# Optimization of EOR Displacement Methods Based on Multiple Factor Analysis

Authors: Zhongcheng Li; Zhidong Bao; Li Chen; Hongyu Zhao; Zenglai Jiang; Hairui Wu; Wanchun Zhao
Journal: Geofluids
 (2022)

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## Abstract

In order to ensure that the new block can select the best displacement method, this paper determines 23 key reservoir basic parameters based on the statistical analysis of the field application of the tertiary oil recovery displacement method in typical blocks at home and abroad. The best displacement method is selected by the fuzzy evaluation method, and the correlation degree between the target block and the typical block is calculated by the improved Deng correlation method; then, the ultimate recovery rate of the target block is determined. Taking a new block of an oil field in China as an example, the optimal displacement method of three typical blocks of polymer flooding, burning oil layer flooding, and ternary composite flooding is selected by the fuzzy evaluation method; then, the improved Deng correlation method calculates that the final recovery rate of the new block using burning oil layer flooding is the tallest, and the burning oil layer flooding is selected the best way to replace the block. Based on this, the optimal results of displacement method are analyzed when porosity and air permeability of the new block reservoir are changed. The method proposed in this paper provides a calculation basis for the optimization of displacement method of the new blocks.


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## Body

## 1. Introduction

As the main energy, oil plays an important role in the world economy and the social development [1, 2]. Since oil is a typical nonrenewable energy, the effective exploration and efficient extraction of oil and natural gas have always been hot topics in the pursuit of international research. At present, the horizontal well volume fracturing technology is mainly used in the unconventional oil and gas production [3, 4], and the conventional oil and gas mostly use the steam flooding, carbon dioxide flooding, and chemical flooding, also known as the tertiary oil recovery technology [5, 6]. Because tertiary recovery technology of the conventional oil and gas is relatively mature [7–11], especially in the context of the continuous collapse of international oil prices, it is great significance and economic benefits to carry out the tertiary recovery technology to improve oil and gas recovery [12]. Because the displacement method is affected and restricted by many factors, which displacement method can improve oil recovery to the greatest extent in some blocks has not formed a unified optimization method, which seriously restricts the efficient development of oil and gas [13–20]. In order to ensure that different target blocks can select the best displacement method, this paper proposes a method based on multiple factor analysis to optimize the EOR displacement method.The flow chart of optimization method for the displacement method of tertiary oil recovery to enhance oil recovery is shown in Figure1. Under different displacement modes, the comprehensive scores of 23 reservoir parameters of the target oilfield are calculated by the fuzzy evaluation method, and the displacement modes suitable for the target block are selected. Using the improved Deng correlation method, the correlation degree of specific parameters between the target block and the typical block is analyzed. According to the correlation degree, the best matching typical block with the target block is selected, and the ratio of geological reserves is used to predict the final recovery factor of the target block and to calculate adapted production data of the target block. The study of this paper provides an important reference for the rapid optimization of the displacement method of the new block. The results have important academic value.Figure 1
The flow chart of optimization method for displacement mode of tertiary oil recovery to enhance oil recovery.


## 2. Fine Quantitative Screening Method for Tertiary Oil Recovery Technology

Combined with the current situation and trend of the tertiary oil recovery technology, drawing lessons from the classification standards formulated by various oil fields and industries, and based on the main reservoir and fluid characteristic parameters of typical field tests, 23 specific reservoir parameters are selected as the key classification indexes. According to the fine quantitative screening criteria, the reservoir parameters formed by 9 kinds of EOR methods, polymer flooding, gravity flooding, alkali polymer binary flooding, polymer surface binary flooding, ternary composite flooding, miscible gas flooding, immiscible gas flooding, burning oil layer flooding, and steam flooding, should be divided according to the importance of different EOR methods, which is helpful for EOR; the results are more accurate.


### 2.1. Establishment of Fine Quantitative Screening Model

The fine quantitative screening method of tertiary oil recovery technology is mainly based on 23 specific reservoir conditions to comprehensively score the feasibility of each kind of enhanced oil recovery technology, which is helpful for the preliminary screening and evaluation of the tertiary oil recovery method in the early stage of oilfield planning when the reservoir needs rapid evaluation or the reservoir parameters are incomplete. The model is calculated by the fuzzy change in the fuzzy relationship, and the comprehensive scoring process is as follows:Let the setU=xixi∈23specificreservoirparameters. Set V=yiyi∈9waysofEORanddisplacement. Among them, the direct product of set U and V:U∗V=xi,yixi∈23reservoirparameters,thefuzzysubsetRin9kindsoftertiaryfloodingmethods, is called the binary fuzzy relation between u and V, which is expressed by matrix as follows:
(1)R=μx1,y1μx1,y2⋯μx1,ynμx2,y1μx2,y2⋯μx2,yn⋮⋮⋱⋮μxm,y1μxm,y2⋯μxm,yn,A=a1,a2,⋯,am,S=A⋅R=a1,a2,⋯,am⋅μx1,y1μx1,y2⋯μx1,ynμx2,y1μx2,y2⋯μx2,yn⋮⋮⋱⋮μxm,y1μxm,y2⋯μxm,yn=S1,S2,⋯,Sn,where Si=a1∧μx1,yi∨a2∧μx2,yi∨a3∧μx3,yi∨⋯∨an∧μxn,yi and ai,μx1,yi∈0,1. S is the comprehensive scoring result of screening (Si stands for the scoring result of the ith oil displacement method); A1, A2,....,An is the result of single parameter scoring according to the screening standard, which represents the proportion of the ith reservoir screening parameter in the j third oil recovery and displacement method.In this model, the comprehensive scoring results of different EOR methods are in the range of (0,1). There is a positive correlation between the comprehensive scoreSi and the adaptability of the tertiary oil recovery method. The larger the comprehensive score Si is, the higher the adaptability of the representative prediction block and the tertiary oil recovery method is, and the more the tertiary oil recovery method can be used to exploit the prediction interval. In this paper, the tertiary oil recovery method with a comprehensive score higher than 0.5 in the screening prediction block is put into the preselection scheme, which is analyzed and screened by the potential evaluation in the later stage.


### 2.2. Formulation of Fine Quantitative Screening Standards

In the process of tertiary oil recovery, when conducting fine quantitative evaluation for different oil displacement methods, there are differences in the factors that need to be considered when selecting different tertiary oil recovery methods, so the proportion of specific parameters of each reservoir in different tertiary oil recovery methods is also different, such as polymer flooding does not need to consider the gas source of evaluation block and single reservoir coefficient. Therefore, it is necessary to formulate the corresponding fine quantitative screening standards for different tertiary oil recovery technologies and divide the proportion of screening standards, so as to facilitate the comprehensive scoring of the feasibility of tertiary oil recovery. According to extensive investigation and expert argumentation, there are 23 selection parameters in total, as shown in Table1.Table 1
Summary of screening parameters.
Serial numberParameter nameUnitRangesParameter category1Reservoir typeGeological parameters2Rock characteristicsGeological parameters3Reservoir depthm0~10000Geological parameters4Reservoir pressureMPaGeological parameters5Reservoir temperature°C0~200Geological parameters6Average effective thickness of single layerm0~250Geological parameters7Net to gross ratiof0~1Geological parameters8Porosity%0~100Geological parameters9Air permeability10-3 μm20~30000Geological parameters10Oil saturation%0~100Geological parameters11Permeability variation coefficientf0~1Geological parameters12Bottom water influenceGeological parameters13Side water impactGeological parameters14Crack/caveGeological parameters15Formation dipGeological parameters16Gas sourceGeological parameters17Upper and lower compartments and tube closureGeological parameters18Single storage coefficient104 t/(km2·m)0~150Geological parameters19Formation crude oil viscositymPa·s0~100000Fluid parameters20Crude oil densityg/cm30.5~1Fluid parameters21Acid value of crude oilmgKOH/g0~40Fluid parameters22Formation water salinitymg/L500~300000Fluid parameters23Divalent ion contentmg/L0~5000Fluid parametersStrict fine quantitative screening criteria can reduce investment risk but may also make the screening potential low; the selection of too wide screening criteria is the opposite. Because the evaluation of tertiary oil recovery potential mainly depends on model prediction and calculation, the fine quantitative screening standard is only to eliminate some obviously unsuitable EOR methods and reduce unnecessary workload. At the same time, due to the different screening criteria under different EOR flooding modes, the important influence parameters considered are also different. Therefore, for the sake of insurance, a wide selection standard should be selected to avoid missing the applicable EOR methods.


### 2.3. Process of Fine Quantitative Screening Method

Firstly, according to different EOR methods, the corresponding fine quantitative screening criteria are determined, and the proportion of parameters in different reservoir influence is divided. Identify the key influence parameters, and give a reasonable proportion of the parameters according to the different influence parameter selection standard ranges of the evaluation block. Then, the proportion of single parameter is determined according to the single parameter for different EOR methods, and according to this proportion, the fuzzy change in fuzzy relation is used to calculate the comprehensive scoring results of the evaluation block under different EOR methods. Finally, the oil displacement method with the comprehensive score greater than 0.5 is selected as the alternative scheme of tertiary oil recovery in the prediction block. This plays an important role in the rapid basic analysis of the block and the detailed technical potential assessment in the later stage.


## 2.1. Establishment of Fine Quantitative Screening Model

The fine quantitative screening method of tertiary oil recovery technology is mainly based on 23 specific reservoir conditions to comprehensively score the feasibility of each kind of enhanced oil recovery technology, which is helpful for the preliminary screening and evaluation of the tertiary oil recovery method in the early stage of oilfield planning when the reservoir needs rapid evaluation or the reservoir parameters are incomplete. The model is calculated by the fuzzy change in the fuzzy relationship, and the comprehensive scoring process is as follows:Let the setU=xixi∈23specificreservoirparameters. Set V=yiyi∈9waysofEORanddisplacement. Among them, the direct product of set U and V:U∗V=xi,yixi∈23reservoirparameters,thefuzzysubsetRin9kindsoftertiaryfloodingmethods, is called the binary fuzzy relation between u and V, which is expressed by matrix as follows:
(1)R=μx1,y1μx1,y2⋯μx1,ynμx2,y1μx2,y2⋯μx2,yn⋮⋮⋱⋮μxm,y1μxm,y2⋯μxm,yn,A=a1,a2,⋯,am,S=A⋅R=a1,a2,⋯,am⋅μx1,y1μx1,y2⋯μx1,ynμx2,y1μx2,y2⋯μx2,yn⋮⋮⋱⋮μxm,y1μxm,y2⋯μxm,yn=S1,S2,⋯,Sn,where Si=a1∧μx1,yi∨a2∧μx2,yi∨a3∧μx3,yi∨⋯∨an∧μxn,yi and ai,μx1,yi∈0,1. S is the comprehensive scoring result of screening (Si stands for the scoring result of the ith oil displacement method); A1, A2,....,An is the result of single parameter scoring according to the screening standard, which represents the proportion of the ith reservoir screening parameter in the j third oil recovery and displacement method.In this model, the comprehensive scoring results of different EOR methods are in the range of (0,1). There is a positive correlation between the comprehensive scoreSi and the adaptability of the tertiary oil recovery method. The larger the comprehensive score Si is, the higher the adaptability of the representative prediction block and the tertiary oil recovery method is, and the more the tertiary oil recovery method can be used to exploit the prediction interval. In this paper, the tertiary oil recovery method with a comprehensive score higher than 0.5 in the screening prediction block is put into the preselection scheme, which is analyzed and screened by the potential evaluation in the later stage.


## 2.2. Formulation of Fine Quantitative Screening Standards

In the process of tertiary oil recovery, when conducting fine quantitative evaluation for different oil displacement methods, there are differences in the factors that need to be considered when selecting different tertiary oil recovery methods, so the proportion of specific parameters of each reservoir in different tertiary oil recovery methods is also different, such as polymer flooding does not need to consider the gas source of evaluation block and single reservoir coefficient. Therefore, it is necessary to formulate the corresponding fine quantitative screening standards for different tertiary oil recovery technologies and divide the proportion of screening standards, so as to facilitate the comprehensive scoring of the feasibility of tertiary oil recovery. According to extensive investigation and expert argumentation, there are 23 selection parameters in total, as shown in Table1.Table 1
Summary of screening parameters.
Serial numberParameter nameUnitRangesParameter category1Reservoir typeGeological parameters2Rock characteristicsGeological parameters3Reservoir depthm0~10000Geological parameters4Reservoir pressureMPaGeological parameters5Reservoir temperature°C0~200Geological parameters6Average effective thickness of single layerm0~250Geological parameters7Net to gross ratiof0~1Geological parameters8Porosity%0~100Geological parameters9Air permeability10-3 μm20~30000Geological parameters10Oil saturation%0~100Geological parameters11Permeability variation coefficientf0~1Geological parameters12Bottom water influenceGeological parameters13Side water impactGeological parameters14Crack/caveGeological parameters15Formation dipGeological parameters16Gas sourceGeological parameters17Upper and lower compartments and tube closureGeological parameters18Single storage coefficient104 t/(km2·m)0~150Geological parameters19Formation crude oil viscositymPa·s0~100000Fluid parameters20Crude oil densityg/cm30.5~1Fluid parameters21Acid value of crude oilmgKOH/g0~40Fluid parameters22Formation water salinitymg/L500~300000Fluid parameters23Divalent ion contentmg/L0~5000Fluid parametersStrict fine quantitative screening criteria can reduce investment risk but may also make the screening potential low; the selection of too wide screening criteria is the opposite. Because the evaluation of tertiary oil recovery potential mainly depends on model prediction and calculation, the fine quantitative screening standard is only to eliminate some obviously unsuitable EOR methods and reduce unnecessary workload. At the same time, due to the different screening criteria under different EOR flooding modes, the important influence parameters considered are also different. Therefore, for the sake of insurance, a wide selection standard should be selected to avoid missing the applicable EOR methods.


## 2.3. Process of Fine Quantitative Screening Method

Firstly, according to different EOR methods, the corresponding fine quantitative screening criteria are determined, and the proportion of parameters in different reservoir influence is divided. Identify the key influence parameters, and give a reasonable proportion of the parameters according to the different influence parameter selection standard ranges of the evaluation block. Then, the proportion of single parameter is determined according to the single parameter for different EOR methods, and according to this proportion, the fuzzy change in fuzzy relation is used to calculate the comprehensive scoring results of the evaluation block under different EOR methods. Finally, the oil displacement method with the comprehensive score greater than 0.5 is selected as the alternative scheme of tertiary oil recovery in the prediction block. This plays an important role in the rapid basic analysis of the block and the detailed technical potential assessment in the later stage.


## 3. Rapid Analogy Evaluation Method of Tertiary Oil Recovery Potential

The fine quantitative screening method of tertiary oil recovery technology starts from the actual field parameters and preliminarily excludes the unsuitable oil displacement methods in the study block, which plays a guiding role in the preliminary screening of the actual oil displacement methods in the oilfield. In the past oilfield development process, there are a large number of successful cases of EOR, which can also play a guiding role for the study block. Therefore, based on the fine quantitative screening method of tertiary oil recovery technology, the rapid analogy evaluation method of tertiary oil recovery can be adopted.The rapid analogy evaluation method of tertiary oil recovery potential takes the technical and economic effect database of the field target block of tertiary oil recovery in China as an important reference basis and provides a convenient method for rapid evaluation and prediction of the corresponding tertiary oil recovery technology and economic potential evaluation of the block. This method is mainly to improve the Deng association method in data statistical analysis. According to the 23 basic reservoir parameters entered by the user in the target block, the comprehensive analysis of the parameters of the analogy target block and the typical block is carried out to obtain the association degree between the target block and each corresponding typical block. The user can select and determine the most matching target block with the analogy typical block according to the association degree and then select the best matching target block with the analogy typical block through the annual production and injection data of the target block which are predicted by using the ratio of geological reserves, and then, the evaluation results of the tertiary oil recovery technology of the target block are obtained.


### 3.1. Establishment of Quick Analogy Evaluation Model

The establishment of the rapid analogy evaluation model of the tertiary oil recovery potential is mainly to calculate the correlation degree of the changes of parameters between the target block and the typical block by improving the Deng correlation method, so as to select the suitable mode of the tertiary oil recovery and displacement in the target block. The improved Deng association method provides a quantitative measurement for the parameter change situation, which is very suitable for dynamic process analysis. In the process of parameter analogy, if the trend of parameter change in two blocks is consistent, that is, the synchronous change is high, at this time, the correlation between the typical block and the target block is high [21]. The theoretical model is as follows.First of all, the parameters of all typical blocks in multiple factor statistics are scored into five gears, namely, 0, 0.25, 0.5, 0.75, and 1, and recorded asXi, that is, Xi=x1i,x2i,x3i⋯xni.Mark the parameters of the target block according to the standard of the typical block, and record asX0, that is, X0=x10,x20,x30,⋯xn0.


#### 3.1.1. Calculation of Correlation Coefficient

Correlation coefficient plays a very important role in the process of measuring the correlation degree of each parameter. In the target blockX0 and several typical blocks Xi, the Deng correlation method can be used to calculate the correlation coefficient of the kth key reservoir basic parameters of the target block and each typical block [21, 22]:
(2)yik=a+Aξ△ik+Aξ,where Δik=xki−x0ik=1,2⋯n,i=1,2⋯m, which represents the absolute difference of the basic parameters of the kth key reservoir between the target block and the ith typical block; a=min1≤k≤nmin1≤j≤mΔik represents the minimum value of absolute difference of basic parameters; a=max1≤k≤nmax1≤j≤mΔik represents the maximum value of absolute difference of basic parameters; and ξ is the resolution coefficient, which is used to improve the significance of the difference between the correlation coefficients. Generally, ξ=0.5 [22, 23].


#### 3.1.2. Correlation Calculation

Association degree is an index used to measure the association degree of target block and typical block.The original Deng correlation algorithm is(3)Ri=1n∑k=1nyiK.In practical work, the importance of key reservoir parameters in different tertiary oil recovery processes is different. When calculating the correlation degree, we should consider the importance of reservoir parameters in different EOR displacement methods to accurately correlate the results, so we need to improve the original Deng correlation degree algorithm to accurately score the results.The improved Deng algorithm is as follows:(4)Ri=∑k=1nWi∗yiK,where Wi is the weight value of the ith key reservoir parameter, which is given according to the situation of different tertiary oil recovery and displacement methods.The result of correlation degree is 0~1. In this paper, we set the boundary of correlation degree as 0.8, and the correlation degree lower than 0.8 indicates that there is a big difference between the two blocks, which will not be considered; from the typical blocks with correlation degree higher than 0.8, we select the typical block with the highest correlation degree as the analogy block.


### 3.2. Assessment Process of Rapid Analogy Potential

First of all, based on the summary of the block data that has completed the field test of tertiary oil recovery, a field case database of different tertiary oil recovery technologies in China is formed. Then, 23 representative basic reservoir parameters are determined. After that, according to the different ranges of screening criteria for different influence parameters in the block, different parameters are scored as 0, 0.25, 0.5, 0.75, and 1. The improved Deng correlation degree is calculated between the target block and the typical block in the database, and the correlation degree between the target block and the typical block is obtained by normalization, and the best matching typical block is optimized and determined. Finally, the annual injection and production data can be obtained by analogy of the proportion of geological reserves, which can quickly evaluate the tertiary oil recovery potential of the target block.


#### 3.2.1. Recovery Prediction

After the correlation degree (RD) between the target block and each typical block is obtained from the rapid potential evaluation analysis, the range of recovery factorX of the target block can be determined according to the correlation degree (RD) and the original recovery factor (OR) of the target block. The specific calculation is as follows:
(5)RD∗OR≤X≤2−RD∗OR.The predicted oil recovery from this formula is in the form of interval fluctuation. At this time, the smaller the correlation between the target block and the typical block, the larger the prediction range of oil recovery, and the more inaccurate the prediction result; the larger the correlation between the target block and the typical block, the smaller the prediction range of oil recovery, and the more accurate the prediction result. When the correlation is 1, the predicted recovery is equal to the original recovery of the target block.


#### 3.2.2. Potential Prediction

After determining the best typical block according to the target block, the production dataX2 of the typical block can be enlarged or reduced corresponding to the ratio of the produced geological reserves y1 of the target block to the produced geological reserves y2 of the typical block, so as to adapt to the production data X1 of the target block. The specific formula is as follows:
(6)X1=X2∗y1y2.The production data of the block includes injection parameters such as water injection and polymer injection and output parameters such as oil production, gas production, and water production. According to the data, the specific tertiary oil recovery method and production plan suitable for the block are determined to achieve the best results.


## 3.1. Establishment of Quick Analogy Evaluation Model

The establishment of the rapid analogy evaluation model of the tertiary oil recovery potential is mainly to calculate the correlation degree of the changes of parameters between the target block and the typical block by improving the Deng correlation method, so as to select the suitable mode of the tertiary oil recovery and displacement in the target block. The improved Deng association method provides a quantitative measurement for the parameter change situation, which is very suitable for dynamic process analysis. In the process of parameter analogy, if the trend of parameter change in two blocks is consistent, that is, the synchronous change is high, at this time, the correlation between the typical block and the target block is high [21]. The theoretical model is as follows.First of all, the parameters of all typical blocks in multiple factor statistics are scored into five gears, namely, 0, 0.25, 0.5, 0.75, and 1, and recorded asXi, that is, Xi=x1i,x2i,x3i⋯xni.Mark the parameters of the target block according to the standard of the typical block, and record asX0, that is, X0=x10,x20,x30,⋯xn0.


### 3.1.1. Calculation of Correlation Coefficient

Correlation coefficient plays a very important role in the process of measuring the correlation degree of each parameter. In the target blockX0 and several typical blocks Xi, the Deng correlation method can be used to calculate the correlation coefficient of the kth key reservoir basic parameters of the target block and each typical block [21, 22]:
(2)yik=a+Aξ△ik+Aξ,where Δik=xki−x0ik=1,2⋯n,i=1,2⋯m, which represents the absolute difference of the basic parameters of the kth key reservoir between the target block and the ith typical block; a=min1≤k≤nmin1≤j≤mΔik represents the minimum value of absolute difference of basic parameters; a=max1≤k≤nmax1≤j≤mΔik represents the maximum value of absolute difference of basic parameters; and ξ is the resolution coefficient, which is used to improve the significance of the difference between the correlation coefficients. Generally, ξ=0.5 [22, 23].


### 3.1.2. Correlation Calculation

Association degree is an index used to measure the association degree of target block and typical block.The original Deng correlation algorithm is(3)Ri=1n∑k=1nyiK.In practical work, the importance of key reservoir parameters in different tertiary oil recovery processes is different. When calculating the correlation degree, we should consider the importance of reservoir parameters in different EOR displacement methods to accurately correlate the results, so we need to improve the original Deng correlation degree algorithm to accurately score the results.The improved Deng algorithm is as follows:(4)Ri=∑k=1nWi∗yiK,where Wi is the weight value of the ith key reservoir parameter, which is given according to the situation of different tertiary oil recovery and displacement methods.The result of correlation degree is 0~1. In this paper, we set the boundary of correlation degree as 0.8, and the correlation degree lower than 0.8 indicates that there is a big difference between the two blocks, which will not be considered; from the typical blocks with correlation degree higher than 0.8, we select the typical block with the highest correlation degree as the analogy block.


## 3.1.1. Calculation of Correlation Coefficient

Correlation coefficient plays a very important role in the process of measuring the correlation degree of each parameter. In the target blockX0 and several typical blocks Xi, the Deng correlation method can be used to calculate the correlation coefficient of the kth key reservoir basic parameters of the target block and each typical block [21, 22]:
(2)yik=a+Aξ△ik+Aξ,where Δik=xki−x0ik=1,2⋯n,i=1,2⋯m, which represents the absolute difference of the basic parameters of the kth key reservoir between the target block and the ith typical block; a=min1≤k≤nmin1≤j≤mΔik represents the minimum value of absolute difference of basic parameters; a=max1≤k≤nmax1≤j≤mΔik represents the maximum value of absolute difference of basic parameters; and ξ is the resolution coefficient, which is used to improve the significance of the difference between the correlation coefficients. Generally, ξ=0.5 [22, 23].


## 3.1.2. Correlation Calculation

Association degree is an index used to measure the association degree of target block and typical block.The original Deng correlation algorithm is(3)Ri=1n∑k=1nyiK.In practical work, the importance of key reservoir parameters in different tertiary oil recovery processes is different. When calculating the correlation degree, we should consider the importance of reservoir parameters in different EOR displacement methods to accurately correlate the results, so we need to improve the original Deng correlation degree algorithm to accurately score the results.The improved Deng algorithm is as follows:(4)Ri=∑k=1nWi∗yiK,where Wi is the weight value of the ith key reservoir parameter, which is given according to the situation of different tertiary oil recovery and displacement methods.The result of correlation degree is 0~1. In this paper, we set the boundary of correlation degree as 0.8, and the correlation degree lower than 0.8 indicates that there is a big difference between the two blocks, which will not be considered; from the typical blocks with correlation degree higher than 0.8, we select the typical block with the highest correlation degree as the analogy block.


## 3.2. Assessment Process of Rapid Analogy Potential

First of all, based on the summary of the block data that has completed the field test of tertiary oil recovery, a field case database of different tertiary oil recovery technologies in China is formed. Then, 23 representative basic reservoir parameters are determined. After that, according to the different ranges of screening criteria for different influence parameters in the block, different parameters are scored as 0, 0.25, 0.5, 0.75, and 1. The improved Deng correlation degree is calculated between the target block and the typical block in the database, and the correlation degree between the target block and the typical block is obtained by normalization, and the best matching typical block is optimized and determined. Finally, the annual injection and production data can be obtained by analogy of the proportion of geological reserves, which can quickly evaluate the tertiary oil recovery potential of the target block.


### 3.2.1. Recovery Prediction

After the correlation degree (RD) between the target block and each typical block is obtained from the rapid potential evaluation analysis, the range of recovery factorX of the target block can be determined according to the correlation degree (RD) and the original recovery factor (OR) of the target block. The specific calculation is as follows:
(5)RD∗OR≤X≤2−RD∗OR.The predicted oil recovery from this formula is in the form of interval fluctuation. At this time, the smaller the correlation between the target block and the typical block, the larger the prediction range of oil recovery, and the more inaccurate the prediction result; the larger the correlation between the target block and the typical block, the smaller the prediction range of oil recovery, and the more accurate the prediction result. When the correlation is 1, the predicted recovery is equal to the original recovery of the target block.


### 3.2.2. Potential Prediction

After determining the best typical block according to the target block, the production dataX2 of the typical block can be enlarged or reduced corresponding to the ratio of the produced geological reserves y1 of the target block to the produced geological reserves y2 of the typical block, so as to adapt to the production data X1 of the target block. The specific formula is as follows:
(6)X1=X2∗y1y2.The production data of the block includes injection parameters such as water injection and polymer injection and output parameters such as oil production, gas production, and water production. According to the data, the specific tertiary oil recovery method and production plan suitable for the block are determined to achieve the best results.


## 3.2.1. Recovery Prediction

After the correlation degree (RD) between the target block and each typical block is obtained from the rapid potential evaluation analysis, the range of recovery factorX of the target block can be determined according to the correlation degree (RD) and the original recovery factor (OR) of the target block. The specific calculation is as follows:
(5)RD∗OR≤X≤2−RD∗OR.The predicted oil recovery from this formula is in the form of interval fluctuation. At this time, the smaller the correlation between the target block and the typical block, the larger the prediction range of oil recovery, and the more inaccurate the prediction result; the larger the correlation between the target block and the typical block, the smaller the prediction range of oil recovery, and the more accurate the prediction result. When the correlation is 1, the predicted recovery is equal to the original recovery of the target block.


## 3.2.2. Potential Prediction

After determining the best typical block according to the target block, the production dataX2 of the typical block can be enlarged or reduced corresponding to the ratio of the produced geological reserves y1 of the target block to the produced geological reserves y2 of the typical block, so as to adapt to the production data X1 of the target block. The specific formula is as follows:
(6)X1=X2∗y1y2.The production data of the block includes injection parameters such as water injection and polymer injection and output parameters such as oil production, gas production, and water production. According to the data, the specific tertiary oil recovery method and production plan suitable for the block are determined to achieve the best results.


## 4. Case Analysis

In order to verify whether the established method in this paper can achieve the desired objectives, the following tertiary oil recovery technique fine quantitative screening method and tertiary oil recovery potential fast analogy evaluation method were verified. Firstly, the suitable tertiary oil displacement mode in the target block is selected according to the fuzzy evaluation method. Then, three case blocks are optimized which are suitable for displacement mode in target block, and the potential of target block is evaluated and analyzed.In the fine quantitative screening method of tertiary oil recovery technology, the fuzzy evaluation method is used to comprehensively score 23 reservoir parameters in the target block under different displacement modes, and the scoring results are shown in Figure2. It can be seen from the analysis that the comprehensive scores of the target block in gravity flooding, alkali polymer binary flooding, polymer surface binary flooding, miscible gas flooding, immiscible gas flooding, and steam flooding are all lower than 0.5. Therefore, the above six oil displacement methods are not suitable for tertiary recovery development in the block. The comprehensive score of the target block in polymer flooding, ternary compound flooding, and burning oil layer flooding is higher than 0.5, so polymer flooding, ternary compound flooding, and burning oil layer flooding displacement can be selected as the development means of tertiary oil recovery in this block, but which displacement mode is selected still needs quantitative analysis of potential evaluation.Figure 2
Comprehensive scoring results of displacement method screening.The blocks A, B, and C with polymer flooding, ternary composite flooding, and burning oil layer flooding displacement mode are selected as typical blocks in the tertiary recovery potential rapid analogy evaluation method, and the specific parameters of target blocks A, B, and C and target blocks are shown in Table2. First of all, the specific reservoir parameters of the target block are scored as 0, 0.25, 0.5, 0.75, and 1 under the displacement mode of different example blocks, as shown in Figures 3–5. Then, through the improved Deng correlation method to solve the correlation degree between the target block and the example block, the analysis shows that the correlation between target block and typical blocks A, B, and C is 0.275, 0.912, and 0.484, respectively. There is a higher correlation between target block and typical block B. In the actual production process, typical block B can be selected as a reference objective: to use the oil displacement method of burning oil layer flooding as the main development means to ensure that the target block can achieve the optimal production effect. As the recovery rate of block B can reach 35.87% in the process of tertiary oil recovery, the final recovery rate of block B is between 35.88% and 45.20% predicted and evaluated by software after calculation. The actual EOR of the target block is 36.62%. Compared with the predicted EOR interval value, the result is within the effective range of the analogy result, which proves the accuracy of the evaluation result.Table 2
Analytical data of examples.
Evaluation parameters (quantitative scoring)Typical block ATypical block BTypical block CTarget blockOil displacement modePolymer floodingBurning oil layer and steam floodingTernary composite floodingTo be matchedReservoir typeAssembly and rules to expand the block of the application well networkAssembly and rules to expand the block of the application well networkAssembly and rules to expand the block of the application well networkAssembly and rules to expand the block of the application well networkRock characteristicsConglomerateConglomerateCarbonatiteConglomerateReservoir depth (m)2330130026222313Reservoir pressure (MPa)Greater than or equal to the minimum miscible pressureGreater than or equal to the minimum miscible pressureGreater than or equal to the minimum miscible pressureGreater than or equal to the minimum miscible pressureReservoir temperature (°C)78708291Average effective thickness of single layer (m)10.23.79.12.8Net to gross ratio (f)0.580.520.640.68Porosity (%)15212333Air permeability (10-3 μm2)325250320135Oil saturation (%)58302627Permeability variation coefficient (f)0.530.600.630.57Bottom water influenceSmallNoNoSmallSide water impactNoSmallNoSmallCrack/caveSmallSmallSmallBigFormation dip6181233Gas sourceNoNoNoAirUpper and lower compartments and tube closureBasic closureCompletely closedBasic closureCompletely closedSingle storage coefficient (104 t/(km2·m))16182015Formation crude oil viscosity (MPa·s)5890012070Crude oil density (g/cm3)0.690.500.850.56Acid value of crude oil (mgKOH/g)16.6228.8811.1512.43Formation water salinity (mg/L)1221251325231231872Divalent ion content (mg/L)5602319130Enhanced oil recovery (%)26.5435.8731.22Treatment testFigure 3
Scoring results of main reservoir parameters of target block and typical block A under polymer flooding mode.Figure 4
Scoring results of main reservoir parameters of target block and typical block B under polymer flooding mode.Figure 5
Scoring results of main reservoir parameters of target block and typical block C under polymer flooding mode.Through the comparative analysis of the above two methods, it can be seen that the refined quantitative screening method of tertiary oil recovery can achieve the quantitative analysis of the tertiary oil recovery mode in the target block, with a wide range of analysis results and fast evaluation speed, which can greatly reduce the workload of detailed evaluation. However, this method can only preliminarily select and evaluate the appropriate flooding mode of the block and cannot predict the actual production and final recovery of the block, so the evaluation results are not detailed enough. In the later stage, it is necessary to analyze the potential of the appropriate tertiary oil recovery technology by analogy evaluation method. The calculation speed of the fast analogy evaluation method of tertiary oil recovery is slightly slower than that of the fine quantitative screening method. However, through comparative analysis with a large number of typical blocks and by reference to the test scheme of the selected representative typical blocks, the effective range of the production, injection data, and recovery factor of the target block can be predicted in detail, which provides the test effect and implementation feasibility of the appropriate technology for the fast evaluation of oil field judgment basis.This paper focuses on how to select a reasonable oil displacement method according to the change of different porosity and air permeability when other basic parameters remain unchanged. As shown in the curve results in Figure6, the two oil displacement methods of in situ combustion and steam flooding increase with the increase of porosity and the increase of oil recovery. There is a critical limit of porosity in gravity flooding, miscible gas flooding, and immiscible gas flooding. When the porosity of reservoir is less than 15%, miscible gas flooding should be used. When the porosity of the reservoir is between 15% and 24%, immiscible gas flooding should be used. When the porosity of the reservoir is between 24% and 27%, in situ combustion should be used. When the porosity of reservoir is more than 27%, gravity flooding should be used.Figure 6
The effect of porosity on EOR.As shown in the curve results in Figure7, steam flooding and gravity flooding increase with the increase of air permeability and the enhanced oil recovery. When the air permeability of the reservoir is less than 8×10−3 μm2, miscible gas flooding should be used. When the air permeability of the reservoir is between 8×10−3 μm2 and 130×10−3 μm2, immiscible gas flooding should be used. When the porosity of reservoir is between 130×10−3 μm2 and 450×10−3 μm2, in situ combustion should be used. When the porosity of the reservoir is greater than 450×10−3 μm2, gravity flooding should be used.Figure 7
The effect of air permeability on EOR.As shown in Table3, we propose the sequence of displacement methods under different porosity and air permeability for the purpose of analyzing how to improve EOR in Figures 1 and 2.Table 3
Sequence of displacement methods with different porosity and air permeability.
Porosity (%)(0,10](10,15](15.22](22,24](24,27](27,36](36,+∞)Displacement methodD>E>A>B>CD>E>B>A>CE>D>C>B>AE>C>A>B>DC>A>B>E>DA>C>B>E>DA>B>C>E>DAir permeability(10-3μm2)(0,8](8,90](90,130](130,150](150,200](200,450](450,+∞)Displacement methodD>E>C>B>AE>D>C>B>AE>C>D>B>AC>E>B>A>DC>B>E>A>DC>B>A>E>DB>C>A>E>DA: gravity flooding; B: steam flooding; C: in situ combustion; D: miscible gas flooding; E: immiscible gas flooding.


## 5. Conclusion

(1)
The fine quantitative screening method of tertiary oil recovery technology is established. This method is based on the classification standards formulated by various oil fields and industries, with 23 reservoir and fluid characteristic parameters as reference indexes, to establish the fine tertiary oil recovery technology screening standards; using the fuzzy relationship in fuzzy control, the original qualitative screening is improved to the quantitative scoring method, which can directly, quickly, and accurately predict the appropriate tertiary oil recovery and oil displacement mode in the study block(2)
Based on multiple factor statistical analysis, a rapid analogy evaluation method of tertiary oil recovery potential is established. Combined with the present situation and development trend of tertiary oil recovery technology at home and abroad, the database of typical field cases of tertiary oil recovery technology in China is developed. By improving the calculation method of the original Deng correlation degree, the correlation degree between the target block and the typical block of each oilfield in the database is obtained by analogy. According to the analogy score, the most matching typical block is designated with the target block. Thus, the potential evaluation indexes such as the final recovery range, actual annual production data, and production data of the target block are predicted by using the ratio of geological reserves(3)
Based on the fine quantitative screening method of tertiary oil recovery technology and the rapid evaluation method of tertiary oil recovery potential, an integrated R & D operation scheme is developed, which can quickly predict and evaluate the tertiary oil recovery technology in the study block(4)
The change rule of EOR under different oil displacement methods is analyzed when the porosity and air permeability of different reservoirs change. The results show that in general, the oil recovery rate of in situ combustion and steam flooding methods increases with the increase of porosity, and there is a critical value in the process of porosity change of large PV profile-control flooding, miscible gas flooding, and immiscible gas flooding. In the same way, with the increase of air permeability, the oil recovery of steam flooding and large PV profile-control flooding increases continuously, and there is a critical value in the process of air permeability change in the in situ combustion, miscible gas flooding, and immiscible gas flooding. This result can be used for reference in the selection of different reservoir flooding methods



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*Source: 6588741-2022-07-22.xml*