Quantitative prediction method for flooding of well section of infilled horizontal well of offshore water-drive oil field

Abstract

The invention discloses a quantitative prediction method for water logging of a well section of an infilled horizontal well of an offshore water-drive oil field. The method comprises the following steps: S1, dividing a well spacing area of the horizontal well into a plurality of grids; s2, establishing a displacement pressure, gravity and buoyancy coupled flooding thickness quantitative prediction mathematical model, and drawing a waterline propulsion chart; s3, based on the waterline propelling condition, the remaining oil distribution coefficient of the well spacing area is calculated; s4, screening remaining oil gathering grids according to the remaining oil distribution coefficient, and quantitatively judging the water logging condition of the well section of the horizontal well; and S5, reevaluating the enrichment degree of the remaining oil, and further evaluating and determining the potential tapping grid of the horizontal well. According to the quantitative prediction method for flooding of the well section of the infilled horizontal well in the offshore water-drive oil field, three-dimensional representation of the flooding position and the flooding degree of the well section of the infilled horizontal well in a high-water-content oil reservoir can be achieved, the remaining oil enrichment area suitable for implementing the horizontal well can be accurately screened and evaluated, then well position deployment of the horizontal well is guided, and the infilled adjustment effect is improved.

Description

Technical Field

[0001] This invention relates to the field of oilfield waterflooding development technology, and in particular to a quantitative prediction method for water flooding in infill horizontal well sections in offshore waterflooding oilfields. Background Technology

[0002] After long-term water-drive development, sandstone oilfields have entered a high water-cut stage, resulting in more complex residual oil. Offshore oilfields currently primarily utilize horizontal well infill drilling to tap into localized residual oil. However, the water flooding in actual horizontal well drilling is complex, leading to rapid increases in water cut and significant production declines, severely impacting efficient oilfield development. Currently, there are three main methods for identifying water flooding in horizontal well sections: first, logging technology, but this requires water flooding identification through logging curves after horizontal well construction, and cannot provide quantitative prediction before drilling; second, numerical simulation methods, the reliability of which depends on the accuracy of residual oil calculations, and its reliability is significantly affected by human factors; and third, dynamic and static data such as production and absorption profiles of surrounding oil and water wells, production dynamics of oil and water wells, and tracer data, but offshore oilfields have limited testing data, especially stratified testing data, which cannot meet prediction needs. Furthermore, all of the above methods focus on well groups and small layers, lacking quantitative characterization and evaluation methods for localized residual oil enrichment areas. Therefore, determining the location and degree of water flooding in horizontal well sections is particularly important in oilfield horizontal well infill drilling adjustments. Summary of the Invention

[0003] This invention addresses the problem that existing technologies cannot effectively predict water flooding in infill horizontal well sections, by providing a quantitative prediction method for water flooding in infill horizontal well sections in water-drive oilfields. This method can quantitatively predict the location and extent of water flooding in infill horizontal wells, effectively guiding well placement and providing a basis for infill adjustments during high water-cut periods in offshore oilfields.

[0004] The present invention solves its problem through the following technical solution: a method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields, comprising the following steps: S1. Divide the area for the proposed horizontal well layout into multiple grids; S2. Establish a mathematical model for quantitative prediction of flooded thickness based on the coupling of displacement pressure, gravity, and buoyancy, and draw a waterline advancement chart. S3. Based on the waterline advance situation, calculate the remaining oil distribution coefficient in the well placement area; S4. Based on the remaining oil distribution coefficient, accurately screen the remaining oil accumulation grid and quantitatively determine the water flooding situation in the horizontal well section; S5. Re-evaluation of the remaining oil enrichment level, further evaluation to determine the grid for tapping the potential of horizontal wells.

[0005] S1. A method for dividing the quasi-horizontal well placement area into multiple grids, including: Based on the reservoir distribution, physical properties, well network type, length of planned horizontal wells, and utilization range of the well placement area, the utilization potential area is divided into several grids.

[0006] S2. The method for establishing a mathematical model for quantitative prediction of flooded thickness based on the coupling of displacement pressure, gravity, and buoyancy, and for drawing waterline advancement charts, is as follows: Based on the water flooding situation of the drilled adjustment wells, it was found that the water flooding pattern within a single layer is mainly bottom water flooding, accounting for 73%. The remaining water flooding types are mainly multi-stage water flooding characteristics affected by interlayers. However, when the reservoir is further subdivided into single sand bodies, the water flooding within the single sand body is still mainly bottom water flooding without the influence of interlayers. The main reason for the bottom water flooding characteristics within the layer is that the displacement phase particles are subjected to the combined effects of displacement pressure, gravity and buoyancy, causing the displacement phase to migrate forward and downward and flow out from the lower part of the oil well.

[0007] Assuming a closed, incompressible, thick oil reservoir, where fluid flow follows Newton's law of seepage, a mathematical model is established that couples displacement pressure, gravity, and buoyancy.

[0008] The displacement phase particles are mainly affected by the displacement pressure on the plane, which is primarily influenced by the production pressure difference between injection and production wells. The specific displacement pressure gradient formula is as follows: (1) In the formula: The bottom hole pressure of the injection well is measured in MPa. The bottom hole flowing pressure of the oil well is in MPa. The distance between injection and production wells is in meters (m). This is the pressure loss conversion factor, which is dimensionless.

[0009] Due to the combined effects of gravity and buoyancy in the longitudinal direction, the longitudinal pressure gradient is: (2) In the formula: The density of the aqueous phase is g / cm³. 3 ; The density of the oil-water mixture is given in g / cm³. 3 g is the acceleration due to gravity, in m / s². 2 .

[0010] The oil-water mixture density dynamically changes with the oil-water saturation during reservoir development, causing variations in gravity and buoyancy as displacement occurs, resulting in different longitudinal sweep patterns at different water-cut stages. The oil-water mixture density can be calculated based on the average water saturation. (3) Meanwhile, according to the BL equation, the formula for average water saturation is: (4) In the formula: The average water saturation of the oil-water two-phase system is dimensionless. Water saturation at the outlet, dimensionless; PV represents the injection porosity multiple. The moisture content at the outlet is dimensionless. The density of the oil phase is g / cm³. 3 .

[0011] The displacing phase particles conform to Darcy's flow law in both the planar and longitudinal directions, and their flow velocity formula is: (5) (6) in The velocity is the planar seepage velocity, in m / d; The longitudinal seepage velocity is expressed in m / d. Let mD be the horizontal permeability of the reservoir. denoted as reservoir vertical permeability, mD. The viscosity of the displaced phase is given in mPa·s.

[0012] Substituting equation (1) into equation (5), we obtain the formula for horizontal seepage velocity: (7) Substituting equations (2), (3), and (4) into equation (6), we obtain the formula for the vertical seepage velocity: (8) Therefore, under the combined action of the three forces, the migration trajectory of the displaced phase particles is obtained, and the distance that the displaced phase particles descend at any position between the oil and water wells is the unflooded thickness within the layer: (9) In the formula: Location between oil and water wells The thickness of the unflooded area is in meters; t is the time (d) for the displacing phase to flow through any location between the oil and water wells. denoted as , which is the distance between any point between the oil and water wells and the water injection well, in meters.

[0013] Therefore, the formula for water-flooded thickness is: (10) In the formula: For position The thickness of the water-flooded area is in meters. For position The effective thickness of the reservoir is given in meters.

[0014] By combining parameters such as reservoir thickness, injection-production well spacing, permeability, injection porosity multiple, and water cut of each grid in the well area, and using the water flooding thickness formula, the water flooding thickness at different grid locations is calculated, thus obtaining waterline advancement maps at different locations between injection and production wells. The waterline maps show that the longitudinal water flooding thickness increases with increasing injection porosity multiple and permeability, and decreases with increasing reservoir thickness, injection-production well spacing, and water cut.

[0015] S3. Based on the waterline advance situation, the method for calculating the remaining oil distribution coefficient in the well placement area is as follows: Based on the waterline advancement in S2, the water-flooded thickness of each grid is obtained. The concept of a residual oil distribution coefficient is introduced to achieve a three-dimensional representation of residual oil-rich areas with different planar sizes and water-flooding degrees, enabling rapid and accurate screening of suitable residual oil-rich areas for horizontal well tapping. Grids with a water-flooded thickness exceeding 80% are defined as water-flooded grids with a weighting coefficient of 0.2; grids with a water-flooded thickness above 50% are defined as sub-water-flooded grids with a weighting coefficient of 0.5; grids with a water-flooded thickness below 50% are defined as sub-retention grids with a weighting coefficient of 0.8; and grids with a water-flooded thickness below 20% are defined as retention grids with a weighting coefficient of 1. The residual oil distribution coefficient is defined as the ratio of the sum of the products of the grid area satisfying the oil layer water-flooded thickness limit and the grid weight to the area of ​​the utilized region. The expression for the residual oil distribution coefficient is as follows: (11) In the formula: The residual oil distribution coefficient is dimensionless. m is the grid area. 2 ; is the grid weight; m and n are the grid dimensions within the enriched region; i and j are the grid coordinates within the enriched region.

[0016] The above-mentioned water flooding level thresholds (20%, 50%, 80%) and corresponding weight coefficients (0.2, 0.5, 0.8, 1.0) are set based on the economic evaluation results of Bohai Oilfield: when the water flooding thickness exceeds 80%, the expected oil production revenue of deploying horizontal wells is lower than the drilling and completion costs, and the economic value is extremely low, so a low weight of 0.2 is assigned; conversely, units with a water flooding thickness of less than 20% represent high-quality remaining oil that has not been used or has been basically not flooded, and have the highest economic value, so the highest weight of 1.0 is assigned.

[0017] S4. The method for accurately screening the remaining oil accumulation grid and quantitatively determining the water flooding situation in the horizontal well section based on the remaining oil distribution coefficient is as follows: The smaller the residual oil distribution coefficient, the greater the risk of water flooding and the larger the scale of water flooding; conversely, the larger the residual oil distribution coefficient, the more concentrated the residual oil. When the residual oil distribution coefficient of the proposed horizontal well placement area is greater than or equal to 0.5, the well placement conditions are met; when the residual oil distribution coefficient of the proposed horizontal well placement area is less than 0.5, the horizontal well placement is cancelled. Simultaneously, the water flooding situation of the horizontal well section can be quantitatively judged by combining the water flooding level of each grid. Horizontal well sections located in water flooded grids and sub-water flooded grids have a water flooding risk, while those located in sub-retention grids and retention grids have no water flooding risk. Based on this, the horizontal well positions are optimized, and horizontal wells are optimally deployed on sub-retention grids and retention grids where the water flooding thickness ratio is less than 50%.

[0018] S5. Re-evaluation of remaining oil enrichment level, and further evaluation of the method for determining the grid for horizontal well potential tapping: Due to the uncertainty and complexity of oil reservoirs, the quantitative distribution results of remaining oil obtained using the remaining oil distribution coefficient need further confirmation. Based on the oilfield development characteristics, four indicators were selected as evaluation indicators for the degree of remaining oil enrichment: distance from water wells, distance from the main flow line, sand body superposition degree, and cumulative injected pore volume. The greater the distance from water wells and the main flow line, the greater the degree of remaining oil enrichment. The sand body superposition degree, formed by the deposition of multiple sand bodies in different phases, represents the degree of heterogeneity of the sand bodies. Enriched areas often exhibit sand body superposition; a greater superposition degree indicates significant differences in vertical connectivity, easily leading to phenomena such as injection-production disconnection, thus forming a remaining oil enrichment area. The cumulative injected pore volume characterizes the degree of mobilization in the area; a smaller cumulative injected pore volume indicates a greater degree of remaining oil enrichment. The values ​​of the four indicators were determined based on the actual reservoir characteristics of the well placement area and the production data of oil and water wells. Based on the magnitude of the indicator values, four evaluation criteria were established: [a, b] for good, (b, c] for relatively good, (c, d] for relatively poor, and (d, e] for poor. The normalized indicators were used to calculate the evaluation vector through a membership function to obtain the evaluation results. The remaining oil clusters selected using the remaining oil distribution coefficient were evaluated. Grids with evaluation results of "good" or "relatively good" had low water flooding risk and could be recommended areas for horizontal well implementation.

[0019] In summary, the technical effects and advantages of this invention are as follows: the method of this invention can achieve three-dimensional characterization of the water flooding thickness, planar water flooding location, and water flooding degree within high water-cut oil reservoirs, accurately screen and evaluate the remaining oil-rich areas suitable for infill horizontal wells, thereby guiding the infill deployment of horizontal wells and improving the infill adjustment effect. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields, according to an embodiment of the present invention. Figure 2 This is a grid division of the well layout area in one embodiment of the present invention; Figure 3 This is a coupled seepage model of displacement pressure, gravity, and buoyancy in one embodiment of the present invention; Figure 4 This is a water flooding thickness distribution diagram between injection and production wells in well group w1, according to one embodiment of the present invention. Figure 5 This is a waterline propulsion diagram according to one embodiment of the present invention; Figure 6 This is a schematic diagram of the residual oil distribution coefficient in one embodiment of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Furthermore, the technical features involved in the different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other. The following example is a method for predicting the location and degree of water flooding in a horizontal well section based on dynamic and static data of an encrypted horizontal well area, but the method is not limited to this embodiment.

[0024] This application takes the infill horizontal wells in the proposed deployment area as the research object. Using reservoir engineering methods, it establishes a mathematical model of coupled seepage based on displacement pressure, gravity, and buoyancy to quantitatively characterize the variation law of water flooding thickness and form an intra-layer waterline advancement chart. Based on this, it proposes the concept of residual oil distribution coefficient, three-dimensionally characterizes the water flooding thickness, planar water flooding location, and water flooding degree in high water-cut oil reservoirs, and proposes an evaluation method for residual oil enrichment areas. It innovatively forms a quantitative prediction method for water flooding infill horizontal well sections in offshore water-drive oilfields, guiding the optimal selection and deployment of horizontal well locations for infill drilling.

[0025] Example 1 Taking the Bohai S oilfield as an example, this invention specifically illustrates a method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields. Figure 1 As shown, it includes the following steps: 1) Divide the proposed horizontal well layout area into multiple grids.

[0026] Taking the planned horizontal well layout area of ​​Oilfield S as an example, the well spacing is 300m, the row spacing is 350m, and the horizontal well length is 300m. This area is artificially divided into 15 grids. Horizontally, the horizontal wells can be divided into three segments: the heel end, the middle end, and the toe end, facilitating the determination of water flooding locations. Figure 2 As shown.

[0027] 2) Establish a mathematical model for quantitative prediction of flooding thickness by coupling displacement pressure, gravity, and buoyancy, and draw a waterline advancement chart.

[0028] Based on the water flooding situation of the drilled adjustment wells, it was found that the water flooding pattern within a single layer is mainly bottom water flooding, accounting for 73%. The remaining water flooding types are mainly multi-stage water flooding characteristics affected by interlayers. However, when the reservoir is further subdivided into single sand bodies, the water flooding within the single sand body is still mainly bottom water flooding without the influence of interlayers. The main reason for the bottom water flooding characteristics within the layer is that the displacement phase particles are subjected to the combined effects of displacement pressure, gravity and buoyancy, causing the displacement phase to migrate forward and downward and flow out from the lower part of the oil well.

[0029] Assuming a closed, incompressible, thick oil reservoir where fluid flow follows Newton's law of seepage, a mathematical model is established based on the coupling of displacement pressure, gravity, and buoyancy, such as... Figure 3 As shown.

[0030] The displacement phase particles are mainly affected by the displacement pressure on the plane, which is primarily influenced by the production pressure difference between injection and production wells. The specific displacement pressure gradient formula is as follows: (1) In the formula: The bottom hole pressure of the injection well is measured in MPa. The bottom hole flowing pressure of the oil well is in MPa. The distance between injection and production wells is in meters (m). This is the pressure loss conversion factor, which is dimensionless.

[0031] Due to the combined effects of gravity and buoyancy in the longitudinal direction, the longitudinal pressure gradient is: (2) In the formula: The density of the aqueous phase is g / cm³. 3 ; The density of the oil-water mixture is given in g / cm³. 3 g is the acceleration due to gravity, in m / s². 2 .

[0032] The oil-water mixture density dynamically changes with the oil-water saturation during reservoir development, causing variations in gravity and buoyancy as displacement occurs, resulting in different longitudinal sweep patterns at different water-cut stages. The oil-water mixture density can be calculated based on the average water saturation. (3) Meanwhile, according to the BL equation, the formula for average water saturation is: (4) In the formula: The average water saturation of the oil-water two-phase system is dimensionless. Water saturation at the outlet, dimensionless; PV represents the injection porosity multiple. ρ represents the moisture content at the outlet, which is dimensionless. o The density of the oil phase is g / cm³. 3 .

[0033] The displacing phase particles conform to Darcy's flow law in both the planar and longitudinal directions, and their flow velocity formula is: (5) (6) in The velocity is the planar seepage velocity, in m / d; The longitudinal seepage velocity is expressed in m / d. Let mD be the horizontal permeability of the reservoir. denoted as reservoir vertical permeability, mD; μ is the viscosity of the displaced phase, mPa·s.

[0034] Substituting equation (1) into equation (5), we obtain the formula for horizontal seepage velocity: (7) Substituting equations (2), (3), and (4) into equation (6), we obtain the formula for the vertical seepage velocity: (8) Therefore, under the combined action of the three forces, the migration trajectory of the displaced phase particles is obtained, and the distance that the displaced phase particles descend at any position between the oil and water wells is the unflooded thickness within the layer: (9) In the formula: Location between oil and water wells The thickness of the unflooded area is in meters; t is the time (d) for the displacing phase to flow through any location between the oil and water wells. denoted as , which is the distance between any point between the oil and water wells and the water injection well, in meters.

[0035] Therefore, the formula for water-flooded thickness is: (10) In the formula: For position The thickness of the water-flooded area is in meters. For position The effective thickness of the reservoir is given in meters.

[0036] The S oilfield is a delta front sedimentary formation, with the main hydrocarbon-bearing layer being the lower section of the Paleogene Dongying Formation. The main reservoir layers are well-developed, with large, continuous sand bodies exhibiting good connectivity and stable distribution, ranging in thickness from 40.0 to 120.0 meters. The reservoir is loosely cemented, exhibiting high porosity and high permeability. Porosity ranges from 27.0% to 35.8%, with an average of 32.0%; permeability ranges from 100.0 mD to 12000.0 mD, with an average of 2815.0 mD. The oilfield commenced production in 1993. After one and two adjustments, the oilfield's recovery rate reached 34%, with a water cut of 92%, entering an ultra-high water-cut stage. The main reservoir layers are generally heavily water-flooded. Taking the W1 well area of ​​S oilfield as an example, the injection-production well distance between W1 and P2 is 350m, the planar permeability is 2800mD, the water-to-vertical ratio is 0.1, the effective thickness of the main layer and the 6 sub-layers is 20m, and the oil density is 0.9707g / cm³. 3 The crude oil viscosity is 50 mPa·s, the injection pore volume is 1.0 PV, the water cut is 91%, the pressure loss coefficient is 0.33, the wellhead pressure of injection well w1 is 10 MPa, the bottom-hole flowing pressure of production well p2 is 5.6 MPa, and the water saturation at the outlet end is obtained by establishing the relationship curve between different injection pore volume ratios and water saturation at the outlet end using oilfield core water drive experiments. Based on these parameters, the water flooding thickness at different locations between injection and production wells is calculated using mathematical model formulas (9) and (10). The calculated water flooding thickness at the oil well end is 11.6 m. Figure 4 As shown, the thickness is consistent with the actual water-flooded thickness.

[0037] The water-flooded thickness of different main layers was calculated using this method, as shown in Table 1. Substituting the parameters in the table into the final model formula, the predicted values ​​matched the measured water-flooded thickness values ​​well, verifying the prediction accuracy and reliability of the model, which can be used to predict water-flooded thickness.

[0038] Table 1 By combining parameters such as reservoir thickness, injection-production well spacing, permeability, injection porosity, and water cut of each grid in the well area, and using the water flooding thickness formula, the water flooding thickness at different grid locations is calculated, thus obtaining waterline advancement maps at different locations between injection and production wells. The waterline maps show that the longitudinal water flooding thickness increases with increasing injection porosity and permeability, and decreases with increasing reservoir thickness, injection-production well spacing, and water cut. Figure 5 As shown.

[0039] 3) Calculate the remaining oil distribution coefficient in the well placement area based on the waterline advance situation.

[0040] Based on the waterline advancement, the water-flooded thickness of each grid is obtained. The concept of a residual oil distribution coefficient is introduced to achieve a three-dimensional representation of residual oil-rich areas with different planar sizes and water-flooding degrees, enabling rapid and accurate screening of suitable residual oil-rich areas for horizontal well exploration. Grids with a water-flooded thickness exceeding 80% are defined as water-flooded grids, with a weighting coefficient of 0.2. Grids with a water-flooded thickness above 50% are defined as sub-water-flooded grids, with a weighting coefficient of 0.5. Grids with a water-flooded thickness below 50% are defined as sub-retention grids, with a weighting coefficient of 0.8; and grids with a water-flooded thickness below 20% are defined as retention grids, with a weighting coefficient of 1. The residual oil distribution coefficient is defined as the ratio of the sum of the products of the grid area satisfying the oil layer water-flooded thickness limit condition and the grid weight to the area of ​​the utilized region. The expression for the residual oil distribution coefficient is as follows: (11) In the formula: The remaining oil distribution coefficient; The grid area is in m3; The area of ​​the enriched region is defined in m². is the grid weight; m and n are the grid dimensions within the enriched region; i and j are the grid coordinates within the enriched region.

[0041] The aforementioned water flooding thresholds (20%, 50%, 80%) and corresponding weighting coefficients (0.2, 0.5, 0.8, 1.0) are set based on the economic evaluation results of the Bohai S oilfield: when the water flooding thickness exceeds 80%, the expected oil production revenue of deploying horizontal wells is lower than the drilling and completion costs, resulting in extremely low economic value, hence a low weight (0.2); conversely, units with a water flooding thickness of less than 20% represent high-quality remaining oil that is unused or basically unflooded, possessing the highest economic value, hence the highest weight (1.0). These weighting coefficients are essentially simplified proxy parameters for the economic value coefficients.

[0042] 4) Based on the remaining oil distribution coefficient, accurately screen the remaining oil accumulation grid and quantitatively determine the water flooding situation in the horizontal well section.

[0043] The smaller the residual oil distribution coefficient, the greater the risk of water flooding and the larger the scale of water flooding; conversely, the larger the residual oil distribution coefficient, the more concentrated the residual oil. Simultaneously, the location of infill wells is optimized based on the water flooding ratio of each grid. When the residual oil distribution coefficient of the proposed horizontal well placement area is greater than or equal to 0.5, the well placement conditions are met; when the residual oil distribution coefficient of the proposed horizontal well placement area is less than 0.5, the infill well location is cancelled. Furthermore, by combining the water flooding level of each grid, the water flooding situation of the horizontal well section can be quantitatively judged. Horizontal well sections located in water flooded grids and sub-water flooded grids have a water flooding risk, while those located in sub-retention grids and retention grids do not have a water flooding risk. Based on this, the location of horizontal wells is optimized, and horizontal wells are optimally deployed in sub-retention grids and retention grids where the water flooding thickness ratio is less than 50%.

[0044] like Figure 6 As shown, the distribution coefficient of remaining oil in this area is calculated as follows: The value is greater than 0.5, thus meeting the conditions for deploying a horizontal well. At the same time, the flooding level at the location of the horizontal well is calculated. The two grids to the left of the horizontal well location are stagnant grids with a flooding thickness ratio of less than 20%, while the grid to the right is a flooded grid with a flooding thickness ratio of more than 80%. Therefore, the horizontal well location is optimized by shifting it to the left by one grid, and the horizontal well is optimized to be deployed on the secondary stagnant grid and the stagnant grid where the flooding thickness ratio is less than 50%. Furthermore, the flooding situation at various points along the horizontal well section can be predicted.

[0045] 5) Re-evaluate the remaining oil enrichment level and further evaluate and determine the grid for tapping the potential of horizontal wells.

[0046] Due to the uncertainty and complexity of underground oil reservoirs, the quantitative distribution results of remaining oil obtained using the remaining oil distribution coefficient need further confirmation. Based on oilfield characteristics, four indicators were selected as evaluation indicators for the degree of remaining oil enrichment: distance from water wells, distance from the main flow line, sand body superposition degree, and cumulative injected pore volume, as shown in Table 2. The greater the distance from water wells and the greater the distance from the main flow line, the greater the degree of remaining oil enrichment. The sand body superposition degree represents the heterogeneity of sand bodies formed by the deposition of multiple sand bodies from different periods. Enriched areas often exhibit sand body superposition; a greater superposition degree indicates significant differences in vertical connectivity, easily leading to phenomena such as injection-production disconnection, thus forming a remaining oil enrichment area. The cumulative injected pore volume characterizes the degree of mobilization in the area; a smaller cumulative injected pore volume indicates a greater degree of remaining oil enrichment. The values ​​of the four indicators were determined based on the actual reservoir characteristics and oil and water well production data of the well placement area. Based on the indicator values, four evaluation criteria were established: [a, b] for good, (b, c] for relatively good, (c, d] for relatively poor, and (d, e] for poor. The normalized indicators were used to calculate the evaluation vector through a membership function to obtain the evaluation results. The remaining oil cluster grids selected using the remaining oil distribution coefficient were evaluated, and the results are shown in Table 3. The seven potential grids with good or relatively good evaluation results among the 15 grids have low water flooding risk and can be considered as recommended areas for deploying horizontal wells.

[0047] Table 2 Table 3 This embodiment was applied to the Bohai S oilfield. Before applying this embodiment, 43 horizontal wells were deployed using traditional numerical simulation methods, with a non-weak water flooding encounter rate of only 75%, mostly exhibiting segmented water flooding characteristics, an average daily oil production of 45 tons, and an average water cut of 86%. Using this invention, 81 development wells were deployed with secondary adjustments, including 60 horizontal wells. Through optimization of the horizontal well locations, the non-weak water flooding encounter rate of the horizontal well sections reached 93% (18% higher than the traditional method), the average daily oil production of new wells was 60 tons (1.3 times that of the traditional method), and the water cut was 75% (11% lower than the traditional method), resulting in a production capacity of 102 × 10⁻⁶ tons. 4 t.

[0048] Finally, it should be noted that the preferred embodiments of the present invention have been described above, but the present invention is not limited to the specific embodiments described above. The devices and structures not described in detail should be understood to be implemented in the ordinary way in the art. Any simple modifications, equivalent changes and modifications made by any person skilled in the art to the above embodiments based on the technical essence of the present invention without departing from the scope of the technical solution of the present invention shall still fall within the protection scope of the technical solution of the present invention.

Claims

1. A quantitative prediction method for water flooding in infill horizontal well sections in offshore water-drive oilfields, characterized in that, Includes the following steps: S1. Divide the area for the proposed horizontal well layout into multiple grids; S2. Establish a mathematical model for quantitative prediction of flooded thickness based on the coupling of displacement pressure, gravity, and buoyancy, and draw a waterline advancement chart. S3. Based on the waterline advance situation, calculate the remaining oil distribution coefficient in the well placement area; S4. Based on the remaining oil distribution coefficient, screen the remaining oil aggregation grid and quantitatively determine the water flooding situation in the horizontal well section; S5. Re-evaluation of the remaining oil enrichment level, further evaluation to determine the grid for tapping the potential of horizontal wells.

2. The method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields according to claim 1, characterized in that, Step S1 divides the quasi-horizontal well placement area into multiple grids using the following method: Based on the reservoir distribution, physical properties, well network type, length of planned horizontal wells, and utilization range of the well placement area, the utilization potential area is divided into several grids.

3. The method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields according to claim 1, characterized in that, Step S2 establishes a mathematical model for quantitative prediction of flooded thickness based on the coupling of displacement pressure, gravity, and buoyancy, and draws a waterline advancement chart, including: Assuming a closed, incompressible, thick oil reservoir where fluid flow follows Newton's law of seepage, a mathematical model coupling displacement pressure, gravity, and buoyancy is established using reservoir engineering methods. The migration trajectory of displaced phase particles is calculated, thereby obtaining a formula for calculating the water-flooded thickness within the thick reservoir. By combining the reservoir thickness, injection-production well spacing, permeability, injection porosity multiple, and water cut parameters of each grid in the well area, and using the water flooding thickness formula, the water flooding thickness at different grid locations is calculated, thereby obtaining the waterline advancement map at different locations between injection and production wells.

4. The method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields according to claim 3, characterized in that, The formula for calculating the thickness of the flooded area is: In the formula: For position The thickness of the water-flooded area is in meters. For position The effective thickness of the reservoir is in meters. Location between oil and water wells Thickness at the un-flooded location, in meters; The longitudinal seepage velocity is m / d; t is the time (d) for the displacing phase to flow through any location between the oil and water wells. denoted as the distance between any point between the oil and water wells and the water injection well, in meters; The velocity is the planar seepage velocity, in m / d; Let mD be the horizontal permeability of the reservoir. D is the vertical permeability of the reservoir, in m; L is the injection-production well spacing, in m; The density of the aqueous phase is g / cm³. 3 ; Water saturation at the outlet, dimensionless; PV represents the injection porosity multiple. The moisture content at the outlet is dimensionless. The density of the oil phase is g / cm³. 3 g is the acceleration due to gravity, m / s² 2 ; This is the pressure loss conversion factor, which is dimensionless. The bottom hole pressure of the injection well is measured in MPa. The bottom hole pressure of the oil well is MPa.

5. The method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields according to claim 1, characterized in that, Step S3, based on the waterline advancement situation, calculates the remaining oil distribution coefficient in the well placement area, including: Based on the waterline advance in S2, the water-flooded thickness of each grid is obtained. The concept of residual oil distribution coefficient is introduced. Grids with a water-flooded thickness exceeding 80% are defined as water-flooded grids with a weighting coefficient of 0.2; grids with a water-flooded thickness above 50% are defined as sub-water-flooded grids with a weighting coefficient of 0.5; grids with a water-flooded thickness below 50% are defined as sub-retention grids with a weighting coefficient of 0.8; and grids with a water-flooded thickness below 20% are defined as retention grids with a weighting coefficient of 1. The ratio of the sum of the product of the area of ​​the grid that meets the water-flooded thickness limit condition and the weight of that grid to the area of ​​the utilized region is defined as the residual oil distribution coefficient.

6. The method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields according to claim 5, characterized in that, The expression for the residual oil distribution coefficient is as follows: In the formula: The residual oil distribution coefficient is dimensionless. m is the grid area. 2 ; is the grid weight; m and n are the grid dimensions within the enriched region; i and j are the grid coordinates within the enriched region.

7. The method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields according to claim 1, characterized in that, Step S4, based on the remaining oil distribution coefficient, filters the remaining oil accumulation grid to quantitatively determine the water flooding situation in the horizontal well section, including: The smaller the residual oil distribution coefficient, the greater the risk of water flooding and the larger the scale of water flooding; conversely, the larger the residual oil distribution coefficient, the more concentrated the residual oil. When the residual oil distribution coefficient of the proposed horizontal well placement area is greater than or equal to 0.5, the well placement conditions are met. When the residual oil distribution coefficient of the proposed horizontal well placement area is less than 0.5, the infill horizontal well locations are cancelled. At the same time, the water flooding situation of the horizontal well section can be quantitatively judged by combining the water flooding level of each grid. There is a risk of water flooding when the horizontal well section is located in the secondary water flooding grid and the water flooding grid, and there is no risk of water flooding when it is located in the secondary stagnant grid and the stagnant grid. Based on this, the horizontal well location is optimized, and the horizontal wells are optimized to be deployed on the secondary stagnant grid and the stagnant grid where the water flooding thickness ratio is less than 50%.

8. The method for quantitative prediction of water flooding in infill horizontal well sections in offshore water-drive oilfields according to claim 1, characterized in that, Step S5 involves re-evaluating the remaining oil enrichment level and further evaluating and determining the horizontal well's potential grid, including: Based on the characteristics of oilfield development, four indicators were selected as evaluation indicators for the degree of remaining oil enrichment: distance from water wells, distance from the main flow line, sand body stacking degree, and cumulative injected pore volume. The greater the distance from water wells and the main flow line, the greater the degree of remaining oil enrichment. The sand body stacking degree represents the heterogeneity of sand bodies formed by the deposition of multiple sand bodies in different phases. The enrichment area often has sand body stacking. The greater the stacking degree, the greater the difference in the vertical connectivity in the plane, which easily leads to the phenomenon of injection and production not being connected, forming a remaining oil enrichment area. The cumulative injected pore volume characterizes the degree of mobilization of the area. The smaller the cumulative injected pore volume, the greater the degree of remaining oil enrichment. The values ​​of the four indicators were determined based on the actual reservoir characteristics of the well layout area and the production data of oil and water wells. Evaluation standards were established based on the value of the indicators. The normalized indicators were used to calculate the evaluation vector through the membership function to obtain the evaluation results. The remaining oil cluster grids selected using the remaining oil distribution coefficient were evaluated. The grids with good or relatively good potential evaluation results have low water flooding risk and can be used as recommended areas for horizontal well implementation.

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