Classification characterization and quantitative evaluation method for differentiated remaining oil in high water cut period

Abstract

The invention provides a classified characterization and quantitative evaluation method for differentiated remaining oil in a high water cut period. The method comprises the following steps: establishing a differentiated remaining oil characterization sample matrix; standardizing differential remaining oil characterization sample data; establishing a sample data correlation coefficient matrix; solving eigenvalues of eigenvectors of the sample data; differential remaining oil main control factors are determined; and calculating a differential residual oil classification characterization comprehensive quantitative evaluation value. The evaluation method is applied to characterization of formation reasons, current situation contradictions and adjustment effects of the differentiated remaining oil in the high-water-cut period and quantitative evaluation calculation, so that classified recognition of the high-water-cut remaining oil is realized. According to the method, classification characterization of the remaining oil in the high-water-cut period is achieved, classification understanding of field technicians on the remaining oil is directly improved, and a differentiated countermeasure method is provided for further improving the differentiated remaining oil recovery ratio in a targeted mode.

Description

Technical Field

[0001] The present invention relates to the field of residual oil evaluation in water-driven oil reservoirs, and in particular to a method for differential classification, characterization and quantitative evaluation of residual oil in a high water-cut period. Background Art

[0002] After years of water drive development, most of my country's onshore oil fields have undergone various adjustments to enhance oil recovery, including formations, well networks, mining systems, profile adjustment, water plugging, etc. The distribution of remaining oil has become extremely complex. After the superposition of multiple hydrodynamic measures, the conventional characterization model of remaining oil distribution has been unable to meet the requirements of further improvement in the high water cut period. Therefore, it is necessary to study and establish new and more detailed remaining oil characterization methods and quantitative evaluation methods for remaining oil.

[0003] The difficulty in characterizing the differentiated remaining oil in the high water-cut period lies in the fact that after years of complex adjustments of various measures in reservoir development, the distribution of the remaining oil has become extremely complex, and the characterization of the remaining oil has become extremely difficult. However, further improving the recovery rate of old oil fields requires a deeper understanding of the characterization of the remaining oil. Summary of the invention

[0004] In order to solve the problem of difficulty in understanding the remaining oil in the high water cut period, the embodiment of the present application provides a method for classification, characterization and quantitative evaluation of differentiated remaining oil in the high water cut period, which realizes the classification, characterization and quantitative evaluation of differentiated remaining oil in the high water cut period, and provides an effective technical method for further improving the recovery rate in the high water cut period.

[0005] The embodiment of the present application provides a method for differential residual oil classification characterization and quantitative evaluation in the high water cut period, including: S1, establishing a differentiated residual oil characterization sample matrix; S2, standardizing differentiated residual oil characterization sample data; S3, establishing a sample data correlation coefficient matrix; S4, obtaining the eigenvalue of the sample data eigenvector; S5, determining the main controlling factors of the differentiated residual oil; S6, calculating the comprehensive quantitative evaluation value of the differentiated residual oil classification characterization.

[0006] Among them, in step S1, the establishment of the differentiated remaining oil characterization sample matrix includes calculating the parameters in the characterization parameter group of each grid node of the reservoir: the differentiated remaining oil formation cause characterization parameter group, the differentiated remaining oil current contradiction characterization parameter group, and the differentiated remaining oil adjustment effect characterization parameter group.

[0007] In step S1, the formation coefficient F is determined c , water multiple C wD , water drive strength Q v The four parameters of extrapolated reflux degree PR are the characterization parameter group of the causes of differential residual oil formation, and the formula is:

[0008] Formation factor Fc : F c =K·H

[0009] Water overflow multiple C wD :

[0010] Water drive strength Q v :Q v =Q w +Q o

[0011] Extrapolated reflux PR:

[0012] Where K is the permeability; H is the thickness; Q w is the water phase velocity; Q o is the oil phase velocity; V p is the pore volume; T is the reflow time at point (x, y); T' is the reflow time at position (x', y') after time Δt.

[0013] Among them, in step S1, the differentiated remaining oil status is reflected in the current remaining oil control status, using the water flooding intensity Q v , Water drive degree D w , Residual oil start-up performance Δ or The four parameters of extrapolated reflux degree PR are the characterization parameter groups of differentiated remaining oil status contradictions, and the formula is:

[0014] Water drive strength Q v :Q v =Q w +Q o

[0015] Water flooding degree D w :

[0016] Residual oil start-up performance Δ or :Δ or =(41.493-Q v ·44.979)·e -0.0252K

[0017] Extrapolated reflux PR:

[0018] Where: S wi is the initial water saturation; S o is the current oil saturation.

[0019] Among them, in step S1, the differential remaining oil adjustment effect is manifested in the improvement of the current remaining oil control status, using the water flooding intensity Q v ·S o , Residual oil start-up performance Δor , Extrapolated reflux degree PR·S o The three parameters are used to differentiate the residual oil measures effect parameter characterization group, and the formula is:

[0020] Water drive strength Q v ·S o :Q v ·S o =(Q w +Q o )·S o

[0021] Residual oil start-up performance Δ or :Δ or =(41.493-Q v ·44.979)·e -0.0252K

[0022] Extrapolated reflux PR·S o :

[0023] In step S2, the sample data is standardized using the following formula:

[0024]

[0025] Where: is the variable index x j The average value of s j is the scalar index x j The variance of

[0026]

[0027] In step S3, the correlation coefficient matrix R is established and the y in the standardized matrix is ​​calculated. i With y j The correlation coefficient r ij , the formula is:

[0028]

[0029] Where: is the variable index y i The average value of is the average value of the variable index yj.

[0030] Among them, in step S4, for a non-zero vector V, the following conditions are satisfied: R·V=λ·V, λ is a scalar, called an eigenvalue, and V is called the eigenvector corresponding to the eigenvalue λ. The characteristic equation of the correlation coefficient matrix R |λI-R|=0 is solved for the eigenvector and eigenvalue.

[0031] Among them, in step S5, the principal component analysis method is used to calculate the differential remaining oil formation cause characterization parameter group, the differential remaining oil current contradiction characterization parameter group, and the differential remaining oil adjustment effect characterization parameter group, and determine the maximum influencing parameter in each parameter group as the main controlling factor of each characterization parameter group, that is:

[0032] The main effect factors are:

[0033] y i j is the standardized parameter variable, a i j is the i-th comprehensive scalar, a i j is called the principal component coefficient, that is, the eigenvector corresponding to the eigenvalue; λ i is the eigenvalue; m is the number of parameters in the parameter group.

[0034] Among them, in step S6, the principal component with the cumulative contribution rate greater than 85% is selected, the characteristic value is used as the weight coefficient, and TT is defined as the differentiated residual oil comprehensive characterization evaluation coefficient of each parameter group, and the expression is:

[0035]

[0036] The differentiated residual oil classification characterization and quantitative evaluation method and device in the high water cut period of the present application embodiment have the following beneficial effects:

[0037] The present invention establishes a characterization parameter group from three perspectives: the formation causes of differentiated residual oil, the contradictions of the current status of differentiated residual oil, and the effects of differentiated residual oil adjustment, and uses the principle of principal component analysis to clarify the main control factors and realize quantitative evaluation of residual oil at three levels. The invention further enriches the characterization and evaluation methods of residual oil, and can quickly, intuitively and quantitatively characterize and evaluate residual oil, which has a very practical significance for the application of the technical method of realizing hydrodynamics to further improve the recovery rate in oil fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a schematic diagram of the process of the differentiated residual oil classification characterization and quantitative evaluation method in the high water cut period of the present application embodiment;

[0039] Figure 2 This is a schematic diagram of the permeability model of the embodiment of the present application;

[0040] Figure 3 This is a schematic diagram of the permeability model of the embodiment of the present application;

[0041] Figure 4 This is a schematic diagram of the permeability model of the embodiment of the present application;

[0042] Figure 5 For Example E1f1 of this application 1-1 Small layer remaining oil formation factor diagram;

[0043] Figure 6 For Example E1f1 of this application 1-1 The contradictory diagram of the current status of the remaining oil in the small layer;

[0044] Figure 7 For Example E1f1 of this application 1-1 Distribution map of water flooding degree in small layers;

[0045] Figure 8 For Example E1f1 of this application 1-1 Small layer water flooding strength increment diagram;

[0046] Fig. 9 For Example E1f1 of this application 1-1 Small layer residual oil start-up lifting amount;

[0047] Fig.10 For Example E1f1 of this application 1-1 Small layer extrapolated reflux lift diagram. DETAILED DESCRIPTION

[0048] The present application is further described below in conjunction with the accompanying drawings and embodiments.

[0049] Embodiment 1

[0050] According to the differentiated residual oil formation cause characterization parameter group, the differentiated residual oil current contradiction characterization parameter group, the differentiated residual oil adjustment effect characterization parameter group, the differentiated residual oil classification characterization main control factor determination method, and the differentiated residual oil classification characterization comprehensive quantitative evaluation calculation method, the present application provides a differentiated residual oil classification characterization and quantitative evaluation method in the high water cut period.

[0051] like Figure 1 As shown, the embodiment of the present application provides a method for differentiated residual oil classification characterization and quantitative evaluation in the high water cut period, including: S1 establishing a differentiated residual oil characterization sample matrix; S2 standardizing differentiated residual oil characterization sample data; S3 establishing a sample data correlation coefficient matrix; S4 obtaining the eigenvalue of the sample data eigenvector; S5 determining the main controlling factors of differentiated residual oil; S6 calculating the differentiated residual oil classification characterization comprehensive quantitative evaluation value.

[0052] The specific implementation is as follows:

[0053] S1: Establishing a differentiated residual oil characterization sample matrix

[0054] The principal component analysis method uses a few unrelated comprehensive indicators to characterize various types of information, and transforms multiple variables into several unrelated variables through dimensionality reduction, thereby obtaining the principal component with the greatest difference. After comparative analysis, the principal component analysis method can effectively remove redundant variables in the data and improve the problem of slow model convergence. The process of principal component analysis is as follows.

[0055] For m observed variables X1,…,X m , the sample number matrix of n observations:

[0056]

[0057] Calculate the parameters in the parameter group of each grid node of the reservoir separately:

[0058] (1) Differentiated residual oil formation cause characterization parameter group, m = 4;

[0059] Formation factor F c : F c =K·H

[0060] Water overflow multiple C wD :

[0061] Water drive strength Q v :Q v =Q w +Q o

[0062] Extrapolated reflux PR:

[0063] (2) Differentiated remaining oil status contradiction characterization parameter group, m = 4;

[0064] Water drive strength Q v :Q v =Q w +Q o

[0065] Water flooding degree D w :

[0066] Residual oil start-up performance Δ or :Δ or =(41.493-Q v ·44.979)·e -0.0252K

[0067] Extrapolated reflux PR:

[0068] (3) Differentiated residual oil adjustment effect characterization parameter group, m = 3;

[0069] Water drive strength Qv ·S o :Q v ·S o =(Q w +Q o )·S o

[0070] Residual oil start-up performance Δ or :Δ or =(41.493-Qv·44.979)·e -0.0252K

[0071] Extrapolated reflux PR·S o :

[0072] Where: K is permeability, D; H is thickness, m; Q w is the water phase velocity, m 3 / s;Q o is the oil phase velocity, m 3 / s; V p is the pore volume; T is the reflow time at point (x, y), s; T' is the reflow time at position (x', y') after time Δt, s; S wi is the initial water saturation, f; S o is the current oil saturation, f.

[0073] S2: Standardization of Differentiated Residual Oil Characterization Sample Data

[0074] The following formula is used to standardize the sample data to eliminate the influence of dimension on parameter index:

[0075]

[0076] in: is the variable index x j The average value of s j is the scalar index x j The variance of .

[0077]

[0078] S3: Establish sample data correlation coefficient matrix

[0079] Calculate the normalized matrix y i With y j The correlation coefficient r ij , that is, the covariance matrix of the data, and establish the correlation coefficient matrix R.

[0080]

[0081] in: is the variable index y i The average value of is the variable index y j The average value of .

[0082] S4: Obtain the eigenvalues ​​of the eigenvector of the sample data

[0083] For a non-zero vector V, if it satisfies the following conditions:

[0084] R·V=λ·V

[0085] Where λ is a scalar, called an eigenvalue, and V is called the eigenvector corresponding to the eigenvalue λ. The eigenvector represents a vector that only expands and contracts without changing direction under a linear transformation. The eigenvalue represents the ratio of this expansion and contraction, that is, the eigenvector and eigenvalue of the characteristic equation |λI-R|=0 of the correlation coefficient matrix R are solved.

[0086] S5: Determine the main controlling factors of differentiated residual oil

[0087] Sort the eigenvalues ​​to satisfy λ1≥λ2≥…≥λ m ≥0, the m predictor variables are integrated into p new variables (comprehensive variables), that is:

[0088]

[0089] Among them: a i1 、a i2 、a im is the i-th comprehensive scalar, that is, the eigenvector corresponding to the eigenvalue, a ij are called principal component coefficients.

[0090] The principal component analysis method is used to calculate the differential parameter groups representing the causes of residual oil formation, the differential parameter groups representing the contradictions in the current status of residual oil, and the differential parameter groups representing the effects of residual oil adjustment, and the maximum influencing parameter in each parameter group is determined as the main controlling factor of each parameter group, namely:

[0091] The main controlling factors are:

[0092] y i j is the standardized parameter variable; a i j is the i-th comprehensive scalar, a i j is called the principal component coefficient, that is, the eigenvector corresponding to the eigenvalue; λ i is the eigenvalue; m is the number of parameters in the parameter group.

[0093] S6: Calculate the comprehensive quantitative evaluation value of differentiated residual oil classification characterization

[0094] The principal components with cumulative contribution rates greater than 85% were selected, and the characteristic values ​​were used as weight coefficients. TT was defined as the comprehensive characterization evaluation coefficient of differentiated remaining oil of each parameter group, which is specifically expressed as follows:

[0095] Comprehensive quantitative evaluation value T:

[0096] According to the differentiated remaining oil formation cause characterization parameter group, differentiated remaining oil current contradiction characterization parameter group, differentiated remaining oil adjustment effect characterization parameter group, differentiated remaining oil classification characterization main control factor determination method, differentiated remaining oil classification characterization comprehensive quantitative evaluation calculation method, this application uses the high water cut period differentiated remaining oil classification characterization and quantitative evaluation method to characterize the formation cause, current contradiction, and adjustment effect of differentiated remaining oil in the high water cut period and perform quantitative evaluation calculation to achieve a classified understanding of high water cut remaining oil. This application solves the classification characterization of high water cut remaining oil, directly improves the classification understanding of remaining oil by on-site technicians, and provides a differentiated countermeasure method for further targeted improvement of differentiated remaining oil recovery rate.

[0097] Embodiment 2

[0098] In view of the complexity of residual oil in the high water-cut stage, the present application analyzes and determines the influencing factors of each level from three levels, namely, the cause of residual oil formation, the contradiction of the current status of residual oil, and the effect of adjusting the residual oil, and establishes a characterization parameter group for each level; the principle of principal component analysis is used to analyze the influence of each parameter in the parameter group, and the main controlling factors of the cause of residual oil formation, the contradiction of the current status of residual oil, and the effect of adjusting the residual oil are determined; at the same time, the parameters of the parameter group as well as the eigenvectors and eigenvalues ​​are used to respectively establish comprehensive quantitative evaluation values ​​of the cause of residual oil formation, the contradiction of the current status of residual oil, and the effect of adjusting the residual oil, so as to realize the classification characterization and comprehensive evaluation of the main controlling factors of residual oil in different sub-layer positions in the high water-cut stage.

[0099] The specific implementation is as follows:

[0100] 1. Establishment of one injection and three extractions model

[0101] (1) Permeability design of high permeability injection and low permeability mining model

[0102] For the model of one injection and three production wells with water injection at high permeability and oil production at low permeability, the relationship between the designed permeability and injection and production wells is as follows: Figure 2 As shown, the hypertonic permeability is 300mD, the hypotonic permeability is 100mD, and the intermediate permeability is 200mD.

[0103] (2) Permeability design of low permeability injection and high permeability mining model

[0104] For the model of one injection and three production wells, water is injected at a relatively low permeability position and oil is produced at a high permeability position, the relationship between the designed permeability and the injection and production wells is as follows: Figure 3 As shown, the hypertonic permeability is 300mD, the hypotonic permeability is 100mD, and the intermediate permeability is 200mD.

[0105] (3) Permeability design of injection-production model at 90 degrees vertical direction

[0106] For the model with one injection and three production wells in vertical direction, the designed permeability and relationship between injection and production wells are as follows: Figure 4 As shown, the hypertonic permeability is 300mD, the hypotonic permeability is 100mD, and the intermediate permeability is 200mD.

[0107] 2. Characterization and evaluation of the causes of residual oil formation in one injection and three recovery

[0108] From the main component analysis table 1 of the residual oil formation of one injection and three recovery, we can see that:

[0109] (1) Under the injection-production condition at 90 degrees vertically, the main factors for the formation of residual oil are determined by all-round factors;

[0110] (2) Under high permeability injection and low permeability production, the main factors for the formation of residual oil are determined by a comprehensive range of factors;

[0111] (3) Under low-permeability injection and high-permeability production conditions, the main factors for the formation of residual oil are determined by a comprehensive range of factors.

[0112] It can be seen that the main factors for the formation of residual oil in one injection and three productions are determined by a comprehensive combination of factors. However, the water injection multiple in the vertical 90-degree direction has the greatest impact, followed by the water injection intensity. For the two modes of high-permeability injection and low-permeability production and low-permeability injection and high-permeability production, the water injection intensity is the greatest influencing factor.

[0113] Table 1. Principal component analysis of residual oil formation in one injection and three recovery

[0114]

[0115]

[0116] (4) Comprehensive comparative evaluation

[0117] For the three well patterns of one injection and three production, comprehensive evaluations were carried out under different heterogeneities. The results are shown in Table 2. When high permeability injection and low permeability production were used, the absolute value of the comprehensive evaluation was the highest, which also corresponded to the highest degree of recovery. When low permeability injection and high permeability production were used, the absolute value of the comprehensive evaluation was the lowest, which corresponded to the lowest degree of recovery. It can be seen that for the same block, the comprehensive evaluation value using the principal component analysis method can quantitatively characterize the effect of water drive on residual oil.

[0118] Table 2 Comparison of comprehensive evaluation of differentiated residual oil formation factors

[0119]

[0120] 3. Evaluation of contradictions in the status quo of remaining oil in one injection and three recovery

[0121] From the main component analysis table 3 of the remaining oil formed by one injection and three recovery, we can see that:

[0122] (1) Under the injection-production condition at 90 degrees vertically, the main factors for the formation of residual oil are determined by all-round factors;

[0123] (2) Under high permeability injection and low permeability production, the main factors for the formation of residual oil are determined by a comprehensive range of factors;

[0124] (3) Under low-permeability injection and high-permeability production conditions, the main factors for the formation of residual oil are determined by a comprehensive range of factors.

[0125] It can be seen that the main factors for the formation of residual oil in one injection and three recovery are determined by all-round factors, among which the start-up of residual oil has the greatest influence, followed by the degree of water drive as the largest influencing factor.

[0126] Table 3. Principal component analysis of the status of remaining oil in the first injection and third recovery

[0127]

[0128]

[0129] (4) Comprehensive comparative evaluation

[0130] For the three well patterns of one injection and three production, comprehensive evaluations were carried out under different heterogeneities. The results are shown in Table 4. For low-permeability injection and high-permeability production, the absolute value of the comprehensive evaluation is the highest, and the corresponding recovery degree is the lowest; for high-permeability injection and low-permeability production, the absolute value of the comprehensive evaluation is the lowest, and the corresponding recovery degree is the highest. It can be seen that for the same block, the comprehensive evaluation value using the principal component analysis method can quantitatively characterize the degree of the current water drive contradiction.

[0131] Table 4 Comparison of comprehensive evaluation of differentiated remaining oil status factors

[0132]

[0133] 4. Characterization and evaluation of the effect of one injection and three recovery of remaining oil measures

[0134] From the principal component analysis table 5 of the effect of the one injection three recovery remaining oil measures, we can see that:

[0135] (1) Under the injection-production condition at 90 degrees vertically, the main factors for the formation of residual oil are determined by all-round factors;

[0136] (2) Under high permeability injection and low permeability production, the main factors for the formation of residual oil are determined by a comprehensive range of factors;

[0137] (3) Under low-permeability injection and high-permeability production conditions, the main factors for the formation of residual oil are determined by a comprehensive range of factors.

[0138] It can be seen that the main factors affecting the effect of the one-injection-three-recovery remaining oil measure are determined by a comprehensive combination of factors, with the extrapolated reflux *SO having the greatest impact, followed by the water drive intensity *SO as the largest influencing factor.

[0139] Table 5. Principal component analysis of the effects of one injection and three recovery measures for remaining oil

[0140]

[0141]

[0142] (4) Comprehensive comparative evaluation

[0143] For the three well patterns of one injection and three production, comprehensive evaluations were carried out under different heterogeneities. The results are shown in Table 6. The comprehensive evaluation effect of liquid extraction is better than that of increased injection, and the effect of liquid extraction and increased injection is better than that of simple liquid extraction.

[0144] Table 6 Comparison of comprehensive evaluation of effect factors of differentiated residual oil measures

[0145]

[0146] The present application utilizes the principle of principal component analysis to analyze the influence of each parameter in the parameter group, and determines the main controlling factors of the cause of residual oil formation, the contradiction of the current status of residual oil, and the effect of adjusting the residual oil. At the same time, the comprehensive quantitative evaluation values ​​of the cause of residual oil formation, the contradiction of the current status of residual oil, and the effect of adjusting the residual oil are established by utilizing each parameter of the parameter group as well as the eigenvector and eigenvalue, thereby realizing the classification characterization and quantitative evaluation of differentiated residual oil in the high water cut period, and providing an effective technical method for further improving the recovery rate in the high water cut period.

[0147] Embodiment 3

[0148] The specific implementation is as follows:

[0149] 1. Characterization and evaluation of the causes of differentiated residual oil formation

[0150] The formation coefficient, water overflow ratio, water drive intensity, and extrapolated backflow parameters were dimensionless, and principal component analysis of the causes of remaining oil formation was performed. The results of solving the eigenvector and characteristic matrix are shown in Table 7. It can be seen that the principal component extrapolated backflow and permeability are the main factors in the first principal component, and the water overflow ratio and water drive intensity are the main factors in the second principal component. It can be seen that the formation of remaining oil in Chen 2 block is affected by multiple factors.

[0151] Table 7 Principal component analysis of the causes of residual oil formation in Chen 2 block

[0152] Serial number <![CDATA[Formation coefficient F c > <![CDATA[Water passing multiple C wD > <![CDATA[Water flooding intensity Q v > Extrapolated reflux PR Corresponding eigenvalues principal component 1 0.703968 -0.06862 -0.08682 -0.70156 1.347469 * 2 0.056742 0.710338 0.694621 -0.09850 1.057148 * 3 0.707837 0.024446 0.017259 0.705742 0.944953 * 4 0.013291 -0.70008 0.713909 -0.00654 0.65043 *

[0153] Note: 0 edge water area; 1 formation coefficient; 2 water overflow multiple; 3 water drive intensity; 4 extrapolated backflow; 5 unaffected by water injection;

[0154] like Figure 5 As shown, Figure 5 In the figure, 0: edge water area 1: water drive intensity 2: water drive degree 3: residual oil start-up 4: extrapolated reflux 5: water injection unaffected. The formation causes of residual oil in each position of each small layer plane are characterized, among which 4 extrapolated reflux and 5 water injection unaffected positions are areas where liquid flow turns to improve injection and production, 2 water overflow multiples area is a high water overflow multiples area, and 3 water flooding intensity area is a high-speed water flooding area. It can be seen that: E1f1 1-1 The unaffected areas of small-layer water injection are located at the high part of the fault and the local edge water area, and have not been affected by well network water injection so far; the residual oil formed by extrapolated reflux is concentrated in the local area of ​​the waist, and the reservoir properties are the main influencing factors in the residual oil-enriched area.

[0155] The remaining reserves of various main formation factors of remaining oil are statistically analyzed, and the results are shown in Table 8. It can be seen that:

[0156] (1) The area controlled by the main factor of water flooding intensity has the least remaining recoverable reserves, with an average remaining oil saturation of 0.251;

[0157] (2) The remaining recoverable reserves in the area controlled by the main factor of water overflow ratio are 100,859 tons, and the average remaining oil saturation is 0.379;

[0158] (3) The area controlled by the formation coefficient main factor has the largest remaining recoverable reserves of 57,643 tons, and the average remaining oil saturation is 0.279;

[0159] (4) The remaining recoverable reserves in the areas controlled by the main factors of extrapolated reflux and water injection are 29,097 tons and 117,242 tons, respectively. The average oil saturation of the extrapolated reflux is 0.348, and the average oil saturation of the areas not affected by water injection is 0.482.

[0160] It can be seen that the area not affected by water injection, formation coefficient and water overflow multiple are the areas with potential for remaining oil development.

[0161] Table 8 Quantitative statistics of the causes of differential residual oil formation

[0162]

[0163]

[0164] 2. Characterization and evaluation of contradictions in the status quo of differentiated remaining oil

[0165] like Figure 6 As shown, Figure 6In the middle, 0: edge water area 1: water drive intensity 2: water drive degree 3: residual oil start-up 4: extrapolation reflux 5: not affected by water injection. E1f1 1-1 The main contradictions of the small layer are the 4 extrapolated backflow contradiction and the 5 uncontrolled water injection area near the edge water position. This area is mainly concentrated on the outer side of the oil wells in the injection and production well group; the main contradiction around the water injection wells is the water drive intensity contradiction.

[0166] The statistical analysis of the current contradiction control of the remaining oil is shown in Table 9.

[0167] ① Current contradiction: The remaining geological reserves under water flooding intensity control are 35,400 tons, the remaining recoverable reserves are 5,277 tons, and the average remaining oil saturation is 0.24. The remaining recoverable reserves are small, the oil saturation is low, and the oil is in a state of no potential;

[0168] ② Current contradiction: The remaining geological reserves in the area with high water drive degree are 38,311 tons, the remaining recoverable reserves are 15,476 tons, and the average oil saturation is 0.336;

[0169] ③ Current contradiction: The remaining recoverable reserves in the remaining oil start-up area are 34,714 tons, with an average oil saturation of 0.451, which has certain potential;

[0170] ④ Current contradiction: The remaining oil extrapolation reflux area controls the remaining recoverable reserves of 136,140, ​​with an average oil saturation of 0.336, which has certain potential;

[0171] ⑤ Current contradiction: The area not affected by the injected water has a remaining recoverable reserve of 118,845 and an average oil saturation of 0.482, which is the main potential area.

[0172] Table 9 Current contradiction control remaining oil situation table

[0173] Unit number Unit Name Remaining geological reserves, t Remaining recoverable reserves, t Average oil saturation 1 Waterflooding strength 35400 5277 0.24 2 Water flooding degree 38311 15476 0.336 3 Residual oil start-up 62781 34714 0.451 4 Extrapolated reflux 344136 136140 0.336 5 Water injection not affected 219432 118845 0.482

[0174] 3. Characterization and evaluation of the effects of differentiated residual oil measures

[0175] like Figure 7-10 As shown, with the current E1f1 1-1 Based on the distribution of water drive degree in small layers, the water drive intensity increment, residual oil start-up increase, and extrapolated reflux increase at different locations are compared. It can be seen that the three indicators have achieved effective improvement, especially in the locations with relatively low water drive degree in the eastern part of the fault block (green and red areas).

[0176] The present application provides a differentiated residual oil classification, characterization and quantitative evaluation method for high water content period, which further enriches the characterization and evaluation methods of residual oil and can quickly, intuitively and quantitatively characterize and evaluate the residual oil. It has very practical significance for the application of technical methods for realizing hydrodynamics to further improve the recovery rate in oil fields.

[0177] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for characterizing and quantitatively evaluating differentiated remaining oil in high water cut period, characterized in that: include: S1, establish a sample matrix for differential residual oil characterization; S2, data standardization of differential residual oil characterization samples; S3, establish the sample data correlation coefficient matrix; S4, obtaining the eigenvalue of the eigenvector of the sample data; S5, determine the main controlling factors of differentiated residual oil; S6, calculate the comprehensive quantitative evaluation value of differentiated remaining oil classification characterization.

2. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to claim 1 is characterized in that: In step S1, the establishment of the differentiated remaining oil characterization sample matrix includes calculating the parameters in the characterization parameter group of each grid node of the reservoir: the differentiated remaining oil formation cause characterization parameter group, the differentiated remaining oil current contradiction characterization parameter group, and the differentiated remaining oil adjustment effect characterization parameter group.

3. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to claim 2 is characterized in that: In step S1, the formation factor F is determined c , water multiple C wD , water drive strength Q v The four parameters of extrapolated reflux degree PR are the characterization parameter group of the causes of differential residual oil formation, and the formula is: Formation factor F c :F c =K·H Water overflow multiple C wD : Water flooding strength Q v :Q v =Q w +Q o Extrapolated reflux PR: Where: K is permeability; H is thickness; Q w is the water phase velocity; Q o is the oil phase velocity; V p is the pore volume; T is the reflow time at point (x, y); T' is the reflow time at position (x', y') after time Δt.

4. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to claim 2 is characterized in that: In step S1, the differentiated remaining oil status is shown in the current remaining oil control status, using the water flooding intensity Q v , Water drive degree D w , Residual oil start-up performance Δ or The four parameters of extrapolated reflux degree PR are the characterization parameter groups of differentiated remaining oil status contradictions, and the formula is: Water flooding strength Q v :Q v =Q w +Q o Water flooding degree D w : Residual oil starting performance Δor: Δor = (41.493-Qv·44.979)·e -0.0252K Extrapolated reflux PR: Where: S wi is the initial water saturation; S o is the current oil saturation.

5. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to claim 2 is characterized in that: In step S1, the differential remaining oil adjustment effect is manifested in the improvement of the current remaining oil control status, using the water flooding intensity Q v ·S o , Residual oil start-up performance Δ or , Extrapolated reflux degree PR·S o The three parameters are used to differentiate the residual oil measures effect parameter characterization group, and the formula is: Water flooding strength Q v ·S o :Q v ·S o =(Q w +Q o )·S o Residual oil starting performance Δor: Δor = (41.493-Qv·44.979)·e -0.0252K Extrapolated reflux PR·S o :

6. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to any one of claims 1 to 5, characterized in that: In step S2, the sample data is standardized using the following formula: in: is the variable index x j The average value of sj is the variance of the scalar indicator xj, 7. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to any one of claims 1 to 5, characterized in that: In step S3, the correlation coefficient matrix R is established and the y in the standardized matrix is ​​calculated. i With y j The correlation coefficient r ij , the formula is: in: is the variable index y i The average value of is the average value of the variable index yj.

8. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to any one of claims 1 to 5, characterized in that: In step S4, for a non-zero vector V, it satisfies the following conditions, R·V=λ·V, Where λ is a scalar, called the eigenvalue, and V is called the eigenvector corresponding to the eigenvalue λ. Solve the characteristic equation of the correlation coefficient matrix R and find the eigenvector and eigenvalue of λI-R=0.

9. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to any one of claims 1 to 5, characterized in that: In step S5, the principal component analysis method is used to calculate the differential remaining oil formation cause characterization parameter group, the differential remaining oil current contradiction characterization parameter group, and the differential remaining oil adjustment effect characterization parameter group, and the maximum influencing parameter in each parameter group is determined as the main controlling factor of each characterization parameter group, that is: The main effect factors are: y i j is the standardized parameter variable, a i j is the i-th comprehensive scalar, a i j is called the principal component coefficient, that is, the eigenvector corresponding to the eigenvalue; λ i is the eigenvalue; m is the number of parameters in the parameter group.

10. The method for differential classification, characterization and quantitative evaluation of residual oil in high water cut period according to any one of claims 1 to 5, characterized in that: In step S6, the principal component with the cumulative contribution rate greater than 85% is selected, and the characteristic value is used as the weight coefficient. TT is defined as the differentiated residual oil comprehensive characterization evaluation coefficient of each parameter group, and the expression is:

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