A method for calculating a phase-controlled reserve chemical flooding wave coefficient

Abstract

The present application relates to a kind of phase-controlled reserves chemical flooding wave and coefficient calculation method, comprising the following steps: (1), establish high-precision three-dimensional porosity and permeability model;(2), calculate phase-controlled reserves chemical flooding wave and coefficient.This method can improve the accuracy of phase-controlled reserves chemical flooding wave and coefficient calculation, thereby providing accurate basis for chemical flooding reservoir engineering design, numerical simulation accuracy, tracking adjustment and post-evaluation of implementation effect of scheme.Compared with the traditional chemical flooding wave and coefficient calculation, the method is more scientific, the concept is clearer, the index is more quantitative, and the chemical flooding wave and coefficient calculation result is more accurate and reliable, which has important significance for guiding oilfield production and development.

Description

Technical Field

[0001] This invention relates to the technical field of quantifying the spatial sweep efficiency of chemical flooding for facies-controlled reservoirs based on three-dimensional geological models, and in particular to a method for improving the calculation accuracy of the spatial sweep efficiency of chemical flooding for facies-controlled reservoirs in three types of oil reservoirs. Background Technology

[0002] The spatial sweep efficiency (SQE) of chemical flooding in phase-controlled reservoirs refers to the extent to which the chemical agent sweeps through the reservoir. It is the ratio of the volume of the reservoir washed by the chemical agent to the total volume of the reservoir. It directly affects the development effectiveness of chemical flooding and is of great significance for the design of chemical flooding reservoir engineering schemes, the accuracy of numerical simulations, follow-up adjustments, and post-implementation evaluation of the scheme's effectiveness. Currently, the commonly used method in oilfields is to calculate the SQE by the ratio of the connected volume of the sand bodies in phase-controlled reservoirs to the total volume of the well group-controlled reserves. This method does not consider the inaccessible porosity of chemical flooding and the connectivity quality between injection and production units, leading to an overestimation of the SQE in phase-controlled reservoirs. This directly affects the results of chemical flooding reservoir engineering scheme design, numerical simulations, follow-up adjustments, and post-implementation evaluation of the scheme's effectiveness. Summary of the Invention

[0003] To address the problems existing in the background art, this invention provides a method for calculating the sweep efficiency of chemical flooding for phase-controlled reserves. This application takes water wells as the center and considers the effects of microscopic accessible porosity, interlayer heterogeneity, and phase transformation in chemical flooding to determine the method for calculating the sweep efficiency of chemical flooding for phase-controlled reserves.

[0004] The technical solution provided by this invention is: a method for calculating the sweep efficiency coefficient of chemical flooding for well group controlled reserves, comprising the following steps:

[0005] Step (1): Establish a high-precision three-dimensional porosity and permeability model:

[0006] ① Based on the current logging sampling interval, reconstruct the porosity and permeability logging interpretation model to complete the fine secondary interpretation of logging parameters, thereby effectively characterizing the heterogeneity within a single well layer;

[0007] ② In the Petrel software platform, based on the fault results of seismic interpretation and combined with the adjustment of fault boundary control lines, a fault model that conforms to the actual spatial morphology is established. The bedding results of seismic interpretation are used as trend constraints to establish the oil layer group-level framework bedding. Using well point layering data, the "thickness constraint" method is used to establish a sedimentary unit-level bedding model with reasonable inter-stratum contact relationships and structural characteristics that conform to geological laws. Through fine verification and adjustment of the contact relationship between the fault model and the bedding model, a sedimentary unit-level structural framework with reasonable fault and bedding contact relationships is established. Considering the contact relationship between each sedimentary unit, the "equal thickness subdivision" technique is used from bottom to top to further subdivide the vertical sedimentary units and establish a three-dimensional fine structural geological model.

[0008] ③ Using the secondary interpretation results of the logging parameters of a single well, and according to the logging sampling interval of 0.125m, a single well LOG file (containing three columns: depth, porosity, and permeability) is created. The single well data file is loaded into the corresponding single well folder in the structural geological model work area. The porosity and permeability data of the single well are discretized, and the porosity and permeability data are collected from the single well folder onto the corresponding grid. In this way, different porosity and permeability values ​​are assigned to different grid depths at the well point location.

[0009] ④ The facies point files (containing three columns: horizontal axis, vertical axis and facies value) of the sedimentary units exported from the existing fine reservoir description work area are loaded into the structural geological model work area. The nearest point method is used to perform interpolation calculations to complete the numericalization of sedimentary facies data points of each sedimentary unit. The grid direct assignment method is applied to sample the numericalized sedimentary facies data of each unit into the grid, and finally a three-dimensional sedimentary facies model is established.

[0010] ⑤ Using sedimentary facies models as trend constraints, and porosity and permeability collected from the grid as the basic data source, we applied stochastic function interpolation theory, variogram analysis, and sequential Gaussian interpolation method to finally establish a high-precision geological model of facies-controlled porosity and permeability three-dimensional physical property parameters.

[0011] Step (2), Calculation of sweep efficiency of phase-controlled reservoir chemical flooding:

[0012] ① Based on the three-dimensional fine geological model, the Geometrical Modeling module is used in the Petrel software platform to establish a grid volume model (Cell volume). The attribute calculator is used to multiply the established grid volume model with the porosity geological model to obtain the total pore volume model at the sedimentary unit level. Based on the total pore volume model, the total pore volume of each sedimentary unit in the block is calculated.

[0013] ② Based on the permeability limit that is difficult for chemical agents to reach as determined by indoor experiments, the attribute calculator is used to filter out the portion of the total pore volume model below the permeability limit, resulting in a macroscopically accessible pore volume model. Based on the microscopic pore volume correction coefficient data for chemical agents under different permeability core conditions determined by indoor experiments, the relationship between permeability and the microscopic pore volume correction coefficient for chemical agents is fitted. In the Geometrical Modeling module, a new constant geometric model is established. The attribute calculator is used to calculate the constant geometric model using the fitted relationship between permeability and the microscopic pore volume correction coefficient for chemical agents, resulting in a pore volume correction coefficient model for each sedimentary unit. The attribute calculator is then used to multiply the pore volume correction coefficient model with porosity to obtain a porosity correction model. Finally, the attribute calculator is used to multiply the porosity correction model with the cell volume model to obtain a pore volume model that does not consider layer combination and planar phase transition.

[0014] ③ On the existing sedimentary facies map of the sub-sedimentary units, complete the division of well groups according to the block well network method, count the sand body combination patterns between different injection and production units in each sedimentary unit well group, determine the sand body phase change type and connectivity type between different injection and production units, delineate the control area of ​​each injection and production unit according to the well network method, and cut the sweep pore volume model established in step ② above without considering the strata combination and planar phase change into the sweep pore volume model at the injection and production unit level without considering the strata combination and planar phase change according to the control area of ​​each injection and production unit;

[0015] ④ Based on the phase transition type of each depositional unit between each injection-production unit determined in step ③ above, and combined with the laboratory experiments to determine the macroscopic sweep pore volume correction coefficient of the chemical agent for different phase transition types, the macroscopic sweep pore volume correction coefficient of the chemical agent for each depositional unit between injection-production units is statistically analyzed. Using the Geometrical Modeling module, a constant geometric model for each injection-production unit is established. The constant geometric model for each depositional unit is assigned a value according to the statistically analyzed macroscopic sweep pore volume correction coefficient of the chemical agent for each depositional unit. In this way, the macroscopic sweep pore volume correction coefficient model of the chemical agent for each injection-production unit is obtained.

[0016] ⑤ Using the attribute calculator, multiply the chemical flooding accessible pore volume model at the injection-production unit level (excluding phase change) by the chemical agent macro-sweep pore volume correction coefficient model at the injection-production unit level. This yields the accessible pore volume model for each sedimentary unit at the injection-production unit level considering phase change. Based on the accessible pore volume model for each injection-production unit considering phase change, merge the accessible pore volume models for each sedimentary unit within all injection-production units in the well group. This yields the chemical flooding accessible pore volume model for each sedimentary unit in the well group considering phase change. Finally, merge the accessible pore volume models for each sedimentary unit in all well groups considering phase change to obtain the chemical flooding accessible pore volume model for each sedimentary unit in the block considering phase change.

[0017] ⑥ Using the attribute calculator, the channel, main body, and Class I sandstone in the sedimentary facies are set as effective sandstones, and the remaining facies are ineffective sandstones. A net-to-gross ratio model is established. The injection-production unit-level porosity model and net-to-gross ratio model are applied to calculate the facies-controlled reserves model of the sedimentary unit.

[0018] ⑦ Using the attribute calculator, divide the combined chemical flooding accessible pore volume model of each sedimentary unit considering phase change with the total pore volume model of each sedimentary unit to obtain the chemical flooding sweep efficiency of the phasing reserves in each sedimentary unit of the block. Simultaneously, filter and refine the phasing reserve model using the chemical flooding sweep efficiency model, removing regions with a sweep efficiency of 0, to obtain the phasing reserves accessible by chemical flooding.

[0019] In step (1) above, step ④, establishing a three-dimensional sedimentary facies model: using the existing fine reservoir description area, sedimentary facies data points are derived according to sedimentary units, including three columns of data: horizontal axis, vertical axis, and facies value. The sedimentary facies data points of each sedimentary unit are added to the three-dimensional fine structural model area. The sedimentary facies data points of each sedimentary unit are quantified according to the nearest point method. The quantified sedimentary facies data of each unit are sampled into the grid through the grid assignment method, and finally a three-dimensional sedimentary facies model is established; then, a porosity geological model and a permeability geological model are established: using 0.125 The results of the in-depth interpretation of the reservoir physical property parameters were obtained. According to the sampling interval of 0.125m, the porosity and permeability data of all single wells in the study area were split, and a LOG physical property parameter file was formed for each single well. The split single well physical property parameter files were loaded into the three-dimensional model. Through data discretization, the single well physical property parameter files were sampled into the grid frame. Then, based on the theory of random function interpolation, the random simulation technology controlled by the sedimentary facies model was adopted. Through variogram analysis, the sequential Gaussian interpolation method was applied to generate a three-dimensional geological model of porosity and permeability physical property parameters.

[0020] In steps ③-⑦ of (2) above, the sand body combination patterns between different injection-production units within each sedimentary unit well group are statistically analyzed. Based on the control area of ​​each injection-production unit, the sweep pore volume model, which does not consider strata combination and planar phase change, is cut into injection-production unit-level sweep pore volume models. The injection-production unit-level chemical flooding accessible pore volume model, which does not consider phase change, is multiplied by the injection-production unit-level chemical agent macroscopic sweep pore volume correction coefficient model to obtain the injection-production unit-level accessible pore volume model considering phase change. The injection-production unit-level chemical flooding accessible pore volume model considering phase change is then divided with the total pore volume model to obtain the chemical flooding sweep pore coefficient model for the phase-controlled reserves of each injection-production unit. By merging the injection-production unit-level chemical flooding sweep pore coefficient models, the overall phase-controlled reserve chemical flooding sweep pore coefficient can be obtained.

[0021] The beneficial effects of this invention are as follows: This method can improve the accuracy of calculating the sweep efficiency coefficient of chemical flooding reservoirs, thereby providing an accurate basis for the design of chemical flooding reservoir engineering schemes, the accuracy of numerical simulation, tracking and adjustment, and the post-implementation evaluation of the scheme's effectiveness. Compared with traditional chemical flooding sweep efficiency coefficient calculations, this method is more scientific, with clearer concepts and more quantifiable indicators, resulting in more accurate and reliable calculation results, which is of great significance for guiding oilfield production and development. Attached Figure Description

[0022] Figure 1 It is a three-dimensional detailed geological model diagram;

[0023] Figure 2 It is a three-dimensional sedimentary facies model diagram;

[0024] Figure 3 It is a high-precision geological model diagram of porosity;

[0025] Figure 4 It is a high-precision permeability geological model diagram;

[0026] Figure 5 This is a diagram of the total pore volume model;

[0027] Figure 6 It is a macroscopically accessible pore volume model diagram;

[0028] Figure 7 This is a curve showing the relationship between the accessible pore volume correction factor and permeability.

[0029] Figure 8 This is a model diagram of the sweepable pore volume correction factor for a sedimentary unit.

[0030] Figure 9 This is a modified accessible porosity model diagram;

[0031] Figure 10 This is a chemical flooding accessible pore volume model diagram (phase transition not considered);

[0032] Figure 11 This is an experimentally determined graph showing the macroscopic sweep pore volume correction coefficient of the phase change agent between injection and production units;

[0033] Figure 12 This is a distribution map of phase change types of well group controlled reserves. Detailed Implementation

[0034] The following describes a method for calculating the sweep efficiency of chemical flooding in phase-controlled reservoirs. However, it is worth noting that this method is not limited to these embodiments. The following detailed description of the method includes specific details. However, those skilled in the art will fully understand any parts not described in detail.

[0035] This application focuses on the calculation of the sweep efficiency of chemical flooding in phase-controlled reserves. It clarifies the methods to improve the accuracy of the calculation of the sweep efficiency of chemical flooding in phase-controlled reserves from three aspects: the establishment of a fine geological model, the determination of the microscopic accessible porosity correction coefficient and the phase change porosity volume correction coefficient.

[0036] The specific process is as follows:

[0037] (1) Establish a high-precision three-dimensional porosity and permeability model:

[0038] ① Based on the current logging sampling interval, reconstruct the logging interpretation model for porosity and permeability, complete the fine secondary interpretation of logging parameters in the study area, and densify the interpretation of reservoir physical property parameters according to the logging sampling interval. This can accurately characterize the heterogeneity within the layer and provide a reliable basis for the fine calculation of the degree of chemical flooding control.

[0039] ② Establish a new work area, load the well head, well top, well logging interpretation breakpoints, seismic interpretation fault files (sticks format), and seismic tracing stratigraphic files. Apply the seismic interpretation stratigraphic data as constraints, and establish a digital layer based on the well top file using convergence interpolation. Activate the fault modeling module, directly convert the seismic interpretation faults (sticks) into a preliminary fault model, apply well logging breakpoint constraints to correct the strike and morphology of the preliminary fault model, and finally establish a digital fault model with accurate location and reasonable morphology. Define a new geological model and determine the simulation boundary, conduct Pillar gridding, and establish a spatial grid geological body and a gridded fault model. Complete the gridding of the digital layers by making horizons, consider the contact relationship between different sedimentary units, and use the "equal thickness subdivision" method to subdivide the thickness of vertical sedimentary units, thereby characterizing the vertical heterogeneity within the layer, and establishing a three-dimensional fine structural model containing fault and structural information. Simultaneously, four checks are conducted on the construction model: consistency checks between bedding planes and strata points, contact relationships between bedding planes and faults, cross-mesh checks between upper and lower bedding planes, and negative volume checks of the mesh. This completes the quality control of the 3D fine construction model. The 3D fine construction model, such as... Figure 1 As shown.

[0040] ③ From the existing detailed reservoir description area (generally GPTmap), export the gridded sedimentary facies data points (including x-axis, y-axis, and facies value columns) of each sedimentary unit. Import the sedimentary facies data points of each sedimentary unit into the structural geological model area. Using the closest point method, complete the numericalization of the sedimentary facies data points of each sedimentary unit. Under the Facies modeling module conditions, apply the grid direct assignment method to sample the numericalized sedimentary facies data of each sedimentary unit into the grid, and finally establish a three-dimensional sedimentary facies model; the three-dimensional sedimentary facies model is as follows: Figure 2 As shown;

[0041] ④ Using the physical property parameters with a sampling interval of 0.125m, the porosity and permeability attribute data of all single wells in the study area were split, and each single well formed a separate physical property parameter log file; the splitting results of the single well physical property parameter data are shown in Table 1.

[0042] Table 1. Data splitting results of physical property parameters of well G229-S345 (physical property parameter log file)

[0043]

[0044] ⑤ Load the single-well physical property parameter log file into the wellhead file, apply the Scale up well logs module to sample the single-well physical property parameters into the mesh frame, and then apply the Petrophysical modeling module. Using stochastic simulation technology constrained by sedimentary facies trends, and through variogram analysis (Data analysis), apply the sequential Gaussian interpolation method to establish a high-precision three-dimensional porosity (Ф) and permeability (stl) geological model; the porosity (Ф) geological model is as follows: Figure 3 As shown, the permeability (STL) geological model is as follows: Figure 4 As shown.

[0045] (2) Calculation of sweep efficiency of phase-controlled reserves by chemical flooding:

[0046] ① Based on the established spatial grid geological body, the Geometrical Modeling module is applied, and the Cellvolume method is selected to establish a grid volume model. Using the Property calculator, the grid volume model is multiplied by the porosity model (Ф). The Porevolume template is selected to obtain the total pore volume model. The total pore volume model is as follows: Figure 5 As shown;

[0047] ② Based on the experimentally determined limit that pores with permeability less than 20 mD are difficult for chemical agents to penetrate, the property calculator is used to filter out pores with permeability less than 20 mD in the total pore volume model, resulting in a macroscopically accessible pore volume model; the macroscopically accessible pore volume model is as follows: Figure 6 As shown;

[0048] ③ Based on the data of the chemical agent's microscopic sweep pore volume correction coefficient under different permeability core conditions determined by indoor experiments, the relationship between permeability and the chemical agent's microscopic sweep pore volume correction coefficient was fitted as follows: Microscopic sweep pore volume correction coefficient = 0.2304ln(permeability) - 0.5589; The curve showing the relationship between the sweepable pore volume correction coefficient and permeability is shown below. Figure 7 As shown;

[0049] ④ Using the property calculator, establish the accessible pore volume correction coefficient model. The accessible pore volume correction coefficient model = 0.2304ln(permeability model) - 0.5589; the accessible pore volume correction coefficient model for each sedimentary unit is as follows: Figure 8 As shown;

[0050] ⑤ Using the property calculator, establish a modified accessible porosity model. The modified accessible porosity model is equal to the product of the accessible pore volume correction coefficient model and the porosity model; the modified accessible porosity model is as follows: Figure 9 As shown;

[0051] ⑥ Using the property calculator, establish an accessible pore volume model that does not consider phase change. The accessible pore volume model without considering phase change is equal to the product of the macroscopically accessible pore volume model and the modified accessible porosity model. The accessible pore volume model for chemical flooding (without considering phase change) is as follows: Figure 10 As shown.

[0052] ⑦ The study area uses a five-point area well network. The Gao 229-Xie 345 well group is selected. Taking the Gao 33 sedimentary unit as an example, the chemical flooding sweep efficiency coefficient of the facies-controlled reserves in a single sedimentary unit of the Gao 229-Xie 345 well group is calculated. From the chemical flooding accessible pore volume model (without considering phase change), the accessible pore volumes (without considering phase change) of the four injection-production units of the Gao 33 sedimentary unit in the Gao 229-Xie 345 well group are read as 23717 m³. 3 32586m 3 27386m 3 23725m 3 The accessible pore volume of chemical flooding without considering phase change is 107414 m³. 3 The sand body combination patterns of the four injection-production units in a typical well group were determined as follows: non-matrix vs. non-matrix combination, non-matrix vs. channel combination, non-matrix vs. non-matrix combination, and non-matrix vs. non-matrix combination. The experimentally determined macroscopic sweep pore volume correction factor for the chemical agent between the non-matrix vs. non-matrix combination was 0.68, and the macroscopic sweep pore volume correction factor for the non-matrix vs. channel combination was 0.863. Thus, the macroscopic sweep pore volume correction factors for the four injection-production units were 0.68, 0.863, 0.68, and 0.68, respectively. The product of the accessible pore volume (without considering phase change) read from each injection-production unit and the corresponding macroscopic sweep pore volume correction factor yielded an accessible pore volume of 16128 m³ for each direction considering phase change in the high 33 sedimentary unit. 3 28122m 3 18622m 3 16133m 3 By considering the phase change in the four injection-production units of the phase-controlled reservoir, the accessible pore volume of the high-33 sedimentary unit is added together to obtain the chemical flooding accessible pore volume of a single layer in the well group, which is 79005 m³. 3 The experimental measurement diagram of the macroscopic sweep pore volume correction coefficient of the phase change agent between the above-mentioned injection and production units is shown in the figure below. Figure 11 As shown.

[0053] ⑧ Using the attribute calculator, the channel, main body, and Class I sandstone in the sedimentary facies were set as effective sandstone, and the remaining facies as ineffective sandstone. A net-to-gross ratio model for the Gao 229-Xie 345 well group was established. Using the porosity model and net-to-gross ratio model of the Gao 229-Xie 345 well group, the facies-controlled reserves model of the Gao 229-Xie 345 well group was calculated. The facies-controlled reserves of the Gao 229-Xie 345 well group were read as 58,000 tons, and the facies-controlled reserves of the Gao 229-Xie 345 well group of the Gao 33 sedimentary unit were 5,000 tons.

[0054] ⑨ The total pore volume of the sedimentary unit 33 in the well group, as read from the total pore volume model, is 167,627 m³. 3 The chemical flooding reachable pore volume of the Gao33 sedimentary unit in the Gao229-Xie345 well group, considering phase change, is 79005 m³. 3 Dividing by the total pore volume of sedimentary unit 33 in well group 167627 m³ 3 The sweep efficiency of the chemical flooding in the Gao33 sedimentary unit, which controls the well group's reserves, is 0.4713. Simultaneously, the phasor-controlled reserve model was filtered using the chemical flooding sweep efficiency model, removing regions with a sweep efficiency of 0. This yields 0.19 million tons of phasor-controlled reserves that can be affected by chemical flooding in the Gao33 sedimentary unit. The distribution map of phasor-controlled reserve phase change types is shown below. Figure 12 As shown.

[0055] This application is highly comprehensive and targeted, with simple and efficient operation methods, and can guide the calculation of sweep efficiency coefficients for phase-controlled reservoir chemical flooding.

Claims

1. A method for calculating the phase-controlled reservoir chemical flooding sweep efficiency, comprising the following steps: (1) Establishing a high-precision three-dimensional porosity and permeability model: According to the current logging sampling interval, the porosity and permeability logging interpretation model is reconstructed, the fine secondary interpretation of logging parameters is completed, and the single well layer heterogeneity is effectively characterized; In the Petrel software platform, based on the fault results of seismic interpretation, combined with fault boundary control line adjustment, a fault model conforming to the actual spatial form is established, the layer results of seismic interpretation are used as the trend constraint to establish the oil reservoir group level framework, the well point layering data is used, and the "thickness constraint" method is used to establish the sedimentary unit level layer model with reasonable interlayer contact relationship and geological regularity of structural characteristics. The contact relationship between faults and layers is adjusted and checked in detail, and a sedimentary unit level structural framework with reasonable contact relationship between faults and layers is established. Considering the contact relationship between each sedimentary unit, the "equal thickness section" technology is used from top to bottom to further subdivide the vertical sedimentary units, and a three-dimensional fine structural geological model is established; The secondary interpretation results of the logging parameters of the single well are used, the logging sampling interval of 0.125m is used to make a single well LOG file, which contains three columns of depth, porosity and permeability, the single well data file is loaded into the corresponding single well folder of the structural geological model work area, the single well porosity and permeability data are discretized, and the porosity and permeability data are collected from the single well folder to the corresponding grid, so that the grid at different depths of the well point position is assigned different porosity and permeability values; The existing fine reservoir description work area derived sedimentary unit facies point file is loaded into the structural geological model work area, which contains three columns of horizontal coordinate, vertical coordinate and facies value, and the nearest point value method is used for interpolation operation to complete the numericalization of the sedimentary facies data points of each sedimentary unit. The grid direct assignment method is used to sample the numericalized sedimentary facies data of each unit to the grid, and finally a three-dimensional sedimentary facies model is established; Taking the sedimentary facies model as the trend constraint condition and the porosity and permeability collected to the grid as the basic data source, applying the random function interpolation theory, through variogram analysis, using the sequential Gaussian interpolation method, a high-precision phase-controlled porosity and permeability three-dimensional physical property parameter geological model is finally established; (2) Phase-controlled reservoir chemical flooding sweep efficiency calculation: ① Based on the three-dimensional fine structural geological model, the Geometrical Modeling module in the Petrel software platform is used to establish the grid volume model Cell volume, and the attribute calculator is used to multiply the established grid volume model and the porosity geological model to obtain the total porosity volume model of the sedimentary unit level. According to the total porosity volume model, the total porosity volume of each sedimentary unit in the block is calculated. (2) According to the permeability limit of the chemical agent determined by the laboratory experiment, the low permeability part of the total pore volume model is removed by using the attribute calculator and the filter function, and the macroscopic available pore volume model is obtained. According to the data of the microcosmic available pore volume correction coefficient of the chemical agent under different permeability core conditions determined by the laboratory experiment, the relationship between the permeability and the microcosmic available pore volume correction coefficient of the chemical agent is fitted. In the Geometrical Modeling module, a new constant geometric model is established, and the constant geometric model is calculated by using the fitted relationship between the permeability and the microcosmic available pore volume correction coefficient of the chemical agent by using the attribute calculator. The available pore volume correction coefficient model of each depositional unit is obtained. The available pore volume correction coefficient model is multiplied by the porosity to obtain the porosity correction model by using the attribute calculator. The porosity correction model is multiplied by the grid volume model Cell volume to obtain the available pore volume model without considering the layer combination and the planar facies change. (3) According to the well pattern of the block, the well group is divided on the existing depositional facies belt map of each depositional unit. The sand body combination mode between different injection-production units in each depositional unit is counted. The sand body facies change type and the connectivity type between different injection-production units are determined. According to the well pattern, the injection-production unit control area of each injection-production unit is delineated. The available pore volume model without considering the layer combination and the planar facies change established in the above step (2) is cut into the available pore volume model of each injection-production unit without considering the layer combination and the planar facies change according to the injection-production unit control area of each injection-production unit. (4) According to the facies change type of each depositional unit between each injection-production unit determined in the above step (3), the macroscopic available pore volume correction coefficient of the chemical agent of each depositional unit between the injection-production units is counted in combination with the macroscopic available pore volume correction coefficient of the chemical agent of different facies change types determined by the laboratory experiment. The constant geometric model of each injection-production unit is established by using the Geometrical Modeling module. Each depositional unit in the constant geometric model is valued according to the counted macroscopic available pore volume correction coefficient of the chemical agent of each depositional unit between the injection-production units. Thus, the macroscopic available pore volume correction coefficient model of the chemical agent of each injection-production unit is obtained. (5) The available pore volume model of each injection-production unit without considering the facies change is multiplied by the macroscopic available pore volume correction coefficient model of the chemical agent of each injection-production unit to obtain the available pore volume model of each depositional unit considering the facies change. The available pore volume model of each depositional unit considering the facies change in all injection-production units in the well group is combined to obtain the chemical drive available pore volume model of each depositional unit considering the facies change of the well group. The available pore volume model of each depositional unit considering the facies change of all well groups is combined to obtain the chemical drive available pore volume model of each depositional unit considering the facies change of the block. ⑥Applying the property calculator, the channel, main body and the first class sandstone in the sedimentary facies are set as effective sandstone, and the rest facies are set as invalid sandstone, the net-to-gross model is established, and the porosity model at injection-production unit level and the net-to-gross model are applied to calculate the facies-controlled reserve model of each sedimentary unit; ⑦Applying the property calculator, the chemical flooding accessible pore volume model of each sedimentary unit considering phase change is divided by the total pore volume model of each sedimentary unit, and the chemical flooding sweep efficiency of each sedimentary unit in the block is obtained. At the same time, the facies-controlled reserve model is filtered by the chemical flooding sweep efficiency model, and the area with sweep efficiency equal to 0 is screened out, and the facies-controlled reserve that can be swept by chemical flooding is obtained.

2. The method of claim 1, wherein: Step (1) further comprises: using the existing fine reservoir description work area to derive sedimentary facies data points of each sedimentary unit, including three columns of data of horizontal coordinates, vertical coordinates and facies values, adding the sedimentary facies data points of each sedimentary unit to the three-dimensional fine structure model work area, completing the numerical value of the sedimentary facies data points of each sedimentary unit according to the nearest point value method, sampling the numerical value of the sedimentary facies data of each unit to the grid through the grid assignment method, and finally establishing a three-dimensional sedimentary facies model; then establish the porosity geological model and the permeability geological model: using the interpretation results of 0.125m reservoir physical property parameters, completing the porosity and permeability data splitting of all single wells in the study area according to the 0.125m physical property parameter sampling interval, and forming a LOG physical property parameter file for each single well; loading the split single well physical property parameter file into the three-dimensional model, sampling the single well physical property parameter file to the grid framework through data discretization processing, then based on the random function interpolation theory, using the random simulation technology controlled by the sedimentary facies model, through the variation function analysis, applying the sequential Gaussian interpolation method, generating the three-dimensional physical property parameter geological model of porosity and permeability.

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