CN110716031B - Low-permeability reservoir polymer injection capability evaluation method - Google Patents
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Abstract
The invention provides a low permeability reservoir polymer injection capability evaluation method, which comprises the steps of obtaining 6 parameters of plugging capability, polymer injection pressure, resistance coefficient, residual resistance coefficient, viscosity retention rate and injection curve characteristics by developing a polymer injection physical simulation experiment under different reservoir conditions, further calculating an influence factor of each parameter by using a gray correlation coefficient method, determining the weight of each parameter, determining the value of each type of each parameter, further determining a polymer injection capability evaluation standard, simply and effectively quantitatively evaluating the polymer injection capability, and preferably selecting a polymer which is suitable for reservoir conditions and has good viscosity increasing property, good shear resistance, good injection property and good stability under oil reservoir conditions according to the standard, thereby improving the oil displacement effects of polymer flooding, binary flooding and the like.
Description
Technical Field
The invention belongs to the technical field of oilfield exploitation, and particularly relates to a method for evaluating the injection capacity of a low-permeability reservoir polymer.
Background
With the extension of water flooding time, the oil field gradually enters a medium-high water content development stage, and particularly for oil reservoirs with serious plane and longitudinal heterogeneity, the polymer flooding can change the oil-water fluidity ratio, enlarge the swept volume and improve the oil flooding efficiency. The polymer flooding is used as a main tertiary oil recovery process for oil field development or yield increase, is widely applied at home and abroad, and the oil increase of each ton of polymer reaches 80-150 tons, and is improved by 6-12 percent compared with the water flooding recovery. The quality of the polymer flooding effect depends on various factors, wherein one important factor is the injection capacity of the polymer, and the factor directly determines the success or failure of the polymer flooding. The injection pressure of a partial well after polymer flooding is greatly increased, so that the actual water injection of the polymer injection well cannot be matched, the formation energy is reduced, the yield is reduced, and the effect of polymer flooding cannot be fully exerted. Therefore, how to accurately evaluate the injection capability of the polymer injection well is one of the key problems influencing the polymer development effect and the overall economic benefit. Especially for low permeability reservoirs with low permeability, small pore throat, strong heterogeneity and high formation water mineralization. According to research, the current injectability evaluation has no mature standard, and the qualitative evaluation is mainly carried out according to the polymer injection pressure, the residual resistance coefficient and the injection curve characteristics. The "evaluation method of injectivity of multi-zone polymer injection well considering viscoelasticity of polymer" filed by the institute of middle sea oil on the year 2015, 07/08 and having application number 201510398172.3. The application relates to a method for evaluating the injection capability of a multi-oil-layer polymer injection well in consideration of polymer viscoelasticity, which mainly solves the injection capability by establishing a polymer seepage mathematical model without considering how to evaluate the polymer injection capability under the real oil reservoir condition.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for evaluating the polymer injection capacity of a low-permeability reservoir, and aims to provide a method for quantitatively evaluating the polymer injection capacity with strong adaptability, simple quantitative evaluation process and accuracy.
In order to realize the purpose, the invention adopts the technical scheme that: a method for evaluating the polymer injection capacity of a low permeability reservoir comprises the following steps:
s1 evaluation index for injection capability of constructed polymer
Constructing corresponding low-permeability reservoir polymer injection capacity evaluation indexes including polymer injection pressure, viscosity retention rate, resistance coefficient, residual resistance coefficient, plugging capacity and injection curve characteristics by developing a low-permeability reservoir polymer injection physical simulation experiment;
s2 classifies the evaluation indexes
According to the result of the polymer injection physical simulation experiment in the step S1, in combination with the actual oil reservoir development, determining the classification basis of each evaluation index in the step S1 one by one, classifying each evaluation index into one type, two types and three types, and determining the classification score;
s3 determining each evaluation index weight
According to the evaluation indexes of S1, respectively calculating the weight of each evaluation index by applying a grey correlation coefficient method;
S4 determining the final score of each evaluation index
Calculating the final scores of the evaluation indexes according to the classification score of each evaluation index obtained in the step S2 and the weight of each evaluation index obtained in the step S3;
s5 comprehensive evaluation of Polymer injectivity
And (4) calculating a total evaluation score according to the final scores of the evaluation indexes obtained in the step (S4) to obtain a polymer injectability evaluation standard, and comprehensively evaluating the injectability of the polymer by applying the standard.
Further, in step S2, the classification of the injection pressure is as follows: according to the oil reservoir development requirement, taking 60% and 90% of the maximum allowable pressure as the polymer injection pressure dividing point, and dividing the polymer injection pressure which is less than or equal to 60% of the maximum allowable pressure into a class; dividing the pressure range from 60% of the maximum allowable pressure to more than the polymer injection pressure and less than or equal to 90% of the maximum allowable pressure into two types; the injection pressure > 90% of the maximum allowable pressure is divided into three categories.
Further, in the step S2, the viscosity retention rate is classified according to the following: according to the results of polymer injection physical simulation experiments, in combination with the actual oil reservoir development, 10% and 40% are taken as the boundary points of the viscosity retention rate, and the viscosity retention rates of more than or equal to 40% are divided into one class; the viscosity retention rate of more than 10% and less than or equal to 40% is divided into two types; viscosity retention of less than 10% is divided into three categories.
Further, in step S2, the classification of the resistance coefficient is as follows: according to the experimental result of polymer injection physical simulation, taking 30 and 70 as resistance coefficient demarcation points, and dividing the resistance coefficients less than or equal to 30 into a class; the drag coefficients greater than 30 and equal to or less than 70 are classified into two types, and the drag coefficients greater than 70 are classified into three types.
Further, in the step S2, the classification of the residual resistance coefficient is based on the following: according to the injection physical simulation experiment result of the polymer, taking 5 and 10 as the dividing points of the residual resistance coefficients, and dividing the residual resistance coefficients less than or equal to 5 into one class; the residual resistance coefficients greater than 5 and equal to or less than 10 are classified into two types, and the residual resistance coefficients greater than 10 are classified into three types.
Further, in step S2, the classification of the plugging capability is as follows: according to the injection physical simulation experiment result of the polymer, taking 20 percent and 40 percent of the reduction of the water permeability before and after the polymer flooding as the blocking capacity dividing points, and dividing the reduction of the water permeability before and after the polymer flooding which is less than or equal to 20 percent into a class; the reduction of the water permeability before and after polymer flooding by more than 20 percent and less than or equal to 40 percent is divided into two types; the reduction of the water permeability before and after polymer flooding by more than 40% is divided into three categories.
Further, in step S2, the classification of the injection curve features is according to the following: the classification of the injection curve features is based on the following: according to a polymer injection physical simulation experiment, drawing a change curve of injection pressure along with injection times, and taking the curve form and the numerical value of the injection pressure as classification bases, specifically, when the injection pressure is less than or equal to 60% of the formation fracture pressure, and the secondary water flooding pressure is less than or equal to 5 times of the primary water flooding pressure, the injection curve is characterized as one type; when the injection pressure is more than 60 percent and less than or equal to 90 percent of the fracture pressure of the stratum, and the primary water drive pressure which is 5 times of the injection pressure is more than or equal to 10 times of the secondary water drive pressure, the injection curve is characterized by two types; when the injection pressure is more than 90% of the formation fracture pressure, and the secondary water drive pressure is more than 10 times the primary water drive pressure, the injection curve is characterized by three types.
Further, in the step S2, the scores of the first class, the second class and the third class are determined to be 100 points, 60 points and 0 points, respectively.
Further, in step S3, a gray correlation coefficient method is applied, and the processing procedure of calculating the weight of each evaluation index is as follows:
the first step is as follows: determining a reference sequence and a comparison sequence, wherein the amplitude of improving the oil displacement efficiency of each group of rock cores is taken as the reference sequence, and the injection pressure, the viscosity retention rate, the residual resistance coefficient, the injection curve characteristic, the plugging capacity and the resistance coefficient are taken as the comparison sequence;
The second step: carrying out dimensionless processing on data
Let x0＝{x0(k) 1, 2, …, m is a reference sequence, xi＝{xi(k) 1, 2, …, m (i is 1, 2, …, n) is a comparison sequence; because the dimensions of the parameters are different, in order to make the parameters comparable, the parameters are subjected to non-dimensionalization treatment by adopting the formula:
xi(k)′＝[xi(k)-minxi(k)]/[maxxi(k)-minxi(k)](A)
In the formula: i is evaluation block row
k is the evaluation parameter column
xi(k) Is the value of the ith row and the kth column;
the third step: calculating correlation coefficient
After the data is subjected to the second step of dimensionless processing, the formula two is used for calculating xi(k) And x0(k) Correlation coefficient of
In the formula: i is the number of rows of the evaluation block
k is the evaluation parameter column
x0(k) Is a reference array
xi(k) Is the value of the ith row and the kth column
Δi(k) Is X0Array and XiAbsolute difference of array at k point
ζi(k) The correlation coefficient rho is a resolution coefficient, and the value range is (0, 1), usually 0.5;
the fourth step: determining the degree of association and calculating the weight of each evaluation index
And calculating the correlation coefficient calculated in the third step by using an equation three-mean method:
in the formula: gamma raykIs the degree of association;
after the correlation degree is obtained, a weight coefficient is obtained through the formula four normalization processing:
in the formula: omegakAre weights.
Further, in step S5, the total score of the comprehensive evaluation is calculated by the following formula:
Wherein: k is an evaluation index number;
n is the classification score of the evaluation index;
w is the evaluation parameter weight;
s is the total score of comprehensive evaluation;
when the total score S of the comprehensive evaluation is more than or equal to 80, the injectability is good; s is more than or equal to 60 and less than 80, which indicates moderate injectability; s < 60, indicating poor injectability.
The invention has the following beneficial effects:
according to the invention, 6 parameters of plugging capacity, polymer injection pressure, resistance coefficient, residual resistance coefficient, viscosity retention rate and injection curve characteristic are obtained by developing a polymer injectability physical simulation experiment, an influence factor of each parameter is calculated by using a grey correlation coefficient method, and the weight of each parameter is determined, so that a polymer injectability evaluation standard is established. According to the standard, the polymer which is suitable for oil reservoir conditions and has good tackifying property, good shearing resistance, good injection property and good stability under oil reservoir conditions is selected preferably, so that the oil displacement effects of polymer flooding, binary flooding and the like are improved. The method disclosed by the invention completely simulates parameters such as pressure, temperature, permeability and porosity of the oil reservoir, can quantitatively evaluate the injection capability of the polymer, has the advantages of strong practicability, simplicity and strong operability, can preferably evaluate the polymer suitable for the oil reservoir, and has a good application prospect.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to clearly understand the technical solutions of the present invention and to implement the technical solutions according to the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings.
Drawings
FIG. 1 is a class of injection profile characteristics;
FIG. 2 is a graph of a class II injection profile;
fig. 3 is a graph of the characteristics of three types of injection curves.
Detailed Description
The following description is given by way of specific embodiments, and the advantages and effects of the present invention will be readily apparent to those skilled in the art from the disclosure herein.
First embodiment
The first embodiment of the invention relates to a low permeability reservoir polymer injection capacity evaluation method, which comprises the following steps:
s1 construction of evaluation index for polymer injectability
Constructing corresponding low-permeability reservoir polymer injection capacity evaluation indexes including polymer injection pressure, viscosity retention rate, resistance coefficient, residual resistance coefficient, plugging capacity and injection curve characteristics by developing a low-permeability reservoir polymer injection physical simulation experiment;
s2 classifies the evaluation indexes
According to the result of the polymer injection physical simulation experiment in the step S1, in combination with the actual oil reservoir development, determining the classification basis of each evaluation index in the step S1 one by one, classifying each evaluation index into one type, two types and three types, and determining the classification score;
S3 determining each evaluation index weight
According to the evaluation indexes of S1, respectively calculating the weight of each evaluation index by applying a grey correlation coefficient method;
s4 determining the final score of each evaluation index
Calculating the final scores of the evaluation indexes according to the classification score of each evaluation index obtained in the step S2 and the weight of each evaluation index obtained in the step S3;
s5 comprehensive evaluation of Polymer injectivity
And (4) calculating a total evaluation score according to the final scores of the evaluation indexes obtained in the step (S4) to obtain a polymer injectability evaluation standard, and comprehensively evaluating the injectability of the polymer by applying the standard.
The invention develops polymer injectivity experiments under different oil reservoir conditions by the method to obtain 6 parameters of plugging capacity, polymer injection pressure, resistance coefficient, residual resistance coefficient, viscosity retention rate and curve form, further calculates the influence factor of each parameter by using a grey correlation coefficient method, and determines the weight of each parameter, thereby establishing a polymer injectivity evaluation standard and simply and effectively quantitatively evaluating the polymer injectivity.
Second embodiment
In addition to the above embodiments, it should be particularly noted that in step S2, the classification of the injection pressure is as follows: according to the oil reservoir development requirement, the polymer injection pressure P cannot exceed 90 percent of the fracture pressure of the stratum, and is preferably below 60 percent, so that 60 percent and 90 percent of the maximum allowable pressure (namely the fracture pressure of the stratum) are used as polymer injection pressure dividing points, and the polymer injection pressure is less than or equal to 60 percent of the maximum allowable pressure and is classified into a category; dividing the pressure range from 60% of the maximum allowable pressure to more than the polymer injection pressure and less than or equal to 90% of the maximum allowable pressure into two types; the injection pressure > 90% of the maximum allowable pressure is divided into three categories.
Furthermore, the viscosity retention rate eta is the ratio of the viscosity of the produced liquid to the viscosity of the solution for preparing the polymer when the injection pressure is stable, and the retention rate is high, so that the polymer molecules can effectively pass through pores and throats and the injectability is good. Specifically, the classification of viscosity retention is based on the following: according to the results of the polymer injection physical simulation experiments, in combination with the actual oil reservoir development, the analysis shows that when the viscosity retention rate is less than 10%, polymer molecules cannot effectively pass through the oil reservoir, the injection pressure is high, and the injection property is poor; when the viscosity retention rate is more than 40%, polymer molecules can effectively pass through the oil reservoir, and the injectivity is good, so that 40% and 10% are used as the boundary points of the viscosity retention rate, and the viscosity retention rates more than or equal to 40% are classified into one class; the viscosity retention rate of more than or equal to 10% and less than 40% is divided into two types; viscosity retention of less than 10% is divided into three categories.
Further, the drag coefficient RFRefers to the ability of a polymer to reduce the fluidity ratio, which is the ratio of the fluidity of water to the fluidity of a polymer solution, and specifically, the drag coefficient is classified as follows: according to the experimental result of polymer injection physical simulation, when the resistance coefficient is less than 30, the injection pressure is low, and the oil displacement effect is good; when the resistance coefficient exceeds 70, the injection pressure is high, and the oil displacement effect is poor; therefore, 30 and 70 are taken as the dividing points of the resistance coefficients, and the resistance coefficients less than or equal to 30 are divided into one class; the drag coefficients greater than 30 and equal to or less than 70 are classified into two types, and the drag coefficients greater than 70 are classified into three types.
Further, the residual drag coefficient RKRefers to the permeability reducing ability of a polymer, i.e., the ratio of the water phase permeability of the rock before and after polymer flooding, and specifically, the classification of the residual drag coefficient is as follows: according to the experimental result of the polymer injection physical simulation, when the residual resistance coefficient is less than 5, injectingThe inlet pressure is low, and the oil displacement effect is good; when the resistance coefficient exceeds 10, the injection pressure is high, and the oil displacement effect is poor; therefore, 5 and 10 are taken as the dividing point of the resistance coefficients, and the residual resistance coefficients less than or equal to 5 are classified into one class; the residual resistance coefficients greater than 5 and equal to or less than 10 are classified into two types, and the residual resistance coefficients greater than 10 are classified into three types.
Further, the plugging capability refers to the decrease of the air permeability of the core before and after the polymer injection, and specifically, the classification of the plugging capability is as follows: according to the injection physical simulation experiment result of the polymer, when the water permeability before and after polymer flooding is reduced by less than 20%, the injection performance is good, and the oil displacement effect is good; when the permeability of the polymer before and after flooding is reduced by more than 40 percent, the injectability is poor, and the flooding effect is poor; therefore, 20 percent and 40 percent are taken as the blocking capacity dividing points, and the reduction of the water permeability before and after polymer flooding is less than or equal to 20 percent, and the polymer flooding is divided into a class; the reduction of the water permeability before and after polymer flooding by more than 20 percent and less than or equal to 40 percent is divided into two types; the reduction of the water permeability before and after polymer flooding by more than 40% is divided into three categories.
According to a polymer injection physical simulation experiment, a curve of the injection pressure changing along with the injection multiple is drawn, and the curve characteristics are analyzed to judge the injection quality integrally. According to the indoor experiment, the polymer with good injectivity is fast in pressure drop when the water flooding is changed, and finally, the polymer is stable and has a low numerical value. The polymer with poor injectability has stable water flooding pressure, the polymer flooding pressure is always increased or more PV is basically stable but the pressure is high, the viscosity retention rate of produced liquid is low, and the pressure drop is less or even not reduced during water flooding.
Specifically, when the polymer injection pressure is less than or equal to 60% of the formation fracture pressure and the secondary water drive pressure is less than or equal to 5 times of the primary water drive pressure, that is, as shown in fig. 1, when the polymer injection multiple is 0-1.0PV, the polymer injection pressure is stable and the value P of the polymer injection pressure is less than or equal to 60% of the formation fracture pressure; when the secondary water flooding volume is 0-0.8PV, the secondary water flooding pressure is stable, the value P of the secondary water flooding pressure is less than or equal to 5 times of the primary water flooding pressure, and the injection curve is considered as one type;
when the polymer injection pressure is more than 60 percent and less than or equal to 90 percent of the stratum fracture pressure, and the primary water drive pressure which is 5 times and less than or equal to 10 times of the secondary water drive pressure, namely as shown in figure 2, when the polymer injection multiple is 0-3.0PV, the polymer injection pressure is stable, and the numerical value P of the stratum fracture pressure which is more than 60 percent and less than or equal to 90 percent of the stratum fracture pressure; when the secondary water flooding volume is 0-0.8PV, the secondary water flooding pressure is stable, the value P of 5 times of primary water flooding pressure which is less than the secondary water flooding pressure is less than or equal to 10 times of primary water flooding pressure, and the injection curve is considered as a second type;
When the injection pressure is more than 90% of the formation fracture pressure and the secondary water flooding pressure is more than 10 times the primary water flooding pressure, that is, as shown in fig. 3, when the polymer injection volume is 0-3.0PV, the injection pressure is always raised or stabilized, and 90% of the formation fracture pressure is less than the value P of the injection pressure; when the secondary water flooding volume is 0-0.8PV, the secondary water flooding is slowly or basically not reduced, and the injection curves are considered to be in three types.
Specifically, the scores of the first class, the second class and the third class are 100 points, 60 points and 0 points, respectively.
The invention provides a low permeability reservoir polymer injectivity evaluation method taking 6 parameters such as plugging capacity, polymer injection pressure, resistance coefficient, residual resistance coefficient, viscosity retention rate, injection curve characteristics and the like as main indexes, and the method is characterized in that according to related parameters obtained by a polymer injectivity physical simulation experiment, a grey correlation coefficient method is utilized to calculate main factors influencing polymer injectivity, and the weight of each item is determined; and the score of each type of each parameter is 100 points according to the first type, 60 points according to the second type and 0 point according to the third type. And combining the two points to determine the evaluation standard of the polymer injectability.
Third embodiment
In addition to the above embodiment, in step S3, each evaluation index weight is determined, and the data is processed by using a gray correlation method, and the processing procedure is as follows:
The first step is as follows: determination of reference sequences and comparison of sequences
Taking the amplitude of improving the oil displacement efficiency of each group of rock cores as a reference sequence, and taking the injection pressure, the viscosity retention rate, the residual resistance coefficient, the injection curve characteristics, the plugging capability and the resistance coefficient as comparison sequences;
the second step: carrying out dimensionless processing on data
Let x0＝{x0(k) 1, 2, …, m is a reference sequence, xi＝{xi(k) 1, 2, …, m (i is 1, 2, …, n) is a comparison sequence; because the dimensions of the parameters are different, in order to make the parameters comparable, the parameters are subjected to non-dimensionalization treatment by adopting the formula:
xi(k)′＝[xi(k)-minxi(k)]/[maxxi(k)-minxi(k)](A)
In the formula: i is evaluation block row
k is the evaluation parameter column
xi(k) Is the value of the ith row and the kth column;
the third step: calculating correlation coefficient
After the data is subjected to the second step of dimensionless processing, the formula two is used for calculating xi(k) And x0(k) Correlation coefficient of
In the formula: i is the number of rows of the evaluation block
k is the evaluation parameter column
x0(k) Is a reference array
xi(k) Is the value of the ith row and the kth column
xi(k) Is X0Array and XiAbsolute difference of array at k point
ζi(k) The correlation coefficient rho is a resolution coefficient, and the value range is (0, 1), usually 0.5;
the fourth step: determining the degree of association and calculating the weight of each evaluation index
And calculating the correlation coefficient calculated in the third step by using an equation three-mean method:
In the formula: gamma raykIs the degree of association;
after the correlation degree is obtained, a weight coefficient is obtained through the formula four normalization processing:
in the formula: omegakAre weights.
The invention realizes the prediction and quantification of unknown information by processing the known information by using a grey correlation method, finds out the correlation of each evaluation parameter, realizes the quantitative description of the evaluation parameters and eliminates the influence of human factors on weight distribution.
Fourth embodiment
In addition to the above embodiment, in step S5, the total score of the comprehensive evaluations is calculated by the following formula:
wherein: k is an evaluation index number;
n is the classification score of the evaluation index;
w is the evaluation parameter weight;
s is the total score of comprehensive evaluation;
when the total score S of the comprehensive evaluation is more than or equal to 80, the injectability is good; s is more than or equal to 60 and less than 80, which indicates moderate injectability; s < 60, indicating poor injectability. On the basis of the evaluation criteria, the low permeability reservoir polymer injectivity is obtained as shown in the following table 1.
TABLE 1 evaluation criteria for polymer injectivity of low permeability reservoirs
The applicable range of the evaluation criterion is as follows:
1) polymers suitable for use preferably in the reservoir conditions;
2) applicable core conditions are as follows: the core is suitable for a cylinder core, the length range is 5.0-50.0 cm, and the diameter range of the cylinder is 2.5-3.8 cm.
3) The permeability range of the rock core is 1-100mD, and the porosity range is 5.0% -15.0%.
4) Suitable for stratum crude oil with viscosity of 0.5-100 mPas, and density of 0.60-0.95g/cm3；
5) The applicable temperature range is 30-100 ℃, and the terminal back pressure range is 0-30 MPa;
6) the flow rate of water injection and gas injection ranges from 0.05ml/min to 10.0 ml/min.
Fifth embodiment
Taking the Changqing low-permeability reservoir as an example, the influence factors of all parameters influencing the polymer injectivity, the polymer injectivity influence factor 0.8153, the viscosity retention rate influence factor 0.7294, the residual resistance coefficient influence factor 0.6764, the injection curve characteristic influence factor 0.6042, the plugging capacity influence factor 0.4543 and the resistance coefficient influence factor 0.3907 are calculated by using a gray correlation coefficient method. The relevancy ranks as: polymer injection pressure > viscosity retention > residual resistance coefficient > injection curve characteristics > plugging capacity > resistance coefficient.
According to literature research, combining oil reservoir development practice, further preliminarily determining the weight of each parameter as follows: the weight of polymer injection pressure is 25%, the weight of viscosity retention rate is 25%, the weight of residual resistance coefficient is 15%, the weight of injection curve characteristic is 15%, the weight of plugging capability is 10%, and the weight of resistance coefficient is 10%. The polymer injectability was determined according to the injectability evaluation criteria.
Core: beret core, manufactured by seviki technologies ltd, beijing, 20cm in length and 2.5cm in diameter.
Water for experiment: 5.6g/l of water is injected into a three-area water north for preparing the polymer; three-zone simulated formation water for core saturation, the mineralization degree is 24.6g/L, and the water type is Na2SO4And (4) molding.
Chemical agents: 600-2000 ten thousand molecular weight linear polymers (fp series) produced by Essen, France.
Application one
The porosity of the beret core is 18.0 percent, the permeability is 53.1mD, the molecular weight of the polymer is 700-: the polymer injection pressure is 5.3MPa, and the score is 25; the viscosity retention rate is 91.0 percent, and the score is 15; the residual resistance coefficient is 3.0, and the score is 15; as shown in fig. 1, the injection pressure is stable, the water-change flooding pressure is reduced quickly and the value is low, and the injection curve score is 15 points; the resistance coefficient is 19.0, and the score is 10; plugging capacity is 24.6, and the score is 6; the total score is 96 points, and the evaluation result is as follows: the injection property is good.
Application two
Beret core porosity 18.8%, permeability 56.7mD, polymer molecular weight 1000 ten thousand: the polymer injection pressure is 16.0MPa, and the score is 15; the viscosity retention rate is 57.2 percent, and the score is 15 points; the residual resistance coefficient is 4.6, and the score is 15; as shown in fig. 1, the injection pressure is stable, the water-change flooding pressure is reduced quickly and the value is low, and the injection curve score is 15 points; the resistance coefficient is 26.5, and the score is 10; plugging capacity is 12.1, and the score is 10; the total score is 100 points, and the evaluation result is as follows: the injection property is good.
Application three
Bailey core porosity of 19.1%, permeability of 53.8mD, polymer molecular weight of 1200-1600 ten thousand: the polymer injection pressure is 3.8MPa, and the score is 15; the viscosity retention rate is 11.2 percent, and the score is 15 points; the residual resistance coefficient is 6.9, and 9 points are obtained; as shown in fig. 2, the injection pressure is stable but higher after pv, the water flooding pressure is high, and the injection curve score is 9 points; the resistance coefficient is 28.6, and the score is 10; the plugging capacity is 31.8, and the score is 6; the comprehensive score is 64 points, and the evaluation result is as follows: the injectability is moderate.
Application four
The porosity of the beret core is 15.4 percent, the permeability is 3.1mD, the molecular weight of the polymer is 500-700 ten thousand: the polymer injection pressure is more than 28.2MPa, and the score is 0; the viscosity retention rate is 3.9 percent, and the score is 0; the residual resistance coefficient is 12, and the score is 0; as shown in fig. 3, the injection pressure is constantly rising and unstable, and the injection curve is scored as 0 point; the resistance coefficient is larger than 31.3, and the score is 6; the plugging capacity is 22.8, and the score is 6; the overall score is 12 points, and the evaluation result is as follows: the injectability is poor.
By comparing the evaluation results of the polymer injectivity of the low-permeability reservoir in the table 2, the rationality of the evaluation method is verified, and a new method is provided for effective evaluation of a polymer flooding injection system.
Table 2 example of low permeability reservoir polymer injectivity evaluation
Claims (6)
1. A low permeability reservoir polymer injection capacity evaluation method is characterized by comprising the following steps:
s1 evaluation index for injection capability of constructed polymer
Constructing corresponding low-permeability reservoir polymer injection capacity evaluation indexes including polymer injection pressure, viscosity retention rate, resistance coefficient, residual resistance coefficient, plugging capacity and injection curve characteristics by developing a low-permeability reservoir polymer injection physical simulation experiment;
s2 classifies the evaluation indexes
According to the polymer injection physical simulation experiment result in the step S1 and in combination with the oil reservoir development practice, determining the classification basis of each evaluation index in the low permeability oil reservoir polymer injection capacity evaluation indexes in the step S1 one by one, dividing each evaluation index into a first class, a second class and a third class, and determining the scores of the first class, the second class and the third class as 100, 60 and 0 respectively;
the classification of the injection pressure is based on the following: according to the oil reservoir development requirement, taking 60% and 90% of stratum fracture pressure as polymer injection pressure dividing points, and dividing the polymer injection pressure which is less than or equal to 60% of the stratum fracture pressure into a class; dividing the stratum fracture pressure into two types, wherein the pressure is more than 60% of the stratum fracture pressure and less than or equal to 90% of the stratum fracture pressure; dividing the injection pressure more than 90% of the formation fracture pressure into three types;
The classification of viscosity retention is as follows: according to the results of polymer injection physical simulation experiments, in combination with the actual oil reservoir development, 10% and 40% are taken as the boundary points of the viscosity retention rate, and the viscosity retention rates of more than or equal to 40% are divided into one class; the viscosity retention rate of 10% or more and 40% or less is classified into two types; viscosity retention rates of less than 10% are divided into three categories;
the drag coefficients are classified as follows: according to the experimental result of polymer injection physical simulation, taking 30 and 70 as resistance coefficient demarcation points, and dividing the resistance coefficients less than or equal to 30 into a class; dividing the resistance coefficient which is more than 30 and less than or equal to 70 into two types, and dividing the resistance coefficient which is more than 70 into three types;
the residual drag coefficients are classified as follows: according to the injection physical simulation experiment result of the polymer, taking 5 and 10 as the dividing points of the residual resistance coefficients, and dividing the residual resistance coefficients less than or equal to 5 into one class; dividing the residual resistance coefficients which are more than 5 and less than or equal to 10 into two types, and dividing the residual resistance coefficients which are more than 10 into three types;
the classification of plugging capacity is based on: according to the injection physical simulation experiment result of the polymer, taking 20 percent and 40 percent of the reduction of the water permeability before and after the polymer flooding as the blocking capacity dividing points, and dividing the reduction of the water permeability before and after the polymer flooding which is less than or equal to 20 percent into a class; the reduction of the water permeability before and after polymer flooding by more than 20 percent and less than or equal to 40 percent is divided into two types; dividing the permeability reduction of water measurement before and after polymer flooding by more than 40 percent into three categories;
The classification of the injection profile features is based on the following: according to a polymer injection physical simulation experiment, drawing a change curve of injection pressure along with injection times, taking the curve form and the numerical value of the injection pressure as classification bases, and when the injection pressure is less than or equal to 60% of the formation fracture pressure and the secondary water drive pressure is less than or equal to 5 times of the primary water drive pressure, the injection curve is characterized as one type; when the injection pressure is more than 60 percent and less than or equal to 90 percent of the fracture pressure of the stratum, and the primary water drive pressure which is 5 times of the injection pressure is more than or equal to 10 times of the secondary water drive pressure, the injection curve is characterized by two types; when the polymer injection pressure is more than 90% of the formation fracture pressure and the secondary water drive pressure is more than 10 times of the primary water drive pressure, the injection curve characteristics are three types;
s3 determining each evaluation index weight
And (3) respectively calculating each evaluation index weight in the low permeability reservoir polymer injection capacity evaluation indexes in the step S1 by using a grey correlation coefficient method, wherein the specific processing process is as follows:
the first step is as follows: determination of reference sequences and comparison of sequences
Taking the amplitude of improving the oil displacement efficiency of each group of rock cores as a reference sequence, and taking the injection pressure, the viscosity retention rate, the residual resistance coefficient, the injection curve characteristics, the plugging capability and the resistance coefficient as comparison sequences;
The second step: carrying out dimensionless processing on data
Respectively carrying out dimensionless treatment on the polymer injection pressure, the viscosity retention rate, the residual resistance coefficient, the injection curve characteristic, the plugging capability and the resistance coefficient;
the third step: calculating correlation coefficient
After the data is processed by the second step of dimensionless, x is calculatedi(k) And x0(k) The correlation coefficient of (a);
the fourth step: determining the degree of association and calculating the weight of each evaluation index
Calculating the association degree by using an average value method according to the association coefficient calculated in the third step, and obtaining a weight coefficient through normalization processing after obtaining the association degree:
s4 determining the final score of each evaluation index
Calculating the final scores of the evaluation indexes according to the classification score of each evaluation index obtained in the step S2 and the weight of each evaluation index obtained in the step S3;
s5 comprehensive evaluation of Polymer injectivity
Calculating a total comprehensive evaluation score according to the final scores of the evaluation indexes obtained in the step S4 to obtain a polymer injectivity evaluation standard, and comprehensively evaluating the injectivity of the polymer by applying the standard; specifically, the total score of the comprehensive evaluation is calculated by the following formula:
wherein: k is an evaluation index number;
n is the classification score of the evaluation index;
W is the evaluation parameter weight;
s is the total score of the comprehensive evaluation;
when the total score S of the comprehensive evaluation is more than or equal to 80, the injectability is good; s is more than or equal to 60 and less than 80, which indicates moderate injectability; s < 60, indicating poor injectability.
2. The method of claim 1, wherein in the second step of step S3, the non-dimensionalization of the injection pressure, the viscosity retention, the residual resistance coefficient, the injection curve characteristic, the plugging capability, and the resistance coefficient comprises: let x0＝{x0(k) 1, 2, …, m is a reference sequence, xi＝{xi(k) 1, 2, …, m, wherein i is 1, 2, …, n, and the parameters of the injection pressure, the viscosity retention rate, the residual resistance coefficient, the injection curve characteristics, the plugging capability and the resistance coefficient are dimensionless processed by adopting a formula one:
xi(k)′＝[xi(k)-minxi(k)]/[maxxi(k)-minxi(k)](A)
In the formula: i is a row of the evaluation block,
k is a column of evaluation parameters,
xi(k) is the value of the ith row and the kth column.
3. The method for evaluating the polymer injectivity of a low-permeability reservoir of claim 1, wherein in the third step of step S3, x isi(k) And x0(k) The correlation coefficient of (d) is calculated using the following equation two:
In the formula: i is the number of evaluation block rows, i is 1, 2, …, n,
k is an evaluation parameter column, k is 1, 2, …, m,
x0(k) for the purpose of reference to the sequence of numbers,
xi(k) is the value of the ith row and the kth column,
Δi(k) is X0Array and XiThe absolute difference of the array at point k,
ζi(k) and p is a correlation coefficient, and the value range of p is (0, 1).
4. The method of claim 3, wherein in the fourth step of step S3, the correlation degree is calculated by the following formula three,
in the formula: r iskIs the degree of association.
5. The method for evaluating the polymer injectivity of a low permeability reservoir of claim 4, wherein in the fourth step of step S3, the weight coefficient is calculated by the following formula:
in the formula: w is akAre weights.
6. The method for evaluating the polymer injectivity of a low permeability reservoir of claim 1, wherein the polymer injectivity evaluation criteria obtained in step S5 are applied in the following ranges:
(1) applicable core conditions are as follows: the core is suitable for a cylinder core, the length range is 5.0-50.0 cm, and the diameter range of the cylinder is 2.5-3.8 cm;
(2) the core permeability range is 1-100 mD, and the porosity range is 5.0% -15.0%;
(3) Suitable for the formation crude oil, the viscosity of the formation crude oil is 0.5-100 mPa ∑ s, and the density is 0.60-0.95g/cm3；
(4) The application temperature range is 30-100 ℃, and the terminal back pressure range is 0-30 MPa;
(5) the flow rate range of water injection and gas injection is 0.05 ml/min-10.0 ml/min.
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