir, intrinsic fracture helps to form secondary pore, and enhances the connectedness of reservoir space.In most of unconventional storages
Layer, including in coal bed gas, shale gas, basement rock and volcanic rock reservoir, intrinsic fracture is main factors on productivity.The shape in crack
Controlled into by many factors, its physical attribute is complicated, horizontal, longitudinally varying big, shows very strong anisotropy.Therefore utilize
Anisotropic seismic response detection crack is current Earth physicists' study hotspot.
FRACTURE PREDICTION is often what is grown up on rock physicses Research on Equivalent Model basis, is had been set up at present
A series of petrophysical model of anisotropic mediums, two-phase media and Two-phase Anisotropic Media.It is but both domestic and external at present
The main still research based on static petrophysical model of crack prediction method, it is pre- in the crack based on dynamic petrophysical model
Survey research aspect almost blank.
AVAZ (amplitude versus offset and azimuth) analysis is that Study of Seismic wavelet reflects through interface
Amplitude, can quantitative study HTI (horizontal transverse isotropic) Jie with incidence angle and azimuthal change afterwards
The Cracks character of matter.However, based on the inverting Fractured Quality Research of AVAZ features by static state under long wavelength's assumed condition etc.
The limitation of dielectric model is imitated, typically can only inverting fracture spacing and fractuer direction.In recent years, with considering splitting for flow mechanism
The development of seam property porous materials models, frequency become seismic properties and are proved to have sensitiveness to more Cracks characters.Therefore, it is based on
Dynamic petrophysical model, become the development that AVAZ response characteristic inverting Cracks characters are future fracture quantitative inversions using frequency and become
Gesture.
Investigated according to correlation, it is less with the method for AVAZ quantitative forecast Cracks characters at present, based on dynamic rock physicses mould
The technology of type inverting Cracks character is in the research starting stage.Ali and Jakobsen (2013) is based on frequency and becomes AVAZ characteristic uses
Bayesian theory and MCMC (Markov chain Monte Carlo) algorithm inverting fracture strike, fracture spacing, fracture aperture
And fracture radius, and estimate permeability；Lan Huitian (2014) becomes AVO invertings fracture spacing, fracture radius and porosity using frequency.
Above two inversion method can not all carry out fluid identification, and the prior information dependence that the former obtains to geology, well logging is big, after
Person does not account for how rationally merging geology, the results of fracture prediction of well logging.
However, actually the complexity in crack requires that right combination geology, well logging and seismic data could be more accurately pre-
Cracks character is surveyed, and certain error often occurs in the prediction result of these information, i.e., inconsistent situation, therefore, needs
Will based on the theoretical research of dynamic rock physicses can balanced geology, well logging and earthquake information usage amount inverting Cracks character side
Method.
The content of the invention
In order to based on the dynamic petrophysical model closer to actual conditions, realize rationally balanced geology, well logging and earthquake
Cracks character is predicted Deng Reservoir data from multiple disciplines, the present invention is theoretical based on Chapman, proposes a kind of method of Cracks character inverting, will
Bayesian theory and genetic algorithm combination inverting HTI media fracture length, fracture strike, fracture spacing and fluid type, and have
Imitate balanced geology, well logging and earthquake information uses amount.
According to an aspect of the present invention, there is provided a kind of method of inverting Cracks character, comprise the following steps：
AVAZ features are become based on frequency and establish inversion objective function；
Establish the likelihood function of fracture parameters respectively according to the solving result of inversion objective function；
The prior distribution of fracture parameters is combined with the likelihood function of fracture parameters, calculates the posterior probability point of fracture parameters
Cloth function；
Inversion result is intuitively shown using the method for statistics.
Further, using the product of prior distribution and likelihood function as posterior probability density function.
Further, fluid type, fracture length and the fracture spacing prior information provided according to geology, well logging is obeyed high
This distribution obtains prior distribution, as stochastic variable and is counted fluid type, fracture length, fracture spacing by the use of bayesian algorithm
Calculate their posterior probability density function.
Further, fluid type, fracture length and fracture spacing prior information geology, well logging obtained is as priori
The desired value of distribution, and standard deviation of the stochastic variable on spatial mesh size is calculated, the Gauss obtained using desired value and standard deviation
It is distributed as prior distribution.
Further, inversion objective function is solved with genetic algorithm.
Further, the likelihood letter of the fracture parameters of Gaussian distributed is built respectively according to the solving result of genetic algorithm
Number, standard deviation is calculated using the result that genetic algorithm obtains as desired value, scope and the desired value of model parameter, desired value determines
The center of Gaussian Profile, standard deviation determine the amplitude of distribution.
Further, stochastic variable is the most termination of inverting in variate-value corresponding to posterior probability Density Distribution peak
Fruit.
Further, the reflection R observed on I incidence angle, K frequency, J observation survey line is utilizedijkWith it is identical
Under the conditions of Q fluid type, P fracture length, the modeling reflectance factor in N number of fracture spacing spatial mesh sizeLeast square fitting structure inversion objective function be：
Wherein, f is frequency, and e is fracture spacing, and l is fracture length, and t is fluid type, and o is known parameters；RijkBe
The incidence angle θ of series of discretei, azimuthWith frequency fkIn the case of reflectance factor observation data, define the side of a certain survey line
Parallactic angle isIt is η that can calculate other surveys line with the azimuthal difference of the survey line according to observation system informationj, i.e., other survey line azimuths
For
Further, using making function in Q fluid type of Genetic algorithm searching, P fracture length, N number of fracture spacing
Corresponding fluid type, fracture length, the value of fracture spacing are as genetic inverse result during fitness minimum values.
The present invention be based on dynamic petrophysical model, using earthquake information construction object function and by geology, well logging information
As prior information, bayesian theory is combined to prediction fracture length, fracture strike, fracture spacing and fluid class with genetic algorithm
Type, and efficient balance geology, well logging and using for earthquake information are measured.Therefore, new method of the invention is being situated between than existing method
Closer to truth in terms of matter supposed premise；More Cracks characters can be predicted in result and carry out fluid identification；Realize
Effective balanced geology, well logging and the reasonable fusion process of earthquake information.Numerical simulation test result shows：It is proposed by the present invention anti-
The method of drilling can predict fracture strike, fracture spacing, fracture length and fluid type.
Brief description of the drawings
Disclosure illustrative embodiments are described in more detail in conjunction with the accompanying drawings, the disclosure above-mentioned and its
Its purpose, feature and advantage will be apparent, wherein, in disclosure illustrative embodiments, identical reference number
Typically represent same parts.
Fig. 1 shows that fluid becomes AVAZ responses for salt solution time-frequency；Fig. 1 a show that AVAZ is responded when frequency is 10Hz；Fig. 1 b
Show that AVAZ responds difference when frequency is 20Hz and 10Hz；Fig. 1 c show AVAZ difference in response when frequency is 40Hz and 10Hz
Value.
Fig. 2 shows genetic algorithm Cracks character inversion result (band) and its likelihood function probability distribution (curve).
Fig. 3 shows Cracks character Posterior probability distribution.
Embodiment
The preferred embodiment of the disclosure is more fully described below with reference to accompanying drawings.Although the disclosure is shown in accompanying drawing
Preferred embodiment, however, it is to be appreciated that may be realized in various forms the disclosure without the embodiment party that should be illustrated here
Formula is limited.On the contrary, these embodiments are provided so that the disclosure is more thorough and complete, and can be by the disclosure
Scope is intactly communicated to those skilled in the art.
Quantitatively characterizing Cracks character, it is that current fracture-type reservoir is ground based on the AVAZ responses comprising seismic dynamics feature
The hot issue studied carefully.In terms of the data investigated, the prediction of fracture property is limited by static petrophysical model, typically
Fracture spacing and fracture strike prediction can only be carried out, and consider the dynamic petrophysical model of seismic wave inducing fluid flowing
Develop into the more Cracks characters of prediction and provide possibility.At present, based on the dynamic rock for considering velocity dispersion and influence of fading
Almost blank, only correlative study also fail to rationally more of effective fusion for the research of physical model progress Cracks character prediction
Section's information carries out FRACTURE PREDICTION.
The present invention is directed to HTI media, becomes AVAZ responses to frequency based on Chapman theory analysises fluid type and fracture length
The influence of feature, establish and filled with reference to bayesian theory and genetic inverse fracture spacing, fracture strike, fracture length and crack
The method for filling out fluid type.
The present disclosure proposes a kind of method of inverting Cracks character, comprise the following steps：
AVAZ features are become based on frequency and establish inversion objective function；
Establish the likelihood function of fracture parameters respectively according to the solving result of inversion objective function；
The prior distribution of fracture parameters is combined with the likelihood function of fracture parameters, calculates the posterior probability point of fracture parameters
Cloth function；
Inversion result is intuitively shown using the method for statistics.
Further, using the product of prior distribution and likelihood function as posterior probability density function.
Further, fluid type, fracture length and the fracture spacing prior information provided according to geology, well logging is obeyed high
This distribution obtains prior distribution, as stochastic variable and is counted fluid type, fracture length, fracture spacing by the use of bayesian algorithm
Calculate their posterior probability density function.
Further, fluid type, fracture length and fracture spacing prior information geology, well logging obtained is as priori
The desired value of distribution, and standard deviation of the stochastic variable on spatial mesh size is calculated, the Gauss obtained using desired value and standard deviation
It is distributed as prior distribution.
Further, inversion objective function is solved with genetic algorithm.
Further, the likelihood letter of the fracture parameters of Gaussian distributed is built respectively according to the solving result of genetic algorithm
Number, standard deviation is calculated using the result that genetic algorithm obtains as desired value, scope and the desired value of model parameter, desired value determines
The center of Gaussian Profile, standard deviation determine the amplitude of distribution.
Further, stochastic variable is the most termination of inverting in variate-value corresponding to posterior probability Density Distribution peak
Fruit.
Specifically, Chapman is theoretical and R ü ger approximately become frequently longitudinal wave reflection coefficient function intoIts
In, f is frequency, and e is fracture spacing, and l is fracture length, and t is fluid type, and o is related to other when being structure Chapman models
Parameter, known parameters are used as in this paper refutation processes.RijkIt is the incidence angle θ in series of discretei, azimuthWith frequency fk
In the case of reflectance factor observation data.The azimuth for defining a certain survey line isOther surveys can be calculated according to observation system information
Line and the azimuthal difference of the survey line are ηj, i.e., other survey line azimuths areThe object function of foundation：
Utilize the reflection R observed on I incidence angle, K frequency, J observation survey lineijkWith Q under the same terms
Fluid type, P fracture length, the modeling reflectance factor in N number of fracture spacing spatial mesh size
Least square fitting structure formula (1), utilize Q fluid type of Genetic algorithm searching, P fracture length, N number of fracture spacing
In corresponding fluid type when making function fitness minimum values in formula (1), fracture length, the value of fracture spacing as losing
Propagation algorithm inversion result.
Build the fracture parameters likelihood function of Gaussian distributed respectively according to genetic algorithm result, i.e. genetic algorithm obtains
Result as desired value, scope and the desired value of model parameter can calculate standard deviation, and desired value is determined in Gaussian Profile
Heart position, standard deviation determine the amplitude of distribution.It is close according to the fluid type of the offers such as geology, well logging, fracture length and crack
Degree prior information Gaussian distributed obtain prior distribution, using bayesian algorithm by unknown parameter be fluid type, crack grow
Degree, fracture spacing as stochastic variable and calculate their posterior probability density function, i.e. prior distribution and likelihood function multiplies
Product is used as posterior probability density function.
Control critical eigenvalue property prior probability variance equilibrium geology, well logging and using for earthquake information are measured, prior probability distribution
Variance selected value is smaller to mean that geology, well logging information are bigger on final result influence；Prior probability distribution variance selected value is got over
Mean that final result depends on earthquake information greatly.Stochastic variable is in variable corresponding to posterior probability Density Distribution peak
Value is the final result of inverting, realizes the prediction of fracture spacing, fracture strike, fracture length and fluid type.
For ease of understanding the scheme of the embodiment of the present invention and its effect, a concrete application example given below.This area
It should be understood to the one skilled in the art that the example, only for the purposes of understanding the present invention, its any detail is not intended to be limited in any way
The system present invention.
AVAZ features are become based on frequency and establish inversion objective function and with genetic algorithm solution, are established respectively according to this result
The likelihood function of fracture parameters (referring to Fig. 2).For example, histogram represents genetic algorithm result in Fig. 2 (a), i.e. fracture spacing is
0.1, using 0.1 as desired value；Calculate the standard of they and desired value 0.1 respectively between the scope 0 to 0.3 of fracture spacing
Difference；The Gaussian Profile of desired value and standard deviation is the likelihood function that curve is fracture spacing in figure.
Secondly, the Cracks character prior information of the acquisitions such as geology, well logging is split with what earthquake obtained using bayesian algorithm
Stitch property likelihood function to combine, calculate the Posterior probability distribution function of Cracks character (referring to Fig. 3).Geology, well logging etc. are obtained
Desired value of the Cracks character as prior probability, and calculate standard deviation of the stochastic variable on spatial mesh size, utilize desired value
The Gaussian Profile obtained with standard deviation is prior probability distribution.The product of prior probability and likelihood function is posteriority on spatial mesh size
Probability-distribution function.Intuitively show inversion result using the method for statistics, numerical value test result demonstrate the feasibility of method with
Stability.
It is described above the presently disclosed embodiments, described above is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.In the case of without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes will be apparent from for the those of ordinary skill in art field.The selection of term used herein, purport
Best explaining the principle of each embodiment, practical application or to the technological improvement in market, or make the art its
Its those of ordinary skill is understood that each embodiment disclosed herein.
Claims (9)
- A kind of 1. method of inverting Cracks character, it is characterised in that comprise the following steps：AVAZ features are become based on frequency and establish inversion objective function；Establish the likelihood function of fracture parameters respectively according to the solving result of inversion objective function；The prior distribution of fracture parameters is combined with the likelihood function of fracture parameters, calculates the Posterior probability distribution letter of fracture parameters Number；Inversion result is intuitively shown using the method for statistics.
- 2. the method for inverting Cracks character according to claim 1, it is characterised in that by prior distribution and likelihood function Product is as posterior probability density function.
- 3. the method for inverting Cracks character according to claim 2, it is characterised in that the stream provided according to geology, well logging Body type, fracture length and fracture spacing prior information Gaussian distributed obtain prior distribution, will be flowed using bayesian algorithm Body type, fracture length, fracture spacing as stochastic variable and calculate their posterior probability density function.
- 4. the method for inverting Cracks character according to claim 3, it is characterised in that the fluid for obtaining geology, well logging The desired value of type, fracture length and fracture spacing prior information as prior distribution, and stochastic variable is calculated in spatial mesh size On standard deviation, the Gaussian Profile obtained using desired value and standard deviation is prior distribution.
- 5. the method for inverting Cracks character according to claim 1, it is characterised in that solve inverting mesh with genetic algorithm Scalar functions.
- 6. the method for inverting Cracks character according to claim 5, it is characterised in that according to the solving result of genetic algorithm The likelihood function of the fracture parameters of Gaussian distributed is built respectively, using the result that genetic algorithm obtains as desired value, model The scope of parameter calculates standard deviation with desired value, and desired value determines the center of Gaussian Profile, and standard deviation determines distribution Amplitude.
- 7. the method for inverting Cracks character according to claim 4, it is characterised in that stochastic variable is in posterior probability density Variate-value corresponding to distribution peak is the final result of inverting.
- 8. the method for inverting Cracks character according to claim 1, it is characterised in that using I incidence angle, K frequency, The reflection R observed on J observation survey lineijkIt is close with Q fluid type, P fracture length, N number of crack under the same terms The modeling reflectance factor spent in spatial mesh sizeLeast square fitting structure inversion objective function For：Wherein, f is frequency, and e is fracture spacing, and l is fracture length, and t is fluid type, and o is known parameters；RijkIt is in a system Arrange discrete incidence angle θi, azimuthWith frequency fkIn the case of reflectance factor observation data, define the azimuth of a certain survey line ForIt is η that can calculate other surveys line with the azimuthal difference of the survey line according to observation system informationj, i.e., other survey line azimuths are
- 9. the method for inverting Cracks character according to claim 8, it is characterised in that utilize Q stream of Genetic algorithm searching Corresponding fluid type when making function fitness minimum values in body type, P fracture length, N number of fracture spacing, fracture length, The value of fracture spacing is as genetic inverse result.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112901158A (en) * | 2021-02-20 | 2021-06-04 | 中国石油天然气集团有限公司 | Hydraulic fracture length prediction method and fracture network modeling method and device |
| CN112948765A (en) * | 2019-12-10 | 2021-06-11 | 豪夫迈·罗氏有限公司 | Method and apparatus for determining the vertical position of a horizontally extending interface between a first component and a second component |
| CN113159321A (en) * | 2021-04-07 | 2021-07-23 | 中南大学 | Bayes inference method for fracture surface morphology under gravity constraint |
| CN113341465A (en) * | 2021-06-11 | 2021-09-03 | 中国石油大学(北京) | Method, device, medium and equipment for predicting ground stress of orientation anisotropic medium |
| CN113486721A (en) * | 2021-06-09 | 2021-10-08 | 北京科技大学 | Pavement crack detection method based on rolling optimization crack classification recognition model |
| CN115292971A (en) * | 2022-10-09 | 2022-11-04 | 中科数智能源科技(深圳)有限公司 | Bayes-based crack attribute analysis method and device and storage medium |
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112948765A (en) * | 2019-12-10 | 2021-06-11 | 豪夫迈·罗氏有限公司 | Method and apparatus for determining the vertical position of a horizontally extending interface between a first component and a second component |
| CN112901158A (en) * | 2021-02-20 | 2021-06-04 | 中国石油天然气集团有限公司 | Hydraulic fracture length prediction method and fracture network modeling method and device |
| CN113159321A (en) * | 2021-04-07 | 2021-07-23 | 中南大学 | Bayes inference method for fracture surface morphology under gravity constraint |
| CN113159321B (en) * | 2021-04-07 | 2022-05-20 | 中南大学 | Bayes inference method for fracture surface morphology under gravity constraint |
| CN113486721A (en) * | 2021-06-09 | 2021-10-08 | 北京科技大学 | Pavement crack detection method based on rolling optimization crack classification recognition model |
| CN113486721B (en) * | 2021-06-09 | 2023-08-29 | 北京科技大学 | Pavement crack detection method based on rolling optimization crack classification recognition model |
| CN113341465A (en) * | 2021-06-11 | 2021-09-03 | 中国石油大学(北京) | Method, device, medium and equipment for predicting ground stress of orientation anisotropic medium |
| CN113341465B (en) * | 2021-06-11 | 2023-05-09 | 中国石油大学(北京) | Directional anisotropic medium ground stress prediction method, device, medium and equipment |
| CN115292971A (en) * | 2022-10-09 | 2022-11-04 | 中科数智能源科技(深圳)有限公司 | Bayes-based crack attribute analysis method and device and storage medium |
| CN115292971B (en) * | 2022-10-09 | 2022-12-20 | 中科数智能源科技(深圳)有限公司 | Bayes-based crack attribute analysis method and device and storage medium |
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