CN105404726B - A kind of capacitor model inverting inter well connectivity method and device based on Gaussian Profile - Google Patents
A kind of capacitor model inverting inter well connectivity method and device based on Gaussian Profile Download PDFInfo
- Publication number
- CN105404726B CN105404726B CN201510734077.6A CN201510734077A CN105404726B CN 105404726 B CN105404726 B CN 105404726B CN 201510734077 A CN201510734077 A CN 201510734077A CN 105404726 B CN105404726 B CN 105404726B
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- well
- water injection
- water filling
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/30—Circuit design
- G06F30/36—Circuit design at the analogue level
- G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
Landscapes
- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of capacitor model inverting inter well connectivity method and device based on Gaussian Profile, including：The initial related data of water filling well group is obtained, including：Water injection rate, Liquid output, stream pressure, water filling section initial time and the connectivity relationship of the water filling well group；Target note, which is filtered out, from the initial related data adopts data；It is to be pressed with the water injection rate of initial fill date match, Liquid output and stream in water filling section that the target note, which adopts data,；Target note is adopted into data and brings capacitor model into, the capacitor model is solved by Gauss distribution method, so as to calculate connectivity parameters；The connectedness that the connectivity parameters are used to characterize between the water injection well and liquid producing well is strong and weak.For method and device provided by the invention solving the acquisition methods of oil deposit inter-well dynamic connectivity in the prior art, it is low the degree of accuracy to be present, influences the technical problems such as normal production and expense height.Realizing reduces cost, simplifies workload and ensure that the technique effect of accuracy.
Description
Technical field
The present invention relates to geophysics's physical prospecting development technique field, more particularly to a kind of electric capacity mould based on Gaussian Profile
Type inverting inter well connectivity method and device.
Background technology
Oil reservoir is a kinetic balance system, and in oil field development, every mouth well may be with around a bite or multiple wells
Be connected, every mouth well is not completely isolated, during water injection well water filling can be attached thereto around it oil-producing well cause it is certain
Fluctuation, the connectedness between oil-producing well fluctuation size and injection-production well have certain contact.
The inter well connectivity of oil reservoir includes static connective and dynamic connectivity.Usual static connectedness refer to applied geology and
The connective result that geophysical prospecting method obtains, is determined by reservoir geologic character and reservoir characteristics.Due to fracture-pore reservoir reservoir
The combination of zones that the characteristics of complicated, traditional geology and physical prospecting (such as the methods of well logging, well testing, Geologic modeling) research obtains belongs to quiet
State category, it can not effectively recognize the connectedness of fracture hole body.And oil deposit inter-well dynamic connectivity refers to after oil reservoir development reservoir between well
The connecting degree of fluid.At present both at home and abroad conventional oil deposit inter-well dynamic connectivity research method mainly include tracer test,
A variety of connective recognition methods such as pressure test, interference test and pulse test.
But when tracer test, pressure test, interference test and pulse test these technique studies note adopt connected relation, deposit
Interference between more wells, produce system difference or during more wells, the problems such as connecting degree is difficult to determine；Normal production is influenceed simultaneously,
It is costly；Limited using well time, data are not enriched, the problems such as can not determining whether to connect for low water cut well；And can also shadow
Ring the normal production and operation to oil field.
That is, the acquisition of oil deposit inter-well dynamic connectivity in the prior art, it is low the degree of accuracy to be present, influences normally to produce
With the technical problem such as expense height.
The content of the invention
The embodiment of the present application is by providing a kind of capacitor model inverting inter well connectivity method and dress based on Gaussian Profile
Put, solve the acquisition methods of oil deposit inter-well dynamic connectivity in the prior art, it is low the degree of accuracy to be present, influences normal production and expense
With high technical problem.
On the one hand, the embodiment of the present application provides following technical scheme：
A kind of capacitor model inverting inter well connectivity method based on Gaussian Profile, including：
Obtain the initial related data of water filling well group；The initial related data packets include：The water injection rate of the water filling well group,
Liquid output, stream pressure, water filling section initial time and connectivity relationship；
Target note, which is filtered out, from the initial related data adopts data；The target note adopts data and is and water filling Duan Zhongchu
Water injection rate, Liquid output and the stream pressure of beginning water filling date match；
Target note is adopted into data and brings capacitor model into, the capacitor model is asked by Gauss distribution method
Solution, so as to calculate connectivity parameters；The connectivity parameters be used to characterize in the water filling well group water injection well and liquid producing well it
Between connectedness it is strong and weak.
Optionally, methods described also includes：Judge whether using stream pressure as calculating described in the connectivity parameters
Target note adopts data, obtains the first judged result；If first judged result is yes, the initial related data is also wrapped
Include：Acquisition time corresponding to the stream pressure of the water filling well group and the stream pressure；The electric capacity mould that the capacitor model is pressed for consideration stream
Type；If first judged result is no, the capacitor model is the capacitor model for not considering stream pressure.
Optionally, it is described not consider that flowing the capacitor model pressed is：Institute
State and consider that the capacitor model that stream is pressed is：
Wherein,For water injection well i the n moment water injection rate；iij(n) it is production liquid of the oil-producing well j in water filling well group i at the n moment
Amount；n0For initial time；For the Liquid output iij(n) convolution；λ is interporosity flow coefficient；τ is
Time lag constant；λijIt is the interporosity flow coefficient between water injection well i and oil-producing well j；τijIt is that time lag between water injection well i and oil-producing well j is normal
Number；For the influence of water injection well first time water filling,Value be equal to uneven constant；Wherein,For the stream pressure of corresponding oil-producing well k in water filling well group i；For the stream pressureConvolution；υkiFor weight；υkiValue be equal to λki；λkiIt is the interporosity flow coefficient between water injection well i and oil-producing well k；τkiIt is
Time lag constant between water injection well i and oil-producing well k.
Optionally, the initial related data of the acquisition water filling well group is specially：Response method is adopted by note and obtains water injection well
The initial related data of group；Or the initial related data of water filling well group is obtained by tracer.
Optionally, the connectivity parameters include：The interporosity flow coefficient of the water filling well group.
Optionally, it is described that target note is adopted data and brings capacitor model into, by Gauss distribution method to the electric capacity
Model is solved, and is included so as to calculate connectivity parameters：Estimating for each oil-producing well is generated at random with Gaussian Profile to alter
Flow coefficient and estimate time lag constant, as initial parameter；By preset range, from the initial parameter, filter out and meet the requirements
Data, as target component；Target note is adopted into partial data in data and the target component brings the electric capacity into
Model, calculate water injection rate estimate；Calculate the error that the water injection rate adopts the water injection rate in data with target note
Value；According to the error amount, by Gauss distribution method, determine to alter described in the water filling well group from the target component
Flow coefficient.
On the other hand, the embodiment of the present application additionally provides a kind of capacitor model inverting inter well connectivity based on Gaussian Profile
Device, including：
Acquisition module, for obtaining the initial related data of water filling well group；The initial related data packets include：The water filling
Acquisition time corresponding to water injection rate, Liquid output and the water injection rate of well group and the Liquid output；
Screening module, data are adopted for filtering out target note from the initial related data；The target note adopts data
For the data in the initial related data with the initial fill time match of the water filling well group；
Computing module, capacitor model is brought into for target note to be adopted into data, by Gauss distribution method to the electricity
Molar type is solved, so as to calculate connectivity parameters；The connectivity parameters are used to characterize water filling in the water filling well group
Connectedness between well and liquid producing well is strong and weak.
Optionally, described device also includes：Judge module, for judging whether using stream pressure as calculating the connection
Property parameter target note adopt data, obtain the first judged result；If first judged result is yes, the electric capacity
The capacitor model that model is pressed for consideration stream；If first judged result is no, the capacitor model is pressed not consider to flow
Capacitor model.
Optionally, the acquisition module includes：First acquisition unit, water filling well group is obtained for adopting response method by note
Initial related data；Or second acquisition unit, for obtaining the initial related data of water filling well group by tracer.
Optionally, described device also includes：Gaussian Computation module, for generating each oil-producing well at random with Gaussian Profile
Estimate and interporosity flow coefficient and estimate time lag constant, as initial parameter；By preset range, from the initial parameter, filter out
Satisfactory data, as target component；Target note is adopted into partial data in data and the target component is brought into
The capacitor model, calculate water injection rate estimate；Calculate the water injection rate and note the water filling adopted in data with the target
The error amount of amount；According to the error amount, by Gauss distribution method, the water filling well group is determined from the target component
Interporosity flow coefficient and time lag constant.
The one or more technical schemes provided in the embodiment of the present application, have at least the following technical effects or advantages：
1st, the method and device that the embodiment of the present application provides, based on Production development data, that is, the initial related data obtained,
It is strong and weak to interwell communication to carry out quantitative analysis, water filling is calculated based on capacitor model combination Gaussian Profile scheduling algorithm and imitated and ripple
And situation, the problem of traditional interwell communication determination methods influence normal production and construction operation is overcome, note is substantially reduced and adopts connection
The cost that power differentiates, simplify the workload that tradition note adopts connected relation differentiation.Further, this method utilizes probability statistics
Thought, the capacitor model is solved using Gauss distribution method, calculates the connectivity parameters, ensure that and connect between well
The accuracy of general character quantitative analysis.
2nd, the method and device that the embodiment of the present application provides, using the thought of probability statistics, uses Gauss distribution method
The capacitor model is solved, first generates estimating interporosity flow coefficient and estimating time lag constant for each oil-producing well at random, then
Optimal solution is searched out in random value, the interporosity flow coefficient and time lag constant of the water filling well group is determined, is combined with practical application
It is even closer, it ensure that the accuracy of inter well connectivity quantitative analysis.
Brief description of the drawings
Fig. 1 is the flow chart of the capacitor model inverting inter well connectivity method based on Gaussian Profile in the embodiment of the present application；
Fig. 2 is Gaussian Profile calculation flow chart in the embodiment of the present application；
Fig. 3 is that Gaussian Profile solves capacitance equation flow chart in the embodiment of the present application；
Fig. 4 is the structure chart of the capacitor model inverting inter well connectivity device based on Gaussian Profile in the embodiment of the present application.
Embodiment
The embodiment of the present application is by providing a kind of capacitor model inverting inter well connectivity method and dress based on Gaussian Profile
Put, solve the acquisition of oil deposit inter-well dynamic connectivity in the prior art, it is low the degree of accuracy to be present, influences normal production and costly
Etc. technical problem.Realizing reduces cost, simplifies workload and ensure that the technique effect of accuracy.
In order to solve technical problem existing for above-mentioned prior art, the overall think of for the technical scheme that the embodiment of the present application provides
Road is as follows：
A kind of capacitor model inverting inter well connectivity method based on Gaussian Profile, including：
Obtain the initial related data of water filling well group；The initial related data packets include：The water injection rate of the water filling well group,
Liquid output, stream pressure, water filling section initial time and connectivity relationship；
Target note, which is filtered out, from the initial related data adopts data；The target note adopts data and is and water filling Duan Zhongchu
Water injection rate, Liquid output and the stream pressure of beginning water filling date match；
Target note is adopted into data and brings capacitor model into, the capacitor model is asked by Gauss distribution method
Solution, so as to calculate connectivity parameters；The connectivity parameters be used to characterize in the water filling well group water injection well and liquid producing well it
Between connectedness it is strong and weak.
By the above as can be seen that being based on Production development data, that is, the initial related data obtained, note well is adopted
Between connect it is strong and weak carry out quantitative analysis, water filling is calculated based on capacitor model combination Gaussian Profile scheduling algorithm and is imitated and involved feelings
Condition, the problem of traditional interwell communication determination methods influence normal production and construction operation is overcome, substantially reduce note and adopt connection power
The cost of differentiation, simplify the workload that tradition note adopts connected relation differentiation.Further, this method utilizes the think of of probability statistics
Think, the capacitor model is solved using Gauss distribution method, the connectivity parameters is calculated, ensure that interwell communication
The accuracy of property quantitative analysis.
In order to be better understood from above-mentioned technical proposal, below in conjunction with Figure of description and specific embodiment to upper
Technical scheme is stated to be described in detail.
Embodiment one：
In embodiment one, there is provided a kind of capacitor model inverting inter well connectivity method based on Gaussian Profile, please join
Fig. 1 is examined, as shown in figure 1, methods described includes：
Step S101, obtain the initial related data of water filling well group；The initial related data packets include：The water filling well group
Water injection rate, Liquid output, stream pressure, water filling section initial time and connectivity relationship；
Step S102, target note is filtered out from the initial related data and adopts data；Target note adopt data be with
The water injection rate of initial fill date match, Liquid output and stream pressure in water filling section；
Step S103, target note is adopted into data and brings capacitor model into, by Gauss distribution method to the electric capacity mould
Type is solved, so as to calculate connectivity parameters；The connectivity parameters be used to characterizing in the water filling well group water injection well and
Connectedness between liquid producing well is strong and weak.
The general principle for the method that the application provides is that the change of water injection well injection rate can cause surrounding oil well Liquid output
Fluctuation, fluctuating range is bigger, and connecting degree is better, and using Production development data, i.e., initial related data can be by mathematics side
Method carrys out quantization signifying note and adopts a connected relation.
For water-drive pool, the Liquid output of usual well water injection rate and surrounding oil well is certain relation be present, can
Oil reservoir is considered as the system i.e. injection and extraction system that a water injection well sends stimulation and surrounding oil well receives stimulation, by using mathematics side
Method realizes that note adopts the quantization signifying of connected relation.Such as it is based on polynary time using oil field development data, with reference to statistical method
Return model etc. to carry out inverting note and adopt connected relation.
The method that the application provides, based on above-mentioned principle, on the basis of the research of existing inter well connectivity, for heterogeneous
Property and the stronger fracture-pore reservoir of well pattern irregular shape carry out qualitative, quantitative dynamic playback algorithm research.By establishing new well
Between connectivity modeling, calculate interwell communication parameter, the connecting degree between quantitative description well.
Below, the implementation steps with reference to Fig. 1 to the capacitor model inverting inter well connectivity method based on Gaussian Profile
It is described in detail：
First, step S101 is performed, obtains the initial related data of water filling well group；The initial related data packets include：Institute
State water injection rate, Liquid output, stream pressure, water filling section initial time and the connectivity relationship of water filling well group.
In the embodiment of the present application, before step S101 is performed, can also first judge whether to add stream pressure data inversion
Inter well connectivity, obtain the first judged result；
If first judged result is yes, the capacitor model flows the capacitor model of pressure for consideration；
If first judged result is no, the capacitor model is the capacitor model for not considering stream pressure.
Can whether be pre-selected as needed by user using stream pressure as calculating institute in specific implementation process
The target note for stating connectivity parameters adopts data.
In the embodiment of the present application, before step S101 is performed, can also first select to obtain the initial related data
Method, can select by note adopt response method obtain water filling well group initial related data；Or water filling is obtained by tracer
The initial related data of well group.
In specific implementation process, the method for initial related data can be preset as needed by user.
Next, performing step S102, filtering out target note from the initial related data adopts data；The target note
It is to be pressed with the water injection rate of initial fill date match, Liquid output and stream in water filling section to adopt data.
Specifically, water injection well can be divided into by initial related data by multiple water filling sections, by reading each water filling
The peak value and water injection time of related oil-producing well in section, the water injection rate and Liquid output for picking out matching are read in, and stream pressure is also needed according to note
Water section relevant information presses data to read the oil-producing well stream on matching date, that is, filters out and the initial fill amount date in water filling section
Water injection rate, Liquid output and the stream pressure matched somebody with somebody.
Subsequently, step S103 is performed, target note is adopted into data and brings capacitor model into, passes through Gauss distribution method pair
The capacitor model is solved, so as to calculate connectivity parameters；The connectivity parameters are used to characterize the water filling well group
Connectedness between interior water injection well and liquid producing well is strong and weak.
Specifically, Gauss distribution method mainly acts on the selection of interporosity flow coefficient and time lag constant.Principle is according to height
This distribution mean μ and standard deviation sigma, Gaussian Profile generate the interporosity flow coefficient and time lag constant of each oil-producing well at random；Select wherein
Live part, give up beyond a range of data, such as -0.3.By the channelling of the optimal solution of every generation every mouth oil-producing well
Coefficient and time lag constant seek its average, and are set to the mean μ of this bite oil-producing well Gaussian Profile.
Specifically, the capacitor model mainly acts on screening optimal solution.General principle is to pick out suitable correlation
Data, including pressed with the water injection rate of water filling section initial fill date match, Liquid output and stream；Generated at random with Gauss distributor
Each group of the interporosity flow coefficient and time lag constant of each round；Data are brought into model and solved, flux matched with true water filling, are obtained every
One each group of cumulative errors of wheel；N number of optimal solution, that is, minimal error are selected in each group of cumulative errors of each round；Ask N number of
Optimal solution parameter mean and the mean μ assigned it in Gauss distributor；Repetitive cycling algebraically is until terminate.
In the embodiment of the present application, the capacitor model in step S103, can be divided into do not consider stream pressure capacitor model and
Consider two kinds of the capacitor model of stream pressure, illustrate separately below：
The first, the capacitor model for not considering stream pressure is：
Wherein,For water injection well i the n moment water injection rate；iij(n) be water filling well group i in oil-producing well j at the n moment
Liquid output；n0For initial time；For the Liquid output iij(n) convolution；λ is channelling system
Number；τ is time lag constant；λijIt is the interporosity flow coefficient between water injection well i and oil-producing well j, characterizes the connectedness between well i and well j；τij
It is the time lag constant between water injection well i and oil-producing well j；λijAnd τijFor estimating water injection well i water injection rate For the influence of water injection well first time water filling,Value be equal to uneven constant.
It is second, described to consider that flowing the capacitor model pressed is：
This method analysis inter well connectivity is that water injection well, oil-producing well and interwell communication relation are considered as into a complication system, base
In flow through oil reservoir and the similar features of electric current flowing, i.e. water power similitude, data are adopted by electric capacity mould using dynamic stream pressure, dynamic note
The new application of type describes the feature of oil reservoir, while considers the influence of water body intrusion.
Wherein,For water injection well i the n moment water injection rate；iij(n) be water filling well group i in oil-producing well j at the n moment
Liquid output；n0For initial time；For the Liquid output iij(n) convolution；λ is channelling system
Number；τ is time lag constant；λijIt is the interporosity flow coefficient between water injection well i and oil-producing well j, characterizes the connectedness between well i and well j；τij
It is the time lag constant between water injection well i and oil-producing well j；λijAnd τijFor estimating water injection well i water injection rate For the influence of water injection well first time water filling,Value be equal to uneven constant；
Wherein,For the stream pressure of corresponding oil-producing well k in water filling well group i；For the stream pressureConvolution；υkiFor weight；υkiValue be equal to λki；λkiIt is
Interporosity flow coefficient between water injection well i and oil-producing well k；τkiIt is the time lag constant between water injection well i and oil-producing well k.
Specifically, uneven constant can obtain according to error calculation, mainly act on correction model error, be divided into
Machine and ratio two ways.The uneven constant of stochastic model, it is that random error daily is used for correction model error；Ratio mode
Uneven constant, be to contact the daily water injection rate of water injection well, daily error after being calculated by a certain percentage for correction model.
Specifically, interporosity flow coefficient λ, characterize：Quantify connective, i.e., each oil-producing well weight connective with water injection well.
Time lag constant, τ, characterize：The dissipation degree of signal between injection-production well.It is random that the initialization of the two coefficients is based on Gauss distribution method
A collection of initial seed is generated, while is contrasted according to the capacitor model of recurrence estimation, evolution N generations with True Data, chooses smaller mistake
A series of seeds of difference, so as to carry out constantly recurrence, change the two coefficients, solve and matched most with history matching for production
Excellent solution, obtain the interporosity flow coefficient of each oil-producing well of each water filling well group and water injection well.
In the embodiment of the present application, the solution throughway of the capacitor model is：
IfFor water injection rates of the water injection well i at the n moment, t is the total duration of inverting, model parameter solve can conclude with
Following optimization problem：
Wherein,For the influence of the stream pressure；
In the embodiment of the present application, the capacitor model parametric solution principle based on Gauss distribution method is：
Gaussian Profile is also known as normal distribution, and it, which is acted on, produces stochastic variable, so as to avoid the generation of local minimum.Gauss
Two parameters, i.e. mean μ and standard deviation sigma are distributed with, mean μ determines the center of normal curve；Standard deviation sigma determines that normal state is bent
The steep of line, its formula are as follows：
Wherein, x is variable.
34.1% region is the number range that anomaly average is less than within a standard deviation in Gaussian Profile.In normal state point
In cloth, ratio shared by this scope is the 68% of whole numerical value, and according to normal distribution, the ratio within two standard deviations is altogether
95%；Ratio within three standard deviations is altogether 99%, thus there is two benefits：
1. it is too big to be effectively protected not deviating by for average optimal selected by each round；
2. simultaneously as normal distribution generates the danger that variable difference it also avoid being absorbed in local optimum at random.
It is random to generate first round seed with reference to Gauss distribution method, by bringing parametric solution capacitor model into.And then choose
A series of optimal solutions, its mean is sought optimal solution, and mean is assigned to mean μ in Gaussian Profile again, again calling module
Selectable, the directive random generation second batch seed of the second wheel is carried out, with this recurrence, is connected between finding optimal solution i.e. well
It is logical to split a point Coefficient Algorithm and restrain.
In the embodiment of the present application, the connectivity parameters include：The interporosity flow coefficient of the water filling well group.
In the embodiment of the present application, the capacitor model parametric solution method based on Gauss distribution method is：
Generate estimating for each oil-producing well at random with Gaussian Profile and interporosity flow coefficient and estimate time lag constant, as initial ginseng
Number；
By preset range, from the initial parameter, satisfactory data are filtered out, as target component；
Target note is adopted into partial data in data and the target component brings the capacitor model into, calculates note
Water estimate；
Calculate the error amount that the water injection rate adopts the water injection rate in data with target note；
According to the error amount, by Gauss distribution method, the water filling well group is determined from the target component
The interporosity flow coefficient.
Specifically, capacitor model, Ke Yishi are solved based on Gauss distribution method：
Advanced line number Data preprocess：
Initial related data is first read (including water injection rate, Liquid output, stream pressure, water filling section initial time and connective to close
System)；Screening adopts data with the water injection rate of initial fill amount date match, Liquid output and stream pressure in water filling section as target note；Again
The data filtered out are brought into model and calculated, after calculating, target note is screened again if still having water filling section not calculate and adopts data,
Until exporting and preserving each water filling section result of calculation.
As shown in Fig. 2 the specific implementation step based on Gauss distribution method can be：
First according to Gaussian Profile mean μ and standard deviation sigma, what Gaussian Profile generated each oil-producing well at random estimates interporosity flow coefficient
With estimate time lag constant；Wherein live part is selected, is given up beyond a range of data, such as -0.3.Every mouth is produced
The interporosity flow coefficient and time lag constant of the optimal solution of oil well seek its average, and are set to the mean μ of this bite oil-producing well Gaussian Profile, if
When module stills need to initialize the next generation, then estimating for each oil-producing well is generated at random and interporosity flow coefficient and estimates time lag constant, it is no
Then terminate.
Further, as shown in figure 3, solving the computational methods of capacitor model based on Gaussian Profile in more detail can be：
First pick out suitable related data, including with the water injection rate of water filling section initial fill date match, Liquid output and
Stream pressure；Each group of each round is generated at random with Gauss distributor again to estimate interporosity flow coefficient and estimate time lag constant；By institute
State that target note adopts partial data in data and the target component is brought into model and solved, it is flux matched with true water filling, obtain
Each group of cumulative errors of each round；The generation target component is returned if this Lun Rengyou group does not have cumulative errors；Each
Take turns and multiple optimal solutions, that is, minimal error are selected in each group of cumulative errors；Seek multiple optimal solution parameter means and assigned
To the mean μ in Gauss distributor；Check whether that reaching cyclic algebra (was set as 10 generations, by constantly analysis and in fact in module
Trample already ensure that can be restrained certainly when circulation reached for 10 generation), returned if not reaching, on the contrary terminate.
Through practice, the method provided using the application, it is contemplated that the influence of water body intrusion, reject invalid signals, can optimize
Capacitor model；Using Gaussian Profile to model solution, on the premise of keeping optimization, while avoid being absorbed in locally optimal solution
Quagmire.
It is the capacitor model inverting inter well connectivity method based on Gaussian Profile provided using the embodiment of the present application below
Concrete application example：
Contrasted according to the report of the TK663 well groups tracer of 08 year with filter method inverting
The production to be matched by the four mouthfuls of liquid producing well times of water injection rate and surrounding for certain section of water filling section for bringing TK663 water injection wells into
After liquid measure, pass throughModel solution, solve specific side
Method：
First, λ and τ is initialized by Gaussian Profile to bring into above-mentioned formula；Typing Liquid output and stream pressure zone enter to calculate again；
Result of calculation subtracts each other the minimum value asked under its absolute value with true water injection rate；According to minimum value, by the method for Gaussian Profile, no
Disconnected optimization λ and τ；Finally draw optimal solution λ and τ.
Result of calculation is shown in Tables 1 and 2：
The TK663 well group connected relation filter methods of table 1 and tracer method contrast table 1
The TK663 well group connected relation filter methods of table 2 and tracer method contrast table 2
Through examining, the well connectedness result is more coincide with tracer test result.Well-group tracer water operation situation,
Tracer peak-peak concentration and the result sizes order that Filtering Analysis obtains are basically identical.
On the other hand, based on same design, there is provided device corresponding to the method in embodiment one, detailed in Example two.
Embodiment two：
In the present embodiment, there is provided a kind of capacitor model inverting inter well connectivity device based on Gaussian Profile, please join
Fig. 4 is examined, Fig. 4 is the structure chart of described device, and described device includes：
Acquisition module 401, for obtaining the initial related data of water filling well group；The initial related data packets include：It is described
Water injection rate, Liquid output, stream pressure, water filling section initial time and the connectivity relationship of water filling well group；
Screening module 402, data are adopted for filtering out target note from the initial related data；The target note adopts number
According to be pressed with the water injection rate of initial fill date match in water filling section, Liquid output and stream；
Computing module 403, capacitor model is brought into for target note to be adopted into data, by Gauss distribution method to described
Capacitor model is solved, so as to calculate connectivity parameters；The connectivity parameters, which are used to characterize in the water filling well group, to be noted
Connectedness between well and liquid producing well is strong and weak.
In the embodiment of the present application, described device also includes：
Judge module, for judging whether to add stream pressure data inversion inter well connectivity, obtain the first judged result；If
First judged result is capacitor model yes, then that the capacitor model is pressed for consideration stream；If first judged result
It is no, then the capacitor model is the capacitor model for not considering stream pressure.
In the embodiment of the present application, the acquisition module includes：
First acquisition unit, for adopting the initial related data of response method acquisition water filling well group by note；Or
Second acquisition unit, for obtaining the initial related data of water filling well group by tracer.
In the embodiment of the present application, described device also includes：
Gaussian Computation module, for generating when estimating interporosity flow coefficient and estimating of each oil-producing well at random with Gaussian Profile
Stagnant constant, as initial parameter；By preset range, from the initial parameter, satisfactory data are filtered out, as target
Parameter；Target note is adopted into partial data in data and the target component brings the capacitor model into, calculates water filling
Measure estimate；Calculate the error amount that the water injection rate adopts the water injection rate in data with target note；According to the error
Value, by Gauss distribution method, the interporosity flow coefficient and time lag constant of the water filling well group are determined from the target component.
The device provided in the present embodiment has been described in detail in embodiment one, so those skilled in the art
Can be succinct for specification according to the structure of the device described above being apparent from the present embodiment, it is just no longer superfluous herein
State.
Technical scheme in above-mentioned the embodiment of the present application, at least has the following technical effect that or advantage：
1st, the method and device that the embodiment of the present application provides, based on Production development data, that is, the initial related data obtained,
Connected between being adopted note well it is strong and weak carry out quantitative analysis, based on capacitor model combination Gaussian Profile scheduling algorithm be calculated water filling by
Imitate and involve situation, overcome the problem of traditional interwell communication determination methods influence normal production and construction operation, substantially reduce note
The strong and weak cost differentiated of connection is adopted, simplifies the workload that tradition note adopts connected relation differentiation.Further, this method is united using probability
The thought learned is counted, the capacitor model is solved using Gauss distribution method, the connectivity parameters is calculated, ensure that
The accuracy of inter well connectivity quantitative analysis.
2nd, the method and device that the embodiment of the present application provides, using the thought of probability statistics, uses Gauss distribution method
The capacitor model is solved, first generates estimating interporosity flow coefficient and estimating time lag constant for each oil-producing well at random, then
Optimal solution is searched out in random value, the interporosity flow coefficient and time lag constant of the water filling well group is determined, is combined with practical application
It is even closer, it ensure that the accuracy of inter well connectivity quantitative analysis.
It should be understood by those skilled in the art that, embodiments of the invention can be provided as method, system or computer program
Product.Therefore, the present invention can use the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware
Apply the form of example.Moreover, the present invention can use the computer for wherein including computer usable program code in one or more
The computer program production that usable storage medium is implemented on (including but is not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The present invention is the flow with reference to method according to embodiments of the present invention, equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that can be by every first-class in computer program instructions implementation process figure and/or block diagram
Journey and/or the flow in square frame and flow chart and/or block diagram and/or the combination of square frame.These computer programs can be provided
The processors of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce
A raw machine so that produced by the instruction of computer or the computing device of other programmable data processing devices for real
The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which produces, to be included referring to
Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or
The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted
Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, so as in computer or
The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in individual square frame or multiple square frames.
Although preferred embodiments of the present invention have been described, but those skilled in the art once know basic creation
Property concept, then can make other change and modification to these embodiments.So appended claims be intended to be construed to include it is excellent
Select embodiment and fall into having altered and changing for the scope of the invention.
Obviously, those skilled in the art can carry out the essence of various changes and modification without departing from the present invention to the present invention
God and scope.So, if these modifications and variations of the present invention belong to the scope of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to comprising including these changes and modification.
Claims (4)
- A kind of 1. capacitor model inverting inter well connectivity method based on Gaussian Profile, it is characterised in that including：Obtain the initial related data of water filling well group；The initial related data packets include：Water injection rate, the production liquid of the water filling well group Amount, stream pressure, water filling section initial time and connectivity relationship；Target note, which is filtered out, from the initial related data adopts data；It is with initially being noted in water filling section that the target note, which adopts data, Water injection rate, Liquid output and the stream pressure of water date match；Generate estimating for each oil-producing well at random with Gaussian Profile and interporosity flow coefficient and estimate time lag constant, as initial parameter；By preset range, from the initial parameter, satisfactory data are filtered out, as target component；Target note is adopted into partial data in data and the target component brings capacitor model into, calculates water injection rate estimation Value；Calculate the error amount that the water injection rate adopts the water injection rate in data with target note；According to the error amount, by Gauss distribution method, determined from the target component described in the water filling well group Interporosity flow coefficient；Wherein, methods described also includes：Judge whether to add stream pressure data inversion inter well connectivity, obtain the first judged result；If first judged result is yes, the capacitor model flows the capacitor model of pressure for consideration；If first judged result is no, the capacitor model is the capacitor model for not considering stream pressure；It is described not consider that flowing the capacitor model pressed is：<mrow> <msub> <mover> <mi>q</mi> <mo>^</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>&lambda;</mi> <mi>p</mi> </msub> <mi>q</mi> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <msup> <mi>e</mi> <mfrac> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mrow> <mi>n</mi> <mo>-</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> </mrow> <mo>)</mo> </mrow> </mrow> <msub> <mi>T</mi> <mi>p</mi> </msub> </mfrac> </msup> <mo>+</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>i</mi> <mo>=</mo> <mi>l</mi> </mrow> </munderover> <msub> <mi>&lambda;</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <msubsup> <mi>i</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>;</mo> </mrow>It is described to consider that flowing the capacitor model pressed is：<mrow> <msub> <mover> <mi>q</mi> <mo>^</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>&lambda;</mi> <mi>p</mi> </msub> <mi>q</mi> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <msup> <mi>e</mi> <mfrac> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mrow> <mi>n</mi> <mo>-</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> </mrow> <mo>)</mo> </mrow> </mrow> <msub> <mi>T</mi> <mi>p</mi> </msub> </mfrac> </msup> <mo>+</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>i</mi> <mo>=</mo> <mi>l</mi> </mrow> </munderover> <msub> <mi>&lambda;</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <msubsup> <mi>i</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>+</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>k</mi> <mo>=</mo> <mi>K</mi> </mrow> </munderover> <msub> <mi>&upsi;</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> </msub> <mo>&lsqb;</mo> <msub> <mi>p</mi> <mrow> <msub> <mi>wf</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <msup> <mi>e</mi> <mfrac> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mrow> <mi>n</mi> <mo>-</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> </mrow> <mo>)</mo> </mrow> </mrow> <msub> <mi>&tau;</mi> <mrow> <mi>k</mi> <mi>j</mi> </mrow> </msub> </mfrac> </msup> <mo>-</mo> <msub> <mi>p</mi> <mrow> <msub> <mi>wf</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> </msub> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>+</mo> <msubsup> <mi>p</mi> <mrow> <msub> <mi>wf</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> </msub> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>&rsqb;</mo> <mo>;</mo> </mrow>Wherein,For water injection well i the n moment water injection rate；iij(n) it is productions of the oil-producing well j in water filling well group i at the n moment Liquid measure；n0For initial time；For the Liquid output iij(n) convolution；λ is interporosity flow coefficient；τ It is time lag constant；λijIt is the interporosity flow coefficient between water injection well i and oil-producing well j；τijIt is the time lag between water injection well i and oil-producing well j Constant；For the influence of water injection well first time water filling,Value be equal to uneven constant；Wherein,For the stream pressure of corresponding oil-producing well k in water filling well group i；For institute State stream pressureConvolution；υkiFor weight；υkiValue be equal to λki；λkiIt is the channelling system between water injection well i and oil-producing well k Number；τkiIt is the time lag constant between water injection well i and oil-producing well k.
- 2. the method as described in claim 1, it is characterised in that it is described obtain water filling well group initial related data be specially：The initial related data of response method acquisition water filling well group is adopted by note；OrThe initial related data of water filling well group is obtained by tracer.
- A kind of 3. capacitor model inverting inter well connectivity device based on Gaussian Profile, it is characterised in that including：Acquisition module, for obtaining the initial related data of water filling well group；The initial related data packets include：The water filling well group Water injection rate, Liquid output, stream pressure, water filling section initial time and connectivity relationship；Screening module, data are adopted for filtering out target note from the initial related data；Target note adopt data be with The water injection rate of initial fill date match, Liquid output and stream pressure in water filling section；Gaussian Computation module, for Gaussian Profile generate at random each oil-producing well estimate interporosity flow coefficient and to estimate time lag normal Number, as initial parameter；By preset range, from the initial parameter, satisfactory data are filtered out, are joined as target Number；Target note is adopted into partial data in data and the target component brings the capacitor model into, calculates water injection rate Estimate；Calculate the error amount that the water injection rate adopts the water injection rate in data with target note；According to the error amount, By Gauss distribution method, the interporosity flow coefficient of the water filling well group is determined from the target component；Judge module, for judging whether that will flow pressure adopts data as the target note for calculating the connectivity parameters, Obtain the first judged result；If first judged result is yes, the initial related data also includes：The water injection well Acquisition time corresponding to the stream pressure of group and the stream pressure；The capacitor model that the capacitor model is pressed for consideration stream；If described One judged result is no, then the capacitor model is the capacitor model for not considering stream pressure；Wherein, it is described not consider that flowing the capacitor model pressed is：<mrow> <msub> <mover> <mi>q</mi> <mo>^</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>&lambda;</mi> <mi>p</mi> </msub> <mi>q</mi> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <msup> <mi>e</mi> <mfrac> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mrow> <mi>n</mi> <mo>-</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> </mrow> <mo>)</mo> </mrow> </mrow> <msub> <mi>T</mi> <mi>p</mi> </msub> </mfrac> </msup> <mo>+</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>i</mi> <mo>=</mo> <mi>l</mi> </mrow> </munderover> <msub> <mi>&lambda;</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <msubsup> <mi>i</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>;</mo> </mrow>It is described to consider that flowing the capacitor model pressed is：<mrow> <msub> <mover> <mi>q</mi> <mo>^</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>&lambda;</mi> <mi>p</mi> </msub> <mi>q</mi> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <msup> <mi>e</mi> <mfrac> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mrow> <mi>n</mi> <mo>-</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> </mrow> <mo>)</mo> </mrow> </mrow> <msub> <mi>T</mi> <mi>p</mi> </msub> </mfrac> </msup> <mo>+</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>i</mi> <mo>=</mo> <mi>l</mi> </mrow> </munderover> <msub> <mi>&lambda;</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <msubsup> <mi>i</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>+</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mrow> <mi>k</mi> <mo>=</mo> <mi>K</mi> </mrow> </munderover> <msub> <mi>&upsi;</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> </msub> <mrow> <mo>&lsqb;</mo> <mrow> <msub> <mi>p</mi> <mrow> <msub> <mi>wf</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> </mrow> </msub> <mrow> <mo>(</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> <mo>)</mo> </mrow> <msup> <mi>e</mi> <mfrac> <mrow> <mo>-</mo> <mrow> <mo>(</mo> <mrow> <mi>n</mi> <mo>-</mo> <msub> <mi>n</mi> <mn>0</mn> </msub> </mrow> <mo>)</mo> </mrow> </mrow> <msub> <mi>&tau;</mi> <mrow> <mi>k</mi> <mi>j</mi> </mrow> </msub> </mfrac> </msup> <mo>-</mo> <msub> <mi>p</mi> <mrow> <msub> <mi>wf</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> </msub> </mrow> </msub> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>+</mo> <msubsup> <mi>p</mi> <mrow> <msub> <mi>wf</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> </msub> </mrow> <mo>&prime;</mo> </msubsup> <mrow> <mo>(</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mo>&rsqb;</mo> </mrow> <mo>;</mo> </mrow>Wherein,For water injection well i the n moment water injection rate；iij(n) it is productions of the oil-producing well j in water filling well group i at the n moment Liquid measure；n0For initial time；For the Liquid output iij(n) convolution；λ is interporosity flow coefficient；τ It is time lag constant；λijIt is the interporosity flow coefficient between water injection well i and oil-producing well j；τijIt is the time lag between water injection well i and oil-producing well j Constant；For the influence of water injection well first time water filling,Value be equal to uneven constant；Wherein,For the stream pressure of corresponding oil-producing well k in water filling well group i；For institute State stream pressureConvolution；υkiFor weight；υkiValue be equal to λki；λkiIt is the channelling system between water injection well i and oil-producing well k Number；τkiIt is the time lag constant between water injection well i and oil-producing well k.
- 4. device as claimed in claim 3, it is characterised in that the acquisition module includes：First acquisition unit, for adopting the initial related data of response method acquisition water filling well group by note；OrSecond acquisition unit, for obtaining the initial related data of water filling well group by tracer.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510734077.6A CN105404726B (en) | 2015-11-02 | 2015-11-02 | A kind of capacitor model inverting inter well connectivity method and device based on Gaussian Profile |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510734077.6A CN105404726B (en) | 2015-11-02 | 2015-11-02 | A kind of capacitor model inverting inter well connectivity method and device based on Gaussian Profile |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105404726A CN105404726A (en) | 2016-03-16 |
| CN105404726B true CN105404726B (en) | 2018-02-13 |
Family
ID=55470213
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510734077.6A Expired - Fee Related CN105404726B (en) | 2015-11-02 | 2015-11-02 | A kind of capacitor model inverting inter well connectivity method and device based on Gaussian Profile |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105404726B (en) |
Cited By (1)
| 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 |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107292074B (en) * | 2016-04-01 | 2020-11-13 | 中国石油化工股份有限公司 | Method for judging connectivity between wells |
| CN107291667B (en) * | 2016-04-01 | 2020-11-13 | 中国石油化工股份有限公司 | Method and system for determining communication degree between wells |
| CN106611081B (en) * | 2016-11-21 | 2019-08-30 | 中国地质大学（武汉） | Judge automatically the integrated approach and system of fracture-pore reservoir production inter well connectivity |
| US11187078B2 (en) | 2017-01-20 | 2021-11-30 | Total Sa | Method for evaluating connectivity between a first well and a second well in a hydrocarbon production field and related system |
| CN107120111B (en) * | 2017-03-24 | 2020-07-07 | 中国地质大学（武汉） | Oil reservoir inter-well communication degree evaluation method and system based on multi-fractal |
| CN110965970B (en) * | 2018-09-29 | 2022-02-11 | 北京国双科技有限公司 | Method and device for determining correlation between water injection well and oil production well |
| CN109389307B (en) * | 2018-10-10 | 2022-03-01 | 中国石油天然气股份有限公司 | Method and device for determining channeling flow of oil reservoir water injection well |
| CN111126650B (en) * | 2018-10-31 | 2022-05-27 | 北京国双科技有限公司 | Model construction method and device for oil field simulation system |
| CN117684929A (en) * | 2022-12-14 | 2024-03-12 | 中国科学院沈阳自动化研究所 | Oil-water well system energy consumption global optimization control method based on inter-well connectivity |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101725346A (en) * | 2009-12-15 | 2010-06-09 | 中国石油大学(华东) | Oil deposit inter-well dynamic connectivity inverting method |
| CN103670369A (en) * | 2013-12-12 | 2014-03-26 | 中国石油天然气股份有限公司 | Method and device for judging communication state between injection wells and production wells |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9140108B2 (en) * | 2011-11-03 | 2015-09-22 | Bp Corporation North America Inc. | Statistical reservoir model based on detected flow events |
-
2015
- 2015-11-02 CN CN201510734077.6A patent/CN105404726B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101725346A (en) * | 2009-12-15 | 2010-06-09 | 中国石油大学(华东) | Oil deposit inter-well dynamic connectivity inverting method |
| CN103670369A (en) * | 2013-12-12 | 2014-03-26 | 中国石油天然气股份有限公司 | Method and device for judging communication state between injection wells and production wells |
Cited By (2)
| 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 |
| 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 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105404726A (en) | 2016-03-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105404726B (en) | A kind of capacitor model inverting inter well connectivity method and device based on Gaussian Profile | |
| CN105389467B (en) | A kind of method and device obtaining interwell communication relationship | |
| CN104950334B (en) | A kind of method and device of predicting reservoir distribution | |
| CN104879103B (en) | A kind of seperated layer water injection effect analysis method | |
| CN102373923B (en) | Reservoir stratum identification method | |
| CN106050225B (en) | A kind of nuclear magnetic resonance log T2 composes the determination method of 100% pure water spectrum | |
| CN103573250B (en) | A kind of calculated level well well is to the method for stratum upper and lower interface distance | |
| AU2009264967B2 (en) | Well log correlation | |
| CN103926617B (en) | Seam hole reservoir body detection method and detection device | |
| CN109057786A (en) | A kind of adaptive model for the estimation of untraditional reservoir recoverable reserves | |
| CN105863628B (en) | A kind of phase of development subtle hydrocarbon reservoir method | |
| CN105631754B (en) | A kind of method and apparatus for the yield cross-sectional data determining overseas oil field | |
| CN106443774A (en) | Method for improving pre-stack depth migration imaging precision of irregular earth surface | |
| CN112147684B (en) | Method and device for characterizing co-deposition fault activity intensity | |
| CN110389382A (en) | A kind of oil-gas reservoir reservoir characterization method based on convolutional neural networks | |
| CN111580181A (en) | Water guide collapse column identification method based on multi-field multi-feature information fusion | |
| CN106503295A (en) | The method and device of oil field Water Flooding Layer explained by a kind of utilization state spatial model | |
| CN109425900A (en) | A kind of Seismic Reservoir Prediction method | |
| CN104656140A (en) | Median filtering method and system based on vertical earthquake attenuation laws | |
| CN103995972A (en) | Stratigraphic correlation method | |
| CN111983683B (en) | Prediction method and system for lake-facies limestone reservoir under low-well condition | |
| CN111753423B (en) | XGboost-based inter-well dynamic connectivity quantification method | |
| CN105116466A (en) | Method and apparatus for determining oil field reservoir physical characteristics | |
| CN108535777A (en) | A kind of seismic first breaks detection method and system | |
| CN106908838A (en) | The method for building target area stratum inelastic attenuation quality factor three-dimensional model |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20180213 Termination date: 20181102 |