Old oil field well pattern reconstruction method based on clustering and double integration

Abstract

The invention provides an old oil field well pattern reconstruction method based on clustering and double integration. The reconstruction method comprises the steps that S1, a target block numerical simulation model is established; s2, carrying out current oil reservoir underground material basic characterization by utilizing the geologic model information; s3, dividing an injection-production unit control range by applying a clustering method; s4, the position of a production well is determined; s5, the number and positions of water injection wells in any injection-production unit are determined; and S6, an injection-production well pattern with the extra-high-water-content later-stage oil reservoir for reserve control and maximization of production is obtained. The aims of optimally configuring the number of oil-water wells in the ultra-high water content later stage of the sandstone reservoir and maximizing the residual geological reserves in the ultra-high water content later stage are achieved.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development, and in particular to a method for reconstructing well networks in old oilfields based on clustering and double integrals. Background Technology

[0002] Most continental sandstone reservoirs have undergone layer reconstruction, three-dimensional and vector development, streamline adjustment, and injection-production coupling technologies, achieving high recovery rates. However, they have also entered the late stage of ultra-high water cut, where high water cut and low efficiency have become the main development bottlenecks. While well pattern density methods have achieved good reserve control, they have failed to pass efficiency evaluation. Therefore, there is an urgent need to research a new well pattern reconstruction method to overcome the current development dilemma of reconstructing well patterns for efficiency in late-stage ultra-high water cut oilfields.

[0003] Chinese invention patent CN117171930A discloses a method for reconstructing well networks in multi-layered reservoirs with ultra-high water cut through vertical layer reorganization. The method mainly involves classifying and reorganizing each layer by evaluating the water energy, production status, and technical policy boundaries of the well network reconstruction of each layer, forming multiple development layers. The key point is to solve the problem of inter-layer interference.

[0004] Chinese invention patent CN111322055A discloses a method for reconstructing the well network in thin-layer oil reservoirs by changing the development method of well rows. It primarily addresses the problems of a large oil-to-water well ratio, low sand body control, reduced well spacing between injection and production wells, low average oil gain per well, and high water cut in thin-layer oil reservoirs. The method achieves well network reconstruction by changing the development methods of oil wells and water rows (polymer flooding and water flooding). The reconstructing scheme includes at least two of the following options: Option 1: Water-driven well rows replace polymer flooding injection wells, and water-driven oil well rows replace polymer flooding production wells; Option 2: Water-driven well rows replace polymer flooding injection wells; Option 3: Water-driven well rows replace polymer flooding production wells. The total recovery rate and total investment cost of each option are determined to select the optimal scheme. This method addresses the well network reorganization resulting from changes in development methods.

[0005] Chinese patent application CN103422849B discloses a method for reconstructing well networks in water-injection development of old oilfields. Based on comprehensive index evaluation, this method optimizes the well network layout by evaluating recovery rates using methods such as the four-point method, five-point method, and inverse nine-point method. This method enables well network deployment based on remaining reserves, but it has not been studied for the precise determination of the location of oil and water wells.

[0006] The existing well network deployment method is basically based on the overall or relatively enriched remaining oil, and uses the optimization of the layer combination, the change of well network method, and the adjustment of the development method to achieve well network reconstruction. However, in the late stage of ultra-high water cut, the overall saturation of remaining oil is low, and there is an urgent need for a new method for well network reconstruction for low-saturation remaining oil. Summary of the Invention

[0007] In view of the above problems, the present invention is proposed to provide a method for reconstructing old oilfield well networks based on clustering and double integrals to overcome or at least partially solve the above problems.

[0008] According to one aspect of the present invention, a method for reconstructing old oilfield well patterns based on clustering and double integrals is provided, the reconstruction method comprising:

[0009] Step S1: Establish a numerical simulation model of the target block;

[0010] Step S2: Utilize geological model information to characterize the current underground material basis of the oil reservoir;

[0011] Step S3: Apply clustering methods to divide the control range of injection and extraction units;

[0012] Step S4: Determine the location of the production well;

[0013] Step S5: Determine the number and location of injection wells within any injection-production unit;

[0014] Step S6: Obtain an injection-production well network for ultra-high water-cut late-stage oil reservoirs to maximize reserve control and utilization.

[0015] Optionally, step S1: establishing a numerical simulation model of the target block specifically includes:

[0016] Organize drilling and logging data and reservoir static data of the target block, establish a geological model, carry out fine numerical simulation of the target reservoir, obtain the current underground flow field parameter distribution, and obtain the underground oil and water distribution, pressure distribution and reservoir physical conditions.

[0017] Establish a numerical simulation model for the target block.

[0018] Optionally, step S2: using geological model information to characterize the current underground material basis of the reservoir specifically includes: using geological model information and employing a weighted average method to characterize the current underground material basis of the reservoir.

[0019] Optionally, the use of geological model information and a weighted average method to characterize the current underground material basis of the reservoir specifically includes:

[0020] Characterization parameters include sand body thickness, effective thickness, porosity, permeability, residual oil saturation, and formation water saturation.

[0021] The 3D model is converted into a planar 2D residual material basis distribution by using vertical grid accumulation;

[0022] Calculate the basic planar distribution characteristics of the remaining material;

[0023] Optionally, step S3: applying clustering methods to divide the control range of injection-production units specifically includes: applying clustering methods to divide the control range of injection-production units based on the principle of balanced control of remaining geological reserves by well groups.

[0024] Optionally, the application of clustering methods, based on the principle of balanced control of remaining geological reserves by well groups, specifically includes the following for dividing the control range of injection-production units:

[0025] The objective function is established based on the principle of maintaining a basic balance of remaining geological reserves controlled by each injection-production unit. The objective function for regional division of the entire area based on clustering is set as follows:

[0026] N i =N / n, i=1, 2,...,n,

[0027] Based on the principle that the reserve control of each injection and production unit is relatively balanced, specifically the sum of the squared differences between injection and production units is minimized, and the design constraint is that the sum of the controlled reserves of each well group is equal to the total remaining controlled reserves of the reservoir, a clustering is carried out.

[0028] Objective function constraint formula:

[0029]

[0030] Clustering numerical constraint formula:

[0031] Median deviation

[0032] Based on the numerical simulation results, the current material distribution field is scanned to determine the relationship between parameter distribution and address. With reference to the remaining oil material reserves and flow direction, a filter matrix U is established. The planar distribution of the remaining oil material reserves is scanned sequentially. The weights set in the filter matrix and the corresponding scanned areas are weighted and summed to determine the areas where the remaining oil material is concentrated in the whole area, the initial position of the injection and production unit, and a set of control area distribution maps of the injection and production unit are obtained.

[0033] Filtering matrix:

[0034]

[0035] The first clustering yields clusters with equal reserves but irregular shapes. Based on the results, a second clustering constraint is carried out using reserves, distance, and permeability fields as constraints to obtain the range of injection-production units with similar reserves and shapes and distances that conform to seepage characteristics.

[0036] Optionally, step S4: determining the location of the production well specifically includes:

[0037] The mass centroid of the remaining oil potential of an irregular injection-production unit is solved by applying the double integral method to obtain the location of the production well.

[0038] Optionally, the method of applying double integral to solve for the mass centroid of the remaining oil potential of the irregular injection-production unit and obtaining the location of the production well specifically includes:

[0039] Considering that the remaining reserve abundance is different in each grid cell within the injection-production unit;

[0040] Let's define the relationship function between the abundance of remaining geological reserves and their location. Let R be a closed region in the plane within the injection-production unit. The abundance of remaining geological reserves at any point is p(x,y). Considering that the distribution of remaining oil abundance is continuous, for any area element dσ of a region, the remaining geological reserve mass element is approximately considered to be concentrated at the point (x,y). Then, the remaining oil mass element within the range of the area element is p(x,y)×dσ.

[0041] The rectangular formulas for calculating the forces exerted by the infinitesimal mass element on the x-axis and y-axis are as follows:

[0042] dM x =yp(x,y)dσ,dM y =xp(x,y)dσ

[0043] Calculate the residual oil mass torque of this infinitesimal element about the two coordinate axes:

[0044]

[0045] The centroid coordinates of the mass of the remaining geological reserves abundance within any injection-production unit are:

[0046]

[0047] (x0, y0) represents the centroid of any injection-production unit on the plane, and the location of the production well; when the thin slice is a homogeneous medium, the centroid coordinates are the geometric center of the plane.

[0048] Based on the actual situation of the oilfield, the oilfield is divided into grids of equal size in planar operation. According to the different oil reserves in each grid, the centroid of the relatively concentrated reserves of each irregular injection-production unit is determined by the integral method, and the location of the production well deployment is determined.

[0049] Optionally, step S5: determining the number and location of injection wells within any injection-production unit specifically includes: deploying the number and location of injection wells within multiple irregular injection-production units based on the principle of maximum balanced displacement.

[0050] Optionally, the number and location of injection wells within multiple irregular injection-production units, based on the principle of maximum balanced displacement, specifically include:

[0051] The entire block was divided into reserve clusters. Based on the determination of the production well locations of irregular injection and production units, the deployment locations of multiple injection and production unit injection well locations were determined according to the principle of maximizing the streamline distribution generated between injection and production wells.

[0052] Optionally, step S6: obtaining an injection-production well pattern for maximizing reserve control and utilization in ultra-high water-cut late-stage reservoirs specifically includes:

[0053] Optimize and adjust water wells in adjacent well groups to determine the best location and number of water wells, forming an injection-production well network for ultra-high water-cut late-stage oil reservoirs with maximum reserve control and utilization.

[0054] Optionally, the optimization and adjustment of water wells in adjacent well groups to determine the optimal location and number of water wells, forming an injection-production well network for ultra-high water-cut late-stage oil reservoirs with maximized reserve control and utilization, specifically includes:

[0055] Given the uneven distribution of remaining underground reserves, and the differences in the location and number of water injection wells corresponding to each production well, it is necessary to comprehensively consider the impact range and flow distribution of each injection-production well network and systematically optimize the location of water injection wells in the reservoir.

[0056] By statistically analyzing the number of grids involved in the streamline... i The swept area ratio Y of the completed injection well i Calculation:

[0057]

[0058] By counting the number of streamlines n in the grid i ,n j Oil production rate f o Based on parameters such as reserve abundance, calculate the remaining recoverable oil reserves controlled in the injection-production unit, and complete the calculation of the remaining recoverable oil reserves control ratio Y2 of the injection well in the injection-production unit:

[0059]

[0060] The basic idea of ​​comprehensive evaluation is a method for evaluating multiple indicators of a complex system as a whole;

[0061] By assigning different weights r to different indicators i The overall evaluation score is determined by weighting the indicators.

[0062] By allocating weights to the evaluation indicators, a comprehensive evaluation is conducted to obtain the final score Y. The final injection well location of the injection and production unit is determined by comprehensive ranking and optimization.

[0063] Y = r i ·Y1+r2·Y2

[0064] The location of injection wells in the well network is determined based on the ranking of the comprehensive evaluation Y.

[0065] The location map of water wells in each well group was calculated, and the water wells in adjacent well areas were optimized to form an injection-production well network for ultra-high water-cut late-stage oil reservoirs with maximum reserve control and utilization.

[0066] This invention provides a method for reconstructing well networks in old oilfields based on clustering and double integrals. The reconstruction method includes: Step S1: establishing a numerical simulation model of the target block; Step S2: using geological model information to characterize the current underground material basis of the reservoir; Step S3: applying clustering methods to divide the control range of injection-production units; Step S4: determining the location of production wells; Step S5: determining the number and location of water injection wells within any injection-production unit; Step S6: obtaining an injection-production well network for ultra-high water-cut late-stage reservoirs to maximize reserve control and utilization. This achieves the goal of optimizing the number of oil and water wells in ultra-high water-cut late-stage sandstone reservoirs and maximizing the utilization of remaining geological reserves in ultra-high water-cut late-stage reservoirs.

[0067] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and in order to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0068] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0069] Figure 1 This is a technical roadmap diagram of the old oilfield well network reconstruction method based on clustering and double integral provided in the embodiments of the present invention;

[0070] Figure 2 This is a map showing the distribution of remaining geological reserves of the target oil reservoir provided in an embodiment of the present invention.

[0071] Figure 3 The distribution range of the primary clustering injection and collection units provided in this embodiment of the invention;

[0072] Figure 4 This invention provides a single-stage clustering injection-production unit control reserve statistics method.

[0073] Figure 5This refers to the distribution range of the secondary clustering injection and collection units provided in the embodiments of the present invention;

[0074] Figure 6 This invention provides a secondary clustering injection-production unit for controlling reserve statistics.

[0075] Figure 7 This invention provides a method for calculating the center of mass within an arbitrary well network range.

[0076] Figure 8 This invention provides a calculation of the residual oil mass center for any injection-production unit in an embodiment of the invention.

[0077] Figure 9 This is a diagram showing the deployment location of production wells in any injection-production unit provided in an embodiment of the present invention.

[0078] Figure 10 This is a schematic diagram of partial adjustment of the injection well location provided in an embodiment of the present invention. Detailed Implementation

[0079] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0080] The terms "comprising" and "having," and any variations thereof, in the specification, embodiments, claims, and drawings of this invention are intended to cover non-exclusive inclusion, such as including a series of steps or units.

[0081] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0082] like Figure 1 As shown, a method for reconstructing old oilfield well networks based on clustering and double integrals is provided. The method includes the following steps:

[0083] Step 1: Establish a numerical simulation model of the target block;

[0084] Step 2: Using geological model information, a weighted average method is used to characterize the current underground material basis of the oil reservoir;

[0085] Step 3: Apply clustering methods to divide the control range of injection-production units based on the principle of balanced control of remaining geological reserves by well groups;

[0086] Step 4: Apply the double integral method to solve for the mass centroid of the remaining oil potential of the irregular injection-production unit, i.e., the location of the production well;

[0087] Step 5: Determine the number and location of injection wells within any injection-production unit based on the principle of maximum balanced displacement.

[0088] Step 6: Conduct optimization and adjustment of water wells in adjacent well groups, determine the optimal location and number of water wells, and form an injection-production well network for ultra-high water-cut late-stage oil reservoirs to maximize reserve control and utilization.

[0089] To achieve the above objectives, the present invention may also employ the following technical solutions:

[0090] In step 1, static data such as drilling and logging data and reservoir data of the target block are collected, a geological model is established, and a detailed numerical simulation of the target reservoir is carried out to obtain the current distribution of underground flow field parameters. The main focus is on understanding the underground oil and water distribution, pressure distribution, and reservoir physical properties.

[0091] In step 2, the geological model information is used to characterize the current underground material basis of the reservoir using a weighted average method. Characterization parameters include sand body thickness, effective thickness, porosity, permeability, remaining oil saturation, and formation water saturation. The 3D model is converted into a planar 2D remaining material basis distribution using a vertical grid accumulation method, and finally the planar distribution characteristics of the remaining material basis are calculated.

[0092] Sand body thickness:

[0093]

[0094] Effective thickness:

[0095]

[0096] Porosity:

[0097]

[0098] Penetration rate:

[0099]

[0100] Residual oil saturation:

[0101]

[0102] Formation water saturation:

[0103]

[0104] Remaining geological reserves:

[0105]

[0106] Among them, S ijk - Oil-bearing area; ρ o- Density of underground crude oil; B O - Crude oil volume coefficient.

[0107] The remaining reserves of each grid were calculated to obtain the distribution map of remaining geological reserves in the reservoir study area. Figure 2 ).

[0108] In step 3, a clustering method is applied to divide the control range of injection-production units based on the principle of balanced control of remaining geological reserves by well groups.

[0109] In step 301, an objective function is established based on the principle of maintaining a basic balance of remaining geological reserves controlled by each injection-production unit. The objective function for regional division of the entire area based on clustering is set as follows:

[0110] N i = N / n, i = 1, 2, ..., n

[0111] Based on the principle that the reserve control of each injection and production unit is relatively balanced, that is, the sum of the squared differences between injection and production units is minimized, and the design constraint is that the sum of the controlled reserves of each well group is equal to the total remaining controlled reserves of the reservoir, a clustering is carried out.

[0112] Objective function constraint formula:

[0113]

[0114] Clustering numerical constraint formula:

[0115] Median deviation

[0116] Based on the numerical simulation results, the current material distribution field is scanned to determine the relationship between parameter distribution and location. Referring to the remaining oil reserves and flow direction, a filter matrix U is established. The planar distribution of remaining oil reserves is scanned sequentially. Using the weights set in the filter matrix and the corresponding scanned regions, a weighted summation calculation is performed to prioritize the determination of areas with relatively concentrated remaining oil reserves, i.e., the initial locations of the injection-production units. Simultaneously, a set of control area distribution maps for the injection-production units is obtained. Figure 3 , Figure 4 ).

[0117] Filtering matrix:

[0118]

[0119] In step 302, the first clustering yields clusters with equal reserves but irregular shapes. Based on this result, a second clustering constraint is carried out using the principle of reserves + distance + permeability field to obtain the range of injection and production units with similar reserves and shapes and distances that conform to seepage characteristics.

[0120] First, considering the injection-production flow characteristics and sedimentation characteristics, the planar distribution law of permeability is calculated, the distance of each injection-production unit from the center of the well group is controlled to be minimized, and constrained in the division of the well group range. The main permeability direction of the injection-production unit is taken as the long axis direction of the injection-production unit range to ensure that the shape of the divided injection-production unit does not appear as a long strip shape.

[0121] Secondly, the grouping and clustering process is progressively simplified. Cluster seeds are determined based on half the controlled reserves of a single well. Then, based on the surrounding units, clustering is controlled according to the principle of dual clustering based on reserves and distance, plus permeability field constraints. After the first clustering result under uniform distribution, some unexpanded grid areas remain undivided. The principle of proximity allocation is used to assign these unexpanded areas to the nearest adjacent injection-production unit, completing the area division task. When the injection-production unit area expands to approximately the target function value of the clustering, it serves as the standard for area division, ensuring that the remaining oil reserves of any single irregular injection-production unit in the entire area basically meet the target function's requirements.

[0122] Quadratic clustering proximity principle constraint:

[0123]

[0124] In the formula, I represents the first clustering direction I, and J represents the first clustering direction J. The planar injection-mapping unit division is completed based on a two-stage clustering method. Figure 5 The remaining material basis of the injection-production unit should be kept within a certain range as much as possible. Figure 6 This provides a good foundation for the well network deployment of injection and production units; at the same time, the flow relationship of the injection and production units conforms to the corresponding seepage relationship.

[0125] In step 4, the double integral method is used to solve for the mass centroid of the remaining oil potential of the irregular injection-production unit, i.e., the location of the production well.

[0126] Considering that the remaining geological reserve abundance is different in each grid cell within the injection-production unit, a function is set to relate the remaining geological reserve abundance to its location, i.e., a closed region R( ) occupies the plane within the injection-production unit. Figure 7 Let p(x, y) be the abundance function of remaining geological reserves at any point. Considering that the distribution of remaining oil abundance is continuous, for any area element dσ, the remaining geological reserve mass element is approximately regarded as concentrated at the point (x, y). Then the remaining oil mass element within the range of this element is p(x, y) × dσ.

[0127] The rectangular formulas for calculating the forces exerted by the infinitesimal mass element on the x-axis and y-axis are as follows:

[0128] dM x =yp(x,y)dσ,dMy =xp(x,y)dσ

[0129] Calculate the residual oil mass torque of this infinitesimal element about the two coordinate axes:

[0130]

[0131] Therefore, the centroid coordinates of the mass of the remaining geological reserves abundance within any injection-production unit are:

[0132]

[0133] (x0, y0) represents the centroid of any injection-production unit on the plane, which is the location of the production well. Figure 8 When the thin sheet is a homogeneous medium, the coordinates of its centroid are the geometric center of the plane.

[0134] Based on the actual conditions of the oilfield, it is known that the area is divided into grids of equal size in planar calculations, resulting in equal grid areas. Given the varying oil reserves in each grid, an integral method is used to determine the centroid of the relatively concentrated reserves for each irregular injection-production unit, thus identifying the location of production wells. Figure 9 ).

[0135] In step 5, the number and location of injection wells in each irregular injection-production unit are determined based on the principle of maximum balanced displacement.

[0136] After the entire block's reserves were clustered and divided, and based on the determined locations of production wells in irregular injection-production units, and considering the role and flow mechanism of injection wells, the deployment locations of injection wells in each injection-production unit were determined with the principle of maximizing the streamline distribution between injection and production wells. Taking a single irregular injection-production unit as an example, the well spacing L and the number of injection wells n in a single injection-production unit were considered. 注 Within the reference range of the injection well location in the injection-production unit, n wells are randomly selected at the yellow boundary of the injection-production unit using a random method. 注 For each injection well location, connect the points sequentially and calculate the area S enclosed by the injection well locations. 总 Simultaneously, the injection and production parameters are initialized, streamlines are formed between the injection and production well locations, the number and density of grids affected by the streamlines are counted, the proportion of the affected area to the total injection and production unit area and the proportion of reserves controlled by the streamlines are calculated, and the proportion close to 1 is the optimal number and location of wells.

[0137] Take a triangle as an example:

[0138] When the coordinates of three points A, B, and C are A(x1, y1), B(x2, y2), and C(x3, y3) respectively, then points A, B, and C can form a triangle. The angle between AC and side AB is ∠A. Therefore, vector AB = (x2 - x1, y2 - y1) and vector AC = (x3 - x1, y3 - y1).

[0139] Let vector AB = a and vector AC = b, then according to the rules of vector operations, we can obtain:

[0140] |a·b|=|a|·|b|·|cosA|

[0141] The area of ​​the triangle is:

[0142]

[0143] S 总 =(x1y2-x1y3+x2y3-x2y1+x3y1-x2y2)

[0144] Therefore, when a polygon formed by multiple points can be divided into multiple triangles, the areas of these triangles can be calculated using the method described above, and then summed to obtain the total area S of the polygon. 总 Summation calculation:

[0145] S 总 =∑S i

[0146] For the grid enclosed by injection wells in an irregular injection-production unit, the number of grids m is counted. i Calculate the area of ​​each individual grid cell, and sum the total area S. 总 :

[0147] S 总 =∑m i ·S 单个网格

[0148] In step 6, the water wells of adjacent well groups are optimized and adjusted to determine the optimal water well location and number of wells in the unit.

[0149] Given the uneven distribution of remaining underground reserves, and the differences in the location and number of injection wells corresponding to each production well, it is necessary to comprehensively consider the impact range and streamline distribution of each injection-production well network to systematically optimize the reservoir's injection well locations. This optimization involves statistically analyzing the number of grids involved in the streamlines. i Complete the calculation of the swept area ratio Y1 of the injection well:

[0150]

[0151] By counting the number of streamlines n in the grid i ,n j Oil production rate fo Based on parameters such as reserve abundance, calculate the remaining recoverable oil reserves controlled in the injection-production unit, and complete the calculation of the remaining recoverable oil reserves control ratio Y2 of the injection well in the injection-production unit:

[0152]

[0153] The basic idea of ​​comprehensive evaluation is a method for evaluating multiple indicators of a complex system as a whole. This is achieved by assigning different weights (r) to different indicators. i The evaluation scores are calculated by weighting the indicators. After allocating weights to the evaluation indicators, a final comprehensive evaluation is performed to obtain the final score Y. The final injection well locations for the injection-production unit are then determined through a comprehensive ranking and optimization.

[0154] Y = r1·Y1 + r2·Y2

[0155] The location of injection wells in the well network is determined based on the ranking of the comprehensive evaluation Y.

[0156] A schematic diagram of partial adjustment of the injection well location, as shown below. Figure 10 As shown.

[0157] The location map of water wells in each well group was obtained through the above calculations, and further optimization of water wells in adjacent well areas was carried out. After the well location optimization of each single irregular injection-production unit was completed, the evaluation index of the entire area was initially calculated. Then, the distance between adjacent injection wells was determined within the entire area, and the distances L1, L2, L3 between different injection well locations in adjacent injection-production units were calculated sequentially. i ,L m The selected distances are sorted from smallest to largest. If the distance between adjacent wells is less than a certain threshold, i.e., the minimum well spacing, a common injection well is used to replace two closely spaced injection wells in adjacent injection and production units. This improves the economic benefits of mining while satisfying the sweep effect.

[0158] Example 1: Ng3-4 formation in a certain oilfield

[0159] Step 1: Establish a numerical simulation model for the target block. The oil-bearing area of ​​this reservoir is 3.6 km². 2 The effective thickness is 14.3m, and the geological reserves of the oil reservoir are 951.6×10⁻⁶. 4 There are a total of 9 sub-layers vertically, including 3 main sub-layers. The reservoir porosity is 32.7–35.6%, and the permeability is 544–1830 × 10⁻⁶. -3 μm 2 The extraction rate was 50.2%.

[0160] Step 2: Using geological model information, a weighted average method is employed to characterize the current underground material basis of the reservoir. Taking the target reservoir as an example, the current underground flow field parameter distribution is first obtained, mainly to understand the underground oil-water distribution, pressure distribution, and reservoir physical properties.

[0161] Due to the complexity of interlayer issues encountered during well network reconstruction, these issues are temporarily disregarded in the reconstruction process; instead, planar issues are considered first. Therefore, it is necessary to first superimpose the vertical upper layers to obtain the planar distribution characteristics before proceeding with well network reconstruction. In the calculation process, thickness is calculated using a vertical superposition method, superimposing the effective thickness and sand body thickness at the same location on the plane according to the principle of vertical consistency. Based on numerical simulation results, the grid numbers in directions I, J, and K of the geological model of the Nanguan 3-4 reservoir in the western area of ​​the Gudao oilfield are 167, 73, and 61, respectively. The 3D model is converted into a planar 2D residual material basis distribution using a vertical grid accumulation method. The calculation methods and results for the main parameters are presented below.

[0162]

[0163] Formation porosity and permeability were processed using a weighted average method, with the weights based on the thickness proportion of each sub-layer in the vertical direction, and the average was then combined.

[0164]

[0165] Porosity

[0166] Step 3: Apply clustering methods to delineate the control range of injection-production units based on the principle of balanced control of remaining geological reserves by well groups. Primary clustering is constrained by equal reserve division, while secondary clustering is constrained by regional expansion, forming a "reserve + distance" double clustering method to delineate the control range of injection-production units.

[0167] Step 4: Apply the double integral method to solve for the remaining oil potential mass centroid coordinates (x0, y0) of the irregular injection-production unit, i.e. the location of the production well, and determine the 30 oil wells in this block.

[0168] Step 5: Based on the principle of maximum balanced displacement, determine the number and location of injection wells in any injection-production unit, and deploy 90 water wells.

[0169] Step 6: Conduct optimization and adjustment of water wells in adjacent well groups, determine the optimal location and number of water wells, and form an injection-production well network for ultra-high water-cut late-stage oil reservoirs to maximize reserve control and utilization.

[0170] The final well network consists of 30 oil wells and 50 water wells. The well network density is inversely correlated with the distribution of remaining reserves; that is, areas with high remaining reserve abundance have high well network density, reaching a maximum of 25.4 wells / km².2 Conversely, areas with low remaining reserves have low well density, with the lowest being 9.1 wells / km². 2 The well spacing is large.

[0171] Example 2: The Sha-2-8 formation in a certain oilfield

[0172] Step 1: Establish a numerical simulation model for the target block. The oil-bearing area of ​​this reservoir is 8.2 km². 2 The effective thickness is 18.43m, and the geological reserves of the oil reservoir are 2296×10⁻⁶. 4 There are 6 sub-layers vertically, including 3 main sub-layers. The average porosity of the reservoir is 28%, and the average permeability is 2400 × 10⁻⁶. -3 μm 2 The recovery rate was 46.5%.

[0173] Step 2: Using geological model information, a weighted average method is employed to characterize the current underground material basis of the reservoir. Characterization parameters include sand body thickness, effective thickness, porosity, permeability, remaining oil saturation, and formation water saturation. Formation porosity and permeability are processed using a weighted average method, with the weights based on the thickness proportion of each sublayer in the vertical direction. The average is then combined to calculate the remaining reserves for each grid, resulting in a distribution map of the remaining geological reserves in the reservoir study area.

[0174] Step 3: Apply clustering methods to delineate the control range of injection-production units based on the principle of balanced control of remaining geological reserves by well groups. Primary clustering is constrained by equal reserve division, while secondary clustering is constrained by regional expansion, forming a "reserve + distance" double clustering method to delineate the control range of injection-production units.

[0175] Step 4: Apply the double integral method to solve for the remaining oil potential mass centroid coordinates (x0, y0) of the irregular injection-production unit, i.e. the location of the production well, and determine the 36 oil wells in this block.

[0176] Step 5: Based on the principle of maximizing balanced displacement, determine the number and location of injection wells within any injection-production unit. A total of 88 wells were deployed.

[0177] Step 6 involves optimizing and adjusting water wells in adjacent well groups to determine the optimal location and number of water wells, forming an injection-production well network for ultra-high water-cut late-stage oil reservoirs that maximizes reserve control and utilization. After optimization, 36 oil wells and 68 water wells are deployed.

[0178] The final well network exhibits an inverse correlation between well density and remaining reserve distribution; that is, areas with high remaining reserve abundance have high well density, reaching a maximum of 19.8 wells / km². 2 Conversely, areas with low remaining reserves have low well density, with the lowest being 8.6 wells / km². 2 The well spacing is large.

[0179] Beneficial effects: Based on clustering and double integral methods, the optimal control area of ​​injection and production units and the optimal control positions of oil and water wells are obtained, so as to achieve the goal of optimizing the number of oil and water wells in the late stage of ultra-high water cut in sandstone reservoirs and maximizing the utilization of the remaining geological reserves in the late stage of ultra-high water cut.

[0180] The above specific embodiments further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for reconstructing well patterns in old oilfields based on clustering and double integrals, characterized in that, The reconstruction method includes: Step S1: Establish a numerical simulation model of the target block; Step S2: Utilize geological model information to characterize the current underground material basis of the oil reservoir; Step S3: Apply clustering methods to divide the control range of injection and extraction units; Step S4: Determine the location of the production well; Step S5: Determine the number and location of injection wells within any injection-production unit; Step S6: Obtain an injection-production well network for ultra-high water-cut late-stage oil reservoirs to maximize reserve control and utilization.

2. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 1, characterized in that, Step S1: Establishing a numerical simulation model of the target block specifically includes: Organize drilling and logging data and reservoir static data of the target block, establish a geological model, carry out fine numerical simulation of the target reservoir, obtain the current underground flow field parameter distribution, and obtain the underground oil and water distribution, pressure distribution and reservoir physical conditions. Establish a numerical simulation model for the target block.

3. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 1, characterized in that, Step S2: Using geological model information to characterize the current underground material basis of the oil reservoir specifically includes: using geological model information and employing a weighted average method to characterize the current underground material basis of the oil reservoir.

4. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 3, characterized in that, The specific methods for characterizing the subsurface material basis of oil reservoirs using geological model information and a weighted average approach include: Characterization parameters include sand body thickness, effective thickness, porosity, permeability, residual oil saturation, and formation water saturation. The 3D model is converted into a planar 2D residual material basis distribution by using vertical grid accumulation; Calculate the basic planar distribution characteristics of the remaining material.

5. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 1, characterized in that, Step S3: Applying clustering methods to divide the control range of injection-production units specifically includes: applying clustering methods to divide the control range of injection-production units based on the principle of balanced control of remaining geological reserves by well groups.

6. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 5, characterized in that, The application of clustering methods, based on the principle of balanced control of remaining geological reserves by well groups, specifically includes the following: The objective function is established based on the principle of maintaining a basic balance of remaining geological reserves controlled by each injection-production unit. The objective function for regional division of the entire area based on clustering is set as follows: N i =N / n,i=1,2,…,n, Where N represents the remaining geological reserves in the region, and n represents the number of injection-production units; The reserves of each injection and production unit are controlled in a relatively balanced manner, specifically the sum of the squared differences between the injection and production units is minimized, while the design constraint is the control reserves of each well group. The sum equals the total remaining controlled reserves of the reservoir, and a clustering is performed; Objective function constraint formula: Where, N ori Note the area of ​​the i-th injection-production well group, thnet ij The effective thickness of the ij-th grid, ρ o Density of underground crude oil, B o Crude oil volume coefficient; Clustering numerical constraint formula: Median deviation Based on the numerical simulation results, the current material distribution field is scanned to determine the relationship between parameter distribution and address. With reference to the remaining oil material reserves and flow direction, a filter matrix U is established. The planar distribution of the remaining oil material reserves is scanned sequentially. The weights set in the filter matrix and the corresponding scanned areas are weighted and summed to determine the areas where the remaining oil material is more concentrated in the whole area, i.e. the initial positions of the injection and production units. At the same time, a set of control area distribution maps of the injection and production units is obtained. Filtering matrix: The first clustering yields clusters with equal reserves but irregular shapes. Based on the results, a second clustering constraint is carried out using reserves, distance, and permeability fields as constraints to obtain the range of injection-production units with similar reserves and shapes and distances that conform to seepage characteristics.

7. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 1, characterized in that, Step S4: Determining the location of the production well specifically includes: The mass centroid of the remaining oil potential of an irregular injection-production unit is solved by applying the double integral method to obtain the location of the production well.

8. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 7, characterized in that, The method of applying double integral to solve for the mass centroid of the remaining oil potential of irregular injection-production units and to obtain the location of production wells specifically includes: Considering that the remaining reserve abundance is different in each grid cell within the injection-production unit; Let's define the relationship function between the abundance of remaining geological reserves and their location. Let R be a closed region in the plane within the injection-production unit. The abundance of remaining geological reserves at any point is p(x,y). Considering that the distribution of remaining oil abundance is continuous, for any area element dσ of a region, the remaining geological reserve mass element is approximately considered to be concentrated at the point (x,y). Then, the remaining oil mass element within the range of the area element is p(x,y)×dσ. The rectangular formulas for calculating the forces exerted by the infinitesimal mass element on the x-axis and y-axis are as follows: dM x =yp(x,y)dσ,dM y =xp(x,y)dσ Calculate the residual oil mass torque of this infinitesimal element about the two coordinate axes: The centroid coordinates of the mass of the remaining geological reserves abundance within any injection-production unit are: (x0, y0) represents the centroid of any injection-production unit on the plane, and the location of the production well; when the thin slice is a homogeneous medium, the centroid coordinates are the geometric center of the plane. Based on the actual situation of the oilfield, the oilfield is divided into grids of equal size in planar operation. According to the different oil reserves in each grid, the centroid of the relatively concentrated reserves of each irregular injection-production unit is determined by the integral method, and the location of the production well deployment is determined.

9. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 1, characterized in that, Step S5: Determining the number and location of injection wells within any injection-production unit specifically includes: deploying the number and location of injection wells within multiple irregular injection-production units based on the principle of maximum balanced displacement.

10. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 9, characterized in that, The specific details regarding the number and location of injection wells within multiple irregular injection-production units, based on the principle of maximum balanced displacement, include: The entire block was divided into reserve clusters. Based on the determination of the production well locations of irregular injection and production units, the deployment locations of multiple injection and production unit injection well locations were determined according to the principle of maximizing the streamline distribution generated between injection and production wells.

11. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 1, characterized in that, Step S6: Obtaining an injection-production well network for maximizing reserve control and utilization of ultra-high water-cut late-stage oil reservoirs specifically includes: Optimize and adjust water wells in adjacent well groups to determine the best location and number of water wells, forming an injection-production well network for ultra-high water-cut late-stage oil reservoirs with maximum reserve control and utilization.

12. The method for reconstructing old oilfield well patterns based on clustering and double integrals according to claim 11, characterized in that, The aforementioned optimization and adjustment of adjacent well groups to determine the optimal location and number of water wells, forming an injection-production well network for ultra-high water-cut late-stage oil reservoirs with maximized reserve control and utilization, specifically includes: Given the uneven distribution of remaining underground reserves, and the differences in the location and number of water injection wells corresponding to each production well, it is necessary to comprehensively consider the impact range and flow distribution of each injection-production well network and systematically optimize the location of water injection wells in the reservoir. By statistically analyzing the number of grids involved in the streamlines l i The swept area ratio Y of the completed injection well l Calculation: By counting the number of streamlines n in the grid i n j Based on parameters such as oil production rate f0 and reserve abundance, calculate the remaining recoverable oil reserves controlled in the injection-production unit, and complete the calculation of the remaining recoverable oil reserve control ratio Y2 of the injection well in the injection-production unit: The basic idea of ​​comprehensive evaluation is a method for evaluating multiple indicators of a complex system as a whole; By assigning different weights r to different indicators i The overall evaluation score is determined by weighting the indicators. By allocating weights to the evaluation indicators, a comprehensive evaluation is conducted to obtain the final score Y. The final injection well location of the injection and production unit is determined by comprehensive ranking and optimization. Y = r1·Y1 + r2·Y2 The location of injection wells in the well network is determined based on the ranking of the comprehensive evaluation Y. The location map of water wells in each well group was calculated, and the water wells in adjacent well areas were optimized to form an injection-production well network for ultra-high water-cut late-stage oil reservoirs with maximum reserve control and utilization.

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