CN107120111A - A kind of appraisal procedure and system of the oil reservoir interwell communication degree based on multi-fractal - Google Patents
A kind of appraisal procedure and system of the oil reservoir interwell communication degree based on multi-fractal Download PDFInfo
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- CN107120111A CN107120111A CN201710289327.9A CN201710289327A CN107120111A CN 107120111 A CN107120111 A CN 107120111A CN 201710289327 A CN201710289327 A CN 201710289327A CN 107120111 A CN107120111 A CN 107120111A
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B49/00—Testing the nature of borehole walls; Formation testing; Methods or apparatus for obtaining samples of soil or well fluids, specially adapted to earth drilling or wells
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- E—FIXED CONSTRUCTIONS
- E21—EARTH DRILLING; MINING
- E21B—EARTH DRILLING, e.g. DEEP DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
- E21B43/00—Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
- E21B43/16—Enhanced recovery methods for obtaining hydrocarbons
- E21B43/20—Displacing by water
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/04—Inference or reasoning models
- G06N5/042—Backward inferencing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Mining
Abstract
The present invention relates to a kind of appraisal procedure and system of the oil reservoir interwell communication degree based on multi-fractal, its method comprises the following steps, and S1 reads and pre-processed the Production development data of injection-production well, obtains the time series of Production development data；S2, is calculated using multi-fractal algorithm the time series that acquisition time is located at the Production development data after water filling in predetermined period, show that acquisition time is located at the multifractal spectra parameter of the Production development data in predetermined period after water filling；S3, the time series progress wave character calculating qualitative evaluation that the Production development data after water filling in predetermined period in a period of time span are located to acquisition time goes out inter-well dynamic connectivity；S4, between well on the basis of the qualitative evaluation of dynamic connecting degree, multifractal spectra parameter is adopted as note and splits a point coefficient, is adopted by note and is split dynamic connecting degree between point quantifies assessment well.The method of the present invention can portray oil reservoir interwell communication degree with fine-grained.
Description
Technical field
The present invention relates to the field that inter well connectivity in oil reservoir development is assessed, and in particular to a kind of oil based on multi-fractal
Hide the appraisal procedure and system of interwell communication degree.
Background technology
Oil reservoir inter well connectivity can be divided into static connective and dynamic connectivity.Generally static state connectedness refers to applied geology
The connective result obtained with geophysical prospecting method, is determined by reservoir geologic character and reservoir characteristics.Because fracture-pore reservoir is preserved
The combination of zones that the characteristics of layer is complicated, traditional geology and physical prospecting (such as well logging, well testing, Geologic modeling method) research are obtained belongs to
Static category, it is impossible to effectively recognize the connectedness of fracture hole body.And oil deposit inter-well dynamic connectivity refers to store up between well after oil reservoir development
The connecting degree of layer fluid.It is a class important method using creation data quantitative inversion inter well connectivity, general principle is by oil
Hide and be considered as the injection and extraction system that a water injection well sends stimulation and surrounding oil well receiving stimulation, reservoir between water injection well, oil well and well
Constitute a complicated dynamic equilibrium system.After water injection oil reservoir, will crude oil or stratum water by the reservoir that has connected to
Oil well displacement, so as to maintain the production of oil well.The change of water injection well water injection rate cause oil well liquid-producing fluctuation to be connected in oil-water well layer
Logical feature reflection, the fluctuating range of oilwell produced fluid amount is related to oil-water well connecting degree, connective better, and production fluid wave is dynamic brighter
It is aobvious, therefore a connecting degree come quantization signifying note can be adopted by mathematical method, its model mainly includes being based on multiple linear regression
Model, system analysis model, elastic compression model, capacitor model and neutral net etc..
Statistical analysis is carried out by the feature to Production development data, it has certain nonlinear characteristic, as described below：
(1) leptokurtosis of the distribution of Production performance data with fertile tail, variance is uncertain or infinite, disobeys normal state
Distribution.
(2) in the change procedure of creation data, aqueous, oil-producing etc. is not the stochastic variable for following random walk, meter
Calculation cannot get unique optimum solution, but have multiple possible solutions.
(3) with the Long Memory Properties influenceed by historical information, (it is exactly long-term that such as oil production gradually decays to Production development data
Memorability, also referred to as time-length interrelation, state continuation) and tendency, with it is global it is orderly (it is determined that) property and local nothing
Sequence (random) property, with feedback effect.
In summary, the change of oil reservoir creation data is not independent, does not follow random walk, disobeys normal state point yet
Cloth, the feature of these properties exactly nonlinear dynamic system, and traditional multiple linear regression model, system analysis model,
Elastic compression model, capacitor model etc. can not fine granularity portray this feature.
The content of the invention
The technical problems to be solved by the invention are to provide a kind of commenting for oil reservoir interwell communication degree based on multi-fractal
Estimate method and system, oil reservoir interwell communication degree can be portrayed with fine-grained.
The technical scheme that the present invention solves above-mentioned technical problem is as follows：A kind of oil reservoir interwell communication journey based on multi-fractal
The appraisal procedure of degree, comprises the following steps,
S1, reads and pre-processes the Production development data of injection-production well, obtain the time series of Production development data；
S2, multi-fractal is used to the time series that acquisition time is located at the Production development data after water filling in predetermined period
Algorithm is calculated, and show that the acquisition time is located at the multifractal spectra ginseng of the Production development data in predetermined period after water filling
Number；
S3, the time sequence of the Production development data after water filling in predetermined period in a period of time span is located to acquisition time
Row carry out wave character calculating, show that the production that the acquisition time is located at after water filling in predetermined period in a period of time span is moved
The waveforms amplitude of state data, and inter-well dynamic connectivity is gone out by the waveforms amplitude qualitative evaluation；
S4, between well on the basis of the qualitative evaluation of dynamic connecting degree, is located at predetermined period after water filling by acquisition time
In the multifractal spectra parameters of Production development data adopted as note and split a point coefficient, adopted and split between point quantifies assessment well by note
Dynamic connecting degree.
The beneficial effects of the invention are as follows：The method of the present invention is based on Production development data inversion inter well connectivity, more effectively
Actual connection situation between reflection well；Meanwhile, multi-fractal is a kind of method of the part research global feature from system,
The main method by Statistical Physics calculates the distribution situation of probability, and method of the invention is based on multi-fractal principle, with reference to many
Multifractal spectrum parameter attribute simultaneously calculates Correlated Spectroscopy parameter, can quantify and obtain interwell communication degree strong or weak relation, so as to thin
Granularity portrays oil reservoir interwell communication degree.
On the basis of above-mentioned technical proposal, the present invention can also do following improvement.
Further, S1 specifically,
S11, reads the Production development data of injection-production well；
S12, filters out the Production development data with initial fill amount date Corresponding matching in multiple water fillings section initial time；
S13, the Production development data filtered out are brought into corresponding preprocessing algorithms and calculated, are drawn and multiple notes
The time series of the Production development data of initial fill amount date difference Corresponding matching in water section initial time.
Further, when the dynamic creation data includes water injection rate, oil production, water content, moisture content and water filling section starting
Between.
Further, in S12, if there is shortage of data in the water injection rate filtered out, oil production, water content and moisture content
Situation, in addition to Data-parallel language is carried out to the water injection rate filtered out, oil production, water content and moisture content.
Beneficial effect using above-mentioned further scheme is：The processing of Data-parallel language can effectively improve the essence subsequently calculated
Degree.
Further, using denoising polishing missing data, or EEMD Time-frequency Decompositions are used, combination supporting vector machine is to each sub- letter
Number modeling and forecasting realizes the interpolation processing polishing missing data of data.
Beneficial effect using above-mentioned further scheme is：Cause low volume data to lack if running into and closing down well, well workover etc., adopt
With denoising polishing missing data；For longer shortage of data, using EEMD Time-frequency Decompositions, combination supporting vector machine is to each subsignal
Modeling and forecasting realizes the interpolation processing of data；Data for different missing degree use different polishing processing methods so that
The data of polishing are more authentic and valid.
Further, S2 specifically,
S21, acquisition time is located at the time series time scale δ of the Production development data after water filling in predetermined period
It is divided into the interval of N (N=1/ δ) individual non-overlapping copies；
S22, calculates the probability measure P of sample in each intervali(δ)；
S23, according to the probability measure P in all intervalsi(δ) and weight factor q obtain the partition letter of multi-fractal algorithm
Number χq(δ)；
S24, to partition function χq(δ) and time scale δ ask logarithm to draw ln χq(δ)~ln δ double logarithmic curves, and pass through
Least square fitting algorithm estimates ln χqThe slope tau (q) of (δ)~ln δ double logarithmic curves；
S25, carries out Legendre transformation to slope tau (q) and weight factor q and draws singular index α and multi-fractal spectral function f
(α)；
S26, draws f (α)~α curve maps and processing is integrated to it, obtains acquisition time and week is preset after water filling
The multifractal spectra parameter of interim Production development data
Beneficial effect using above-mentioned further scheme is：Multi-fractal the presence or absence of is defined on fractal structure poor multiple
The set that scaling exponent is constituted, local conditions or point shape different on fractal structure are described by a spectral function
Special structure behavior and feature of the structure in evolutionary process caused by different levels；By calculating probability measure Pi, partition
Function χq(δ) and performance figure τ (q), α and multi-fractal spectral function f (α) are obtained using least square method regression fit；In f
In (α)~α figures, Δ α (i.e. αmax-αmin) uniformity coefficients of data is represented, Δ α is bigger, then it represents that curve is more irregularly, and right
In the scope corresponding to each singular index α, f (α) represents that the interval fractal dimension, the i.e. interval censored data are uneven
Degree, f (α)~α figures are integratedResult as fluctuation complexity characterize inter well connectivity.
Further, the time series of Production development data of the acquisition time in predetermined period after water filling includes in S21
The time series of oil production and the time series of water content；The production that acquisition time is located at after water filling in predetermined period in S26 is moved
The multifractal spectra parameter of state data includes the multifractal spectra parameter of oil production and the multifractal spectra parameter of water content.
Further, in S3, the Production development after water filling in predetermined period in a period of time span is located to acquisition time
The time series of data carries out concretely comprising the following steps for wave character calculating,
S31, choose acquisition time be located at Production development data after water filling in predetermined period in a period of time span when
Between sequence；
S32, when acquisition time is located at after water filling one section in predetermined period in calculating local window in units of time window
Between Production development data in span time series fluctuation amplitude, and be located at using sliding time window record acquisition time
The maximum fluctuation amplitude of the time series of Production development data after water filling in predetermined period in a period of time span, wherein,
Acquisition time is located at the maximum ripple of the time series of the Production development data in predetermined period in a period of time span after water filling
Dynamic amplitude is the waveforms amplitude that acquisition time is located at the Production development data after water filling in predetermined period in a period of time span.
Further, the acquisition time in S31 is located at the Production development number in predetermined period in a period of time span after water filling
According to for moisture content, acquisition time is located at the ripple of the Production development data in predetermined period in a period of time span after water filling in S32
Dynamic amplitude is the fluctuation amplitude of moisture content.
Beneficial effect using above-mentioned further scheme is：Connected well creation data can have certain change after water filling in theory
Change feature, dynamic connecting degree is stronger between the bigger well of fluctuation characteristic change in the case of identical water filling；Oil well production number after water filling
According to wave character reflect interwell communication degree to a certain extent, under normal circumstances, its fluctuating change driven by water filling,
The combined influence of the factors such as pumping, stroke, jig frequency, reflects the energy variation that producing well is produced in production process, and improper
In the case of, such as frequently close down well, replacing oil nozzle, well-flushing (being referred to as working system change above) or creation data missing incomplete
When (quality of data is poor), maximum fluctuation often shows irregularities；In all kinds of creation datas, the fluctuation of moisture content after water filling
Situation is influenceed the most substantially by water filling, therefore can be sentenced to a certain extent by the fluctuation size for calculating moisture content before and after water filling
Disconnected interwell communication relation.
Based on a kind of above-mentioned appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal, present invention also offers one
The assessment system of the oil reservoir interwell communication degree based on multi-fractal of kind.
A kind of assessment system of the oil reservoir interwell communication degree based on multi-fractal, including pretreatment module, multi-fractal
Dynamic connecting degree qualitative assessment module between parameter generation module, wave character computing module and well is composed,
Pretreatment module, it is used to read and pre-processes the Production development data of injection-production well, obtains Production development data
Time series；
Multifractal spectra parameter generation module, it is used to be located at acquisition time the Production development after water filling in predetermined period
Data are calculated using multi-fractal algorithm, show that the acquisition time is located at the Production development number in predetermined period after water filling
According to multifractal spectra parameter；
Wave character computing module, it is used to be located at acquisition time after water filling in predetermined period in a period of time span
Production development data carry out wave character calculating, show that the acquisition time is located at after water filling a period of time span in predetermined period
The waveforms amplitude of interior Production development data, and inter-well dynamic connectivity is gone out by the waveforms amplitude qualitative evaluation；
Dynamic connecting degree qualitative assessment module between well, it is used for the basis of the qualitative evaluation of dynamic connecting degree between well
On, the multifractal spectra parameter that acquisition time is located at the Production development data after water filling in predetermined period is adopted as note to split point it is
Number, is adopted by note and splits dynamic connecting degree between point quantifies assessment well.
The beneficial effects of the invention are as follows：The system of the present invention is based on Production development data inversion inter well connectivity, more effectively
Actual connection situation between reflection well；Meanwhile, multi-fractal is a kind of method of the part research global feature from system,
The main method by Statistical Physics calculates the distribution situation of probability, and system of the invention is based on multi-fractal principle, with reference to many
Multifractal spectrum parameter attribute simultaneously calculates Correlated Spectroscopy parameter, can quantify and obtain interwell communication degree strong or weak relation, so as to thin
Granularity portrays oil reservoir interwell communication degree.
Brief description of the drawings
Fig. 1 is a kind of overall flow figure of the appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal of the present invention；
The idiographic flow that Fig. 2 is S1 in a kind of appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal of the present invention
Figure；
The idiographic flow that Fig. 3 is S2 in a kind of appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal of the present invention
Figure；
The idiographic flow that Fig. 4 is S3 in a kind of appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal of the present invention
Figure；
Fig. 5 is TK634 well group Outline of regional geological setting figures；
Fig. 6 is that the TK634 well groups that multi-fractal method is obtained split a point graph of a relation；
Fig. 7 is TK617CH well group Outline of regional geological setting figures；
Fig. 8 is that the TK617CH well groups that multi-fractal method is obtained split a point graph of a relation；
Fig. 9 is a kind of structured flowchart of the assessment system of the oil reservoir interwell communication degree based on multi-fractal of the present invention.
Embodiment
The principle and feature of the present invention are described below in conjunction with accompanying drawing, the given examples are served only to explain the present invention, and
It is non-to be used to limit the scope of the present invention.
As shown in figure 1, a kind of appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal, comprises the following steps,
S1, reads and pre-processes the Production development data of injection-production well, obtain the time series of Production development data；
S2, multi-fractal is used to the time series that acquisition time is located at the Production development data after water filling in predetermined period
Algorithm is calculated, and show that the acquisition time is located at the multifractal spectra ginseng of the Production development data in predetermined period after water filling
Number；
S3, the time sequence of the Production development data after water filling in predetermined period in a period of time span is located to acquisition time
Row carry out wave character calculating, show that the production that the acquisition time is located at after water filling in predetermined period in a period of time span is moved
The waveforms amplitude of state data, and inter-well dynamic connectivity is gone out by the waveforms amplitude qualitative evaluation；
S4, between well on the basis of the qualitative evaluation of dynamic connecting degree, is located at predetermined period after water filling by acquisition time
In the multifractal spectra parameters of Production development data adopted as note and split a point coefficient, adopted and split between point quantifies assessment well by note
Dynamic connecting degree.
Specific explanations explanation is carried out to S1~S4 separately below.
As shown in Fig. 2 S1 is specially：
S11, reads the Production development data of injection-production well；Wherein, the dynamic creation data include water injection rate, oil production,
Water content, moisture content and water filling section initial time；
S12, filters out the Production development data with initial fill amount date Corresponding matching in multiple water fillings section initial time；
Wherein, if the water injection rate filtered out, oil production, water content and moisture content have shortage of data, in addition to screening
The water injection rate, oil production, water content and the moisture content that go out carry out the processing of Data-parallel language；Data-parallel language processing method be：If 1.
Run into and close down well, well workover etc. and cause low volume data to lack, using denoising polishing missing data；2. for longer shortage of data, adopt
EEMD Time-frequency Decompositions are used, combination supporting vector machine realizes that the interpolation processing of data carrys out polishing data to each subsignal modeling and forecasting；
S13, the Production development data filtered out are brought into corresponding preprocessing algorithms and calculated, are drawn and multiple notes
The time series of the Production development data of initial fill amount date difference Corresponding matching in water section initial time.
In S2, after predetermined period is two months, that is, this specific embodiment data object is each water filling
60 days (i.e. two months) injection-production well water content time series and oil production time series (according to tracer test feelings
Condition water filling is general in two months by effect)；Multi-fractal the presence or absence of is defined on fractal structure poor multiple scaling exponent institutes group
Into a set, local condition different on fractal structure is described by a spectral function or fractal structure was developing
Special structure behavior caused by different levels and feature in journey.Multifractal spectra parameter is calculated and uses box dimension, and it is counted
Calculate flow as shown in Figure 3：
S21, to be located at the one-dimensional etui that time scale is δ (δ ＜ 1) to acquisition time after water filling in predetermined period
The time series of Production development data is covered, i.e., acquisition time is located at into the Production development data after water filling in predetermined period
Time series the intervals of N (N=1/ δ) individual non-overlapping copies is divided into time scale δ；Wherein, acquisition time is located at after water filling
The time series of Production development data in predetermined period includes the time series of oil production and the time series of water content；
S22, calculates the probability measure P of sample in each intervali(δ)；Wherein, I is rememberedi(δ) is time scale when being δ
The probability measure P of i-th interval interior all samples moisture content value or oil-producing value sum, the then sample in i-th of intervali(δ)
For：
If the time series of this water content or the time series of oil production have multi-fractal features, in dimensionless interzone
Inside meet following power law relation:
Pi(δ)∝δα (2)
Wherein, α is the mark P corresponding to i-th of intervaliThe singular index of (δ) size, reflects PiChange each with δ interval
Different unusual degree；
Time scale with identical α is designated as N for δ interval numberα(δ), is reduced with δ, Nα(δ) is continuously increased, if this
There is multiple scale relation in the time series of water content or the time series of oil production, then following power law is met in dimensionless interzone
Relation：
Nα(δ)∝δ-f(α)(δ→0) (3)
Wherein, multi-fractal spectral function f (α) represents each PiIn have identical α subsets element number with δ reduce and increase
Big speed；
S23, according to the probability measure P in all intervalsi(δ) and weight factor q obtain the partition letter of multi-fractal algorithm
Number χq(δ)；It is therein, define the partition function χ of multi-fractal algorithmq(δ) is the q rank squares of normalized water content or oil production：
χq(δ) is reflection normalized water content or oil production PiThe statistic of (δ) inhomogeneities, q is weight factor, is passed through
Weighting is handled, and reaches the purpose for studying fine structure by different level；
S24, to partition function χq(δ) and time scale δ ask logarithm to draw ln χq(δ)~ln δ double logarithmic curves, and pass through
Least square fitting algorithm estimates ln χqThe slope tau (q) of (δ)~ln δ double logarithmic curves；Specifically, by point shape from phase
Understood like property, χq(δ) and δ meet following power law relation in dimensionless interzone：
χq(δ)∝δτ(q) (5)
Logarithm is asked to produce ln χ above formula both sidesq(δ)~ln δ curves, wherein slope of a curve τ (q) is performance figure, τ
(q) ln χ can be passed throughqLinear Points in (δ)~ln δ double logarithmic curves carry out least square fitting to be estimated；
S25, carries out Legendre transformation to slope tau (q) and weight factor q and draws singular index α and multi-fractal spectral function f
(α)；Specifically, on the premise of known q~τ (q) curve, by Legendre transformation (Legendre transformation),
α (q) and f (α) can be obtained by q and τ (q)：
S26, draws f (α)~α curve maps and processing is integrated to it, obtains acquisition time and week is preset after water filling
The multifractal spectra parameter of interim Production development dataWherein, acquisition time is located at predetermined period after water filling
In Production development data multifractal spectra parameter including oil production multifractal spectra parameter and the multi-fractal of water content
Compose parameter.
In summary, by calculating probability measure Pi, partition function χq(δ) and performance figure τ (q), using least square method
Regression fit obtains α and multi-fractal spectral function f (α)；In f (α)~α figures, Δ α (i.e. αmax-αmin) represent the equal of data
Even degree, Δ α is bigger, then it represents that curve is more irregularly；And for the scope corresponding to each Singularity Degree index α, f (α) table
Show the interval fractal dimension, the i.e. uneven degree of the interval censored data；By f (α)~α figures integrationKnot
Fruit characterizes interwell communication degree as the complexity of fluctuation.
In S3, the maximum ripple of creation data such as moisture content in a period of time span in predetermined period after charging is calculated
Dynamic, the maximum of difference is fluctuated as local maxima between selection crest and trough；Assuming that access time span is T, time window
Mouth size is t (t<T), the moisture content local maxima undulating value in T-t+1 time window is solved, wherein the office of i-th of window
Portion's maximum fluctuation is designated as δi,δmax=max { δ1, δ2..., δT-t+1It is maximum fluctuation value in latter section of time span of water filling；δiTool
Body judges as shown in Figure 4：
In S3, acquisition time is located at the Production development data after water filling in predetermined period in a period of time span when
Between sequence carry out wave character calculating and concretely comprise the following steps,
S31, choose acquisition time be located at Production development data after water filling in predetermined period in a period of time span when
Between sequence；Wherein, the Production development data that acquisition time is located at after water filling in predetermined period in a period of time span are moisture content；
If oil well to be judged occurs in that the interference of production system during water content is fluctuated, (such as change oil nozzle size, well-flushing stops the behaviour such as well
Make), decide whether to weed out the well as the case may be；
S32, the acquisition time in local window is calculated in units of time window and is located at after water filling one in predetermined period
The fluctuation amplitude of the time series of Production development data in section time span, and the collection is recorded using sliding time window
Time is located at the maximum fluctuation width of the time series of the Production development data in predetermined period in a period of time span after water filling
Value, wherein, the acquisition time is located at the time sequence of the Production development data in predetermined period in a period of time span after water filling
The maximum fluctuation amplitude of row is that production of the acquisition time in a period of time span in predetermined period after water filling is moved
The waveforms amplitude of state data；In addition, acquisition time is located at the Production development number in predetermined period in a period of time span after water filling
According to fluctuation amplitude be moisture content fluctuation amplitude.
In S3, injection-production well Production development data can have certain variation characteristic after water filling in theory, in identical water filling feelings
Dynamic connecting degree is stronger between fluctuation characteristic changes bigger well under condition；The wave character of producing well creation data is certain after water filling
Interwell communication degree is reflected in degree；Under normal circumstances, its fluctuating change by water filling driving, pumping, stroke, jig frequency etc. because
The combined influence of element, reflects the energy variation that producing well is produced in production process；And under abnormal condition, such as frequently close down
It is maximum when well, replacing oil nozzle, well-flushing (being referred to as working system change above) or creation data lack not (quality of data is poor) entirely
Fluctuation often shows irregularities；In all kinds of creation datas, the fluctuation of moisture content is influenceed the most substantially by water filling after water filling,
Therefore interwell communication relation can be qualitatively judged to a certain extent by calculating the fluctuation size of moisture content before and after water filling.
S4 does the qualitative assessment of connecting degree using multi-fractal method, comprises the following steps that：The interwell communication degree in S3
On the basis of qualitative calculating, the multifractal spectra parameter of the oil production drawn in comprehensive S2 and the multifractal spectra parameter of water content are made
Adopted for note and split a point coefficient, each producing well water splits a point situation after reflection water filling；Split point coefficient bigger, dynamically connected between general well
Degree is stronger.
The method of the present invention, the purpose is to set up the mapping relations between Production performance data and interwell communication degree,
By calculating multifractal spectra parameter come the strong or weak relation of rational judgment interwell communication degree.General principle is water injection well injection rate
Change often cause the fluctuation of surrounding oil well Liquid output, fluctuating range is bigger, and connecting degree is better, for Production development number
A connecting degree is adopted according to by mathematical method quantization signifying note.The Production development data of fracture-pore reservoir such as water content, oil production
Deng dynamic change do not follow random walk, also disobey normal distribution, the Nonlinear Dynamic of the fertile tail of spike is presented in whole distribution
Force system feature, therefore traditional statistical method and temporal model can not effectively portray complicated note milling machine reason.Multi-fractal is a kind of
From the method for system part research global feature, its probability distribution situation is calculated by the method for Statistical Physics, using many
Multifractal spectrum parameter describes sustained water injection, closes down the variation characteristic of creation data after the various working systems of well, well-flushing change, and excavates
Relevance between moisture content, oil-producing fluctuation and water filling, quantitative analysis oil reservoir injection adopts interwell communication degree.It is dynamic that the algorithm is based on production
State data, the distribution for calculating probability using the method for Statistical Physics connects strong and weak progress quantitative analysis between being adopted to note, in understanding note
On the basis of the direction of flow that becomes a mandarin, water filling is calculated by effect situation by multi-fractal algorithm.It the method overcome traditional interwell communication
The problem of determination methods influence normal production and construction operation, reduction note adopts the strong and weak cost differentiated of connection, while simplifying tradition note
Adopt the workload of connected relation differentiation.
The concrete application of the inventive method is introduced by taking system in Tahe Oilfield fracture-pore reservoir as an example below：
System in Tahe Oilfield fracture-pore reservoir, is the special oil reservoir based on solution cavity, fracture hole.Hole, hole, seam are in different ways
And scale will constitute a variety of Storage categories, with very strong aeolotropic characteristics.Mainly include the Triassic system, the sandstone of the Carboniferous System
Oil reservoir, and the Ordovician system Carbonate Reservoir.Oilfield reserve is visited essentially from ORDOVICIAN CARBONATE oil reservoir, Ordovician reservoir
Bright reserves account for the 81.7% of the total proved reserves in oil field, and current oil field main force oil-producing formation is Ordovician system fracture hole acid carbonate rock stratum.
Survey region includes 296 mouthfuls of wells, and historical summary has more than the data (from 2001 to 2015) of 15 years.Algorithm running environment：
The systems of Windows 7,4G running memories, 2.94GHz Pentium (R) Dual-Core CPU；Running tool：VS2010；Programming
Language：C/C++.Experiment test object select be system in Tahe Oilfield Unit 467.
Experiment test object select be the unit of system in Tahe Oilfield 4672 injection-production well groups, be TK634 (2009 respectively
On April 23, in) and TK617CH (on November 27th, 2007).Based on creation data data, choose this 2 injection-production well group water fillings it
These data are carried out multifractal spectra parameter calculating, obtain interwell communication degree result by the creation data of 60 days afterwards.
Tracer verification is a kind of traditional method for judging interwell communication relation, by delivering tracer, the well around
Middle sampling, analysis sample etc. carry out clear and definite interwell communication relation.The method of the present invention is used as ginseng using actual injection-production well tracer experiments
According to the checking that progress result of calculation connectedness judges.Multi-fractal result and tracer Comparative result are as follows：
(1) TK634 well groups (on April 23rd, 2009)
TK634 wells are a bite development wells disposed on the construction of the area pasture of system in Tahe Oilfield 6 north 6, and TK634 well locations are in TK7-
Unit 607 and S67 units, and the binding site of the T606 unit areas at northeast position are as shown in Figure 5.The well in May, 2002
Go into operation within 24th, anhydrous production during operation, water-free oil production period is longer, added up 15.5626 ten thousand tons of liquid of production, oil-producing 12.4326 so far
Ten thousand tons.31.2 tons of aqueous of daily output at present, day 2.3 tons of oil-producing, aqueous 92.5%.
The TK634 well group water fillings that multi-fractal method is obtained split point relation pair than as shown in table 1：
Table 1
It is as shown in Figure 6 that the TK634 well groups that multi-fractal method is obtained split point relation；
By table 1 and Fig. 6, tracer water operation connects parameter attribute with multi-fractal method and relatively coincide.Through examining, well group
Tracer water operation situation is consistent with the connection parameter logistic size order that multi-fractal is obtained, and both scales
Very close to illustrating that the connective result of the well is more coincide with tracer test result.
(2) TK617CH well groups (on November 27th, 2007)
TK617CH well locations are on the area northeast of system in Tahe Oilfield 6, No. 2 structural highs in pasture north, and production layer position is the Ordovician system
O1-2y.The natural energy of some oil wells in region fracture-cavity units such as Fig. 7, unit is mostly larger, anhydrous time productive life compared with
Long, initil output is high, and the oil well in unit has different degrees of emptying phenomenon in drilling process, illustrates preserving in unit
Body is solution cavity, meets the oil reservoir of hole development.
It is as shown in table 2 that point relation is split in the TK617CH well group water fillings that multi-fractal method is obtained：
Table 2
It is as shown in Figure 8 that Fig. 8 splits point relation for the TK617CH well groups that multi-fractal method is obtained；
Pass through table 2 and Fig. 8, it can be seen that tracer water operation connects parameter attribute with multi-fractal method and relatively coincide.Through inspection
Test, well-group tracer water operation situation is consistent with the connection parameter logistic size order that multi-fractal is obtained, and both
Scale is very close to illustrating that the connective result of the well is more coincide with tracer test result.
Generally speaking, from the result of contrast chart above with from the point of view of analysis, multi-fractal studies interwell communication degree
Experimental result is consistent with the result of tracer, substantially conforms to the actual conditions in oil field, the result that new method is calculated more accurately with
Reliably, with certain practical value, certain promotion is played in the exploitation to oil reservoir.
Based on a kind of above-mentioned appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal, present invention also offers one
The assessment system of the oil reservoir interwell communication degree based on multi-fractal of kind.
As shown in figure 9, a kind of assessment system of the oil reservoir interwell communication degree based on multi-fractal, including pretreatment mould
Dynamic connecting degree qualitative assessment module between block, multifractal spectra parameter generation module, wave character computing module and well,
Pretreatment module, it is used to read and pre-processes the Production development data of injection-production well, obtains Production development data
Time series；
Multifractal spectra parameter generation module, it is used to be located at acquisition time the Production development after water filling in predetermined period
Data are calculated using multi-fractal algorithm, show that the acquisition time is located at the Production development number in predetermined period after water filling
According to multifractal spectra parameter；
Wave character computing module, it is used to be located at acquisition time after water filling in predetermined period in a period of time span
Production development data carry out wave character calculating, show that the acquisition time is located at after water filling a period of time span in predetermined period
The waveforms amplitude of interior Production development data, and inter-well dynamic connectivity is gone out by the waveforms amplitude qualitative evaluation.
The system of the present invention is based on connection feelings actual between Production development data inversion inter well connectivity, more effective reflection well
Condition；Meanwhile, multi-fractal is a kind of method of the part research global feature from system, mainly by the side of Statistical Physics
Method calculates the distribution situation of probability, and system of the invention is based on multi-fractal principle, with reference to multifractal spectra parameter attribute and counts
Correlated Spectroscopy parameter is calculated, can quantify and obtain interwell communication degree strong or weak relation, is connected so as to fine-grained portray between oil reservoir well
Logical degree.
The foregoing is only presently preferred embodiments of the present invention, be not intended to limit the invention, it is all the present invention spirit and
Within principle, any modification, equivalent substitution and improvements made etc. should be included in the scope of the protection.
Claims (10)
1. a kind of appraisal procedure of the oil reservoir interwell communication degree based on multi-fractal, it is characterised in that：Comprise the following steps,
S1, reads and pre-processes the Production development data of injection-production well, obtain the time series of Production development data；
S2, the time series that the Production development data after water filling in predetermined period are located to acquisition time uses multi-fractal algorithm
Calculated, show that acquisition time is located at the multifractal spectra parameter of the Production development data in predetermined period after water filling；
S3, enters to the time series that acquisition time is located at the Production development data after water filling in predetermined period in a period of time span
Traveling wave shape feature calculation, show that acquisition time is located at the Production development data in predetermined period in a period of time span after water filling
Waveforms amplitude, and inter-well dynamic connectivity is gone out by the waveforms amplitude qualitative evaluation；
S4, between well on the basis of the qualitative evaluation of dynamic connecting degree, acquisition time is located at after water filling in predetermined period
The multifractal spectra parameter of Production development data is adopted as note splits a point coefficient, is adopted by note and splits dynamic between point quantifies assessment well
Connecting degree.
2. a kind of appraisal procedure of oil reservoir interwell communication degree based on multi-fractal according to claim 1, its feature
It is：S1 specifically,
S11, reads the Production development data of injection-production well；
S12, filters out the Production development data with initial fill amount date Corresponding matching in multiple water fillings section initial time；
S13, the Production development data filtered out are brought into corresponding preprocessing algorithms and calculated, and are drawn and multiple water fillings section
The time series of the Production development data of initial fill amount date difference Corresponding matching in initial time.
3. a kind of appraisal procedure of oil reservoir interwell communication degree based on multi-fractal according to claim 2, its feature
It is：The dynamic creation data includes water injection rate, oil production, water content, moisture content and water filling section initial time.
4. a kind of appraisal procedure of oil reservoir interwell communication degree based on multi-fractal according to claim 3, its feature
It is：In S12, if the water injection rate filtered out, oil production, water content and moisture content have shortage of data, also wrap
Include and Data-parallel language is carried out to the water injection rate filtered out, oil production, water content and moisture content.
5. a kind of appraisal procedure of oil reservoir interwell communication degree based on multi-fractal according to claim 4, its feature
It is：Using denoising polishing missing data, or EEMD Time-frequency Decompositions are used, combination supporting vector machine is to each subsignal modeling and forecasting
Realize the interpolation processing polishing missing data of data.
6. a kind of assessment side of oil reservoir interwell communication degree based on multi-fractal according to any one of claim 3 to 5
Method, it is characterised in that：S2 specifically,
S21, the time series that acquisition time is located at the Production development data after water filling in predetermined period is split with time scale δ
Into the interval of N (N=1/ δ) individual non-overlapping copies；
S22, calculates the probability measure P of sample in each intervali(δ)；
S23, according to the probability measure P in all intervalsi(δ) and weight factor q obtain the partition function χ of multi-fractal algorithmq
(δ)；
S24, to partition function χq(δ) and time scale δ ask logarithm to draw ln χq(δ)~ln δ double logarithmic curves, and pass through minimum
Square law fitting algorithm estimates ln χqThe slope tau (q) of (δ)~ln δ double logarithmic curves；
S25, carries out Legendre transformation to slope tau (q) and weight factor q and draws singular index α and multi-fractal spectral function f (α)；
S26, draws f (α)~α curve maps and processing is integrated to it, obtains acquisition time in predetermined period after water filling
Production development data multifractal spectra parameter
7. a kind of appraisal procedure of oil reservoir interwell communication degree based on multi-fractal according to claim 6, its feature
It is：In S21 acquisition time be located at the Production development data in predetermined period after water filling time series include oil production when
Between sequence and water content time series；Production development data of the acquisition time in predetermined period after water filling is more in S26
Multifractal spectrum parameter includes the multifractal spectra parameter of oil production and the multifractal spectra parameter of water content.
8. a kind of assessment side of oil reservoir interwell communication degree based on multi-fractal according to any one of claim 3 to 5
Method, it is characterised in that：In S3, the Production development number after water filling in predetermined period in a period of time span is located to acquisition time
According to time series carry out wave character calculating and concretely comprise the following steps,
S31, chooses the time sequence that acquisition time is located at the Production development data after water filling in predetermined period in a period of time span
Row；
S32, calculated in units of time window acquisition time in local window be located at after water filling in predetermined period a period of time across
The fluctuation amplitude of the time series of Production development data in degree, and water filling is located at using sliding time window record acquisition time
The maximum fluctuation amplitude of the time series of Production development data in predetermined period in a period of time span afterwards, wherein, collection
Time is located at the maximum fluctuation width of the time series of the Production development data in predetermined period in a period of time span after water filling
Value is the waveforms amplitude that acquisition time is located at the Production development data after water filling in predetermined period in a period of time span.
9. a kind of appraisal procedure of oil reservoir interwell communication degree based on multi-fractal according to claim 8, its feature
It is：The Production development data that acquisition time in S31 is located at after water filling in predetermined period in a period of time span are moisture content,
The fluctuation amplitude that acquisition time is located at the Production development data in predetermined period in a period of time span after water filling in S32 is aqueous
The fluctuation amplitude of rate.
10. a kind of assessment system of the oil reservoir interwell communication degree based on multi-fractal, it is characterised in that：Including pretreatment mould
Dynamic connecting degree qualitative assessment module between block, multifractal spectra parameter generation module, wave character computing module and well,
Pretreatment module, it is used to read and pre-processes the Production development data of injection-production well, obtains the time of Production development data
Sequence；
Multifractal spectra parameter generation module, it is used to be located at acquisition time the Production development data after water filling in predetermined period
Calculated using multi-fractal algorithm, show that the acquisition time is located at the Production development data in predetermined period after water filling
Multifractal spectra parameter；
Wave character computing module, it is used to be located at acquisition time the production after water filling in predetermined period in a period of time span
Dynamic data carries out wave character calculating, show that the acquisition time is located at after water filling in predetermined period in a period of time span
The waveforms amplitude of Production development data, and inter-well dynamic connectivity is gone out by the waveforms amplitude qualitative evaluation；
Dynamic connecting degree qualitative assessment module between well, it is used between well on the basis of the qualitative evaluation of dynamic connecting degree,
The multifractal spectra parameter that acquisition time is located at the Production development data after water filling in predetermined period is adopted as note and splits a point coefficient,
Adopted by note and split dynamic connecting degree between point quantifies assessment well.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107895092A (en) * | 2017-12-07 | 2018-04-10 | 中国地质大学（武汉） | A kind of interwell communication quantitative evaluation method that modeling is adopted based on complex nonlinear note |
| CN107942357A (en) * | 2017-11-17 | 2018-04-20 | 中国矿业大学 | A kind of adaptive differential method of estimation of geodesic survey non-equidistant sequential noise |
| CN109872007A (en) * | 2019-03-12 | 2019-06-11 | 中国地质大学（北京） | Oil reservoir injection based on support vector machines agent model adopts parameter Multipurpose Optimal Method |
| CN109902405A (en) * | 2019-03-06 | 2019-06-18 | 北京林业大学 | A kind of hydrology degree of communication evaluation method |
| CN111350477A (en) * | 2018-12-20 | 2020-06-30 | 中国石油天然气股份有限公司 | Method for determining potential interval for improving efficiency of water injection system |
| CN111753423A (en) * | 2020-06-24 | 2020-10-09 | 厦门大学 | XGboost-based inter-well dynamic connectivity quantification method |
| CN112085254A (en) * | 2020-08-05 | 2020-12-15 | 中国地质大学（武汉） | Prediction method and model based on multi-fractal cooperative measurement gating cycle unit |
| CN115134269A (en) * | 2022-06-28 | 2022-09-30 | 北京邮电大学 | Method and device for detecting connectivity of multi-agent system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105389467A (en) * | 2015-11-02 | 2016-03-09 | 中国地质大学（武汉） | Method and apparatus of acquiring inter-well communication relationship |
| CN105404726A (en) * | 2015-11-02 | 2016-03-16 | 中国地质大学（武汉） | Method and device for reverting inter-well connectivity through Gaussian distribution-based capacitance model |
| CN106526693A (en) * | 2016-09-30 | 2017-03-22 | 中国石油天然气股份有限公司 | Crack recognition method and device |
-
2017
- 2017-04-27 CN CN201710289327.9A patent/CN107120111B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105389467A (en) * | 2015-11-02 | 2016-03-09 | 中国地质大学（武汉） | Method and apparatus of acquiring inter-well communication relationship |
| CN105404726A (en) * | 2015-11-02 | 2016-03-16 | 中国地质大学（武汉） | Method and device for reverting inter-well connectivity through Gaussian distribution-based capacitance model |
| CN106526693A (en) * | 2016-09-30 | 2017-03-22 | 中国石油天然气股份有限公司 | Crack recognition method and device |
Non-Patent Citations (3)
| Title |
|---|
| 周赤非: "《军事系统学概论》", 31 December 2013, 军事科学出版社 * |
| 熊钰等: "油水井分层产量计算新方法", 《石油地质与工程》 * |
| 金志勇等: "非线性时间序列井间连通性分析方法", 《油气地质与采收率》 * |
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| CN107942357A (en) * | 2017-11-17 | 2018-04-20 | 中国矿业大学 | A kind of adaptive differential method of estimation of geodesic survey non-equidistant sequential noise |
| CN107895092A (en) * | 2017-12-07 | 2018-04-10 | 中国地质大学（武汉） | A kind of interwell communication quantitative evaluation method that modeling is adopted based on complex nonlinear note |
| CN107895092B (en) * | 2017-12-07 | 2020-02-14 | 中国地质大学（武汉） | Inter-well communication quantitative evaluation method based on complex nonlinear injection-production modeling |
| CN111350477B (en) * | 2018-12-20 | 2021-11-30 | 中国石油天然气股份有限公司 | Method for determining potential interval for improving efficiency of water injection system |
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