CN109816182B - Progressive splitting optimization method for injection and production dynamic regulation and control of water-flooding oil reservoir - Google Patents
Progressive splitting optimization method for injection and production dynamic regulation and control of water-flooding oil reservoir Download PDFInfo
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Abstract
The invention discloses a progressive splitting optimization method of a water-flooding oil reservoir injection and production dynamic regulation scheme, which comprises the following steps: firstly, determining the quantity of oil-water wells to be optimized, the total production time, the initial working system of each oil-water well and constraint conditions; setting the splitting level number, splitting factors and initial regulation time step number of each oil-water well, and constructing the injection and production optimization problem under the current splitting level number by initial solution of each oil-water well; and solving the injection and production optimization problem under the current splitting grade number according to the selected optimization algorithm and the set termination condition of the step-by-step splitting optimization method, and obtaining the regulation time step number and the step length of each oil-water well under the current splitting grade number and the optimal working system of each oil-water well in each regulation time step. Compared with the prior art, the invention can determine the optimal working system of each oil-water well at each regulation time step while determining the optimal regulation time step.
Description
Technical Field
The invention belongs to the field of oil and gas field development, and particularly relates to a progressive splitting optimization method for dynamic regulation and control of water-drive reservoir injection and production.
Background
The water flooding is widely applied as one of means for improving the oil reservoir recovery ratio. In the water flooding process, if the oil-water well keeps a fixed working system for a long time, an dominant seepage channel is easy to form, so that the area outside the dominant seepage channel is poor in water injection effect, and the development effect is influenced. The dynamic regulation and control of the water-flooding oil reservoir injection and production refers to dynamic regulation of the working system of each oil-water well in the oil reservoir development process, and the working system of each oil-water well can be reset at intervals to enable liquid flow to be turned and flow lines to be redistributed, so that a fixed water flow channel can be broken easily, larger sweep is formed, and further the development effect is improved.
The optimal injection and production dynamic regulation scheme is determined by determining an optimal regulation time step on the basis of fully considering the heterogeneity of geological parameters of a reservoir, the mutual interference among oil-water wells, the dynamic characteristics of oil-water flow in the reservoir and the like, and simultaneously determining the working system of each oil-water well in each regulation time step. The conventional injection and production optimization method combines the oil reservoir numerical simulation technology and the optimization correlation theory, can only optimize the working system of each oil-water well under the condition of a given regulation time step, and cannot optimize the regulation time step. In addition, because of the large number of optimization variables of the injection and production dynamic regulation and optimization problem, the conventional injection and production optimization method faces the problems of huge calculation amount and easy sinking into local optimal solution even if only the working system of each oil-water well is optimized.
Disclosure of Invention
The invention aims to provide a step-by-step split optimization method for dynamically regulating and controlling the injection and production of a water-flooding oil reservoir, which combines an oil reservoir numerical simulation technology and an optimization theory, simultaneously determines an optimal regulating time step and an optimal working system of each oil-water well on each regulating time step, realizes scientific, accurate and quick optimal design of the injection and production dynamic regulating and controlling scheme of the water-flooding oil reservoir, and is beneficial to further improving the oil reservoir recovery ratio.
In order to achieve the above object, the present invention adopts the following scheme:
a progressive splitting optimization method of a water-flooding reservoir injection and production dynamic regulation scheme comprises the following steps:
step 1: collecting and arranging data, and determining the number of oil-water wells to be optimized, the total production time, the initial working system of each oil-water well and constraint conditions;
step 2: setting the splitting level number, the splitting factor and the initial regulation time step number of each oil-water well, and constructing the injection and production optimization problem under the current splitting level number;
step 3: selecting an optimization algorithm, setting a termination condition of a step-by-step splitting optimization method, and solving an injection and production optimization problem under the current splitting grade number by using the selected optimization algorithm to obtain the regulation time step number and step length of each oil-water well under the current splitting grade number and the optimal working system of each oil-water well under each regulation time step;
step 4: judging whether the termination condition of the step-by-step splitting optimization method in the step 3 is met, if so, terminating the step-by-step splitting optimization method, wherein the regulation time step corresponding to the current splitting level is the optimal regulation time step, and the optimal solution of the injection and production optimization problem of the current splitting level is the optimal working system; if not, continuing the step 5;
step 5: resetting the split grading number, equally dividing each current regulation time step of each well according to the split factor, taking the optimal solution of the injection and production optimization problem of the previous split grading number as the initial solution of the injection and production optimization problem of the current split grading number, and constructing the injection and production optimization problem of the current split grading number; and then returns to step 3.
Further, in the step 1, the number of the oil-water wells to be optimized is m, the total production time is T, and the initial working system of each oil-water well is
And constraint is +.>
Where i=1, 2, …, m,
representing the initial working system of the ith well; />
Representing the lower limit of the working system of the ith well; />
Representing the upper limit of the working system of the ith well;
setting the splitting number in step 2 to be L, the splitting factor to be S and the initial regulation time step number of each well to be N 0 Taking the initial working system of each oil-water well as the initial solution
Wherein L is an integer greater than or equal to 0, S is an integer greater than 0，N 0 Is an integer > 0;
represents the initial working regime of the ith well at the jth control time step at 0 split level, here +.>
The injection and production optimization problem constructed under the current split grading number is as follows:
wherein, 
and->
Representing the lower and upper limits, respectively, of the working regime of the ith well at the jth conditioning time step at a split level of 0, where +.>
NPV(Q 0 ) Is an objective function; argmax is the find maximum operator;
the termination condition of the stepwise split optimization method described in step 3 is (NPV (Q) L * )-NPV(Q L-1 * ))/NPV(Q L -1 * ) Sigma is less than or equal to sigma, wherein NPV (Q L * ) For the optimum value at the current split level, NPV (Q L-1 * ) The sigma is more than or equal to 0 and less than or equal to 0.3, which is the optimal value of the previous splitting grading number;
alternatively, termination conditions of the progressive split optimization methodFEVAL is smaller than or equal to FEVAL for the upper limit value of the number of times of evaluation of the objective function max Wherein FEVAL is the number of objective function evaluations, FEVAL max For the upper limit value of the number of times of objective function evaluation, FEVAL is not less than 100 max ≤100000；；
The regulation time step number N of each oil-water well under the current splitting grading number L ＝N 0 S L Step size DeltaT L ＝T/N L Solving the injection and production optimization problem under the current split grading number by using a selected optimization algorithm to obtain the optimal solution of each oil-water well at each regulation time step
Wherein->
Representing the optimal working system of the ith well in the jth regulation time step in the L level;
the number of splitting stages reset in step 5 is L, and the number of splitting stages L is set by adding 1 to the previous number of splitting stages, and equally dividing each current time step of each well according to splitting factors, specifically including:
regulation time step number N under current cleavage grade number L L ＝N 0 S L ；
The regulation time step delta T of each regulation time step under the current cleavage grade number L L ＝T/N L ；
Setting the optimal solution of the injection and production optimization problem under the previous split level L-1 as an initial working system under the current split level L, wherein the used formula is as follows:
the constraint condition of the injection and production optimization problem of the previous split level L-1 is expanded into the constraint condition of the current split level L, and the use formula is as follows:
the injection and production optimization problem under the current split grading number is constructed as follows:
wherein, 
Returning to the step 3.
Furthermore, the initial working system of each oil-water well in the step 1 is daily liquid production or production pressure.
Further, in step 2, l= 0,S =2, n 0 =1. The values of the three parameters are generally given according to the actual conditions of the oil field (such as the number of oil-water wells to be optimized, the optimized speed/precision requirements and the like).
Further, the optimization algorithm in the step 3 is any one of a genetic algorithm, a generalized pattern search algorithm and a particle swarm algorithm.
Compared with the prior art, the invention has the following beneficial effects:
1. the optimal working system of each oil-water well at each regulation time step can be determined while the optimal regulation time step is determined;
2. the fine regulation and control optimization problems with a plurality of optimization variables are converted into a series of regulation and control optimization problems with a plurality of optimization variables, the number of the regulation and control optimization problems is gradually changed from small to large, and the optimal solution with the smaller optimization variables is sequentially used as the initial solution of the problem with the larger optimization variables, so that the optimizing efficiency can be remarkably improved, and the problem of sinking into the local optimal solution is avoided.
Drawings
Fig. 1 shows the optimal working system of each well when the splitting level is l=0;
in the figure: 1. 1 st well; 2. and 2 nd well.
Fig. 2 shows the optimal working system of each well when the splitting level is l=1;
in the figure: 1. 1 st well; 2. and 2 nd well.
Fig. 3 shows the optimal working system of each well when the splitting level is l=2;
in the figure: 1. 1 st well; 2. and 2 nd well.
Fig. 4 shows the optimal working system of each well when the splitting level is l=3;
in the figure: 1. 1 st well; 2. and 2 nd well.
Detailed Description
The foregoing and other objects, features and advantages of the invention will be apparent from the following more particular description of the invention, as illustrated in the accompanying drawings in which:
step 101: collecting and arranging data of the embodiment blocks, wherein for the embodiment, the number of oil wells to be optimized is 2, and well names are PRO-01 and PRO-02 respectively; the total production time of the embodiment block t=720d; the initial working system of PRO-01 is the liquid production speed
The constraint is that q1 is more than or equal to 0 0 ≤40m 3 The lower limit of the liquid production speed of the/d, i.e. PRO-01 well is 0m 3 And/d, upper limit of 40m 3 /d; the initial working regime of PRO-02 is the rate of liquid production +.>
The constraint condition is that
Namely the lower limit of the liquid production speed of the PRO-02 well is 0m 3 And/d, the upper limit is 80m 3 /d。
Step 201: setting the splitting level L=0, splitting factor S=2, and initial regulating time step number N of each well 0 The termination condition of the progressive split optimization method is that the optimum value difference between the two stages is less than 10%.
Step 202: calculating the regulation time step number N of each well under the current splitting grade number L L . Calculated using the following formula:
N L ＝N 0 S L
for this embodiment, when the front split grading number l=0, N L ＝1×2 0 ＝1。
Step 203: calculating each regulation time step delta T of each well under the current splitting grade number L L . Calculated using the following formula:
ΔT L ＝T/N L
for this embodiment, when the front split step number l=0, Δt L ＝720/1＝720d。
Step 204: the initial working system of each well under the current splitting grade number L is set as follows:
wherein m is the number of oil-water wells.
For this embodiment, the number of oil wells m=2, and the current time step N is adjusted when the current split step l=0 L =1, therefore, at this time
Step 205: the working system constraint conditions of each well under the current splitting grade number L are set as follows:
wherein, 
for this embodiment, when the front split grading number l=0, the constraint is
Step 206: constructing an injection and production optimization problem under the current splitting grading number L, wherein the variable to be optimized is a working system Q of each well under the current splitting grading number L L The initial value is the initial working system of each well under the current splitting grade number L
The constraint condition is that
The optimization objective function is maximized for producing a net present value NPV. Specifically, the optimization problem can be expressed as follows:
step 301: selecting a proper optimization algorithm, setting an optimization algorithm termination condition, and solving the injection and production optimization problem under the current split grading number by using the selected optimization algorithm.
For the present embodiment, when the current split level number l=0, the generalized pattern search algorithm GPS is selected as the solving algorithm, and the termination condition of the optimizing algorithm is set to the maximum solution evaluation number feval=500.
Step 302: and solving the injection and production optimization problem under the current split grading number by using the selected optimization algorithm to obtain the optimal working system of each oil-water well at each regulation time step under the current regulation time step number.
For this embodiment, when the front split grading number l=0, the solution results in
At this time, the corresponding optimal production net present value NPV * L ＝5.3×10 6 Dollars, the operating regime curve for each oil and water well is shown in figure 1.
Step 401: judging whether the termination condition of the step-by-step splitting optimization method is met.
For this example, the net present value NPV is optimally produced at the current split level L * L ＝5.3×10 6 Dollars, the previous split level L-1 was absent, believing NPV * L-1 =0 dollars. The optimal value difference between the two stages is
Equal to infinity, and does not meet the termination condition of the progressive splitting optimization method.
Step 402: if the termination condition of the step-by-step splitting optimization method is not satisfied, step 501 is entered; otherwise, step 403 is entered.
Step 403: the optimal working system corresponding to the current splitting grading number L is the optimal working system of the target block, and the corresponding regulating time step is the optimal regulating time step. And (5) ending the operation.
Step 501: the split level number l=l+1 is set.
For this embodiment, the current split level number l=1 at this time.
Step 502: each of the control time steps for each well was equally divided into S.
For this embodiment, the split factor s=2.
Step 503: calculating the regulation time step number N of each well under the current splitting grade number L L . Calculated using the following formula:
N L ＝N 0 S L
for this embodiment, when the front split level number l=1, N L ＝1×2 1 ＝2。
Step 504: calculating each regulation time step delta T of each well under the current splitting grade number L L . Calculated using the following formula:
ΔT L ＝T/N L
for this embodiment, when the front split level number l=1, Δt L ＝720/2＝360d。
Step 505: setting the optimal solution of the injection and production optimization problem of the previous split level L-1 as an initial working system under the current split level L, and using the following formula:
the initial working schedule at the current split level number L is thus expressed as follows:
wherein m is the number of oil-water wells.
For the embodiment, the number of oil-water wells is m=2, and when the current splitting level is l=1, the current time step number N is adjusted L =2, at this time
Step 506: the constraint condition of the injection and production optimization problem of the previous split level L-1 is expanded into the constraint condition of the current split level L, and the use formula is as follows:
the working schedule constraint conditions of each well under the current splitting grade number L are obtained as follows:
wherein, 
for this embodiment, when the front split level number l=1, the constraint is
Step 507: constructing an injection and production optimization problem under the current splitting grading number L, wherein the variable to be optimized is a working system Q of each well under the current splitting grading number L L The initial value is the initial working system of each well under the current splitting grade number L
The constraint condition is that
The optimization objective function is maximized for producing a net present value NPV. Specifically, the optimization problem can be expressed as follows:
step 508: returning to step 301.
For this embodiment, the iterative computation is sequentially looped according to the above steps, so as to obtain:
when the splitting level L=1, the time step number N of each well is regulated 1 =2, each well modulation time step Δt 1 =360 d, optimal working regime
As shown in FIG. 2, the net present value NPV is optimally produced * 1 ＝10.3×10 6 Dollars. At this time, the optimal value difference between the two stages is +.>
If the termination condition is not met, continuing circulation;
when the splitting grade number L=2, the time step number N of each well is regulated 2 =4, each well modulation time step Δt 2 =180d, optimal working regime
As shown in FIG. 3, the net present value NPV is optimally produced * 2 ＝12.3×10 6 Dollars. At this time, the optimal value difference between the two stages is +.>
If the termination condition is not met, continuing circulation;
when the splitting level L=3, the time step number N of each well is regulated 3 =8, each well modulation time step Δt 3 =90d, optimal working regime
As shown in FIG. 4, the net present value NPV is optimally produced * 3 ＝12.5×10 6 Dollars. At this time, the optimal value difference between the two stages is +.>
And (5) meeting the termination condition, and ending the calculation.
Claims (4)
1. A progressive splitting optimization method of a water-flooding reservoir injection and production dynamic regulation scheme is characterized by comprising the following steps of: the method comprises the following steps:
step 1: collecting and arranging data, and determining the number of oil-water wells to be optimized, the total production time, the initial working system of each oil-water well and constraint conditions;
step 2: setting the splitting level number, the splitting factor and the initial regulation time step number of each oil-water well, and constructing the injection and production optimization problem under the current splitting level number;
step 3: selecting an optimization algorithm, setting a termination condition of a step-by-step splitting optimization method, and solving an injection and production optimization problem under the current splitting grade number by using the selected optimization algorithm to obtain the regulation time step number and step length of each oil-water well under the current splitting grade number and the optimal working system of each oil-water well under each regulation time step;
step 4: judging whether the termination condition of the step-by-step splitting optimization method in the step 3 is met, if so, terminating the step-by-step splitting optimization method, wherein the regulation time step corresponding to the current splitting level is the optimal regulation time step, and the optimal solution of the injection and production optimization problem of the current splitting level is the optimal working system; if not, continuing the step 5;
step 5: resetting the split grading number, equally dividing each current regulation time step of each well according to the split factor, taking the optimal solution of the injection and production optimization problem of the previous split grading number as the initial solution of the injection and production optimization problem of the current split grading number, and constructing the injection and production optimization problem of the current split grading number; then returning to the step 3;
the number of the oil-water wells to be optimized in the step 1 is m, the total production time is T, and the initial working system of each oil-water well is
And constraint is +.>
Where i=1, 2, …, m,
representing the initial working system of the ith well; />
Representing the lower limit of the working system of the ith well; />
Representing the upper limit of the working system of the ith well;
setting the splitting number in step 2 to be L, the splitting factor to be S and the initial regulation time step number of each well to be N 0 Taking the initial working system of each oil-water well as the initial solution
Wherein, l is an integer greater than or equal to 0, S is an integer greater than 0, N 0 Is an integer > 0;
represents the initial working regime of the ith well at the jth control time step at 0 split level, here +.>
i＝1，2，…，m，j＝1，2，…，N 0 ；
The injection and production optimization problem constructed under the current split grading number is as follows:
wherein, 
and->
Representing the lower and upper limits, respectively, of the working regime of the ith well at the jth conditioning time step at a split level of 0, where +.>
NPV(Q 0 ) Is an objective function; argmax is the find maximum operator;
the termination condition of the stepwise split optimization method described in step 3 is (NPV (Q) L *)-NPV(Q L-1 *))/NPV(Q L-1 * ) Sigma is less than or equal to sigma, wherein NPV (Q L * ) For the current splitOptimum value in the series, NPV (Q L-1 * ) The sigma is more than or equal to 0 and less than or equal to 0.3, which is the optimal value of the previous splitting grading number;
or, the termination condition of the step-by-step split optimization method is that the upper limit value FEVAL of the evaluation times of the objective function is less than or equal to FEVAL max Wherein FEVAL is the number of objective function evaluations, FEVAL max For the upper limit value of the number of times of objective function evaluation, FEVAL is not less than 100 max ≤100000；
The regulation time step number N of each oil-water well under the current splitting grading number L ＝N 0 S L Step size DeltaT L ＝T/N L Solving the injection and production optimization problem under the current split grading number by using a selected optimization algorithm to obtain the optimal solution of each oil-water well at each regulation time step
Wherein->
Representing the optimal working system of the ith well in the jth regulation time step in the L level;
the number of splitting stages reset in step 5 is L, and the number of splitting stages L is set by adding 1 to the previous number of splitting stages, and equally dividing each current time step of each well according to splitting factors, specifically including:
regulation time step number N under current cleavage grade number L L ＝N 0 S L ；
The regulation time step delta T of each regulation time step under the current cleavage grade number L L ＝T/N L ；
Setting the optimal solution of the injection and production optimization problem under the previous split level L-1 as an initial working system under the current split level L, wherein the used formula is as follows:
the constraint condition of the injection and production optimization problem of the previous split level L-1 is expanded into the constraint condition of the current split level L, and the use formula is as follows:
the injection and production optimization problem under the current split grading number is constructed as follows:
wherein,
Returning to the step 3.
2. The progressive split optimization method of the water-flooding oil reservoir injection and production dynamic regulation scheme of claim 1, wherein the method comprises the following steps of: and (3) the initial working system of each oil-water well in the step (1) is daily liquid yield or production pressure.
3. The progressive split optimization method of the water-flooding oil reservoir injection and production dynamic regulation scheme of claim 1, wherein the method comprises the following steps of: in step 2, l= 0,S =2, n 0 ＝1。
4. The progressive split optimization method of the water-flooding oil reservoir injection and production dynamic regulation scheme of claim 1, wherein the method comprises the following steps of: the optimization algorithm in the step 3 is any one of a genetic algorithm, a generalized pattern search algorithm and a particle swarm algorithm.
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| CN107829718A (en) * | 2017-02-10 | 2018-03-23 | 中国石油化工股份有限公司 | Oil reservoir well pattern and injection-production program Optimization Design based on balanced water drive theory |
| CN108868712A (en) * | 2017-12-07 | 2018-11-23 | 长江大学 | A kind of oil reservoir development production optimization method and system based on connectivity method |
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| CN107829718A (en) * | 2017-02-10 | 2018-03-23 | 中国石油化工股份有限公司 | Oil reservoir well pattern and injection-production program Optimization Design based on balanced water drive theory |
| CN108868712A (en) * | 2017-12-07 | 2018-11-23 | 长江大学 | A kind of oil reservoir development production optimization method and system based on connectivity method |
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