Weak gel depth profile control and flooding moisture content prediction method for sandstone reservoir in high water cut stage

Abstract

The invention discloses a water content prediction method for weak gel depth profile control and flooding in a high water cut stage of a sandstone reservoir. The method mainly solves the problem that an existing method cannot accurately predict the water content change rule in the weak gel profile control and flooding stage and is poor in applicability. The method comprises the following steps: S1, acquiring dynamic and static parameters of a statistical block; s2, through an indoor weak gel profile control and displacement oil displacement experiment, the reservoir permeability after weak gel profile control and displacement, the residual resistance coefficient after weak gel profile control and displacement, the equivalent viscosity of a weak gel solution, and the average water saturation and the oil phase index at different times after weak gel is injected in the statistical block are obtained; s3, establishing a moisture content prediction model in the gel profile control and flooding stage; s4, based on the established water content prediction model and the obtained data; and predicting the water content at different times after profile control and flooding to obtain predicted values of the water content at different times after weak gel depth profile control and flooding. According to the method, the change curve of the weak gel depth profile control and flooding water content along with the injection time can be obtained, and then main factors influencing the water content change in the profile control and flooding process are clarified.

Description

Technical field:

[0001] The invention relates to the technical field of oilfield water plugging and flooding, and in particular to a method for predicting the water content of weak gel deep flooding in a sandstone reservoir during a high water content period. Background technology:

[0002] With the continuous deepening of oilfield development, the main blocks of the oilfield have entered the high water content development period, the water content has risen sharply, and a water channel has been formed. Weak gel flooding can effectively block the plane and vertical heterogeneous layers on the basis of improving the oil-water mobility ratio, reduce the water content of the block, and increase the water drive recovery rate. In order to further improve the flooding effect and control the water content increase to the maximum extent, it is necessary to continuously adjust the injection and production parameters during the flooding process to improve the effect and benefits of the well group and the block. Therefore, predicting the change law of oil increase and water reduction in the gel flooding stage and clarifying the main factors affecting the change of water content during the flooding process are of great practical significance for improving the development effect of weak gel flooding in the high water content period of old oilfields.

[0003] At present, the existing moisture content prediction methods have the following main shortcomings:

[0004] (1) In terms of the displacement characteristics of injected fluids, the reservoir heterogeneity of sandstone reservoirs is enhanced during the high water content period, and the swept volume of weak gel flooding is significantly different from that of conventional water flooding. However, the existing methods do not consider the influence of the swept volume of the displacement medium on the water content prediction.

[0005] (2) In terms of injected fluid properties, the residual resistance generated after the weak gel system is injected into the underground and cross-linked will cause changes in the shape of the oil-water relative permeability curve, while the existing methods have not considered the impact of the residual resistance coefficient on the water content prediction.

[0006] (3) In terms of fluid migration laws, after the weak gel system enters the reservoir, adsorption and retention will cause a decrease in the local permeability of the porous medium, but existing methods do not consider the impact of the decrease in local permeability on water cut prediction.

[0007] Based on the above reasons, the calculation results of the current water drive water content prediction model are quite different from the actual situation of the oil field. It is impossible to accurately predict the water content change law in the weak gel drive stage, and it is impossible to effectively guide the parameter adjustment during the oil field drive process. It has poor applicability and cannot meet the needs of the oil field. Summary of the invention:

[0008] The present invention aims to provide a method for predicting the water content of weak gel deep flooding in sandstone reservoirs during the high water content period in order to solve the problems that the existing methods in the background technology are far from the actual conditions of the flooding mine and cannot accurately predict the water content change law in the weak gel flooding stage, thus cannot effectively guide the parameter adjustment in the flooding process of the oil field, and have poor applicability. The method for predicting the water content of weak gel deep flooding in sandstone reservoirs during the high water content period can obtain a curve of the water content of weak gel deep flooding with injection time, and further clarify the main factors affecting the water content change in the flooding process, providing a basis and guidance for the optimization design of injection and production parameters of gel flooding in the high water content period of the oil field.

[0009] The present invention solves the problem through the following technical solution: The method for predicting the water content of weak gel deep flooding in sandstone reservoirs with high water content comprises the following steps:

[0010] Step 1: Obtain dynamic and static parameters of the statistical block by statistical block actual data, production well history and indoor experimental data;

[0011] Step 2: Obtain the reservoir permeability K after weak gel flooding in the statistical block through indoor weak gel flooding experiment a , residual resistance coefficient F after weak gel flooding rr , Equivalent viscosity of weak gel solution μ wp , Average water saturation at different times after injection of weak gel and oil phase index n o ;

[0012] Step 3: Consider the reservoir permeability K after weak gel deep flooding in the high water content period through the water flooding water cut diversion equation a , residual resistance coefficient F after weak gel flooding rr , Equivalent viscosity of weak gel solution μ wp Parameters, establish a model for predicting water content in the gel flooding stage;

[0013] Step 4: Based on the established model for predicting water content in the gel flooding stage and the acquired data, the water content at different times after the weak gel deep flooding is predicted to obtain the predicted values ​​of water content at different times after the weak gel deep flooding.

[0014] Furthermore, the dynamic parameters include production time t, displacement pressure difference p and oil phase effective permeability K e ;

[0015] The static parameters include irreducible water saturation S wi , residual oil saturation S or , well pattern density n, skin coefficient s, wellbore radius r w , oil leakage radius r e 、Crude oil viscosity μ o、Pore volume V in well control range p and the effective thickness of the reservoir h.

[0016] Furthermore, the dynamic equivalent permeability K of the reservoir after weak gel flooding is a The reservoir dynamic equivalent permeability K is calculated by correcting the reservoir permeability. a ;

[0017] The reservoir dynamic equivalent permeability K a The calculation formula is:

[0018] K a =K min +(KK min ) / F rr (i) (2)

[0019] Where: K min is the minimum permeability of the reservoir, F rr (i) is the residual resistance coefficient and K is the reservoir permeability.

[0020] Furthermore, the residual resistance coefficient F after gel flooding rr , when the average residual resistance coefficient before the injection of gel solution is known, the weighted residual resistance coefficient in the next time step is calculated by the injected gel mass concentration and the maximum residual resistance coefficient at the current time;

[0021] The residual resistance coefficient F rr The calculation formula for (i) is:

[0022]

[0023] Where: F rr (i) is the residual resistance coefficient at the i-th time step, ΔV(i) is the pore volume of the gel injected at the i-th time step, is the average water saturation of the reservoir at the i-1th time step, F rr (i-1) is the residual resistance coefficient at the i-1th time step, F rmax The maximum residual resistance coefficient, the maximum residual resistance coefficient F rmax Determined by indoor experiments.

[0024] Furthermore, the equivalent viscosity μ of the gel solution is wp , calculate the underground equivalent viscosity of the gel solution in the next time step through the equivalent viscosity of the injected gel solution at the current time and the multiple of the injected pore volume;

[0025] The subsurface equivalent viscosity μ of the gel solution is shown wp The calculation formula is:

[0026]

[0027] Where: μ wp (i) is the underground equivalent viscosity of the gel solution at the oth time step, is the average water saturation of the reservoir at the i-1th time step, μ wp (i-1) is the underground equivalent viscosity of the gel solution at the i-1th time step, μ wg is the viscosity of the gel solution, and ΔV(i) is the pore volume injected into the gel at the i-th time step.

[0028] Furthermore, the average water saturation According to the initial water saturation and the current recovery degree of the research block, the average water saturation at production time i is calculated.

[0029] The average water saturation The calculation formula is:

[0030]

[0031] in: is the average water saturation of the reservoir at the i-th time step, S wi is the irreducible water saturation, and R(i) is the oil reservoir recovery degree at the i-th time step.

[0032] Furthermore, the oil phase index n o It can be obtained by regression of the relative permeability curve measured by indoor experiments.

[0033] Furthermore, the oil phase index n o The calculation method comprises the following steps:

[0034] Step 1: Dimensionless normalization of water saturation in relative permeability data to obtain S wD ;

[0035] Said to S wD The calculation formula is:

[0036]

[0037] Step 2: Draw the oil phase index regression curve and obtain the oil phase index n through the regression equation o .

[0038] Furthermore, the oil phase index n is obtained by regression equation o The method is:

[0039] Draw the oil phase index regression curve; according to the obtained S wD , calculated According to Kro Calculated Draw on excel software and The relationship curve of oil phase index n is obtained by regression equation o ;

[0040] The oil phase index regression curve is:

[0041]

[0042] Where: K ro is the relative permeability of the oil phase, S wD is the normalized water saturation, N is the constant term of the regression equation, n o is the oil phase index.

[0043] Furthermore, the water content prediction model for the gel flooding stage established in step 3 is:

[0044]

[0045] Where: f wp Predict water content for gel flooding stage, f; μ o is the formation crude oil viscosity, mPa.s; μw p is the underground equivalent viscosity of the gel solution, mPa·s; K a , is the corrected equivalent permeability, mD; K e is the effective permeability of the oil phase, mD; V k is the permeability variation coefficient; V p is the pore volume within the well control range, m 3 , r e is the oil leakage radius, m; r w is the wellbore radius, m; s is the skin coefficient; t is the production time, month; n is the well pattern density, mouth / km 2 ;n o is the oil phase index; h is the effective thickness of the reservoir, m; p is the displacement pressure difference, MPa, S wi is the bound water saturation, f; S or is the residual oil saturation, f; a and b are semi-logarithmic curves K ro / K rw The coefficient of the equation related to water saturation.

[0046] Furthermore, the method for establishing a water cut prediction model in the gel flooding stage includes:

[0047] 1.1) Reservoir water saturation S w Formula (8) and flow splitting equation (9) are:

[0048]

[0049] The flow splitting equation is:

[0050] 1.2) Reservoir water saturation S w Formula (8) shows that the oil phase index has a great influence on water saturation; the water saturation S of the reservoir is w Substitute the formula into the flow splitting equation The new water cut prediction model for water flooding is obtained:

[0051]

[0052] 1.3) When adjusting the drive, μ is taken as μ wp ; by F rr Calculate K a Finally, we can find f at different times wp .

[0053] Compared with the above background technology, the present invention has the following beneficial effects:

[0054] The method for predicting the water content of weak gel deep flooding in sandstone reservoirs during the high water content period of the present invention takes into account more comprehensive factors, and for the first time considers factors such as reservoir heterogeneity, the swept volume of weak gel in the reservoir, the equivalent viscosity of the gel system after underground gelation, the residual resistance coefficient, the mass concentration, the injection pore volume multiple of the flooding system, and the injection speed. The model can be used to predict the water content of weak gel deep flooding. The results can provide a basis and guidance for the optimization design of injection and production parameters of gel flooding during the high water content period of oil fields. Description of the drawings:

[0055] Attached Figure 1 This is a flow chart of the method for predicting water content of weak gel deep flooding in sandstone reservoirs during high water content period of the present invention;

[0056] Attached Figure 2 This is the well location map of weak gel flooding in the Grape 126 well area according to the embodiment of the present invention;

[0057] Attached Figure 3 This is the oil phase index regression curve of the well area of ​​Grape 126 in the embodiment of the present invention;

[0058] Attached Figure 4 This is a curve diagram for predicting water cut in the well area of ​​Pu 126 according to an embodiment of the present invention. Specific implementation method:

[0059] In order to make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0060] As attached Figure 1As shown, the present invention provides a method for predicting water content of weak gel deep flooding in sandstone reservoirs during high water content period, comprising the following steps:

[0061] Step 1: Obtain dynamic and static parameters of the statistical block by statistical block actual data, production well history and indoor experimental data;

[0062] The dynamic parameters include production time t, displacement pressure difference p and oil phase effective permeability K e ; The static parameters include irreducible water saturation S wi , residual oil saturation S or , well pattern density n, skin coefficient s, wellbore radius r w , oil leakage radius r e 、Crude oil viscosity μ o 、Pore volume V in well control range p and the effective thickness of the reservoir h.

[0063] Step 2: Obtain the reservoir permeability K after weak gel flooding in the statistical block through indoor weak gel flooding experiment a , residual resistance coefficient F after weak gel flooding rr , Equivalent viscosity of weak gel solution μ wp , Average water saturation at different times after injection of weak gel and oil phase index n o ;

[0064] The dynamic equivalent permeability K of the reservoir after weak gel flooding a The reservoir dynamic equivalent permeability K is calculated by correcting the reservoir permeability. a ;

[0065] The reservoir dynamic equivalent permeability K a The calculation formula is:

[0066] K a =K min +(KK min ) / F rr (i) (2)

[0067] Where: K min is the minimum permeability of the reservoir, F rr (i) is the residual resistance coefficient and K is the reservoir permeability.

[0068] The residual resistance coefficient F after gel flooding rr , when the average residual resistance coefficient before the injection of gel solution is known, the weighted residual resistance coefficient in the next time step is calculated by the injected gel mass concentration and the maximum residual resistance coefficient at the current time;

[0069] The residual resistance coefficient Frr The calculation formula for (i) is:

[0070]

[0071] Where: F rr (i) is the residual resistance coefficient at the i-th time step, ΔV(i) is the pore volume of the gel injected at the i-th time step, is the average water saturation of the reservoir at the i-1th time step, F rr (i-1) is the residual resistance coefficient at the i-1th time step, F rmax The maximum residual resistance coefficient, the maximum residual resistance coefficient F rmax Determined by indoor experiments.

[0072] The equivalent viscosity μ of the gel solution wp , calculate the underground equivalent viscosity of the gel solution in the next time step through the equivalent viscosity of the injected gel solution at the current time and the multiple of the injected pore volume;

[0073] The subsurface equivalent viscosity μ of the gel solution is shown wp The calculation formula is:

[0074]

[0075] Where: μ wp (i) is the underground equivalent viscosity of the gel solution at the oth time step, is the average water saturation of the reservoir at the i-1th time step, μ wp (i-1) is the underground equivalent viscosity of the gel solution at the i-1th time step, μ wg is the viscosity of the gel solution, and ΔV(i) is the pore volume injected into the gel at the i-th time step.

[0076] The average water saturation According to the initial water saturation and the current recovery degree of the research block, the average water saturation at production time i is calculated.

[0077] The average water saturation The calculation formula is:

[0078]

[0079] in: is the average water saturation of the reservoir at the i-th time step, S wi is the irreducible water saturation, and R(i) is the oil reservoir recovery degree at the i-th time step.

[0080] The oil phase index n nIt can be obtained by regression of the relative permeability curve measured by indoor experiments. Oil phase index n o The specific calculation method includes the following steps:

[0081] Step 1: Dimensionless normalization of water saturation in relative permeability data to obtain S wD ;

[0082] Said to S wD The calculation formula is:

[0083]

[0084] Step 2: Draw the oil phase index regression curve and obtain the oil phase index n through the regression equation o ;

[0085] Draw the oil phase index regression curve; according to the obtained S wD , calculated According to K ro Calculated Draw on excel software and The relationship curve of oil phase index n is obtained by regression equation o ;

[0086] The oil phase index regression curve is:

[0087]

[0088] Where: K ro is the relative permeability of the oil phase, S wD is the normalized water saturation, N is the constant term of the regression equation, n o is the oil phase index.

[0089] Step 3: Consider the reservoir permeability K after weak gel deep flooding in the high water content period through the water flooding water cut diversion equation a , residual resistance coefficient F after weak gel flooding rr , Equivalent viscosity of weak gel solution μ wp Parameters, establish a model for predicting water content in the gel flooding stage;

[0090] The established model for predicting water content in the gel flooding stage is:

[0091]

[0092] Where: f wp Predict water content for gel flooding stage, f; μ o is the formation crude oil viscosity, mPa.s; μw pis the underground equivalent viscosity of the gel solution, mPa·s; K a , is the corrected equivalent permeability, mD; K e is the effective permeability of the oil phase, mD; V k is the permeability variation coefficient; V p is the pore volume within the well control range, m 3 , r e is the oil leakage radius, m; r w is the wellbore radius, m; s is the skin coefficient; t is the production time, month; n is the well pattern density, mouth / km 2 ;n o is the oil phase index; h is the effective thickness of the reservoir, m; p is the displacement pressure difference, MPa, S wi is the bound water saturation, f; S or is the residual oil saturation, f; a and b are semi-logarithmic curves K ro / K rw The coefficient of the equation related to water saturation.

[0093] The method for establishing a water cut prediction model in the gel flooding stage is:

[0094] 1.1) Reservoir water saturation S w Formula (8) and flow splitting equation (9) are:

[0095]

[0096]

[0097] 1.2) Reservoir water saturation S w Formula (8) shows that the oil phase index has a great influence on water saturation; the water saturation S of the reservoir is w公式 Substituting into the flow splitting equation The new water cut prediction model for water flooding is obtained:

[0098]

[0099] 1.3) When adjusting the drive, μ is taken as μ wp ; by F rr Calculate K a Finally, we can find f at different times wp .

[0100] Step 4: Based on the established model for predicting water content in the gel flooding stage and the acquired data, the water content at different times after the weak gel deep flooding is predicted to obtain the predicted values ​​of water content at different times after the weak gel deep flooding.

[0101] Example 1

[0102] Taking the Pu 126 well area of ​​Putaohua Oilfield as the research object, a method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage of the present invention is specifically described, comprising the following steps:

[0103] Step 1: Statistical basic data

[0104] The Pu 126 well area in Putaohua Oilfield was taken as the research object (see Figure 2 ), calculate the predicted value of water content after well area flooding. According to the static data of reservoir in the well area, well history data, indoor test data, etc., the dynamic and static parameters such as geological reserves, recovery degree, well pattern density, injection and production well point permeability, bottom hole flow pressure, wellbore radius, water saturation, fluid viscosity, etc. in the test area, as well as the test data such as oil-water relative permeability and gel viscosity are statistically used for formula calculation. The basic data statistics of Pu 126 well area are shown in Table 1.

[0105] Table 1

[0106]

[0107] Step 2: Calculate the oil phase index n o

[0108] Formula 6 is used to perform dimensionless normalization on the water saturation in the oil-water relative permeability data (Table 2) measured in the indoor experiment to obtain S wD .

[0109] Table 2

[0110] <![CDATA[S w ]]> <![CDATA[K rw ]]> <![CDATA[K ro ]]> <![CDATA[S wD ]]> 0.415 0 1 0 0.4588 0.009 0.623 0.110106 0.485 0.023 0.461 0.175968 0.5092 0.037 0.354 0.236802 0.5418 0.06 0.28 0.318753 0.592 0.098 0.2 0.444947 0.666 0.147 0.127 0.63097 0.748 0.24 0.065 0.837104 0.8128 0.374 0.014 1

[0111] Apply formula 7 to draw the oil phase index regression curve, and obtain the oil phase index n through the regression equation o =1.498, see Figure 3 .

[0112] Step 3: Calculate the average water saturation of the reservoir at different production times

[0113] The water drive recovery rate of Pu 126 well area before flooding was 48%, and the annual oil production rate after flooding was 0.3%. The annual recovery rate R(i) after flooding can be calculated. Using formula 5, the average water saturation of the reservoir at different injection times can be calculated. The calculation results of average water saturation at different stages of weak gel flooding in Pu 126 well area are shown in Table 3.

[0114] Table 3

[0115]

[0116] Step 4: Calculate the equivalent viscosity μ of the gel solution wp

[0117] The viscosity of the gel solution injected into the Pu 126 well area wg =300mPa·s. When the gel solution is injected into the underground for cross-linking, the viscosity increases. The equivalent viscosity of the gel solution at the current injection time is 900mPa·s. Formula 4 is used to calculate the equivalent viscosity of the weak gel solution at different production times of weak gel flooding in the Pu 126 well area. The calculation results of the equivalent viscosity of the gel solution at different stages of weak gel flooding in the Pu 126 well area are shown in Table 4.

[0118] Table 4

[0119]

[0120]

[0121] Step 5: Calculate the residual resistance coefficient F after gel flooding rr

[0122] The maximum residual resistance coefficient F of the gel solution injected into the Pu 126 well area rrmax =20. After the gel solution is injected into the underground for cross-linking, the viscosity increases. The residual resistance coefficient of the gel solution at the current injection time is 35. Formula 3 is used to calculate the weighted residual resistance coefficient of the weak gel flooding in the Pu 126 well area at different times. The calculation results of the residual resistance coefficient of the weak gel flooding in the Pu 126 well area at different stages are shown in Table 5.

[0123] Table 5

[0124]

[0125] Step 6: Calculate the dynamic equivalent permeability K of the gel flooding reservoir a

[0126] The absolute permeability of the reservoir in the Pu 126 well area is K = 200mD, and the minimum permeability of the reservoir is K min =80mD, dynamic equivalent permeability of reservoir after weak gel flooding K a The residual resistance coefficients of weak gel flooding at different stages in the Pu 126 well area were calculated using Formula 2 and are shown in Table 6.

[0127] Table 6

[0128]

[0129]

[0130] Step 7: Calculate the water content of the weak gel depth flooding in the Pu 126 well area

[0131] Substitute the statistical data and calculated data from step 1 to step 6 into formula 1 to obtain the predicted water content at different times after the weak gel deep flooding (see Table 7), and draw a curve as shown in Figure 4 .

[0132] Table 7

[0133]

Claims

1. A method for predicting water content of weak gel deep flooding in sandstone reservoirs during high water content period, characterized by: The following steps are involved: Step 1: Obtain dynamic and static parameters of the statistical block by statistically analyzing actual data of the statistical block, production well history and indoor experimental data; Step 2: Obtain the reservoir permeability K after weak gel flooding in the statistical block through indoor weak gel flooding experiment a , residual resistance coefficient F after weak gel flooding rr , Equivalent viscosity of weak gel solution μ wp , Average water saturation at different times after injection of weak gel and oil phase index n o ; Step 3: Consider the reservoir permeability K after weak gel deep flooding during the high water content period obtained in step 2 through the water drive water cut diversion equation and reservoir water saturation formula. a , residual resistance coefficient F after weak gel flooding rr , Equivalent viscosity of weak gel solution μ wp Parameters, establish a model for predicting water content in the gel flooding stage; Step 4: Based on the established model for predicting water content in the gel flooding stage and the acquired data, the water content at different times after the weak gel deep flooding is predicted to obtain the predicted values ​​of water content at different times after the weak gel deep flooding.

2. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 1 is characterized by: The dynamic parameters include production time t, displacement pressure difference p and oil phase effective permeability K e ; The static parameters include irreducible water saturation S wi , residual oil saturation S or , well pattern density n, skin coefficient s, wellbore radius r w , oil leakage radius r e 、Crude oil viscosity μ o 、Pore volume V in well control range p and the effective thickness of the reservoir h.

3. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 1, characterized in that: The dynamic equivalent permeability K of the reservoir after weak gel flooding a The reservoir dynamic equivalent permeability K is calculated by correcting the reservoir permeability. a ; The reservoir dynamic equivalent permeability K a The calculation formula is: K a =K min +(K-K min ) / F rr (i) (2) Where: K mim is the minimum permeability of the reservoir, F rr (i) is the residual resistance coefficient and K is the reservoir permeability.

4. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 1, characterized in that: The residual resistance coefficient F after gel flooding rr , when the average residual resistance coefficient before the injection of gel solution is known, the weighted residual resistance coefficient in the next time step is calculated by the injected gel mass concentration and the maximum residual resistance coefficient at the current time; The residual resistance coefficient F rr The calculation formula for (i) is: Where: F rr (i) is the residual resistance coefficient at the i-th time step, ΔV(i) is the pore volume of the gel injected at the i-th time step, is the average water saturation of the reservoir at the i-1th time step, F rr (i-1) is the residual resistance coefficient at the i-1th time step, F rrmax The maximum residual resistance coefficient, the maximum residual resistance coefficient F rrmax Determined by indoor experiments.

5. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 1, characterized in that: The equivalent viscosity μ of the gel solution wp , calculate the underground equivalent viscosity of the gel solution in the next time step through the equivalent viscosity of the injected gel solution at the current time and the multiple of the injected pore volume; The subsurface equivalent viscosity μ of the gel solution shown wp The calculation formula is: Where: μ wp (i) is the underground equivalent viscosity of the gel solution at the i-th time step, is the average water saturation of the reservoir at the i-1th time step, μ wp (i-1) is the underground equivalent viscosity of the gel solution at the i-1th time step, μ wg is the viscosity of the gel solution, and ΔV(i) is the pore volume injected into the gel at the i-th time step.

6. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 1, characterized in that: The average water saturation According to the initial water saturation and the current recovery degree of the research block, the average water saturation at production time i is calculated. The average water saturation The calculation formula is: in: is the average water saturation of the reservoir at the i-th time step, S wi is the irreducible water saturation, and R(i) is the oil reservoir recovery degree at the i-th time step.

7. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 1, characterized in that: The oil phase index n o It can be obtained by regression of the relative permeability curve measured by indoor experiments.

8. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 7, characterized in that: The oil phase index n o The calculation method comprises the following steps: Step 1: Dimensionless normalization of water saturation in relative permeability data to obtain S wD ; Said to S wD The calculation formula is: Step 2: Draw the oil phase index regression curve and obtain the oil phase index n through the regression equation o ; The oil phase index n is obtained by regression equation o The method is: Draw the oil phase index regression curve; according to the obtained S wD , calculated According to K ro Calculated Draw on excel software and The relationship curve of oil phase index n is obtained by regression equation o ; The oil phase index regression curve is: Where: K ro is the relative permeability of the oil phase, S wD is the normalized water saturation, N is the constant term of the regression equation, n o is the oil phase index.

9. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 1, characterized in that: The water content prediction model for the gel flooding stage established in step 3 is: Where: f wp Predict water content for gel flooding stage, f; μ o is the formation crude oil viscosity, mPa.s; μw p is the underground equivalent viscosity of the gel solution, mPa·s; K a , is the corrected equivalent permeability, mD; K e is the effective permeability of the oil phase, mD; V k is the permeability variation coefficient; V p is the pore volume within the well control range, m 3 , r e is the oil leakage radius, m; r w is the wellbore radius, m; s is the skin coefficient; t is the production time, month; n is the well pattern density, mouth / km 2 ;n o is the oil phase index; h is the effective thickness of the reservoir, m; p is the displacement pressure difference, MPa, S wi is the bound water saturation, f; S or is the residual oil saturation, f; a, b are semi-logarithmic curves K ro / K rw The coefficient of the equation related to water saturation.

10. The method for predicting water content of weak gel deep flooding in sandstone reservoirs at high water content stage according to claim 9, characterized in that: The method of establishing a water cut prediction model in the gel flooding stage includes: 1.1) Reservoir water saturation S w Formula (8) and flow splitting equation (9) are: 1.2) Reservoir water saturation S w Formula (8) shows that the oil phase index has a great influence on water saturation; the water saturation S of the reservoir is w公式 Substitute into the flow splitting equation The new water cut prediction model for water flooding is obtained: 1.3) When adjusting the drive, μ is taken as μ wp ; by F rr Calculate K a Finally, we can find f at different times wp .

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