CN106055827B - A kind of reservoir numerical simulation parameters sensitivity analysis device and method - Google Patents
A kind of reservoir numerical simulation parameters sensitivity analysis device and method Download PDFInfo
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- CN106055827B CN106055827B CN201610425340.8A CN201610425340A CN106055827B CN 106055827 B CN106055827 B CN 106055827B CN 201610425340 A CN201610425340 A CN 201610425340A CN 106055827 B CN106055827 B CN 106055827B
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Abstract
The present invention relates to a kind of reservoir numerical simulation parameters sensitivity analysis device and methods.Its technical solution be include following device: parameter obtaining device, for the parameter and data fields of analog result to be connect and obtained with numerical simulator；Model construction device, for constructing adjoint variable independently of the associated model of simulation calculating variable, and according to the coefficient matrix of simulator solving result building associated model；Solving device, using obtained adjoint variable, solves sensitivity coefficient matrix of the objective function about model cootrol variable for solving adjoint variable；Analytical equipment carries out sensitivity to parameter impact analysis according to obtained result.Beneficial effect is: the present invention can greatly improve the efficiency that reservoir engineer carries out history matching, obtain the fitting result of high quality, hence it is evident that shorten the fitting period, and do not need to concentrate on energy on the reservoir physical parameter of complexity early period, reduce personnel cost.
Description
Technical field
The present invention relates to a kind of Oil and Natural Gas Engineering field, in particular to a kind of reservoir numerical simulation sensitivity to parameter
Analytical equipment and method.
Background technique
For reservoir engineer, solves problem of reservoir engineering and largely use numerical simulation technology, how to verify numerical value
The reliability of analogsimulation is the work of history matching, however during conventional history matching, it can only once operate a well
Or a well group can be operated, it is difficult intuitively to judge the parameter of reservoir items is how to influence history matching as a result, pole
It is subjective, and the interminable time is carrying out trial and error process repeatedly.In order to accelerate the precision and efficiency of history matching, a variety of grind is proposed
Study carefully method.
Business software in petroleum works field about reservoir numerical simulation auxiliary history matching at present, such as
The SimOpt module of Schlumberger company Eclipse, the CMOST module of the CMG software of CMG company, Roxar company
EnABLE etc., there are mainly two types of the parameters sensitivity analysis methods of use: gradient simulator method and experimental design method.
Gradient simulator method calculates target about the gradient of control variable by direct solution flow model in porous media state equation
For function to the sensibility of model parameter, process is as follows:
(1) difference for establishing flow model in porous media state equation solves format, and for each grid block, state variable includes phase
PressureAnd phase saturation.In addition, for the grid block containing well, bottom pressureAlso it is used as state variable.Model
Control variable generally comprises: the permeability in three directions、、, porosity, relative permeabilityAnd skin factor
Deng.
(2) gradient equations is directly obtained to a certain control variable derivation according to state equation.
It (3) is about state variable by a certain observation data definitionWith control variableObjective function.Then objective functionTo control variable?The gradient value at moment is sensibility of the control parameter about observed parameter.
To solve a certain observation data to the derivative of all model parameters, need to construct and solve and model parameter quantity phase
Deng gradient equations.Hypothesized model number of parameters is, production time step is, then observation data institute having time pair is found out
The gradient value of all model parameters also needs additionally to solve other than needing solving state equationSubgradient equation.
Therefore, gradient method has the characteristics that calculation amount is proportional to model parameter quantity, this to contain a large amount of moulds in processing
It cannot achieve when the problem of shape parameter.Practical numerical simulation for oil-gas reservoir model usually contains huge number of grid node (tens
The block models of ten thousand nodes are relatively conventional), and usually contain several parameters on each grid node (such as permeability, has porosity
Imitate thickness etc.), model parameter enormous amount.For each parameter, fortune of the calculating target function to the gradient of the parameter
Evaluation time can have more 20% than simulator normal operation, and the sensibility that obtain all mesh parameters will be one very large
Engineering, only this method is just applicable in when model variable is fewer.
Experimental design method determines the possible value range of each parameter first, by certain test design method (as just
Hand over experimental design, Latin hypercube design etc.), reasonable combination design is carried out to strategy parameter, is covered all with less scheme
Strategy parameter range, and use corresponding statistical analysis technique, study and predict the variation of these parameters to model output value
Influence degree, evaluate the sensibility rank of parameters.Experimental design method equally exists certain limitation: model parameter becomes
The design of the selection and testing program of changing range all has certain subjectivity；It needs to design a variety of testing programs, repeatedly transports
Row simulator, operand are big；When the model parameter of required research is too many, paid no attention to using the result that statistical method is handled
Think, precision does not reach requirement.
Summary of the invention
The purpose of the present invention is to drawbacks described above of the existing technology, and it is quick to provide a kind of reservoir numerical simulation parameter
Perceptual analysis device and method, the correlation that the quick optimization model responsive parameter of computer means can be utilized, determine parameter,
Reservoir engineer's in-depth is assisted to improve the efficiency of reservoir numerical simulation history matching work to the understanding of oil reservoir.
A kind of reservoir numerical simulation parameters sensitivity analysis device that the present invention mentions, technical solution be include following dress
It sets:
Parameter obtaining device, for the parameter and data fields of analog result to be connect and obtained with numerical simulator；
Model construction device, for constructing adjoint variable independently of the associated model of simulation calculating variable, and according to simulation
The coefficient matrix of device solving result building associated model；
Solving device, using obtained adjoint variable, solves objective function about model control for solving adjoint variable
The sensitivity coefficient matrix of variable processed；
Analytical equipment carries out sensitivity to parameter impact analysis according to obtained result.
Preferably, parameter obtaining device connect and gets parms with a variety of commercial oil pool numerical simulations.
A kind of reservoir numerical simulation parameters sensitivity analysis method that the present invention mentions, comprising the following steps:
The associated model that adjoint variable calculates variable independently of simulation is established, direct solution gradient equations is avoided；
The coefficient matrix of associated model is constructed, adjoint equation is solved and obtains adjoint variable；
Sensitivity coefficient accounting equation is established, using obtained adjoint variable, objective function is solved and becomes about model cootrol
The sensitivity coefficient matrix of amount carries out sensitivity analysis.
Preferably, associated model is constructed by Lagrangian method, simulation meter of the adjoint variable independently of master mould
Variable is calculated, direct solution gradient equations is avoided.
Preferably, the coefficient matrix of above-mentioned associated model is obtained by the solving result of state equation: in associated model is
Matrix numberFor state equation transposition Jacobian matrix, the Jacobian matrix transposition during being iteratively solved by state equation is obtained
It arrives, without rebuilding；Coefficient matrixTo accumulate term-term matrix with state equation, parsed by the accumulation item derivation of state equation
It arrives；Partial derivative for objective function about control variable, is parsed to obtain by the governing equation derivation of well.
The beneficial effects of the present invention are: generation building process of the coefficient matrix of (1) associated model without complexity, it can be direct
From the solving result of state equation；(2) solve gradient calculation amount be only dependent upon observation data bulk number, without taking
Certainly only it need to construct to solve a certain observation data to the derivative of all model parameters in the quantity of model parameter and solve one
Corresponding adjoint equation；(3) computational efficiency is high, only needs associated model of master mould of forward modeling and inverting, so that it may
To the sensitivity coefficient of each mesh parameter of institute's having time, parameters sensitivity analysis efficiency is substantially increased.
In short, the present invention can greatly improve the efficiency that reservoir engineer carries out history matching, the quasi- of high quality is obtained
It closes as a result, being obviously shortened and is fitted the period, and do not need to concentrate on energy on the reservoir physical parameter of complexity early period, reduce personnel
Cost.
Detailed description of the invention
Fig. 1 is the device of the invention block diagram；
Fig. 2 is techniqueflow chart of the invention；
Fig. 3 is analysis process block diagram of the invention；
In upper figure: step 210,220,230, step 310,320,330, parameter obtaining device 510, model construction device
520, solving device 530, analytical equipment 540.
Specific embodiment
In conjunction with attached drawing 1-3, the invention will be further described:
A kind of reservoir numerical simulation parameters sensitivity analysis device that the present invention mentions, technical solution is to include with lower part
Point:
Parameter obtaining device 510, for the parameter and data fields of analog result to be connect and obtained with numerical simulator；
Model construction device 520, for constructing adjoint variable independently of the associated model of simulation calculating variable, and according to mould
The coefficient matrix of quasi- device solving result building associated model；
Solving device 530, using obtained adjoint variable, solves objective function about mould for solving adjoint variable
The sensitivity coefficient matrix of type control variable；
Analytical equipment 540 carries out sensitivity to parameter impact analysis according to obtained result.
Preferably, parameter obtaining device connect and gets parms with a variety of commercial oil pool numerical simulations.
In addition, a kind of reservoir numerical simulation parameters sensitivity analysis method that the present invention mentions, comprising the following steps:
The associated model that adjoint variable calculates variable independently of simulation is established, direct solution gradient equations is avoided；
The coefficient matrix of associated model is constructed, adjoint equation is solved and obtains adjoint variable；
Sensitivity coefficient accounting equation is established, using obtained adjoint variable, objective function is solved and becomes about model cootrol
The sensitivity coefficient matrix of amount carries out sensitivity analysis.
Preferably, associated model is constructed by Lagrangian method, simulation meter of the adjoint variable independently of master mould
Variable is calculated, direct solution gradient equations is avoided.
Preferably, the coefficient matrix of above-mentioned associated model is obtained by the solving result of state equation: in associated model is
Matrix numberFor state equation transposition Jacobian matrix, the Jacobian matrix transposition during being iteratively solved by state equation is obtained
It arrives, without rebuilding；Coefficient matrixTo accumulate term-term matrix with state equation, parsed by the accumulation item derivation of state equation
It arrives；Partial derivative for objective function about control variable, is parsed to obtain by the governing equation derivation of well.
Shown in Fig. 2 is the technical flow that numerical reservoir model history fitting parameter sensibility is calculated based on adjoint system method
Cheng Tu, this method may be implemented greatly to shorten the scheme consumed when calculating.
In its step 210, adjoint equation is established:
The target of reservoir numerical simulation parameters sensitivity analysis is sensitivity of the calculating target function about control variable change
The gradient value of degree, i.e. calculating target function to control variable.The present invention is based on adjoint system theories, by introducing Lagrange
Operator is established with functional:
In formula,For objective function,It can claim adjoint variable in Three-dimensional Flow.
It is obtained to functional total differential:
The coefficient matrix of adjoint variable is obtained by carrying out total differential with functional and constraint condition being added, then obtains companion
With variable independently of the adjoint equation of model state variable:
In formula:=state equation transposition Jacobian matrix；=and state equation accumulation term-term matrix；=mesh
Partial derivative of the scalar functions about control variable.
In its step 220, adjoint variable is solved:
Adjoint equation formula is solved according to inverse chronological order, the adjoint variable of each time step can be obtained.
In its step 230, sensitivity coefficient accounting equation is established, solves sensitivity coefficient matrix.
It willAs control variableFunction, it is rightTotal differential is carried out to obtain:
It is available to acquire sensitivity coefficient equation by contrast (3) and formula (4) are as follows:
In formula:It is objective function to the derivative of control variable, can be obtained by the governing equation derivation of well；It is state equation to the derivative of control variable, can be obtained by state equation derivation.
After Solving Equation of State convergence, using adjoint method calculating target function to the sensibility of model cootrol variable
When, it need to only be can be realized by two steps: (1) construct associated model correlation matrix, solved associated model and calculate adjoint variable；(2) it brings adjoint variable into adjoint equation independently of model state variable, solves sensitivity coefficient equation, calculate sensitive system
Number。
Wherein, objective function is the production target to be analyzed, such as bottom pressure, producing gas-oil ratioAnd production
Water-oil factorDeng.
Pressure gradient expression formulaState variable is no longer dependent on to the derivative of control variable, therefore whole process only need to be according to just
Time series solves a set of flow regime equation and solves the identical adjoint equation of a set of scale with according to inverse time series
The gradient value that by the adjoint equation calculating target function independently of model state variable all grids are controlled with variable, calculates
Amount and the number of control variable are substantially unrelated, only walk with the production timeIt is related.Unlike traditional gradient method, it is desirable that
Data institute's having time is observed to the gradient value of all model parameters, other than needing solving state equation, it is only necessary to additional to solve
The secondary adjoint equation formula with state equation same size.
Fig. 3 shows analysis process block diagram, is that stream is implemented in the simulation calculation module concrete operations implemented based on the present invention
Journey.In operating process shown in Fig. 3:
Wherein in step 310, the present invention can by external common numerical simulator (such as Eclipse, CMG) into
The data acquisition of row the model calculation and parameter field, for constructing adjoint matrix model and subsequent calculating.Next establishes adjoint
Equation obtains oil reservoir multiphase, the state equation of multicomponent constant temperature seepage flow and using fully implicit solution first under finite volume control method
Finite difference method solves.Finally, according to adjoint system theory, established about objective function by introducing Lagrangian and
The adjoint functional of state equation sets up adjoint variable independently of model state variable with side by the way that constraint condition is added
Journey.Jacobian matrix transposition during wherein the left end term system matrix number of adjoint equation can be iteratively solved directly by state equation
It obtains, without rebuilding.Right-hand vector coefficient matrix is only related with the accumulation item of state equation, accumulation item that can directly to state equation
Derivation obtains, and objective function can be by directly parsing to obtain about the partial derivative matrix of control variable to the governing equation of well.
Wherein in step 320, purpose is intended to solve adjoint variable, using linear algebra solution musical instruments used in a Buddhist or Taoist mass according to inverse chronological order
Adjoint equation formula is solved, the adjoint variable of each time step can be obtained.
In a step 330, purpose is intended to establish sensitivity coefficient accounting equation, solves sensitivity coefficient matrix.By to mesh
Scalar functions carry out total differential processing about the expression formula of control variable, compare with functional derivative expression formula, obtain objective function
To the gradient matrix (sensitivity coefficient matrix) of control variable, and solved.
Using the reservoir numerical simulation parameters sensitivity analysis new technology and dress provided by the present invention based on associated model
It sets, the efficiency that reservoir engineer carries out history matching can be greatlyd improve, obtain the fitting result of high quality, hence it is evident that shorten quasi-
The period is closed, and does not need to concentrate on energy on the reservoir physical parameter of complexity early period, reduces personnel cost.
The above, is only part preferred embodiment of the invention, and anyone skilled in the art may benefit
Equivalent technical solution is modified or is revised as with the technical solution of above-mentioned elaboration.Therefore, technology according to the present invention
Any simple modification or substitute equivalents that scheme is carried out, belong to the greatest extent the scope of protection of present invention.
Claims (1)
1. a kind of reservoir numerical simulation parameters sensitivity analysis method, it is characterized in that the following steps are included:
The associated model that adjoint variable calculates variable independently of simulation is established, direct solution gradient equations is avoided；
The coefficient matrix of associated model is constructed, adjoint equation is solved and obtains adjoint variable；
Sensitivity coefficient accounting equation is established, using obtained adjoint variable, solves objective function about model cootrol variable
Sensitivity coefficient matrix carries out sensitivity analysis；
Associated model is constructed by Lagrangian method, and adjoint variable calculates variable independently of the simulation of master mould, is avoided
Direct solution gradient equations；
The coefficient matrix of the associated model is obtained by the solving result of state equation: the coefficient matrix in associated modelFor shape
State equation transposition Jacobian matrix, the Jacobian matrix transposition during being iteratively solved by state equation obtain, without rebuilding；System
Matrix number B is to accumulate term-term matrix with state equation, parses to obtain by the accumulation item derivation of state equation；D is objective function
About the partial derivative of control variable, parse to obtain by the governing equation derivation of well；
In establishing the associated model that adjoint variable calculates variable independently of simulation, adjoint equation is established:
The target of reservoir numerical simulation parameters sensitivity analysis is sensitivity of the calculating target function about control variable change,
That is gradient value of the calculating target function to control variable；Based on adjoint system theory, companion is established by introducing Lagrangian
With functional:
(1)
In formula, m is objective function,It can claim adjoint variable in Three-dimensional Flow；
It is obtained to functional total differential:
(2)
The coefficient matrix of adjoint variable is obtained by carrying out total differential with functional and constraint condition being added, is then obtained with change
Measure the adjoint equation independently of model state variable:
(3)
In formula:=state equation transposition Jacobian matrix；B=and state equation accumulate term-term matrix；D=objective function about
Control the partial derivative of variable.
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| CN106886649A (en) * | 2017-03-01 | 2017-06-23 | 中国海洋石油总公司 | A kind of multielement hot fluid is handled up injection parameter optimization method |
| CN110634534A (en) * | 2018-06-06 | 2019-12-31 | 中国石油化工股份有限公司 | Chemical process parameter sensitivity determination method based on extended Fourier amplitude analysis |
| CN109670195B (en) * | 2018-07-30 | 2020-05-08 | 长江大学 | EnKF oil reservoir auxiliary history fitting method fusing single well sensitivity localization |
| CN109902329B (en) * | 2018-09-21 | 2023-06-02 | 长江大学 | Auxiliary history fitting method, system, storage medium and equipment for oil reservoir simulation |
| CN109726465B (en) * | 2018-12-26 | 2022-07-29 | 电子科技大学 | Three-dimensional non-adhesive low-speed streaming numerical simulation method based on non-structural curved edge grid |
| CN112417737B (en) * | 2020-12-11 | 2022-07-08 | 西南石油大学 | Unconventional oil and gas reservoir flow distribution model parameter sensitivity acquisition method and system |
| CN112580861B (en) * | 2020-12-11 | 2022-11-01 | 西南石油大学 | Control method and system for production optimization problem of unconventional oil and gas reservoir |
| CN115470664B (en) * | 2022-11-15 | 2023-06-27 | 中科数智能源科技(深圳)有限公司 | Crack sensitivity analysis method for fractured reservoir |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101807225A (en) * | 2010-04-07 | 2010-08-18 | 杨勤涛 | Thickened oil numerical reservoir simulation method and device |
| CN103541704A (en) * | 2012-07-11 | 2014-01-29 | 中国石油化工股份有限公司 | Method of improving deep super-thick oil reservoir recovery efficiency |
| CN104239661A (en) * | 2013-06-08 | 2014-12-24 | 中国石油化工股份有限公司 | Large-scale numerical reservoir simulation calculation method |
| CN105298452A (en) * | 2015-10-26 | 2016-02-03 | 中国石油天然气股份有限公司 | Oil reservoir three-dimensional gas injection method and well pattern structure |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010104537A1 (en) * | 2009-03-11 | 2010-09-16 | Exxonmobil Upstream Research Company | Adjoint-based conditioning of process-based geologic models |
-
2016
- 2016-06-15 CN CN201610425340.8A patent/CN106055827B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101807225A (en) * | 2010-04-07 | 2010-08-18 | 杨勤涛 | Thickened oil numerical reservoir simulation method and device |
| CN103541704A (en) * | 2012-07-11 | 2014-01-29 | 中国石油化工股份有限公司 | Method of improving deep super-thick oil reservoir recovery efficiency |
| CN104239661A (en) * | 2013-06-08 | 2014-12-24 | 中国石油化工股份有限公司 | Large-scale numerical reservoir simulation calculation method |
| CN105298452A (en) * | 2015-10-26 | 2016-02-03 | 中国石油天然气股份有限公司 | Oil reservoir three-dimensional gas injection method and well pattern structure |
Non-Patent Citations (1)
| Title |
|---|
| 基于梯度算法的水驱油藏注采优化研究;潜欢欢;《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑》;20111115;第3.2.2节 |
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