CN107291667B - Method and system for determining communication degree between wells - Google Patents
Method and system for determining communication degree between wells Download PDFInfo
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- CN107291667B CN107291667B CN201610203017.6A CN201610203017A CN107291667B CN 107291667 B CN107291667 B CN 107291667B CN 201610203017 A CN201610203017 A CN 201610203017A CN 107291667 B CN107291667 B CN 107291667B
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Abstract
The invention discloses a method for determining the communication degree between wells, which comprises the following steps: determining the connectivity among wells; determining a communication coefficient, namely determining the communication coefficient between the communication wells by establishing a mathematical model and given constraint conditions; an evaluation standard establishing step, namely obtaining an evaluation standard of the communication degree between the communication wells according to the communication coefficient and the distribution range of the statistical samples; and determining the inter-well communication degree, namely determining the inter-well communication degree according to the communication coefficient and the evaluation standard. The method can quickly and accurately obtain the inter-well communication coefficient, so that the inter-well communication degree can be calculated more accurately.
Description
Technical Field
The invention belongs to the technical field of oil reservoir development, and particularly relates to a method and a system for determining the communication degree between wells.
Background
The fracture-cavity type oil reservoir is a main oil reservoir type in northwest of China, and starts to enter a full flooding development stage along with the continuous development, and the main problems to be faced are how to establish an injection-production well pattern and how to adjust the injection-production well pattern after flooding. Aiming at the problems, the research on the communication between wells of the fracture-cavity oil reservoir mainly comprises two aspects: firstly, the communication condition between wells is cleared, namely whether the injection wells and the production wells or even the production wells are communicated or not, and the problem of how to establish an injection well pattern is mainly solved; the other is to know the communication strength between the injection and production wells definitely, so as to solve the problem of water drive adjustment after flooding. At present, the methods mainly adopted by the technology for quantitatively evaluating the communication among wells comprise the following methods.
The basic principle of evaluating the connectivity among wells by the grey correlation degree is as follows: the change of the production of one oil well in the well group can have close correlation or interference with the water injection quantity of a certain surrounding water injection well, the property has uncertainty (namely ash property), and the grey correlation analysis can just solve the similar problem. However, the method has the problem of determining the relevance, many scholars find that the relevance of two variables cannot be accurately reflected by the calculation method of the relevance, and meanwhile, the value of a resolution coefficient is a change interval, and the difference of analysis results is large due to different values.
When the oil reservoir engineering method is used for evaluating the communication degree between wells, a plurality of production dynamic indexes are often adopted, and when evaluation results of different indexes are contradictory, the fuzzy mathematical evaluation method shows the advantages of the method. The method for evaluating the connectivity among wells by fuzzy mathematical evaluation summarizes numerical values of different evaluation indexes by constructing a membership function to obtain a comprehensive evaluation result. However, there are many types of membership functions, and the simplest trapezoidal formula is currently used in oil fields. Whether the trapezoidal equation is suitable for evaluating connectivity remains to be proven. On the other hand, the calculation of the weight also has problems, and the weight determination methods such as the analytic hierarchy process and the like are subjective determination methods depending on the experience of engineers, so that the accuracy is low.
The numerical simulation method inversion interwell connectivity technology is based on static data, such as parameter fields of porosity, permeability, saturation, reservoir thickness and the like of an oil layer, and an oil reservoir geological model is established; then, fitting production histories such as bottom hole pressure, water yield and oil yield of different single wells of the oil reservoir, and verifying a geological model; and finally, calculating and obtaining the communication coefficient of the oil reservoir on the basis of the model, and evaluating the communication degree. However, the numerical simulation method requires a lot of dynamic and static data, and it is very difficult to collect data that all really conforms to the oil reservoir. In addition, the fracture-cavity oil reservoir modeling method has problems, the uncertainty of the model is large, dynamic history fitting is tedious and time-consuming work, and multiple solutions exist in the method. Therefore, the reliability of the method for determining the connectivity among wells by inversion of the numerical simulation method is not high.
Multiple linear regression derives from the idea of injection-production balance, considering that the water injection rate for all wells in a well group is equal to the production fluid plus the bottom water (or side water) invasion rate for all wells. And solving an estimated value of the weight coefficient by adopting a least square method, wherein the estimated value at the moment is the communication degree between the wells. The prior scholars mainly have two characteristics when the inter-well connectivity is calculated by adopting a multiple linear regression method: firstly, applying injection-production balance, and displaying and representing inter-well communication coefficients as weights of liquid production amounts of different production wells; and secondly, solving a linear equation set to obtain a communication coefficient by adopting a least square method (curve fitting and approximation method) and by the minimum sum of squares of errors and zero partial derivative. However, for a large amount of production dynamic data, the application of the least square method to calculate results in a huge data matrix, which increases the difficulty of solution. In addition, the solved communication coefficient is easy to be a negative value, and is not consistent with the physical significance of the actual oil reservoir, and the accuracy is still to be verified.
Disclosure of Invention
In order to solve the problems, the invention provides a method and a system for determining the inter-well communication degree, which are used for rapidly and accurately calculating the inter-well communication coefficient so that the inter-well communication degree is calculated more accurately.
According to an embodiment of the invention, a method for determining the communication degree between wells is provided, which comprises the following steps:
determining the connectivity among wells;
determining a communication coefficient, namely determining the communication coefficient between the communication wells by establishing a mathematical model and given constraint conditions;
an evaluation standard establishing step, namely obtaining an evaluation standard of the communication degree between the communication wells according to the communication coefficient and the distribution range of the statistical samples;
and determining the inter-well communication degree, namely determining the inter-well communication degree according to the communication coefficient and the evaluation standard.
According to an embodiment of the present invention, the communication coefficient determining step further includes:
establishing an injection-production balance mathematical model with constraint conditions based on the condition of one injection and multiple production in the injection-production well group, wherein the mathematical model comprises the communication coefficient;
preliminarily determining a communication coefficient by adopting a Monte Carlo method;
and carrying out normalization processing on the preliminarily determined communication coefficient to obtain a final communication coefficient.
According to an embodiment of the present invention, the step of preliminarily determining the connectivity coefficient using the monte carlo method further comprises:
acquiring a well group communication relation, a maximum fluctuation value of produced fluid of each production well in the well group and actual water injection data in a water injection time period;
a Gaussian distribution function is adopted, the maximum fluctuation value of the produced fluid of each production well in the communicated well group is taken as a constraint condition, and a group of random numbers are generated aiming at each communicated coefficient;
substituting the random number corresponding to each communication coefficient into the mathematical model to calculate the estimated value of the water injection amount;
according to the estimated water injection quantity and the actual water injection quantity data, obtaining the water injection quantity closest to the actual water injection quantity data and a corresponding random number;
and respectively taking the random numbers as the axis values of Gaussian distribution of the corresponding wells, generating a new group of random numbers corresponding to the well communication coefficient, returning to the water injection quantity estimation step until the water injection quantity estimation value is equal to the actual water injection quantity, and determining the communication coefficient.
According to one embodiment of the invention, the mathematical model is:
wherein the content of the first and second substances,
indicating the water injection amount of the ith water injection well; q. q.sj(n) represents the fluid production of the production well surrounding the injection well; beta is a0jExpressing an unbalanced constant, and taking the physical meaning of the water invasion amount of bottom water; beta is aijRepresenting the communication coefficient of the jth production well and the ith water injection well; j represents the number of production wells in the ith injection well group,
the constraint conditions are as follows:
βij∈(wj-d,wj+d)
wherein, wjA dimensionless crest value representing production data for the j-th production well, and d a threshold for allowable variation.
According to an embodiment of the present invention, the evaluation criterion establishing step further comprises:
counting the frequency of occurrence of the communication coefficients of different injection and production well groups and different injection and production periods, and drawing an accumulated frequency distribution map;
respectively reading the communication coefficients corresponding to different accumulation percentages in the accumulation frequency distribution graph;
and obtaining the evaluation standard of the communication degree between wells according to the communication coefficients corresponding to different cumulative percentages.
According to one embodiment of the invention, the inter-well connectivity determining step comprises determining inter-well connectivity from tracer test results.
According to one embodiment of the invention, the interwell connectivity determining step comprises determining interwell connectivity from well production dynamic data, comprising:
acquiring production dynamic data of each production well from a production data table;
judging the connectivity between injection wells and production wells according to the production curve change condition of the production wells during water injection, wherein,
and if the internal pressure and the produced liquid of the production well obviously increase during water injection or the water content of the production well obviously changes, the communication between the injection wells and the production wells is indicated.
According to one embodiment of the invention, a production injection well is considered to be disconnected from a production well if the operating regime changes while the production profile of the production well changes during waterflooding.
According to one embodiment of the invention, the initially determined connectivity coefficients are normalized based on the following equation:
wherein k is the number of water wells, m is the number of oil wells in the ith water injection well group, and betaijAnd expressing the communication coefficient of the j production well and the i water injection well.
According to another aspect of the invention, the inter-well connectivity determining system comprises an inter-well connectivity determining module, a communication module and a communication module, wherein the inter-well connectivity determining module is used for determining the connectivity between wells;
the communication coefficient determining module is used for determining the communication coefficient between the communication wells by establishing a mathematical model and given constraint conditions;
the evaluation standard establishing module is used for acquiring an evaluation standard of the communication degree between the communication wells according to the communication coefficient and the distribution range of the statistical samples;
and the inter-well communication degree determining module is used for determining the inter-well communication degree according to the communication coefficient and the evaluation standard.
The invention has the beneficial effects that:
the invention adopts random point taking near the Gaussian distribution axis value to ensure that the axis value gradually approaches the actual value to obtain the connectivity coefficient, and compared with the general idea of uniformly taking points, the invention accelerates the approaching speed to the actual value; on the other hand, according to the characteristics of actual production dynamic fluctuation, the communication coefficient is constrained, and compared with the least square method, the condition that the communication coefficient is a negative value cannot occur, so that the calculation result is more accurate.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required in the description of the embodiments or the prior art:
FIG. 1 is a flow diagram of a method according to one embodiment of the invention;
FIG. 2 is a schematic flow diagram of a Monte Carlo algorithm according to one embodiment of the invention;
FIG. 3 is a schematic diagram of a cumulative probability distribution according to one embodiment of the invention;
FIG. 4 is a schematic illustration of an INJ-WELL6 voidage replacement response curve according to one embodiment of the present invention;
FIG. 5 is a schematic illustration of a connectivity coefficient cumulative probability distribution according to an embodiment of the present invention; and
FIG. 6 is a graph of water injection splitting number comparison analysis according to one embodiment of the present invention.
Detailed Description
The following detailed description of the embodiments of the present invention will be provided with reference to the drawings and examples, so that how to apply the technical means to solve the technical problems and achieve the technical effects can be fully understood and implemented. It should be noted that, as long as there is no conflict, the embodiments and the features of the embodiments of the present invention may be combined with each other, and the technical solutions formed are within the scope of the present invention.
The invention is based on the injection-production balance principle, and considers the injection well, the production well and the pore canal between the wells in the oil deposit as a complete system, wherein, the injection amount of the injection well can be regarded as the excitation of the system, the liquid production amount of the production well is the response output of the system, and the total output amount of the production well is equal to the total injection amount in the oil deposit plus the water invasion amount of bottom water. The method is based on the analysis of the inter-well communication relation, adopts a multiple linear regression method to establish a mathematical model, adopts Monte Carlo random distribution to calculate the inter-well communication coefficient, and finally evaluates the strength of the communication degree between injection wells and production wells.
Fig. 1 shows a flow chart of a method according to an embodiment of the invention, which is described in detail below with reference to fig. 1.
First, step S110 is an inter-well connectivity determination step. Specifically, in this step, the following two methods are generally used to determine the connectivity between wells. One method is to directly adopt the tracer test result to judge the connectivity between wells aiming at the injection and production well group which is tested by the tracer.
In another method, for an injection-production well group which is not subjected to a tracer test, whether the wells are communicated or not can be judged by comparing whether the production curves of the surrounding production wells are changed or not after water injection. The indexes judged by the method are the data of the flowing pressure, the produced liquid, the produced oil, the water content and the like of the production wells in the injection and production well group, and the data are derived from a production dynamic data table of an oil field. The specific process for determining the connectivity between wells by using the method is as follows.
Production dynamic data for each production well is first obtained from a production data table. The obtained production dynamic data comprises water injection time and water injection quantity of the water injection well, pressure, production fluid, water content and the like of the production well.
And then analyzing the change condition of the production curve of the production well during water injection, and judging the connectivity between the injection and production wells according to the change condition of the production curve. In particular, the internal pressure and the produced liquid of the production well obviously increase during water injection; or the water content of the production well is obviously changed, if the water content is obviously increased, flooding is caused, and if the water content is obviously decreased, the oil displacement effect is caused. The situations are all shown that the injection wells and the production wells are communicated. In addition, it should be noted that, since the change of the working schedule has a great influence on the production curve of the production well, if the production curve of the production well changes during the water injection period and the working schedule (nozzle tip, stroke order, etc.) also changes, the change of the production curve is considered to be caused by the influence of the working schedule itself, and the injection and production wells are not communicated with each other, and therefore, the exclusion should be given.
Next, a step S120 of determining a communication coefficient is performed, and a communication coefficient between the communication wells is determined by establishing a mathematical model and a given constraint condition. Specifically, the connection coefficient determining step further includes the following steps. Firstly, based on the condition of one injection and multiple production in the injection and production well group, an injection and production balance mathematical model with constraint conditions is established, and the mathematical model comprises a communication coefficient. Considering the actual field application, the mathematical model is represented as follows:
wherein the content of the first and second substances,
indicating the water injection amount of the ith water injection well; q. q.sj(n) represents the fluid production of the production well surrounding the injection well; beta is a0jExpressing an unbalanced constant, and taking the physical meaning of the water invasion amount of bottom water; beta is aijRepresenting the communication coefficient of the jth production well and the ith water injection well; j represents the number of production wells in the ith waterflooding well group.
According to the actual situation, the multivariate model needs to be changed within the range with actual physical significance, the multivariate model does not have actual significance when exceeding the range, and the set constraint conditions are as follows:
βij∈(wj-d,wj+d) (2)
wherein, wjThe dimensionless crest value representing the production data for the j-th production well, i.e. (maximum crest value of the liquid production volume of the j-th production well during waterflooding)/(sum of maximum crest values of all production wells within the well group), is reflected as the extent of the j-th production well fluctuation, d represents a permitted variation threshold with a default value of 0.1. The physical meaning is to constrain betaijAnd the variation cannot be too extensive within the range of production data fluctuation.
And then, preliminarily determining the connection coefficient by adopting a Monte Carlo method. The Monte Carlo method is a method for solving the calculation problem by using random numbers, and the main idea is to produce a series of random points in Gaussian distribution, compare the random points with target values respectively to obtain the random points closest to the target values, then use the new random points as the axis points in Gaussian distribution to produce a new group of random points, compare the new group of random points with the target values, and repeat the steps until the random points are equal to the target points.
Applying the above method requires two points to be noted: the method has the advantages that the occurrence probability near the axis points of the Gaussian distribution is the maximum, a new group of random points are generated by taking the random value close to the target value as the average value of the Gaussian distribution each time, the random points are concentrated near the dominant points, and the speed of approaching the target value is accelerated; and secondly, the communication coefficient uses the fluctuation characteristic of the liquid production curve as a constraint to prevent the random value from exceeding the range of the actual physical significance. And (3) solving the connection coefficient by adopting a computer iteration, wherein the specific steps are shown in figure 2.
Firstly, acquiring a well group communication relation, a maximum fluctuation value of produced fluid of each production well in the well group and actual water injection data in a water injection time period. The connectivity of the well groups can be obtained from the injection-production response results (or tracer results), and the production dynamic data and the water injection amount data in the water injection time period can be obtained from the production data table.
Then, a Gaussian distribution function is adopted, the maximum fluctuation value of the produced fluid of each production well in the connected well group is taken as a constraint condition, and a group of random numbers are generated aiming at each connected coefficient. Specifically, a Gaussian distribution function is adopted to carry out on each communication coefficient betaijA group of random numbers are randomly generated, and the maximum fluctuation value of the produced liquid of each production well is used as a constraint when the random numbers are generated, so that the value is not too extensive.
Then, estimates of the water injection amount are calculated in place of the equations (1), respectively. Specifically, a difference value between a water injection estimated value and an actual value is obtained by adopting multivariate linear regression. For example, if the connectivity coefficients are n, each yielding m random values, then m will be calculatednAnd (4) estimating the water injection quantity. In this process, MxN round calculations need to be performed.
Comparison of m respectivelynThe estimated value of the individual water injection amount and the actual water injection amount are obtained, the water injection amount closest to the actual water injection amount is obtained, and the corresponding water injection amountA set of random numbers. If the difference between the estimated value of the water injection amount and the actual value is converged (less than a certain precision), the set of random numbers is the final communication coefficient. Otherwise, selecting the closest water injection estimation value, taking a group of random numbers corresponding to the closest water injection estimation value as the axis values of Gaussian distribution of the corresponding well respectively, generating a group of new random numbers corresponding to the well communication coefficient, and recalculating the water injection estimation value until the water injection estimation value is equal to the actual value.
Finally, as the sum of the communication coefficients between different injection wells and production wells in the well group is 1, the communication coefficients obtained above should be normalized. Specifically, the final connectivity coefficient is obtained after the treatment based on the following formula
And k is the number of the water wells, and m is the number of the oil wells in the ith water injection well group.
And the step S130 of establishing an evaluation standard is carried out, and the evaluation standard of the communication degree between the communication wells is obtained according to the communication coefficient and the distribution range of the statistical samples. Specifically, the frequency of occurrence of the connectivity coefficients of different injection-production well groups and different injection-production periods is counted, and a cumulative frequency distribution map is drawn, as shown in fig. 3. Specifically, the connection coefficients of different injection-production well groups and different injection-production periods calculated in step S120 are used as samples, the frequency of occurrence of different connection coefficients is counted, and a cumulative frequency distribution curve is drawn. And then, respectively reading the communication coefficients corresponding to different accumulation percentages in the accumulation frequency distribution map, and obtaining the evaluation standard of the communication degree between wells according to the communication coefficients corresponding to the different accumulation percentages. For example, through a large number of sample point statistics, the distribution range of the sample points is divided into quarters, the communication coefficients with the cumulative percentages of 25%, 50% and 75% are respectively read on the cumulative frequency distribution curve, the numerical values are a, b and c, at this time, the weak communication is communication coefficient < a, the medium weak communication is communication coefficients (a-b), the medium strong communication is communication coefficients (b-c), and the strong communication is communication coefficient > c, so that the evaluation criterion of the communication degree is obtained.
And finally, a step S140 of determining the communication degree among wells, wherein the communication degree among wells is determined according to the communication coefficient and the evaluation standard. Specifically, the inter-well communication degree can be judged according to the communication coefficient and the evaluation standard.
The present invention will be described below by way of a specific example. The experimental well group is a S1 hole unit-injection-production well group G1 of a certain oil field. The oil reservoir is a special oil reservoir mainly comprising a karst cave and a fracture cave. The holes, the holes and the seams can form various reservoir types according to different modes and scales, the oil field reservoirs have serious heterogeneity, and the condition that the wells are statically communicated and dynamically not communicated often occurs, so that the method of the patent is needed to calculate the communication degree between the wells, find the splitting water amount of the water injection well to each well production well and guide later-stage water injection development and adjustment.
The specific steps of the experiment are as follows:
(1) and reading the water injection time, the water injection quantity and the dynamic production data (liquid production, fluctuation intensity and the like) of the production wells in the well group from the production dynamic data table.
(2) The communication between the injection WELLs and the production WELLs of the G1 WELL group is obtained from tracer test reports, and the water injection WELLs INJ are known to be communicated with WELL1, WELL2, WELL3, WELL4 and WELL 5. Connectivity of low water WELLs could not be obtained due to limitations of tracer testing, and for this purpose injection and production response analysis was used to analyze that production WELL WELL6 undergoes significant changes in pressure, fluid production, and oil production during INJ flooding, as shown in FIG. 4. Furthermore, the working system of the WELL6 is not changed, so that the INJ is communicated with the WELL6, and the communication relation of the whole WELL group is clarified.
(3) And determining the communication degree between injection wells and production wells. And (3) circulating M rounds based on a Monte Carlo method, wherein each round is performed for N times, a group of numbers are randomly selected in each round, the peak value of the liquid production of each production well is used as a constraint, the group of random numbers is used for calculating the difference value between the estimated value and the actual value of the water injection amount, after the N times are finished, the difference values are compared and the minimum value is stored, the calculation of the next round is performed, whether the minimum value of the two rounds is converged or not is compared, if the minimum value is not converged, the group of numbers are respectively used as the average value of Gaussian distribution of the corresponding well, and the average value is substituted into the Gaussian distribution. M rounds can obtain the convergence value of the minimum value and a group of random numbers corresponding to the convergence value.
(4) The set of random numbers is dimensionless using equation (3) to obtain the connectivity coefficient. The communication coefficients of WELL1, WELL2, … …, WELL6 and INJ are respectively 0.07, 0.13, 0.22, 0.25, 0.15 and 0.18.
And (3) experimental result verification:
(1) TK663 well group connectivity comparison
According to the cumulative frequency distribution curve of all the well groups of the oil reservoir, as shown in fig. 5, the communication coefficient is less than 0.1 (corresponding to a cumulative frequency of 25%) for weak communication, 0.1-0.15 (corresponding to a cumulative frequency of 50%) for medium weak, 0.15-0.23 (corresponding to a cumulative frequency of 75%) for medium strong, and greater than 0.23 for strong communication. Table 1 is a comparison table of the communication strength of G1 wells based on monte carlo multiple regression and tracer tests. The experimental results show that the calculation result of the invention is basically consistent with the result of the tracer.
TABLE 1 TK663 well group calculation result comparison table
(2) Comparison of split conditions of water injection amount
The communication coefficient applied to the development of water injection is the water injection splitting number, and fig. 6 is a comparison of the calculation result (b) of the invention and the tracer test result (a), so that the water injection splitting coefficient calculated by the invention is more consistent with the tracer test result, and the water injection splitting ratio is basically consistent in size and sequence. Meanwhile, as the connectivity of a low-water-content production well cannot be tested by a tracer test, the unallocated water injection amount exists, and the method can reversely show the water injection split amount of the well 6. Therefore, the method can comprehensively reflect the real situation of the fracture-cavity oil reservoir and can be applied in practice.
According to another aspect of the invention, the system for determining the degree of the well communication comprises a well communication determining module, a communication coefficient determining module, an evaluation criterion establishing module and a well communication degree determining module.
The inter-well connectivity determining module is used for determining the connectivity among wells; the communication coefficient determining module determines the communication coefficient between the communication wells by establishing a mathematical model and given constraint conditions; the evaluation standard establishing module is used for obtaining an evaluation standard of the communication degree between the communication wells according to the communication coefficient and the distribution range of the statistical samples; and the inter-well communication degree determining module is used for determining the inter-well communication degree according to the communication coefficient and the evaluation standard.
The invention adopts random point taking near the Gaussian distribution axis value to ensure that the axis value gradually approaches the actual value to obtain the connectivity coefficient, and compared with the general idea of uniformly taking points, the invention accelerates the approaching speed to the actual value; on the other hand, according to the characteristics of actual production dynamic fluctuation, the communication coefficient is constrained, and compared with the least square method, the condition that the communication coefficient is a negative value cannot occur, so that the calculation result is more accurate.
Although the embodiments of the present invention have been described above, the above description is only for the convenience of understanding the present invention, and is not intended to limit the present invention. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. A method of determining a degree of communication between wells, comprising:
determining the connectivity among wells;
determining a communication coefficient, namely determining the communication coefficient between the communication wells by establishing a mathematical model and given constraint conditions;
wherein the communication coefficient determining step further comprises:
establishing an injection-production balance mathematical model with constraint conditions based on the condition of one injection and multiple production in an injection-production well group, wherein the mathematical model comprises the communication coefficients:
preliminarily determining a communication coefficient by adopting a Monte Carlo method;
the step of preliminarily determining the connection coefficient by adopting the Monte Carlo method further comprises the following steps:
acquiring a well group communication relation, a maximum fluctuation value of produced fluid of each production well in the well group and actual water injection data in a water injection time period;
a Gaussian distribution function is adopted, the maximum fluctuation value of the produced fluid of each production well in the communicated well group is taken as a constraint condition, and a group of random numbers are generated aiming at each communicated coefficient;
substituting the random number corresponding to each communication coefficient into the mathematical model to calculate the estimated value of the water injection amount;
according to the estimated water injection quantity and the actual water injection quantity data, obtaining the water injection quantity closest to the actual water injection quantity data and a corresponding random number;
respectively taking the random numbers as the axis values of Gaussian distribution of the corresponding wells, generating a new group of random numbers corresponding to the well communication coefficient, returning to the water injection quantity estimation step until the water injection quantity estimation value is equal to the actual water injection quantity, and determining the communication coefficient;
carrying out normalization processing on the preliminarily determined communication coefficient to obtain a final communication coefficient;
an evaluation standard establishing step, namely obtaining an evaluation standard of the communication degree between the communication wells according to the communication coefficient and the distribution range of the statistical samples;
and determining the inter-well communication degree, namely determining the inter-well communication degree according to the communication coefficient and the evaluation standard.
2. The determination method according to claim 1, characterized in that the mathematical model is:
wherein n represents a connectivity coefficient;
indicating the water injection amount of the ith water injection well; q. q.sj(n) represents the fluid production of the production well surrounding the injection well; beta is a0jExpressing an unbalanced constant, and taking the physical meaning of the water invasion amount of bottom water; beta is aijRepresenting the communication coefficient of the jth production well and the ith water injection well; j represents the number of production wells in the ith injection well group,
the constraint conditions are as follows:
βij∈(wj-d,wj+d)
wherein, wjA dimensionless crest value representing production data for the j-th production well, and d a threshold for allowable variation.
3. The determination method according to any one of claims 1 to 2, wherein the evaluation criterion establishing step further comprises:
counting the frequency of occurrence of the communication coefficients of different injection and production well groups and different injection and production periods, and drawing an accumulated frequency distribution map;
respectively reading the communication coefficients corresponding to different accumulation percentages in the accumulation frequency distribution graph;
and obtaining the evaluation standard of the communication degree between wells according to the communication coefficients corresponding to different cumulative percentages.
4. The method of claim 1, wherein the inter-well connectivity determining step comprises determining inter-well connectivity from tracer test results.
5. The method of determining of claim 1, wherein the step of determining interwell connectivity comprises determining interwell connectivity from well production dynamic data comprising:
acquiring production dynamic data of each production well from a production data table;
judging the connectivity between injection wells and production wells according to the production curve change condition of the production wells during water injection, wherein,
and if the internal pressure and the produced liquid of the production well obviously increase during water injection or the water content of the production well obviously changes, the communication between the injection wells and the production wells is indicated.
6. The method of claim 5, wherein the production wells are considered not to be in communication if the operating regime changes while the production profile of the production wells changes during the waterflood.
7. The determination method according to claim 1, characterized in that the initially determined connection coefficient is normalized based on the following expression:
and k is the number of the water wells, m is the number of the oil wells in the ith water injection well group, and the communication coefficient of the jth production well and the ith water injection well is represented.
8. A system for determining the communication degree between wells comprises,
the inter-well connectivity determining module is used for determining the connectivity among wells;
the communication coefficient determining module is used for determining the communication coefficient between the communication wells by establishing a mathematical model and given constraint conditions;
wherein the connectivity coefficient determination module further comprises:
establishing an injection-production balance mathematical model with constraint conditions based on the condition of one injection and multiple production in an injection-production well group, wherein the mathematical model comprises the communication coefficients:
preliminarily determining a communication coefficient by adopting a Monte Carlo method;
the step of preliminarily determining the connection coefficient by adopting the Monte Carlo method further comprises the following steps:
acquiring a well group communication relation, a maximum fluctuation value of produced fluid of each production well in the well group and actual water injection data in a water injection time period;
a Gaussian distribution function is adopted, the maximum fluctuation value of the produced fluid of each production well in the communicated well group is taken as a constraint condition, and a group of random numbers are generated aiming at each communicated coefficient;
substituting the random number corresponding to each communication coefficient into the mathematical model to calculate the estimated value of the water injection amount;
according to the estimated water injection quantity and the actual water injection quantity data, obtaining the water injection quantity closest to the actual water injection quantity data and a corresponding random number;
respectively taking the random numbers as the axis values of Gaussian distribution of the corresponding wells, generating a new group of random numbers corresponding to the well communication coefficient, returning to the water injection quantity estimation step until the water injection quantity estimation value is equal to the actual water injection quantity, and determining the communication coefficient;
carrying out normalization processing on the preliminarily determined communication coefficient to obtain a final communication coefficient;
the evaluation standard establishing module is used for acquiring an evaluation standard of the communication degree between the communication wells according to the communication coefficient and the distribution range of the statistical samples;
and the inter-well communication degree determining module is used for determining the inter-well communication degree according to the communication coefficient and the evaluation standard.
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| CN110410065B (en) * | 2019-06-24 | 2022-05-03 | 中国石油化工股份有限公司 | Input parameter analysis method and device for dynamic connectivity model among multiple wells |
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