Method for quantitatively predicting initial flooding of infilled well in medium-low permeability water drive development oil field

Abstract

The invention provides a method for quantitatively predicting initial flooding of an infilled well in a medium-low permeability water drive development oil field, aiming at the problem that the infilled well flooding degree prediction is inaccurate and the deployment of the infilled well cannot be effectively guided in the prior art. The method comprises the following steps: S1, determining water logging coefficient evaluation indexes, and calculating the numerical value of each evaluation index; s2, based on the calculated numerical values of the evaluation indexes, establishing a water logging coefficient evaluation boundary; s3, determining the weight of each evaluation index of the flooding coefficient; s4, calculating a water logging factor of each dense well to be deployed; and S5, based on the flooding factors of the to-be-deployed infilled wells, the well positions of the infilled wells are optimized. According to the method, the flooding degree of the infilled well can be quantitatively predicted, the flooding prediction of the infilled well is changed from qualitative to quantitative, the prediction precision is improved, the deployment of the infilled well is effectively guided, the effect of the infilled well is improved, and the infilled well adjustment space is expanded.

Description

Technical Field:

[0001] The present invention relates to the technical field of oilfield water injection development, and particularly to a method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability waterflooding development oilfields. Background Art:

[0002] Currently, the existing methods for predicting the water flooding of infill wells include two categories: First, before the deployment of infill wells, by using dynamic and static data such as sedimentary facies maps, structural maps, sub-layer data, production data of oil and water wells, and tracer tests in the proposed infill well area, comprehensively judge the waterflood front of injection wells and predict the water flooding status of the proposed infill wells, that is, whether they are water flooded. Second, after the deployment of infill wells, further predict water flooding by interpreting the water flooded layers of the infill well logging curves and analyzing the water washing degree of inspection wells. The above methods have the following problems:

[0003] (1) From the actual water flooding status of the infill wells put into production in recent years, there is a certain deviation between the water flooding status of the infill wells predicted by the existing technology and the actual situation, which affects the effect of infill wells.

[0004] (2) This method can only qualitatively judge whether the infill wells are water flooded and cannot quantitatively characterize the degree of water flooding. In the current situation where the objects of infill adjustment are poor and it is difficult to optimize the potential of infill wells, it is not conducive to optimizing infill wells and determining the drilling sequence.

[0005] (3) There is little test data such as tracers and liquid production and water absorption profiles in the medium and low permeability oil reservoirs in the periphery of the long wall, and even less stratified test data, making it difficult to judge the water flooding status of the whole well and each layer of infill wells.

[0006] (4) The technology for interpreting the water flooded layers of infill well logging curves and analyzing the water washing status of inspection wells is applicable to verifying the water flooding prediction results after infill and guiding the perforation of infill wells, and cannot be used to optimize infill wells.

[0007] For the above reasons, the current water flooding prediction technology cannot effectively guide the deployment of infill well positions and cannot meet the requirements of the current infill adjustment plan for the oilfields in the periphery of the long wall. Summary of the Invention:

[0008] The present invention aims at the problem in the background art that the prediction of the water flooding degree of infill wells in the existing technology is inaccurate and cannot effectively guide the deployment of infill well positions, and provides a method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability waterflooding development oilfields. This method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability waterflooding development oilfields can quantitatively predict the water flooding degree of infill wells, transform the qualitative prediction of water flooding of infill wells into quantitative prediction, improve the prediction accuracy, effectively guide the deployment of infill well positions, improve the effect of infill wells, and expand the space for infill adjustment.

[0009] The present invention can achieve the solution of its problems through the following technical solutions: This method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability waterflooding development oilfields includes the following steps:

[0010] S1. Determine the evaluation index of the water flooding coefficient and calculate the values of each evaluation index;

[0011] S2. Based on the calculated values of each evaluation index, establish the judgment boundary of the water flooding coefficient;

[0012] S3. Determine the weights of each evaluation index of the water flooding coefficient;

[0013] S4. Calculate the water flooding factors of each planned infill well;

[0014] S5. Optimize the well positions of the infill wells based on the water flooding factors of each planned infill well.

[0015] Furthermore, the method for determining the evaluation index of the water flooding coefficient in step S1 includes:

[0016] According to the infill well location map, sedimentary facies belt map and basic production data of oil and water wells in the study area, analyze the injection-production relationship and injection-production dynamics of oil and water wells around the infill wells, summarize the main factors affecting the water flooding of infill wells, and thus determine that the evaluation indexes of the water flooding coefficient are 7 items, namely the number of old water lines, the perpendicular distance from the water line, the distance between injection and production wells of the old water line, the angle between the new and old water lines, the cumulative water production ratio of surrounding oil wells, the current water cut of surrounding oil wells, and the cumulative injection volume of surrounding water wells.

[0017] Furthermore, the calculation method of the values of each evaluation index in step S1 is as follows:

[0018] According to the injection-production relationship between the infill well and the surrounding oil and water wells, calculate the values of each index, namely the number of old water lines, the perpendicular distance from the water line, the distance between injection and production wells of the old water line, the angle between the new and old water lines, the cumulative water production ratio of surrounding oil wells, the current water cut of surrounding oil wells, and the cumulative injection volume of surrounding water wells, well by well and layer by layer.

[0019] Furthermore, the method for establishing the judgment boundary of the water flooding coefficient in S2 based on the calculated values of each evaluation index includes:

[0020] According to the values of each index in the study area obtained in step S1, count the distribution ranges of the values of 7 indexes, namely the number of old water lines, the perpendicular distance from the water line, the distance between injection and production wells of the old water line, the angle between the new and old water lines, the cumulative water production ratio of surrounding oil wells, the current water cut of surrounding oil wells, and the cumulative injection volume of surrounding water wells for the infill wells;

[0021] Based on the statistical distribution ranges of the values of the 7 indexes, classify each index in combination with the dynamic characteristics of the infill wells, and establish the judgment boundary of the water flooding coefficient.

[0022] Furthermore, there are 4 judgment boundaries of the water flooding coefficient, which are 0.2, 0.4, 0.6, and 0.8 respectively.

[0023] Furthermore, the method for determining the weights of the evaluation indexes of the water flooding coefficient in step S3 is:

[0024] Using the linear regression method, statistically analyze the fitting correlation between the 7 indicators of the infill wells and the water flooding coefficient and the initial water cut respectively to determine the degree of correlation.

[0025] Determine the weights of each indicator according to the determined degree of correlation.

[0026] Further, the calculation of the water flooding factor in step S4:

[0027] Based on the design of the proposed infill well positions in the infill test area, statistically analyze the 7 indicators of the proposed infill wells well by well and layer by layer. According to the grading range determined in step 2, the judgment boundary of the water flooding coefficient corresponding to the grading indicators, and the indicator weights in step 3, use the weighted method to calculate the water flooding factors of each proposed infill well to be deployed.

[0028] Further, the method for optimizing the infill well positions in step S5 is:

[0029] Optimize the deployment of the corresponding infill well positions according to the water flooding factors of each proposed infill well;

[0030] Obtain the upper limit value of the water flooding factor according to the reservoir type in the infill test area;

[0031] Based on the obtained upper limit value of the water flooding factor, optimize and determine the infill well positions.

[0032] Further, the reservoir types in the infill test area include medium and low permeability oil reservoirs;

[0033] The upper limit value of the water flooding factor for the medium permeability oil reservoir is 0.6; the upper limit value of the water flooding factor for the low permeability oil reservoir is 0.5.

[0034] Further, the method for optimizing and determining the infill well positions based on the obtained upper limit value of the water flooding factor is:

[0035] For the wells with a water flooding factor greater than the upper limit value, cancel the infill well positions;

[0036] For the wells with a water flooding factor less than or equal to the upper limit value, retain the infill wells.

[0037] Compared with the above background technology, the present invention can have the following beneficial effects:

[0038] The method of the present invention can predict the water flooding condition at the initial production stage of the infill wells and optimize the infill well positions.

[0039] After applying this method, by calculating the flooding factor of the proposed infill wells, the flooding degree was quantitatively predicted, providing a basis for optimizing the proposed infill wells. The water cut at the initial production stage of the infill wells optimized by this method has a good correlation with the predicted flooding factor, and the proportion of highly flooded wells in the infill wells is greatly reduced, minimizing the flooding risk of the infill wells and reducing the ineffective drilling infrastructure investment. The goal of quantitatively predicting the flooding degree of the proposed infill wells and guiding the deployment of infill well positions was achieved in the case of lacking test data such as tracers and fluid production and water absorption profiles.

[0040] This application optimizes the deployment of infill well positions based on the flooding factor of infill wells. After implementing this method on-site in Zhaozhou Oilfield, 69 infill oil wells were planned, with a built production capacity of 3.51×10 4 t. The average daily oil production per well of the infill wells at the initial stage was 1.71 t. After infilling, the water cut of the old wells was relatively stable. The infill wells accounted for 27.8% of the total number of wells in the whole area, but the annual production after four years of production still accounted for half of the total production in the whole area, and the predicted recovery rate was increased by 3 percentage points. Among the 69 infill wells, only 10 wells had an initial water cut of more than 90%, and the proportion of highly flooded wells was 14.5%. Compared with other infill well schemes that did not use this method to optimize the infill well positions, the proportion of highly flooded wells was reduced by more than 15%. Description of the drawings:

[0041] Attached Figure 1 is the flow chart of the method of the present invention;

[0042] Attached Figure 2 is a schematic diagram of four indicators characterizing the injection-production relationship in the embodiment of the present invention; (a - number of old water lines; b - perpendicular distance from the water line; c - angle between the new and old water lines; d - injection-production well distance of the old water line; )

[0043] Attached Figure 3 is a schematic diagram of three indicators characterizing the injection-production degree in the embodiment of the present invention;

[0044] Attached Figure 4 is the fitting curve of the flooding coefficient of the old water line number and the initial water cut in the embodiment of the present invention. Detailed implementation manners:

[0045] To make the objectives, technical solutions and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0046] The following examples are methods for predicting the flooding factor based on the dynamic and static data of infill wells at different positions. However, it should be noted that this method is not limited to this embodiment. In the following detailed description of this method, some specific details are described in detail. However, those skilled in the art can also fully understand the parts that are not described in detail.

[0047] This application takes the encrypted wells in the encrypted adjustment test area or the encrypted wells in a similar encrypted area as the research object. On the basis of qualitatively analyzing the factors affecting the water flooding of encrypted wells, it quantifies the relationship between each influencing factor and the initial water flooding status of encrypted wells, proposes the concept of "water flooding factor" to consider the comprehensive influence of the main factors on water flooding, and innovatively forms a method for quantitatively predicting the initial water flooding of encrypted wells in medium and low permeability water drive development oilfields. Based on the designed proposed encrypted wells in the current encrypted test area, this method is used to calculate the water flooding factors of the proposed encrypted wells, and then to guide the optimization and deployment of encrypted well positions.

[0048] As Figure 1 shown, a method for quantitatively predicting the initial water flooding of encrypted wells in medium and low permeability water drive development oilfields includes the following steps:

[0049] S1. Determine the evaluation indexes of the water flooding coefficient and calculate the values of each evaluation index;

[0050] Based on the encrypted well location map, sedimentary facies belt map and basic production data of oil and water wells in the encrypted well area of the study area, analyze the injection-production relationship and injection-production dynamics of oil and water wells around the encrypted wells, summarize the main factors affecting the water flooding of encrypted wells, and thus determine that the evaluation indexes of the water flooding coefficient are 7 items: the number of old water lines, the vertical distance from the water line, the injection-production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of surrounding oil wells, the current water cut of surrounding oil wells, and the cumulative injection volume of surrounding water wells.

[0051] According to the injection-production relationship between the encrypted wells and the surrounding oil and water wells, calculate the values of each index item by well and layer, including the number of old water lines, the vertical distance from the water line, the injection-production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of surrounding oil wells, the current water cut of surrounding oil wells, and the cumulative injection volume of surrounding water wells.

[0052] S2. Based on the calculated values of each evaluation index, establish the judgment boundary of the water flooding coefficient;

[0053] According to the values of each index obtained in step S1 in the study area, statistically analyze the distribution range of the values of 7 index items, including the number of old water lines, the vertical distance from the water line, the injection-production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of surrounding oil wells, the current water cut of surrounding oil wells, and the cumulative injection volume of surrounding water wells;

[0054] Based on the statistical distribution range of the 7 index values, classify each index in combination with the dynamic characteristics of the encrypted wells, and establish the judgment boundary of the water flooding coefficient.

[0055] The judgment boundaries of the water flooding coefficient are divided into 4, which are 0.2, 0.4, 0.6, and 0.8 respectively.

[0056] S3. Determine the weights of each evaluation index of the water flooding coefficient;

[0057] Using the linear regression method, statistically analyze the fitting correlations between the 7 indicators of the infill wells and the water flooding coefficients and initial water cut respectively to determine the degree of correlation.

[0058] Determine the weights of each indicator according to the determined degree of correlation.

[0059] S4. Calculate the water flooding factors of each proposed infill well.

[0060] Based on the proposed infill well location design in the infill test area, statistically analyze the 7 indicators of each proposed infill well layer by layer. According to the grading range determined in step 2, the judgment boundary of the water flooding coefficient corresponding to the grading indicators and the indicator weights in step 3, use the weighted method to calculate the water flooding factors of each proposed infill well.

[0061] S5. Optimize the infill well locations based on the water flooding factors of each proposed infill well. The specific methods include:

[0062] Optimize the deployment of the corresponding infill well locations according to the water flooding factors of each proposed infill well.

[0063] Obtain the upper limit value of the water flooding factor according to the reservoir type in the infill test area; the reservoir types in the infill test area include medium and low permeability oil reservoirs.

[0064] The upper limit value of the water flooding factor for medium permeability oil reservoirs is 0.6; the upper limit value of the water flooding factor for low permeability oil reservoirs is 0.5.

[0065] Optimize and determine the infill well locations based on the obtained upper limit value of the water flooding factor. The specific optimization method is:

[0066] For wells with a water flooding factor greater than the upper limit value, cancel the infill well locations.

[0067] For wells with a water flooding factor less than or equal to the upper limit value, retain the infill wells.

[0068] Example 1

[0069] Taking the Fang 483 block of Songfangtun Oilfield as an example, specifically illustrate a method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability water flooding developed oilfields according to the present invention, including the following steps:

[0070] 1) Design and calculate the evaluation indicators of the water flooding coefficient.

[0071] Taking the Fang 483 block as an example, based on the well location map of 17 infill wells in the block, the sedimentary facies belt map, the development effect of the infill wells and the production data of the basic oil and water wells in the infill well area, analyze the injection-production relationship and injection-production dynamics of the oil and water wells around the infill wells, summarize the main factors affecting the water flooding of the infill wells, and thus design and calculate the numerical values of 7 indicators including the number of old water lines, the vertical distance from the water line, the injection-production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of the surrounding oil wells, the current water cut of the surrounding oil wells, and the cumulative injection volume of the surrounding water wells.

[0072] As Figure 2 shown, the four indicators characterizing the injection-production relationship are the number of old water lines, the vertical distance from the water line, the injection-production well distance of the old water line, and the angle between the new and old water lines.

[0073] The specific parameter calculation methods are as follows:

[0074] The encrypted well location map and sedimentary facies belt map are obtained from the static database.

[0075] Number of old water lines: In a certain sedimentary unit, if the oil layer at the location of the encrypted well is developed and connected to the surrounding basic oil and water wells, the injected water in the surrounding basic well pattern may have reached the encrypted well. Therefore, the injection-production relationship coefficient of the basic oil and water wells is defined as the number of old water lines, that is, the number of injection-production connections formed by the surrounding basic oil and water wells connected to the encrypted well.

[0076] Vertical distance from the water line: In a certain sedimentary unit, the vertical distance from the encrypted well to the old water line formed in the well pattern where the encrypted well is located. When the number of old water lines is greater than 1, the minimum value is taken; when the number of old water lines is 0, infinity is taken.

[0077] Angle between the new water line and the old water line: In a certain sedimentary unit, the included angle between the new water line formed by the encrypted well and the water well and the old water line. When the number of old water lines is greater than 1, the minimum value is taken; when the number of old water lines is 0, infinity is taken.

[0078] Injection-production well distance of the old water line: In a certain sedimentary unit, the injection-production well distance of the old water line formed in the basic well pattern. When the number of old water lines is greater than 1, the minimum value is taken; when the number of old water lines is 0, infinity is taken.

[0079] As Figure 3 shown, the three indicator items characterizing the injection-production degree are the cumulative water production ratio of the surrounding oil wells, the current water cut of the surrounding oil wells, and the cumulative injection volume of the surrounding water wells.

[0080] The three indicators characterizing the injection-production degree are determined based on the production data of the oil and water wells in the well pattern.

[0081] The production data of the basic oil and water wells in the encrypted well area are obtained from the dynamic database.

[0082] Explanation of each parameter:

[0083] Cumulative water production ratio of the surrounding oil wells: In a certain sedimentary unit, the ratio of the cumulative water production of the oil wells with old water lines formed in the basic well pattern to the cumulative liquid production. When the number of old water lines is greater than 1, the maximum value is taken; when the number of old water lines is 0, infinitesimal is taken.

[0084] Current water cut of the surrounding oil wells: In a certain sedimentary unit, the water cut value before encryption of the oil wells with old water lines formed in the basic well pattern. When the number of old water lines is greater than 1, the maximum value is taken; when the number of old water lines is 0, infinitesimal is taken.

[0085] Cumulative injection volume of surrounding wells: In a certain sedimentary unit, it is the cumulative injection volume of the wells where the old water line has formed in the basic well pattern. When the number of old water lines is greater than 1, the maximum value is taken; when the number of old water lines is 0, an infinitesimal value is taken.

[0086] Calculate the values of 7 indicators for each infill well in each sedimentary unit respectively.

[0087] 2) Establish the evaluation boundary of water flooding coefficient

[0088] Based on the numerical distribution ranges of 7 indicators, namely the number of old water lines of infill wells, the perpendicular distance from the water line, the injection-production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of surrounding oil wells, the current water cut of surrounding oil wells, and the cumulative injection volume of surrounding wells in the study area, and combined with the dynamic characteristics of infill wells, classify the indicators and establish the evaluation boundary of the water flooding coefficient. The evaluation boundaries of the water flooding coefficient are 4, namely 0.2, 0.4, 0.6, and 0.8, and the evaluation boundaries of the water flooding coefficient are shown in Table 1.

[0089] Table 1.

[0090]

[0091]

[0092] 3) Determine the weights of the evaluation indicators of the water flooding coefficient

[0093] Use the linear regression method to statistically analyze the fitting correlation between the water flooding coefficient corresponding to 7 indicators of infill wells and the initial water cut respectively, and determine the indicator weights according to the degree of correlation. The weights of the evaluation indicators of the water flooding coefficient are shown in Table 2.

[0094] Taking 4 indicators representing the injection-production relationship, namely the number of old water lines, the injection-production well distance of the old water line, the perpendicular distance from the water line, and the angle between the new and old water lines, as an example, the method for determining their weights is as follows:

[0095] Obtain the above indicator values through step S1; through step S2, obtain the water flooding coefficient of each indicator. Take the average value of each sedimentary unit for a single well, and then respectively fit the linear relationship between the water flooding coefficient of a single well of each indicator and the initial water cut of the infill well, and then obtain the square value of the correlation coefficient (R 2 ). For example, the linear regression curve of the water flooding coefficient of the indicator of the number of old water lines and the initial water cut of the infill well is as Figure 4, the squared correlation coefficient is 0.8657. For the same indicators, the water flooding coefficients of the distance between injection-production wells of the old water line, the perpendicular distance from the water line, and the angle between the new and old water lines are linearly fitted with the initial water cut of the infill wells, and the squared correlation coefficients obtained are 0.2364, 0.4366, and 0.4344 respectively. The sum of the fitting correlation coefficients of the four indicators is 1.9731. The proportion of the squared value of each indicator's correlation coefficient is the indicator weight, which are 0.44, 0.12, 0.22, and 0.22 respectively. The method for determining the weights of the three indicators characterizing the injection-production degree is the same as the above method. Within the same system, the water flooding coefficient of a single indicator weighted by its corresponding weight can obtain the water flooding coefficient of the system. The linear relationships between the water flooding coefficients of each system and the initial water cut of the infill wells are respectively fitted, and then the squared correlation coefficients are obtained. By the same method, the weights of the injection-production system and the injection-production degree are 0.55 and 0.45 respectively.

[0096] Table 2

[0097]

[0098]

[0099] 4) Calculation of the water flooding factor of the proposed infill wells

[0100] Based on the proposed infill wells designed in the infill test area, seven indicators of the water flooding influencing factors of the proposed infill wells are determined for each well and each sedimentary unit. The water flooding coefficient values of single indicators of each sedimentary unit of the proposed infill wells are determined by applying the classification of each indicator in Table 1; the water flooding coefficient values of seven indicators of a single well of the proposed infill wells are respectively determined by the method of averaging by sedimentary unit. The water flooding coefficients of the injection-production relationship and the injection-production degree of the infill wells are respectively calculated by weighting the corresponding water flooding coefficient values of each indicator and the weights of each indicator in Table 2; the water flooding factor of a single well of the proposed infill wells is determined by weighting according to the weights of the two types of systems of injection-production relationship and injection-production degree in Table 2.

[0101] 5) Optimize the well positions of the infill wells according to the upper limit values of the water flooding factors of oilfields with different permeabilities;

[0102] Optimize the well position deployment according to the water flooding factor of the proposed infill wells calculated in step 4). According to the upper limit values of the water flooding factors of oilfields with different permeabilities, for medium-permeability oilfields, the infill well positions are cancelled for wells with a water flooding factor greater than 0.6, and the infill wells are retained for those less than or equal to 0.6; for low-permeability oilfields, the infill well positions are cancelled for wells with a water flooding factor greater than 0.5, and the infill wells are retained for those less than or equal to 0.5.

[0103] This application has a high degree of summarization and pertinence. The operation method is simple and efficient, and it can guide the optimization of the well positions of infill wells in oilfields. At present, the water flooding risk of infill wells can only be qualitatively judged, and the water flooding risk degree cannot be quantitatively characterized, and there is no similar quantitative method for comparison.

[0104] This application optimizes the deployment of infill wells based on the encrypted water flooding factor. After implementing this method at the field of Zhaozhou Oilfield, 69 infill oil wells are planned, with a built production capacity of 3.51×104t. The initial average daily oil production per well of the infill wells is 1.71t. After the infill, the water cut of the old wells is relatively stable. The infill wells account for 27.8% of the total wells in the whole area. However, the annual production after four years of production still accounts for half of the total production in the whole area, and the recovery factor is expected to increase by 3 percentage points. Among the 69 infill wells, only 10 wells have an initial water cut of more than 90%, and the proportion of highly water flooded wells is 14.5%. Compared with other infill programs that do not use this method to optimize the infill well positions, the proportion of highly water flooded wells is reduced by more than 15%.

[0105] Those of ordinary skill in the art will realize that the embodiments described herein are to assist the reader in understanding the implementation methods of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations that do not depart from the essence of the present invention based on the technical revelations disclosed in the present invention, and these deformations and combinations are still within the scope of protection of the present invention.

Claims

1. A method for quantitatively predicting the initial water flooding of infill wells in medium - low permeability water - flooding developed oilfields, Characterized in that: It includes the following steps: S1. Determine the evaluation indexes of the water - flooding coefficient and calculate the values of each evaluation index; S2. Based on the calculated values of each evaluation index, establish the judgment boundary of the water - flooding coefficient; S3. Determine the weights of each evaluation index of the water - flooding coefficient; S4. Calculate the water - flooding factors of each proposed infill well; S5. Optimize the well positions of the infill wells based on the water - flooding factors of each proposed infill well.

2. The method for quantitatively predicting the initial water flooding of infill wells in medium - low permeability water - flooding developed oilfields according to claim 1, Characterized in that: The method for determining the evaluation indexes of the water - flooding coefficient in step S1 includes: Based on the infill well location map, sedimentary facies belt map and the production data of basic oil and water wells in the infill well area of the study area, analyze the injection - production relationship and injection - production dynamics of the oil and water wells around the infill wells, summarize the main factors affecting the water flooding of the infill wells, and thus determine that the evaluation indexes of the water - flooding coefficient are 7 items: the number of old water lines, the vertical distance from the water line, the injection - production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of the surrounding oil wells, the current water cut of the surrounding oil wells and the cumulative injection volume of the surrounding water wells; among them, the indexes representing the injection - production relationship are 4 items: the number of old water lines, the vertical distance from the water line, the injection - production well distance of the old water line and the angle between the new and old water lines; the indexes representing the injection - production degree are the cumulative water production ratio of the surrounding oil wells, the current water cut of the surrounding oil wells and the cumulative injection volume of the surrounding water wells.

3. The method for quantitatively predicting the initial water flooding of infill wells in medium - low permeability water - flooding developed oilfields according to claim 2, Characterized in that: The calculation method of the values of each evaluation index in step S1 is: Based on the injection - production relationship between the infill well and the surrounding oil and water wells, calculate the values of each index item by item for each well and each layer, including the number of old water lines, the vertical distance from the water line, the injection - production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of the surrounding oil wells, the current water cut of the surrounding oil wells and the cumulative injection volume of the surrounding water wells.

4. The method for quantitatively predicting the initial water flooding of infill wells in medium - low permeability water - flooding developed oilfields according to claim 3, Characterized in that: The method for establishing the judgment boundary of the water - flooding coefficient in S2 based on the calculated values of each evaluation index includes: Based on the values of each index in the study area obtained in step S1, statistically analyze the distribution ranges of the values of 7 index items, including the number of old water lines, the vertical distance from the water line, the injection - production well distance of the old water line, the angle between the new and old water lines, the cumulative water production ratio of the surrounding water wells, the current water cut of the surrounding oil wells and the cumulative injection volume of the surrounding water wells for the infill wells; Based on the distribution ranges of the values of the 7 statistically analyzed index items, classify each index in combination with the dynamic characteristics of the infill wells and establish the judgment boundary of the water - flooding coefficient.

5. The method for quantitatively predicting the initial water flooding of infill wells in medium - low permeability water - flooding developed oilfields according to claim 4, Characterized in that: The judgment boundaries of the water - flooding coefficient are 4, which are 0.2, 0.4, 0.6 and 0.8 respectively.

6. The method for quantitatively predicting the initial water flooding of infill wells in medium - low permeability water - flooding developed oilfields according to claim 5, Characterized in that: The method for determining the weights of the evaluation indexes of the water - flooding coefficient in step S3 is: Use the linear regression method to statistically analyze the fitting correlation between the water - flooding coefficient corresponding to the 7 indexes of the infill well and the initial water cut respectively, and determine the degree of correlation; Determine the weights of each index according to the determined degree of correlation.

7. The method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability water flooding developed oilfields according to claim 6, characterized in that: In the step S4 of calculating the water flooding factor: Based on the design of the proposed infill well positions in the infill test area, statistically count 7 indexes of the proposed infill wells layer by layer and well by well. According to the grading range determined in step 2, based on the water flooding coefficient evaluation boundary corresponding to the grading index and the index weights in step 3, use the weighted method to calculate the water flooding factors of each proposed infill well to be deployed.

8. The method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability water flooding developed oilfields according to claim 7, characterized in that: The method for optimizing the positions of infill wells in the step S5 is: Optimize the deployment of the corresponding infill well positions according to the water flooding factors of each proposed infill well; Obtain the upper limit value of the water flooding factor according to the reservoir type of the infill test area; Based on the obtained upper limit value of the water flooding factor, optimize and determine the positions of infill wells.

9. The method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability water flooding developed oilfields according to claim 8, characterized in that: The reservoir types in the infill test area include medium and low permeability oil reservoirs; The upper limit value of the water flooding factor for medium permeability oil reservoirs is 0.6; the upper limit value of the water flooding factor for low permeability oil reservoirs is 0.

5.

10. The method for quantitatively predicting the initial water flooding of infill wells in medium and low permeability water flooding developed oilfields according to claim 8, characterized in that: The method for optimizing and determining the positions of infill wells based on the obtained upper limit value of the water flooding factor is: For wells with a water flooding factor greater than the upper limit value, cancel the infill well positions; For wells with a water flooding factor less than or equal to the upper limit value, retain the infill wells.

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