CN108427141B - A kind of method and system identified in sedimentary formation with extracting cycle fluctuation - Google Patents
A kind of method and system identified in sedimentary formation with extracting cycle fluctuation Download PDFInfo
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Abstract
The invention discloses a kind of to identify the method and system fluctuated with extracting cycle in sedimentary formation, this method comprises: initially setting up sedimentation rate curve, then make wavelet basis function and wavelet transform is made to deposition rate curve, the curve for having stable period is found in the details coefficients of wavelet decomposition, restore the sedimentary wave curve influenced by the cyclic fluctuation further according to the reconstructing method of wavelet transform, the wave equation of the sedimentary wave curve is finally write out according to the signal reconstruction formula of wavelet transform, and the sedimentary wave curve up to stratum is not bored in application wave equation calculating drilling well, according to the predictable geological condition not bored up to stratum of deposition rate variation of curve of cyclical fluctuations reflection.Method and system in the present invention have expanded the technical method of fluction analysis, fast decoupled and period wave can be extracted from deposition rate curve, it is easy to operation, be conducive to the popularization and application of fluction analysis research in actual operation, solve the practical problem in production.
Description
Technical field
The present invention relates to technical field of geophysical exploration, and in particular to one kind related with basin fluction analysis is depositing
The method and system with extracting cycle fluctuation are identified in stratum.
Background technique
Sedimentary basin fluction analysis is to have decomposited rule from some periods, quasi-periodic, aperiodic geological phenomenon
The wave process of rule simultaneously establishes wave equation, realizes a kind of method to geological process quantitative study.Period of waves identifies conduct
Key technology in the research of basin fluction analysis, currently used method is sliding-window filtering method, it may be assumed that utilizes dimensional variation
Sliding window carries out glide filter analysis to deposition rate curve, and identifying and extracting based on the analysis results has periodically fluctuation
Curve.
Since basin fill evolutionary process by multi-level period and aperiodicity factor controlling and influences, filled in basin
Deposition often shows as the features such as periodicity and randomness, mutability and " Multiple Time Scales ", therefore to identify and extract basin
The cyclic fluctuation process under multi-level cyclic fluctuation factor controlling during ground sedimentary evolution, it is finer heavy to need
Product rate curve.
Using sliding-window filtering method fine deposition rate curve higher to resolution ratio carry out cyclic fluctuation identification with
When extraction, due to the high resolution of finer deposition rate curve, change frequency is fast, and geology filters sliding window size variation
Need with small step change, to obtain richer cycle information, it is also necessary to have longer drilling depth, which increase identification with
The difficulty and complexity of extracting cycle fluctuation.When therefore carrying out fluction analysis for finer basin fill rate curve,
It needs new, easy method and the cyclic fluctuation being recorded in sedimentary formation is identified and extracted.
Summary of the invention
There is a problem of that complicated for operation, difficulty is big for existing cyclic fluctuation identification and extractive technique, mesh of the invention
: apply wavelet analysis technology, propose it is a kind of simple and easy to do, and small, the high-efficient cyclic fluctuation identification of operation difficulty with
Extracting method and system.
The present invention provides a kind of method identified in sedimentary formation with extracting cycle fluctuation, comprising the following steps:
S10: sedimentation rate curve is established；
S20: making discrete wavelet analysis to the sedimentation rate curve in step S10, obtains analysis result；
S30: the curve for having stable period is found in the analysis result that step S20 is obtained, and summarizes corresponding mathematics
Equation；
S40: carrying out signal reconstruction to the curve that step S30 is obtained respectively, and the curve obtained at this time is corresponding week
The comprehensive deposition curve of cyclical fluctuations under the influence of fluctuations of phase property；
S50: corresponding wave equation is established according to the curve of cyclical fluctuations that step S40 is obtained；
S60: the sedimentary wave curve prediction that the stratum reached is not bored in drilling well is made according to the wave equation that step S50 is established.
In one embodiment of the invention, the analysis of discrete wavelet described in step S20 is using Meyer small echo as mother
Small echo carries out wavelet transform analysis.
In one embodiment of the invention, analysis result described in step S20 is a series of approximations point decomposed and obtained
Measure curve ANWith details coefficients curve DN, N value be a series of positive integers, the positive integer be derived from positive integer collection 1,2 ... ...,
K-1, K }, wherein K is the number decomposed.
In one embodiment of the invention, curve described in step S30 is cyclic curve or nearly cyclic curve.
In one embodiment of the invention, signal reconstruction described in step S40 is according to wavelet transform
What the signal reconstruction process of Mallat algorithm carried out.
In one embodiment of the invention, wave equation described in step S50 is according to wavelet transform Mallat
The signal reconstruction formula of algorithm obtains, and the signal reconstruction formula is as follows:
AN-1=AN+DN,
It wherein, is A approximation component curve, D is details coefficients curve, and N is the number decomposed.
In one embodiment of the invention, sedimentary wave curve prediction described in step S60, passes through deposition rate
The strata condition for not boring the stratum reached is predicted in variation.
In one embodiment of the invention, the content of the prediction be do not bore the lithology up to stratum, depositional environment variation,
Buried history and/or tectonism.
Another aspect of the present invention also provides a kind of system identified in sedimentary formation with extracting cycle fluctuation,
Include:
Deposition rate curved unit, for establishing sedimentation rate curve；
Discrete wavelet analytical unit, for making discrete wavelet to the sedimentation rate curve in deposition rate curved unit
Analysis obtains analysis result；
Periodic searches unit has stable period for finding from analysis result obtained in discrete wavelet analytical unit
Curve, and summarize corresponding math equation；
Curve of cyclical fluctuations recovery unit: for carrying out signal reconstruction respectively to the curve obtained in periodic searches unit,
The curve obtained at this time is the comprehensive deposition curve of cyclical fluctuations under respective cycle influence of fluctuations；
Wave equation establishes unit, establishes corresponding wave for the curve of cyclical fluctuations according to obtained in curve of cyclical fluctuations recovery unit
Dynamic equation；And
Curve of cyclical fluctuations predicting unit, the wave equation established in unit is established for wave equation and makes drilling well and does not bore reaches
The sedimentary wave curve prediction on stratum.
In one embodiment of the invention, curve of cyclical fluctuations predicting unit is by the variation of deposition rate to not boring the ground reached
The strata condition of layer is predicted.
The method and system fluctuated with extracting cycle are identified in sedimentary formation in the present invention, have expanded fluction analysis
Technical method, fast decoupled and period wave can be extracted from deposition rate curve, it is easy to operation, be conducive to fluctuate
The popularization and application of analysis and research in actual operation, solve the practical problem in production.
Detailed description of the invention
The invention will be described in more detail below based on embodiments and refering to the accompanying drawings.Wherein:
Fig. 1 is the flow chart that the embodiment of the present invention one identifies the method fluctuated with extracting cycle in sedimentary formation；
Fig. 2 is the deposition rate curve that step S10 chooses in the embodiment of the present invention two；
Fig. 3 is the approximation component curve and details coefficients curve decomposed in step S20 in the embodiment of the present invention two；
Fig. 4 be in the embodiment of the present invention two in sedimentary formation identify with extracting cycle fluctuation method application result and
Using the comparison diagram for the result that glide filter method analyzes；
Fig. 5 be in sedimentary formation in the embodiment of the present invention three method application the result of identification and extracting cycle fluctuation and
Using the comparison diagram for the result that glide filter method analyzes；
Fig. 6 is the structural schematic diagram of identification and extracting cycle fluctuation in sedimentary formation in the embodiment of the present invention four.
In the accompanying drawings, identical component uses identical appended drawing reference.Attached drawing is not according to actual ratio.
Specific embodiment
It is detailed with specific embodiment with reference to the accompanying drawings in order to keep disclosed technology contents more detailed and complete
Carefully illustrate the purpose of the present invention, technical solution and technical effect.Although it should be strongly noted that being said for attached drawing
It is bright, it will be appreciated by those of skill in the art that accompanying drawings and embodiments are not intended to limit the invention covered range.
The chronomere Ma (million anniversary) being related in the application is 1000000 years；Mallat algorithm is
It is theoretical in conjunction with multiresolution analysis by S.Mallat in the case where being inspired for the pyramid algorith of picture breakdown, the signal of proposition
The decomposition and reconstruction algorithm of tower multiresolution analysis, abbreviation Mallat fast algorithm, be a kind of fast orthogonal wavelet decomposition and
Restructing algorithm, its status in wavelet analysis are equal to status of the Fast Fourier Transform (FFT) in Fourier analysis, the algorithm
Even without the expression of scaling function and wavelet function, it is only necessary to the filter coefficient in two-scale equation, so that it may
To carry out wavelet function feedback.
Meyer small echo is in first constructed in 1986 by French mathematician Y.Meyer with arbitrary order slickness
Orthonormal Wavelets have arbitrary order continuity, symmetry and exponential damping characteristic, it is to pass through a pair without time-domain expression
The frequency spectrum of conjugate quadrature mirror mirror filter group defines, and wavelet function is formula (a) in the definition of frequency domain:
In formula (a), v (x) is the auxiliary function for constructing Meyer small echo, meets formula (b)
That is:
And
ν (x)+ν (1-x)=1 (d).
Dmeyer small echo is discrete Meyer small echo, cannot be used when being used for wavelet transform due to Meyer small echo quick
Algorithms of Discrete Wavelet Transform, therefore when using Mallat algorithm, discrete Meyer small echo, i.e. Dmeyer small echo need to be used.
Embodiment one
As shown in Figure 1, for the process identified in sedimentary formation with the method for extracting cycle fluctuation in the present embodiment
Figure, method in this implementation the following steps are included:
S10: sedimentation rate curve is established；
S20: making discrete wavelet analysis to the sedimentation rate curve in step S10, obtains analysis result；
S30: the curve for having stable period is found in the analysis result that step S20 is obtained, and summarizes corresponding mathematics
Equation；
S40: carrying out signal reconstruction to the curve that step S30 is obtained respectively, and the curve obtained at this time is corresponding week
The comprehensive deposition curve of cyclical fluctuations under the influence of fluctuations of phase property；
S50: corresponding wave equation is established according to the curve of cyclical fluctuations that step S40 is obtained；
S60: the sedimentary wave curve prediction that the stratum reached is not bored in drilling well is made according to the wave equation that step S50 is established.
Embodiment two
In the present embodiment, with regard to the specific application of the method in embodiment one, specially to article, " Caidamu Basin is newborn
For wave process and and Hydrocarbon Relationship " (Jin Zhijun, Li Jingchang, the Caidamu Basin the Cenozoic wave process such as good outstanding person of soup and with oil
Air to close system [J] geology journal, 2006,80 (3): 359-365.) used in deposition rate histogram obtained by discrete sampling
Deposition rate curve, carry out the identification of period wave using method proposed by the present invention and extract, can be according to using the present invention to obtain
Recognition result and article in the result that obtains using glide filter method compare verifying.The comparison of detailed process and result
It is described in detail in the present embodiment.
Step S10: sedimentation rate curve is established；
The specific method for building up of layer deposition rate curve has extensive record, those skilled in the art's root in the prior art
It can be convenient completion according to the prior art, do not repeating herein.In the present embodiment, the deposition rate curve specifically chosen is as schemed
It is article " Caidamu Basin Cenozoic wave process and and Hydrocarbon Relationship " (Jin Zhijun, Li Jingchang, bavin such as good outstanding person of soup shown in 2
Up to the wooden Basin In The Cenozoic wave process and with Hydrocarbon Relationship [J] geology journal, 2006,80 (3): 359-365.) used in sink
The deposition rate curve that product rate histogram is obtained by discrete sampling.
Step S20: making discrete wavelet analysis to the sedimentation rate curve in step S10, obtains analysis result；This reality
It applies wavelet transform in example and uses Mallat algorithm, morther wavelet Meyer need to use discrete Meyer small echo, i.e. Dmeyer small echo.
Deposition rate curve therein obtains a series of approximation component curve A of decomposition after this step wavelet transformNAnd details
Component curve DN, N value is a series of positive integers, and the positive integer is derived from positive integer collection { 1,2 ... ..., K-1, K }, and wherein K is
The number of decomposition.
Specific curve is as shown in figure 3, wherein A is approximation component curve and D is details coefficients curve: for deposition rate song
The approximation component curve A that line is decomposited through step S20 as wavelet transformNWith details coefficients curve DN, in the present embodiment, K
It is 6.
Step S30: finding the curve for having stable period in the analysis result that step S20 is obtained, and summarizes corresponding
Math equation；In the present embodiment, the curve is cyclic curve or nearly cyclic curve, and the corresponding fluctuation of the curve is
For using the curve cycle value as the cyclic fluctuation in period；
Specifically, since geological process has complexity, non-stationary and developing under a certain trend non-linear etc. special
Point, leading to each fluctuation in cyclic fluctuation is not the period stringent constant absolute periodic wave in mathematical meaning, they
Period can make minor change around a certain fixed value, show as basic or make periodical cycle evolution generally about a certain period,
This period in possible long point of a certain earth history period, may become short point in another earth history period, therefore thin again
Periodic quantity is found in section component curve around a certain numerical value basicly stable curve in error range.
Specifically, in the present embodiment, the present embodiment finds the period in the details coefficients that step S20 is obtained and is respectively
Two of 20Ma (curve D4 in Fig. 3) and 9.8Ma (curve D3 in Fig. 3) have the curve of stable period.From in Fig. 3 in response curve
Initial phase value is read, and amplitude function is fitted according to amplitude variations situation, then writes out the approximation of this two cyclic curves
Equation, as shown in formula (1) and formula (2):
Step S40: signal reconstruction is carried out respectively to the curve that step S30 is obtained, the curve obtained at this time is phase
Answer the comprehensive deposition curve of cyclical fluctuations under the influence of cyclic fluctuation；In the present embodiment, signal reconstruction is according to wavelet transform
What the signal reconstruction process of Mallat algorithm carried out.
Signal reconstruction is carried out according to the signal reconstruction formula of wavelet transform Mallat algorithm, the curve obtained at this time is i.e.
For the comprehensive deposition rate fluctuation curve under the influence of corresponding cyclic fluctuation.According to the restructuring procedure, 20Ma weeks in the present embodiment
Comprehensive deposition rate fluctuation curve under the influence of phase fluctuation (the curve D4 in Fig. 3) is approximation component A3(curve A3 in Fig. 3),
The comprehensive deposition curve of cyclical fluctuations under the influence of 9.8Ma cyclic swing (curve D3 in Fig. 3) is approximation component A2(curve A2 in Fig. 3).
Step S50: corresponding wave equation is established according to the curve of cyclical fluctuations that step S40 is obtained；In the present embodiment, fluctuation
Equation is obtained according to the signal reconstruction formula of wavelet transform Mallat algorithm, the signal reconstruction formula are as follows: AN-1=AN+
DN, (wherein, it is A approximation component curve, D is details coefficients curve, and N is the number decomposed.)
In the present embodiment, according to the decomposition curve in step S40, can establish comprehensive deposition rate fluctuation curve A3 and
The wave equation of A2, respectively as shown in formula (3) and (4):
Step S60: according to step S50 establish wave equation make drilling well do not bore the stratum reached sedimentary wave curve it is pre-
It surveys.In the present embodiment, sedimentary wave curve prediction described in step S60, variation by deposition rate is not to boring the ground reached
The strata condition of layer is predicted.The content of prediction is not bore the lithology up to stratum, depositional environment variation, buried history and/or structure
Make variation etc..
Fig. 4 is identifying in the present embodiment in sedimentary formation and the method application result of extracting cycle fluctuation and uses
The comparison diagram for the result that glide filter method analyzes: in Fig. 4 ordinate be the time, unit Ma (Million anniversary,
1000000 years), abscissa is deposition rate, unit m/Ma (rice/million year, rice every million years).Two columns are article " bavin among Fig. 4
Up to the wooden Basin In The Cenozoic wave process and and Hydrocarbon Relationship " in using glide filter method analyze as a result, as original image；Fig. 4
Middle left end column and right end column curve are the result analyzed using the embodiment of the present invention.In article " Caidamu Basin Cenozoic wave
Dynamic process and and Hydrocarbon Relationship " using glide filter method analyze as a result, i.e. in original image, curve M is that 30Ma sliding window obtains
Deposition rate sliding average curve, curve N is the obtained deposition rate sliding average curve of 15Ma sliding window, and curve Y is 5Ma
The deposition rate sliding average curve that sliding window obtains, curve n1 are the curve of cyclical fluctuations for being 20Ma the period, and curve n2 is the period to be
The curve of cyclical fluctuations of 9.6Ma；The song in curve M ' and original image in the result analyzed using the embodiment of the present invention, in the column of left end
Line M is corresponding, and curve N ' is corresponding with the curve N in original image, and curve Y ' is corresponding with the curve Y in original image, the period wave in right end column
N1 ' is corresponding with the period wave n1 that original image is decomposed, and period wave n2 ' is corresponding with period wave n2, in terms of comparing result, using the present invention point
The comprehensive deposition curve of cyclical fluctuations and period wave of precipitation all with article " Caidamu Basin Cenozoic wave process and and Hydrocarbon Relationship "
The result analyzed using glide filter method is almost the same.
Embodiment three
In order to further verify the validity of the method in the present invention, the present embodiment is by the method application in the present invention
In article " identification of Tarim Basin high frequency waves and its meaning ", (Fan Guozhang, Jin Zhijun, Liu Guochen wait the Tarim Basin high frequency waves
Identification and its meaning [J] deposit journal, 2001,19 (2): 245-248.) used in deposition rate curve analyzed.Tool
Body method is identical as embodiment two, is not repeating herein.In the present embodiment, be illustrated in figure 5 using the present invention in method into
The comparison diagram of the analysis result obtained in the result and article of row analysis using sliding-window filtering method.As shown in figure 5, curve A '
It is the curve of cyclical fluctuations obtained using the method in the present invention with curve B '；Curve A and curve B is to filter in article using sliding window
The curve of cyclical fluctuations that wave method obtains.Wherein: curve A ' is corresponding with curve A, and curve B ' is corresponding with curve B.By the comparison in figure it is found that
The two is almost the same.Further prove the validity of the method in the present invention.
Example IV
As shown in fig. 6, for identifying in the present invention in sedimentary formation, the structure of the system fluctuated with extracting cycle is shown
It is intended to, which includes:
Deposition rate curved unit 1, for establishing sedimentation rate curve；
Discrete wavelet analytical unit 2 is discrete small for making to the sedimentation rate curve in deposition rate curved unit
Wave analysis obtains analysis result；
Periodic searches unit 3 has stable period for finding from analysis result obtained in discrete wavelet analytical unit
Curve, and summarize corresponding math equation；
Curve of cyclical fluctuations recovery unit 4: for carrying out signal reconstruction respectively to the curve obtained in periodic searches unit,
The curve obtained at this time is the comprehensive deposition curve of cyclical fluctuations under respective cycle influence of fluctuations；
Wave equation establishes unit 5, establishes for the curve of cyclical fluctuations according to obtained in curve of cyclical fluctuations recovery unit corresponding
Wave equation；And
Curve of cyclical fluctuations predicting unit 6, the wave equation established in unit is established for wave equation and makes drilling well and does not bore reaches
Stratum sedimentary wave curve prediction.
Preferably, discrete wavelet analytical unit 2 is using Dmeyer small echo as morther wavelet, using Mallat algorithm to deposition rate
Curve carries out wavelet transform analysis.
Preferably, the analysis result of discrete wavelet analytical unit 2 is a series of approximation component curve A for decomposing and obtainingNWith
Details coefficients curve DN, wherein N is the number decomposed, and N value is a series of positive integers, and the positive integer is derived from positive integer collection
{ 1,2 ... ..., K-1, K }, wherein K is the number decomposed.
Preferably, the curve for having stable period that periodic searches unit 3 is found is cyclic curve or nearly cyclic curve.
Preferably, curve of cyclical fluctuations recovery unit 4 is according to the signal reconstruction process of wavelet transform Mallat algorithm to week
The curve obtained in phase search unit carries out signal reconstruction respectively, and the curve obtained at this time is respective cycle fluctuation shadow
The comprehensive deposition curve of cyclical fluctuations under ringing；
Preferably, wave equation is established the curve of cyclical fluctuations according to obtained in curve of cyclical fluctuations recovery unit of unit 5 and is established accordingly
Wave equation, the specific signal reconstruction formula according to wavelet transform Mallat algorithm obtains, the signal reconstruction
Formula is as follows:
AN-1=AN+DN,
It wherein, is A approximation component curve, D is details coefficients curve, and N is the number decomposed.
Preferably, curve of cyclical fluctuations predicting unit 6 by the variation of deposition rate to do not bore the strata condition on the stratum reached into
Row prediction.The content of prediction is not bore the lithology up to stratum, depositional environment variation, buried history and/or tectonism.
Cyclic fluctuation identification as basin fluction analysis research in key point, practical fluction analysis study in have compared with
Big difficulty.This can be effectively reduced with the method and system of extracting cycle fluctuation in identifying in the present invention in sedimentary formation
Difficulty keeps identification period of waves and extraction simple and easy to do and efficient.
Although by reference to preferred embodiment, invention has been described, the case where not departing from the scope of the present invention
Under, various improvement can be carried out to it and can replace component therein with equivalent.Especially, as long as there is no structures to rush
Prominent, items technical characteristic mentioned in the various embodiments can be combined in any way.The invention is not limited to texts
Disclosed in specific embodiment, but include all technical solutions falling within the scope of the claims.
Claims (10)
1. a kind of method identified in sedimentary formation with extracting cycle fluctuation, which comprises the following steps:
S10: sedimentation rate curve is established；
S20: making discrete wavelet analysis to the sedimentation rate curve in step S10, obtains analysis result；
S30: the curve for having stable period is found in the analysis result that step S20 is obtained, and summarizes corresponding math equation；
S40: signal reconstruction is carried out respectively to the curve that step S30 is obtained, the curve obtained at this time is respective cycle
The comprehensive deposition curve of cyclical fluctuations under influence of fluctuations；
S50: corresponding wave equation is established according to the curve of cyclical fluctuations that step S40 is obtained；
S60: the sedimentary wave curve prediction that the stratum reached is not bored in drilling well is made according to the wave equation that step S50 is established.
2. the method according to claim 1 identified in sedimentary formation with extracting cycle fluctuation, which is characterized in that step
Discrete wavelet analysis described in rapid S20 is progress wavelet transform analysis using Meyer small echo as morther wavelet.
3. the method according to claim 1 identified in sedimentary formation with extracting cycle fluctuation, which is characterized in that step
Analysis result described in rapid S20 is a series of approximation component curve A for decomposing and obtainingNWith details coefficients curve DN, N value is one
Serial positive integer, the positive integer are derived from positive integer collection { 1,2 ... ..., K-1, K }, and wherein K is total decomposition number.
4. the method according to claim 1 identified in sedimentary formation with extracting cycle fluctuation, which is characterized in that step
Curve described in rapid S30 is cyclic curve or nearly cyclic curve.
5. the method according to claim 3 identified in sedimentary formation with extracting cycle fluctuation, which is characterized in that step
Signal reconstruction described in rapid S40 is carried out according to the signal reconstruction process of wavelet transform Mallat algorithm.
6. the method according to claim 5 identified in sedimentary formation with extracting cycle fluctuation, which is characterized in that step
Wave equation described in rapid S50 is obtained according to the signal reconstruction formula of wavelet transform Mallat algorithm, the signal weight
Structure formula is as follows:
AN-1=AN+DN,
Wherein, ANFor approximation component curve, DNFor details coefficients curve, N is the number decomposed.
7. special according to claim 1 to any method identified in sedimentary formation with extracting cycle fluctuation in 6
Sign is, sedimentary wave curve prediction described in step S60, by the variation of deposition rate to the stratum for not boring the stratum reached
Situation is predicted.
8. the method according to claim 7 identified in sedimentary formation with extracting cycle fluctuation, which is characterized in that institute
The content for stating prediction is not bore the lithology up to stratum, depositional environment variation, buried history and/or tectonism.
9. a kind of system identified in sedimentary formation with extracting cycle fluctuation characterized by comprising
Deposition rate curved unit, for establishing sedimentation rate curve；
Discrete wavelet analytical unit, for making discrete wavelet point to the sedimentation rate curve in deposition rate curved unit
Analysis obtains analysis result；
Periodic searches unit, for finding the song for having stable period from analysis result obtained in discrete wavelet analytical unit
Line, and summarize corresponding math equation；
Curve of cyclical fluctuations recovery unit, for carrying out signal reconstruction respectively to the curve obtained in periodic searches unit, at this time
Obtained curve is the comprehensive deposition curve of cyclical fluctuations under respective cycle influence of fluctuations；
Wave equation establishes unit, establishes corresponding fluctuation side for the curve of cyclical fluctuations according to obtained in curve of cyclical fluctuations recovery unit
Journey；And
Curve of cyclical fluctuations predicting unit establishes the wave equation established in unit for wave equation and makes drilling well and do not bore the stratum reached
Sedimentary wave curve prediction.
10. the system according to claim 9 identified in sedimentary formation with extracting cycle fluctuation, which is characterized in that
The curve of cyclical fluctuations predicting unit predicts the strata condition for not boring the stratum reached by the variation of deposition rate.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012146894A2 (en) * | 2011-04-26 | 2012-11-01 | Kenneth Rayvenor Lusty Armitage | Oil & gas exploration and production |
| US8885440B2 (en) * | 2007-01-05 | 2014-11-11 | Madhumita Sengupta | Constructing velocity models near salt bodies |
| CN105044797A (en) * | 2015-08-06 | 2015-11-11 | 中国石油天然气股份有限公司 | Quantitative recovery method for carbonate rock stratum denudation amount |
| CN105204069A (en) * | 2014-06-27 | 2015-12-30 | 中国石油化工股份有限公司 | Strata denudation amount recovery method |
| CN106202749A (en) * | 2016-07-15 | 2016-12-07 | 长江大学 | Deposition analogy method deposition process controlled based on datum level |
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| CN105204069A (en) * | 2014-06-27 | 2015-12-30 | 中国石油化工股份有限公司 | Strata denudation amount recovery method |
| CN106295835A (en) * | 2015-05-21 | 2017-01-04 | 中国石油化工股份有限公司 | The Forecasting Methodology of oil & gas pool size distribution |
| CN105044797A (en) * | 2015-08-06 | 2015-11-11 | 中国石油天然气股份有限公司 | Quantitative recovery method for carbonate rock stratum denudation amount |
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