CN106802986B - A kind of viscous crude bottom and edge water takes turns CO2 more and handles up evaluation method - Google Patents
A kind of viscous crude bottom and edge water takes turns CO2 more and handles up evaluation method Download PDFInfo
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Abstract
The present invention provides a kind of viscous crude bottom and edge water and takes turns CO more2The evaluation method handled up.The evaluation method are as follows: the actual parameter of the practical each factor of oil reservoir of measurement establishes reservoir model on this basis, and simulation, which obtains handling up exploiting oil production and not handling up, exploits oil production, obtains oil increment of handling up；With oil increment of handling up for evaluation affiliated partner, it calculates the amendment weight of each factor and establishes degree of membership calculation method, the evaluations matrix of modeling scheme and practical solution is obtained, in conjunction with the amendment weight of each factor, calculates the average value of the comprehensive score of each modeling scheme and all factors of practical solutionAnd CjAnd it sorts；IfThen evaluation result is preferable；IfThen evaluation result is poor.The present invention is able to solve the infull bring weight difficulty assignment of in-situ data, evaluations matrix difficulty calculates, evaluation boundary lack according to, evaluation result is unreasonable the problems such as, to instructing viscous crude bottom and edge water to take turns CO more2It handles up and carries out rational evaluation and be of great significance.
Description
Technical Field
The invention belongs to thickened oil CO2The technical field of huff and puff effect evaluation relates to a viscous crude edge and bottom water reservoir multi-wheel CO2A throughput evaluation method.
Background
CO of thickened oil2The huff and puff technology is a production adjustment measure for improving the final recovery ratio of crude oil in a heavy oil reservoir, and the huff and puff technology becomes an effective method for solving the problem of rapid water rise in the development process of a common heavy oil reservoir, particularly a bottom water heavy oil reservoir due to the advantages of short implementation time, quick effect, capability of controlling water, no damage to stratum, no pollution and the like. Thus, CO2The throughput effect evaluation method becomes a problem to be solved by the technology.
In the conventional effect evaluation method, a fuzzy comprehensive evaluation method is most commonly adopted, because the geological conditions and development measures of all wells are different, and the development effect of a single well in the whole oil reservoir can be more objectively reflected by establishing the membership relation between throughput oil increment and all influence factors. However, in the actual evaluation process, the data is often incomplete in field data, or the number of evaluation wells is small, so that the establishment of the weight and membership degree of the influencing factors is often lack of data support, and the evaluation result is unreasonable, and therefore, a new evaluation method needs to be adopted.
Disclosure of Invention
Aiming at the problems of difficult weight assignment, difficult evaluation matrix calculation, unreasonable evaluation result and the like caused by incomplete field data, the invention aims to provide a viscous oil bottom-edge water reservoir multi-wheel CO2The throughput evaluation method can provide reasonable evaluation limits, so that the unreasonable problems can be solved.
The purpose of the invention is realized by the following technical scheme:
the invention provides a thickened oilEdge-bottom water reservoir multi-wheel CO2The evaluation method of throughput comprises the following steps:
measuring actual parameters of factors of an actual oil reservoir, establishing an oil reservoir model based on the actual parameters, and simulating to obtain throughput oil production and non-throughput oil production to obtain throughput oil production; oil yield obtained by stimulation of huff and puff production-oil yield expected by non-huff and puff production is huff and puff.
Step two, taking throughput oil increment as an evaluation correlation object, and calculating correction weights of all factors;
establishing a calculation method of membership of each factor by means of an oil reservoir numerical simulation technology to respectively obtain evaluation matrixes of a simulation scheme and an actual scheme;
step four, calculating the average value of the comprehensive scores of all the factors of each simulation scheme according to the evaluation matrix of the simulation scheme and the correction weight of each factor
Step five, calculating the comprehensive score C of all factors of the actual scheme according to the evaluation matrix of the actual scheme and the correction weight of each factorjAnd sorting;
step six, comparingAnd CjGiving an evaluation conclusion; if it isThe evaluation result is better; if it isThe evaluation result is poor.
In the above evaluation method, the throughput increasing amount is an increase of the oil yield of the numerical simulation throughput plan with respect to the oil yield of the numerical simulation non-throughput plan. When the throughput oil increasing amount is predicted specifically, two schemes of throughput mining and non-throughput mining need to be simulated respectively, and the oil yield obtained by the throughput mining simulation-the oil yield obtained by the non-throughput mining simulation is the throughput oil increasing amount.
In the evaluation method, the membership degree belongs to a concept in a fuzzy evaluation function, and the fuzzy comprehensive evaluation is a very effective multi-factor decision method for comprehensively evaluating objects influenced by various factors. If there is a number A (x) e 0, 1 corresponding to any element x in the domain of interest (scope of study) U, then A is called the fuzzy set on U, and A (x) is called the membership of x to A. When x varies among U, A (x) is a function, called the membership function of A. The closer to 1 the degree of membership A (x) is, the higher the degree to which x belongs to A, and the closer to 0A (x) is, the lower the degree to which x belongs to A. And (3) representing the degree of the x belonging to the A by using a membership function A (x) which takes the value in the interval 0, 1.
In the above evaluation method, the correction weight of each factor is preferably calculated by using formula (I):
wherein, aiEmpirical weight for factor i; a. theiA correction weight for the ith factor; 1, 2, … …, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data.
In the above evaluation method, preferably, the step of establishing a membership degree calculation method for each factor by using an oil reservoir numerical simulation technique to obtain the evaluation matrix of the simulation scheme and the evaluation matrix of the actual scheme respectively comprises:
designing a reasonable parameter variation range for each factor according to the measured actual parameters of each factor of the actual oil reservoir (namely, designing according to the parameter distribution range of each factor in the actual condition of the oil field and properly expanding, wherein the expansion ratio is generally +/-20%);
predicting the corresponding throughput oil increment when each factor parameter changes by means of an oil reservoir numerical simulation technology;
establishing a functional relation between each factor and membership degree according to the throughput oil increasing amount;
obtaining an evaluation matrix of the simulation scheme according to the membership degree corresponding to each factor;
and calculating the membership corresponding to each factor value of the actual scheme according to the established membership calculation method to obtain an actual scheme evaluation matrix.
In the evaluation method, the numerical reservoir simulation technology is a conventional method in oil and gas field development and production prediction research, and is a method for establishing an oil reservoir model and simulating oil field exploitation by means of numerical simulation professional software such as ECLIPSE or CMG and the like based on actual oil reservoir characteristic parameters so as to predict oil reservoir recovery and develop dynamic data.
In the above evaluation method, preferably, the factors include a plurality of factors selected from a group consisting of a position of the interlayer, a deposition rhythm, a water content in production, a length of a water outlet section, a position of a horizontal section, a distance of the parallel wells, a throughput round, a formation dip angle, an effective thickness of an oil layer, formation heterogeneity, a heterogeneous degree of the water outlet section, throughput time, a periodic gas injection amount, a gas injection speed, a soaking time, a liquid production speed after production and a liquid production speed of the parallel wells.
In the above evaluation method, preferably, the functional relationship between each factor and the membership degree is as follows:
obtaining the membership y corresponding to the interlayer position by using the formula (1)1a、y1bAnd y1c：
(Note: y)1a0 (no interlayer, water content in production 0.28) means that when water in production is 0.28 and no interlayer, the degree of membership corresponding to the position of the interlayer is 0; other relationships are similarly meant. )
Obtaining the membership y corresponding to the deposition rhythm by using the formula (2)2a、y2bAnd y2c：
Obtaining the membership y corresponding to the water content of the production by using the formula (3)3a、y3bAnd y3c：
Wherein f isw0Contains water for production;
the membership y corresponding to the length of the water outlet section is obtained by the formula (4)4a、y4bAnd y4c：
The membership y corresponding to the position of the water outlet section is obtained by the formula (5)5a、y5bAnd y5c：
Wherein, the point A is the toe end of the horizontal well, and the point B is the heel end of the horizontal well;
obtaining the membership y corresponding to the position of the horizontal section by using the formula (6)6a、y6bAnd y6c：
Obtaining the membership y corresponding to the parallel well distance by using the formula (7)7a、y7bAnd y7c：
Wherein: "apart" means the vertical distance between two adjacent parallel horizontal wells;
obtaining membership y corresponding to the throughput round by using the formula (8)8：
Calculating the corresponding membership y of the formation dip angle by using the formula (9)9a、y9bAnd y9c：
Wherein θ is the formation dip angle, °;
calculating the corresponding membership y of the effective thickness of the oil layer by using the formula (10)10a、y10bAnd y10c：
Wherein h is the effective thickness of the oil layer, m;
by using(11) Calculating the degree of membership y corresponding to the stratigraphic heterogeneity11a、y11bAnd y11c：
Wherein, VkIs Lorentzian coefficient used for representing the formation heterogeneity;
calculating the membership y corresponding to the heterogeneous degree of the water outlet section by using the formula (12)12a、y12bAnd y12c：
Wherein, KvThe permeability is extremely poor and is used for expressing the heterogeneous degree of the water outlet section;
calculating membership y corresponding to the timing of throughput by using equation (13)13a、y13bAnd y13c：
Wherein f is the timing of throughput;
calculating membership y corresponding to periodic gas injection quantity by using formula (14)14：
y14＝3.3E-06Qig-0.333 formula (14)
Wherein Q isigFor periodic gas injection, sm3；
Calculating the membership y corresponding to the gas injection speed by using the formula (15)15a、y15bAnd y15c：
Wherein v isigAs the rate of gas injection, sm3/d；
Calculating the membership y corresponding to the soaking time by using the formula (16)16a、y16bAnd y16c：
Wherein t is the soaking time, d;
calculating the membership y corresponding to the liquid extraction speed after well production by using the formula (17)17a、y17bAnd y17c：
Wherein v islTo produce the liquid velocity after well opening, rm3/d；
Calculating the membership y corresponding to the liquid extraction speed of the parallel well by using the formula (18)18a、y18bAnd y18c：
Wherein q islFor the fluid production rate of the parallel well, rm3/d。
In the above evaluation method, preferably, the step of calculating an average value (as an evaluation limit) of the composite scores of all the factors of each simulation scenario based on the simulation scenario evaluation matrix and the correction weights of each factor includes:
firstly, the calculated correction weights of all factors are combined into a correction weightVector, calculating the product of the correction weight vector and the evaluation matrix of the simulation scheme to obtain the score vector of the simulation scheme; calculating the comprehensive score c of all the factors of the simulation scheme by using the formula (II)j：
Wherein A isiA correction weight for the ith factor; 1, 2, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data; bjiThe membership degree corresponding to the ith factor of the jth simulation scheme; j 1, 2.... m; m is the total number of simulation schemes; c. CjThe composite score of all factors for the jth simulation scenario;
the average of the composite scores for all the factors for each simulation protocol was then calculated using equation (III)Reference values as evaluation limits:
wherein,the average value of the comprehensive scores of all the factors of each simulation scheme; c. CjThe composite score of all factors for the jth simulation scenario; j is 1, 2, … …, m; and m is the total number of simulation schemes.
In the above evaluation method, preferably, the step of calculating and ranking the composite scores of all the factors of the actual solution according to the actual solution evaluation matrix and the correction weights of the factors includes:
firstly, the calculated correction weight of each factor is formed into a correction weight vector, and then the vector is countedCalculating the product of the correction weight vector and the actual scheme evaluation matrix to obtain a score vector of the actual scheme; calculating the comprehensive score C of all factors of the actual scheme by using the formula (IV)j：
Wherein A isiA correction weight for the ith factor; 1, 2, … …, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data; b isjiThe membership degree corresponding to the factor of the ith item of the jth practical scheme; j ═ 1, 2, … …, M; m is the total number of actual schemes; cjThe scores are integrated for all the factors of the jth actual scheme;
then, the score C is integrated for all factors of the actual schemejThe sizes are sorted.
The invention provides a viscous oil edge and bottom water reservoir multi-wheel CO2The throughput evaluation method comprises the steps of firstly, realizing weight correction under the condition of incomplete data through a numerical splitting method; secondly, establishing a membership calculation method through an exhaustion method by means of an oil reservoir numerical simulation technology to obtain an evaluation matrix based on throughput oil increment; then, evaluating the mean value according to an exhaustive simulation scheme, and giving an evaluation limit; and comparing the evaluation score of the actual scheme with the evaluation limit to obtain an evaluation conclusion.
The invention provides a viscous oil edge and bottom water reservoir multi-wheel CO2The huff and puff evaluation method covers the investigation range and possible data parameters of an evaluation target through an oil reservoir numerical simulation exhaustion method, establishes a scientific membership calculation method, obtains a reliable evaluation matrix and provides a reasonable evaluation limit; the method can solve the problems of difficult weight assignment, difficult evaluation matrix calculation, lack of basis of evaluation boundary, unreasonable evaluation result and the like caused by incomplete field data, and can be used for guiding the multiple CO rounds of the viscous oil bottom-edge water reservoir2The scientific, effective and reasonable evaluation of the handling has important practical significance.
Detailed Description
The technical solutions of the present invention will be described in detail below in order to clearly understand the technical features, objects, and advantages of the present invention, but the present invention is not limited to the practical scope of the present invention.
Examples
The embodiment provides a viscous crude edge and bottom water reservoir multi-wheel CO2The huff and puff evaluation method is used for carrying out multiple rounds of CO on the heavy oil bottom water reservoir of 37 horizontal wells with complete dynamic and static data2The throughput evaluation comprises the following steps:
measuring actual parameters of factors of an actual oil reservoir, establishing an oil reservoir model according to the actual parameters, and simulating to obtain throughput oil production and non-throughput oil production to obtain throughput oil increase; oil yield obtained by stimulation of huff and puff production-oil yield expected by non-huff and puff production is huff and puff.
Step two, taking throughput oil increment as an evaluation correlation object, and calculating the correction weight A of each factor by adopting a formula (I)i：
Wherein, aiEmpirical weight for factor i; a. theiA correction weight for the ith factor; 1, 2, … …, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data.
Table 1 shows the correction weights of the factors calculated and corrected according to the actual field dynamic and static data of the horizontal well.
TABLE 1
| Serial number | Influencing factor name/Unit | Modifying weights |
| 1 | Dip/degree of formation | 0.0025 |
| 2 | Position of the interlayer | 0.0178 |
| 3 | Effective thickness of oil layer/m | 0.0636 |
| 4 | Deposition rhythm | 0.0019 |
| 5 | Reservoir heterogeneity (Lorentz coefficient V)k) | 0.1271 |
| 6 | Put into production with water/f | 0.0089 |
| 7 | Length of water production zone/m | 0.0089 |
| 8 | Position of water producing segment | 0.0089 |
| 9 | Heterogeneous degree (permeability extremely poor K) of water producing segmentv) | 0.0089 |
| 10 | Position of horizontal segment | 0.0235 |
| 11 | Timing of throughput (water content)/f | 0.0953 |
| 12 | Periodic gas injection quantity/sm3 | 0.1174 |
| 13 | Gas injection rate/(sm)3/d) | 0.0089 |
| 14 | Soaking time/d | 0.0095 |
| 15 | Well production rate/(rm)3/d) | 0.0025 |
| 16 | Parallel well spacing/m | 0.1468 |
| 17 | Parallel well fluid production speed/(rm)3/d) | 0.1887 |
| 18 | Number of rounds of taking and putting | 0.1589 |
Establishing a calculation method of membership of each factor by means of an oil reservoir numerical simulation technology to respectively obtain evaluation matrixes of a simulation scheme and an actual scheme; the method comprises the following specific steps:
(1) designing a reasonable parameter variation range for each factor according to the measured actual parameters of each factor of the actual oil reservoir (designing according to the parameter distribution range of each factor in the actual condition of the oil field and enlarging +/-20 percent); table 2 shows the reasonable parameter variation range of each factor designed according to the actual field data of the oil field.
TABLE 2
(2) Predicting the corresponding throughput oil increment when each factor parameter changes by means of an oil reservoir numerical simulation technology; by means of ECLIPSE or CMG and other numerical simulation professional software, an oil reservoir model is established based on actual oil reservoir characteristic parameters, oil field exploitation is simulated, and therefore oil reservoir recovery efficiency is predicted and dynamic data are developed.
(3) Establishing a functional relation between each factor and membership degree according to the throughput oil increasing amount;
the established functional relation of the factors and the membership degrees is respectively as follows:
obtaining the membership y corresponding to the interlayer position by using the formula (1)1a、y1bAnd y1c：
Obtaining the membership y corresponding to the deposition rhythm by using the formula (2)2a、y2bAnd y2c：
Obtaining the membership y corresponding to the water content of the production by using the formula (3)3a、y3bAnd y3c：
Wherein f isw0Contains water for production;
the membership y corresponding to the length of the water outlet section is obtained by the formula (4)4a、y4bAnd y4c：
The membership y corresponding to the position of the water outlet section is obtained by the formula (5)5a、y5bAnd y5c：
Wherein, the point A is the toe end of the horizontal well, and the point B is the heel end of the horizontal well;
obtaining the membership y corresponding to the position of the horizontal section by using the formula (6)6a、y6bAnd y6c：
Obtaining the membership y corresponding to the parallel well distance by using the formula (7)7a、y7bAnd y7c：
Obtaining membership y corresponding to the throughput round by using the formula (8)8：
Calculating the corresponding membership y of the formation dip angle by using the formula (9)9a、y9bAnd y9c：
Wherein θ is the formation dip angle, °;
calculating the corresponding membership y of the effective thickness of the oil layer by using the formula (10)10a、y10bAnd y10c：
Wherein h is the effective thickness of the oil layer, m;
calculating the degree of membership y corresponding to the stratigraphic heterogeneity by using the formula (11)11a、y11bAnd y11c：
Wherein, VkIs the Lorentz coefficient;
calculating the membership y corresponding to the heterogeneous degree of the water outlet section by using the formula (12)12a、y12bAnd y12c：
Wherein, KvVery poor permeability;
calculating membership y corresponding to the timing of throughput by using equation (13)13a、y13bAnd y13c：
Wherein f is the timing of throughput;
calculating membership y corresponding to periodic gas injection quantity by using formula (14)14：
y14＝3.3E-06Qig-0.333 formula (14)
Wherein Q isigFor periodic gas injection, sm3；
Calculation of membership corresponding to gas injection velocity by equation (15)Degree y15a、y15bAnd y15c：
Wherein v isigAs the rate of gas injection, sm3/d；
Calculating the membership y corresponding to the soaking time by using the formula (16)16a、y16bAnd y16c：
Wherein t is the soaking time, d;
calculating the membership y corresponding to the liquid extraction speed after well production by using the formula (17)17a、y17bAnd y17c：
Wherein v islTo produce the liquid velocity after well opening, rm3/d；
Calculating the membership y corresponding to the liquid extraction speed of the parallel well by using the formula (18)18a、y18bAnd y18c：
Wherein q islFor the fluid production rate of the parallel well, rm3/d。
Calculating the membership degrees of different parameters corresponding to the factors according to the formulas (1) to (18).
(4) Obtaining an evaluation matrix of the simulation scheme according to the membership degree corresponding to each factor;
(5) and calculating the membership corresponding to each factor value of the actual scheme according to the established membership calculation method to obtain an actual scheme evaluation matrix.
Calculating the average value of the comprehensive scores of all the factors of each simulation scheme according to the simulation scheme evaluation matrix and the correction weight of each factor; the specific method comprises the following steps:
firstly, the correction weights of all the factors obtained by calculation form a correction weight vector, and the product of the correction weight vector and the evaluation matrix of the simulation scheme is calculated to obtain a score vector of the simulation scheme; calculating the comprehensive score c of all the factors of the simulation scheme by using the formula (II)j：
Wherein A isiA correction weight for the ith factor; 1, 2, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data; bjiThe membership degree corresponding to the ith factor of the jth simulation scheme; j 1, 2.... m; m is the total number of simulation schemes; c. CjThe composite score of all factors for the jth simulation scenario;
the average of the composite scores for all the factors for each simulation protocol was then calculated using equation (III)Reference values as evaluation limits:
wherein,the average value of the comprehensive scores of all the factors of each simulation scheme; c. CjThe composite score of all factors for the jth simulation scenario; j is 1, 2, … …, m; and m is the total number of simulation schemes.
Step five, calculating the comprehensive score C of all factors of the actual scheme according to the evaluation matrix of the actual scheme and the correction weight of each factorjAnd sorting; the specific method comprises the following steps:
firstly, the correction weights of all the factors obtained by calculation form a correction weight vector, and the product of the correction weight vector and the evaluation matrix of the actual scheme is calculated to obtain a score vector of the actual scheme; calculating the comprehensive score C of all factors of the actual scheme by using the formula (IV)j：
Wherein A isiA correction weight for the ith factor; 1, 2, … …, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data; b isjiThe membership degree corresponding to the factor of the ith item of the jth practical scheme; j ═ 1, 2, … …, M; m is the total number of actual schemes; cjThe scores are integrated for all the factors of the jth actual scheme;
and then sorting the comprehensive score of all factors of the actual scheme.
The calculation results are shown in tables 3 and 4. Table 3 shows the comprehensive scores c of all the factors of each simulation scheme, which are obtained by obtaining the evaluation matrix of the simulation scheme according to the membership degree corresponding to each factor and calculating after correcting the product of the weight vector and the evaluation matrix of the simulation schemejAnd average of the composite scores of all the factors of each simulation(evaluation limit).
Table 4 shows the evaluation matrix of the actual solution obtained by calculating the membership corresponding to each factor value of the actual solution according to the established membership calculation method, and the comprehensive score C of all the factors of the actual solution obtained by correcting the product of the weight vector and the evaluation matrix of the actual solutionjAnd sorting the results.
Step six, comparingAnd CjGiving an evaluation conclusion; if it isThe evaluation result is better; if it isThe evaluation result is poor, and the comparison result in Table 4 shows that the oil field has multiple CO cycles of the actual 37-port heavy oil edge bottom water reservoir2The throughput evaluation results were: the throughput effect of the well before the sequence No. 28 is better, and the throughput effect of the well after the sequence No. 28 is poorer.
In conclusion, the thickened oil bottom water reservoir provided by the invention has multiple CO wheels2The huff and puff evaluation method covers the investigation range and possible data parameters of an evaluation target through an oil reservoir numerical simulation exhaustion method, establishes a scientific membership calculation method, obtains a reliable evaluation matrix and provides a reasonable evaluation limit; the method can solve the problems of difficult weight assignment, difficult evaluation matrix calculation, lack of basis of evaluation boundary, unreasonable evaluation result and the like caused by incomplete field data, and can be used for guiding the multiple CO rounds of the viscous oil bottom-edge water reservoir2The scientific, effective and reasonable evaluation of the handling has important practical significance.
Claims (4)
1. Multiple-wheel CO for heavy oil edge and bottom water reservoir2The evaluation method of throughput comprises the following steps:
measuring actual parameters of factors of an actual oil reservoir, establishing an oil reservoir model based on the actual parameters, and simulating to obtain throughput oil production and non-throughput oil production to obtain throughput oil production;
step two, taking throughput oil increment as an evaluation correlation object, and calculating correction weights of all factors;
establishing a calculation method of membership of each factor by means of an oil reservoir numerical simulation technology to respectively obtain evaluation matrixes of a simulation scheme and an actual scheme;
step four, calculating the average value of the comprehensive scores of all the factors of each simulation scheme according to the evaluation matrix of the simulation scheme and the correction weight of each factor
Step five, calculating the comprehensive score C of all factors of the actual scheme according to the evaluation matrix of the actual scheme and the correction weight of each factorjAnd sorting;
step six, comparingAnd CjGiving an evaluation conclusion; if it isThe evaluation result is better; if it isThe evaluation result is poor;
in the third step, a calculation method of membership of each factor is established by means of an oil reservoir numerical simulation technology, and the step of respectively obtaining evaluation matrixes of the simulation scheme and the actual scheme comprises the following steps:
designing parameter variation ranges for all factors according to the measured actual parameters of all factors of the actual oil reservoir;
predicting the corresponding throughput oil increment when each factor parameter changes by means of an oil reservoir numerical simulation technology;
establishing a functional relation between each factor and membership degree according to the throughput oil increasing amount;
obtaining an evaluation matrix of the simulation scheme according to the membership degree corresponding to each factor;
calculating the membership corresponding to each factor value of the actual scheme according to the established membership calculation method to obtain an actual scheme evaluation matrix;
the factors comprise a plurality of factors of interlayer position, deposition rhythm, production water content, water outlet section length, water outlet section position, horizontal section position, parallel well distance, huff and puff turns, stratum inclination angle, effective thickness of an oil layer, stratum heterogeneity, water outlet section heterogeneous degree, huff and puff time, periodic gas injection quantity, gas injection speed, well closing time, liquid production speed after well production and liquid production speed of parallel wells;
the functional relation of each factor and the membership degree is as follows:
obtaining the membership y corresponding to the interlayer position by using the formula (1)1a、y1bAnd y1c：
And 1, round:
and 2, round 2:
and (3) round:
obtaining the membership y corresponding to the deposition rhythm by using the formula (2)2a、y2bAnd y2c：
And 1, round:
and 2, round 2:
and (3) round:
obtaining the membership y corresponding to the water content of the production by using the formula (3)3a、y3bAnd y3c：
And 1, round:
and 2, round 2:
and (3) round:
wherein f isw0Contains water for production;
the membership y corresponding to the length of the water outlet section is obtained by the formula (4)4a、y4bAnd y4c：
And 1, round:
and 2, round 2:
and (3) round:
the membership y corresponding to the position of the water outlet section is obtained by the formula (5)5a、y5bAnd y5c：
And 1, round:
and 2, round 2:
and (3) round:
wherein, the point A is the toe end of the horizontal well, and the point B is the heel end of the horizontal well;
obtaining horizontal segment position correspondences using equation (6)Degree of membership y6a、y6bAnd y6c：
And 1, round:
and 2, round 2:
and (3) round:
obtaining the membership y corresponding to the parallel well distance by using the formula (7)7a、y7bAnd y7c：
And 1, round:
and 2, round 2:
and (3) round:
obtaining membership y corresponding to the throughput round by using the formula (8)8：
Calculating the corresponding membership y of the formation dip angle by using the formula (9)9a、y9bAnd y9c：
And 1, round: y is9a＝-0.0078θ2+0.245θ-0.663
And 2, round 2:
and (3) round: y is9c＝-0.0078θ2+0.245 theta-0.663 type (9)
Wherein θ is the formation dip angle, °;
calculating the corresponding membership y of the effective thickness of the oil layer by using the formula (10)10a、y10bAnd y10c：
And 1, round:
and 2, round 2:
and (3) round: y is10c0.0826h-0.0909 type (10)
Wherein h is the effective thickness of the oil layer, m;
calculating the degree of membership y corresponding to the stratigraphic heterogeneity by using the formula (11)11a、y11bAnd y11c：
And 1, round:
and 2, round 2:
and (3) round:
wherein, VkIs the Lorentz coefficient;
calculating the membership y corresponding to the heterogeneous degree of the water outlet section by using the formula (12)12a、y12bAnd y12c：
And 1, round: y is12a＝-0.0204Kv+1.0204
And 2, round 2: y is12b＝1
And (3) round:
wherein, KvIs the difference in permeability level;
calculating membership y corresponding to the timing of throughput by using equation (13)13a、y13bAnd y13c：
And 1, round: y is13a＝1.053f
And 2, round 2:
and (3) round:
wherein f is the timing of throughput;
calculating membership y corresponding to periodic gas injection quantity by using formula (14)14：
y14＝3.3E-06Qig-0.333 formula (14)
Wherein Q isigFor periodic gas injection, sm3；
Calculating the membership y corresponding to the gas injection speed by using the formula (15)15a、y15bAnd y15c：
And 1, round: y is15a＝1.3E-05vig-0.25
And 2, round 2:
and (3) round:
wherein v isigAs the rate of gas injection, sm3/d；
Calculating the membership y corresponding to the well-closing time by using the formula (16)16a、y16bAnd y16c：
And 1, round: y is16a＝0.0189t-0.132
And 2, round 2:
and (3) round:
wherein t is well closing time and d;
calculating the membership y corresponding to the liquid extraction speed after well production by using the formula (17)17a、y17bAnd y17c：
And 1, round: y is17a＝0.0333vl-0.333
And 2, round 2:
and (3) round:
wherein v islTo produce the liquid velocity after well opening, rm3/d；
Calculating the membership y corresponding to the liquid extraction speed of the parallel well by using the formula (18)18a、y18bAnd y18c：
And 1, round:
and 2, round 2:
and (3) round:
wherein q islFor the fluid production rate of the parallel well, rm3/d。
2. The evaluation method according to claim 1, wherein the correction weight of each factor is calculated by using formula (I):
wherein, aiEmpirical weight for factor i; a. theiA correction weight for the ith factor; 1, 2, … …, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data.
3. The evaluation method according to claim 1, wherein the step of calculating an average value of the composite scores of all the factors of each simulation scheme based on the simulation scheme evaluation matrix and the correction weights of each factor comprises:
firstly, the correction weights of all the factors obtained by calculation form a correction weight vector, and the product of the correction weight vector and the evaluation matrix of the simulation scheme is calculated to obtain a score vector of the simulation scheme; calculating the comprehensive score c of all the factors of the simulation scheme by using the formula (II)j：
Wherein A isiA correction weight for the ith factor; 1, 2, … …, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data; bjiThe membership degree corresponding to the ith factor of the jth simulation scheme; j is 1, 2, … …, m; m is the total number of simulation schemes; c. CjThe composite score of all factors for the jth simulation scenario;
the average of the composite scores for all the factors for each simulation protocol was then calculated using equation (III)Reference values as evaluation limits:
wherein,the average value of the comprehensive scores of all the factors of each simulation scheme; c. CjThe composite score of all factors for the jth simulation scenario; j is 1, 2, … …, m; and m is the total number of simulation schemes.
4. The evaluation method according to claim 1, wherein the step of calculating and ranking the composite scores of all the factors of the actual solution based on the actual solution evaluation matrix and the correction weights of the factors comprises:
firstly, the correction weights of all the factors obtained by calculation form a correction weight vector, and the product of the correction weight vector and the evaluation matrix of the actual scheme is calculated to obtain a score vector of the actual scheme; calculating the comprehensive score C of all factors of the actual scheme by using the formula (IV)j：
Wherein A isiA correction weight for the ith factor; 1, 2, … …, N (N ≦ N); n is the total number of factors required by scheme evaluation; n is the total number of factors actually provided by the field data; b isjiThe membership degree corresponding to the factor of the ith item of the jth practical scheme; j ═ 1, 2, … …, M; m is the total number of actual schemes; cjThe scores are integrated for all the factors of the jth actual scheme;
then, the score C is integrated for all factors of the actual schemejThe sizes are sorted.
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