Grid Design Method for Reservoir Numerical Simulation

Abstract

The present invention provides a reservoir numerical simulation grid design method, which comprises: step 1, optimizing the model area and formulating the area selection criteria; step 2, establishing reservoir models with different grid steps and conducting numerical simulation research; step 3, optimizing the dynamic and static comprehensive evaluation parameters and establishing a model grid step evaluation parameter library; step 4, scoring and optimizing the grid step based on the reservoir type, and establishing a scoring standard suitable for the reservoir type in a specific research area. The reservoir numerical simulation grid design method of the present invention draws on the concept of typical volume units, and aims at the problem that the large step grid cannot accurately describe the small geological body and its spatial variation, and the small step grid calculation time greatly increases and convergence problems. By establishing a dynamic and static comprehensive evaluation parameter system, the different grid step models are comprehensively scored, and the quantitative optimization of the grid step is realized.

Description

Technical Field

[0001] The invention relates to the technical field of oil reservoir engineering oil reservoir numerical simulation, in particular to an oil reservoir numerical simulation grid design method. Background Art

[0002] Reservoir numerical simulation methods and technologies are used throughout the discovery and development of oil fields. They are key technologies for formulating reservoir development plans, optimizing development adjustment measures, and conducting research on the distribution of remaining oil. The design of the step size of the reservoir numerical simulation grid is an important part of this technology. Large step size grids cannot accurately describe small geological bodies and their spatial changes, and will also cause large errors in the simulation of injection and production dynamic responses; small step size grids can accurately describe irregular reservoir boundaries, reservoir discontinuities, fault trajectories, microstructures, pressure and saturation changes between injection and production wells and nearby, and reduce numerical dispersion. However, the calculation time increases significantly. If the step size is too small, it will be difficult to solve the flow equation, causing computational convergence and error problems. Therefore, how to select and optimize the step size of the reservoir numerical simulation grid is the key to improving the accuracy and efficiency of reservoir numerical simulation. To this end, we have invented a new reservoir numerical simulation grid design method to solve the above technical problems. Summary of the invention

[0003] The purpose of the present invention is to provide a reservoir numerical simulation grid design method which can achieve accurate description of the dynamic and static state of the reservoir and improve the calculation efficiency.

[0004] The object of the present invention can be achieved through the following technical measures: a reservoir numerical simulation grid design method, which comprises: step 1, optimizing the model area and formulating the area selection criteria; step 2, establishing reservoir models with different grid steps and conducting numerical simulation research; step 3, optimizing the dynamic and static comprehensive evaluation parameters and establishing a model grid step evaluation parameter library; step 4, based on the grid step scoring and optimization of the reservoir type, establishing a scoring standard suitable for the reservoir type in a specific study area.

[0005] The purpose of the present invention can also be achieved by the following technical measures:

[0006] In step 1, the selection criteria for the optimized model area are: for the same developed reservoir, the dense well pattern area at the high structural position is selected; for the reservoir with a short development time or in the reservoir development evaluation stage, the reservoir with a higher degree of structural and sedimentary adjacent development is selected as the optimized design model area by analogy.

[0007] In step 2, the optimized model area data is used to establish reservoir geological models with different grid steps, and the reservoir numerical simulation technology is used to perform numerical simulation on the models with different grid steps.

[0008] In step 3, the influence of grid step size on the reservoir geological body, heterogeneity, fitting rate and other dynamic and static data matching rate and calculation efficiency is fully considered, and a reservoir model grid step size evaluation parameter library is established.

[0009] In step 3, according to the characteristics of unconformity reservoirs and data, three types of evaluation parameters are selected: geological body geometric parameters, fitting parameters and other parameters.

[0010] Step 4 includes:

[0011] (a) According to the reservoir type and research purpose, select the evaluation parameter combination from the evaluation parameter library and formulate the type weight T i and parameter weight P j ;

[0012]

[0013]

[0014] Where n is the number of selected parameter types, which is a natural number less than or equal to 3, and m is the number of selected parameters in each type;

[0015] (b) Carry out parameter scoring, establish a rating scale, and conduct rating assessment on various parameters;

[0016] (c) Based on the scoring and weighting of each parameter, the comprehensive scores of the models at different grid scales are calculated:

[0017]

[0018] Among them, S is the comprehensive score of reservoir model grid, S ij is the score of the jth parameter of the i-th category;

[0019] (d) The grid scale is optimized based on the comprehensive scores of each model, and the one with the highest score is the optimal grid scale.

[0020] The reservoir numerical simulation grid design method of the present invention draws on the concept of typical volume units, and aims to solve the problems that large-step-size grids cannot accurately describe small geological bodies and their spatial changes, and that small-step-size grids have a significant increase in calculation time and convergence. By establishing a dynamic and static comprehensive evaluation parameter system, different grid step-size models are comprehensively scored to achieve quantitative optimization of grid step sizes. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A flowchart of a specific embodiment of the reservoir numerical simulation grid design method of the present invention;

[0022] Figure 2 A comparison diagram of geological body models of different grid scales in a specific embodiment of the present invention;

[0023] Figure 3 A comparison diagram of reserve fitting rates of models with different grid scales in a specific embodiment of the present invention;

[0024] Figure 4 A comparison diagram of moisture content fitting curves of different grid scale models in a specific embodiment of the present invention;

[0025] Figure 5 A comparison diagram of the remaining oil saturation fields of different grid scale models in a specific embodiment of the present invention;

[0026] Figure 6 This is a comparison chart of the numerical simulation calculation time of different grid scale models in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings.

[0028] like Figure 1 As shown, Figure 1 The present invention is a flow chart of the reservoir numerical simulation grid design method.

[0029] Step 101, optimizing the model area selection, through the formulation of area selection criteria, select the typical area that can reflect the reservoir type in the study area to carry out grid step research; for the same developed reservoir, select the dense well network area in the high structural part; for the reservoir with a short development time or in the reservoir development evaluation stage, select the adjacent high-development reservoir with the same structure and sedimentation as the optimized design model area by analogy.

[0030] Step 102, reservoir modeling and numerical simulation. Based on the optimization of model area selection, reservoir geological models with different grid steps are designed, and models with different grid steps are simulated using reservoir numerical simulation technology without any grid coarsening.

[0031] Step 103, optimization of dynamic and static comprehensive evaluation parameters. Based on full consideration of the influence of grid step size on reservoir geological bodies, heterogeneity, fitting rate, dynamic and static data matching rate, and calculation efficiency, a reservoir model grid step size evaluation parameter library as shown in Table 1 is established.

[0032] Table 1. Parameter library for reservoir model grid step size evaluation

[0033]

[0034] Step 104, scoring and optimization of grid step length based on reservoir type. Based on the scoring and optimization of grid step length of reservoir type, a scoring standard applicable to the reservoir type in a specific study area is established to select the optimal grid step length. First, based on the reservoir type and research purpose, a combination of evaluation parameters is selected from the evaluation parameter library, and type weights and parameter weights are formulated; secondly, a grade scoring table is established to grade various parameters. On this basis, the comprehensive scores of models with different grid scales are calculated; finally, the grid scale is optimized based on the comprehensive scores of each model, and the one with the highest score is the optimal grid scale. Specifically including:

[0035] (a) According to the reservoir type and research purpose, select the evaluation parameter combination from the evaluation parameter library and formulate the type weight T i and parameter weight P j .

[0036]

[0037] Where n is the number of selected parameter types, which is a natural number less than or equal to 3, and m is the number of selected parameters in each type.

[0038] (b) Carry out parameter scoring, establish a rating table as shown in Table 2, and carry out rating assessment on various parameters;

[0039] Table 2 Rating table

[0040]

[0041] (c) Based on the scoring and weighting of each parameter, the comprehensive scores of the models at different grid scales are calculated:

[0042]

[0043] Among them, S is the comprehensive score of reservoir model grid, S ij is the score of the jth parameter of the i-th category.

[0044] (d) The grid scale is optimized based on the comprehensive scores of each model, and the one with the highest score is the optimal grid scale.

[0045] The following is a specific embodiment of the present invention:

[0046] This embodiment is an oil reservoir in an angle unconformity formation with a long development time. Therefore, the well area at the high position of the oil reservoir is selected as the study area to carry out grid step design research.

[0047] ① Reservoir geological modeling and numerical simulation

[0048] On the basis of optimizing the selection of model area, unconformity reservoir modeling technology is applied to establish three-dimensional geological models of different grid scales, and numerical simulation research is carried out in combination with production dynamic data. In this embodiment, five grid step models of 5m×5m, 10m×10m, 15m×15m, 20m×20m and 30m×30m are established.

[0049] ②Optimal selection of dynamic and static comprehensive evaluation parameters

[0050] According to the characteristics and data of unconformity reservoirs, this embodiment optimizes five evaluation parameters: erosion line, reserve fitting rate, water cut fitting rate, residual oil saturation, rationality and timeliness.

[0051] ③ Determination of parameter weights

[0052] Based on the reservoir characteristics of this embodiment, weights of various types and single parameters were formulated (Table 3).

[0053] Table 3 Weight table of each type and single parameter

[0054]

[0055] ④ Evaluation parameter rating and grid step optimization

[0056] The scores of different grid models are calculated by analyzing and comparing the simulation results of models with different grid step sizes with the actual static and dynamic data of the reservoir model area, and combining them with the grade score table. Figure 2 Comparison diagram of geological models at different grid scales. Figure 2 Middle (a) picture~ Figure 2 The grid scales in the middle (e) figure are 5m×5m, 10m×10m, 15m×15m, 20m×20m, and 30m×30m. Taking the 5m×5m model as an example, Figure 2 As shown in Figure (a), the model achieves a fine depiction of the erosion line and is rated as high-level. Figure 3 , Figure 4 It can be seen that the reserve fitting rate of the model is greater than 90%, and the water cut fitting rate level is 70%-80%; Figure 5 Comparison diagram of remaining oil saturation field of models with different grid scales. Figure 5 Middle (a) picture~ Figure 5 The grid scales in the middle (e) figure are 5m×5m, 10m×10m, 15m×15m, 20m×20m, and 30m×30m respectively; Figure 5 As can be seen from Figure (a), the water drive front edge in the saturation field diagram of this model is more detailed and reasonable. Figure 6 It can be seen that the timeliness of the model is poor and the evaluation level is low.

[0057] By analyzing and evaluating all grid step models and combining the parameter weight table, the scores of each grid model are calculated. In this embodiment, the 15m×15m model gets the highest score of 88 points, which is the optimal grid step for the reservoir.

[0058] The reservoir numerical simulation grid design method of the present invention draws on the concept of typical volume units, based on the data of dense well network and highly developed reservoirs, uses different grid step models to perform dynamic and static fitting effect analysis and comparison and grade assessment of the reservoir, and quantitatively selects the optimal grid step of reservoirs with the same sedimentary type and scale, which can not only achieve accurate description of the dynamic and static state of the reservoir, but also improve computational efficiency and shorten the research cycle.

Claims

1. A grid design method for reservoir numerical simulation, characterized in that: The reservoir numerical simulation grid design method includes: Step 1, select the optimal model area and formulate the selection criteria; Step 2: Establish reservoir models with different grid steps and conduct numerical simulation studies; Step 3: Optimize dynamic and static comprehensive evaluation parameters and establish a model grid step evaluation parameter library; Step 4: Establish a scoring standard suitable for the study area, calculate the comprehensive scores of models with different grid scales based on the numerical model results, and determine the optimal grid scale for the reservoir model; Step 4 includes: (a) According to the reservoir type and research purpose, select the evaluation parameter combination from the evaluation parameter library and formulate the type weight T i and parameter weight P j ; Where n is the number of selected parameter types, which is a natural number less than or equal to 3, and m is the number of selected parameters in each type; (b) Carry out parameter scoring, establish a rating scale, and conduct rating assessment on various parameters; (c) Based on the scoring and weighting of each parameter, the comprehensive scores of the models at different grid scales are calculated: Among them, S is the comprehensive score of reservoir model grid, S ij is the score of the jth parameter of the i-th category; (d) The grid scale is optimized based on the comprehensive scores of each model, and the one with the highest score is the optimal grid scale.

2. The reservoir numerical simulation grid design method according to claim 1, characterized in that: In step 1, the selection criteria for the optimized model area are: for the same developed reservoir, the dense well pattern area at the high structural position is selected; for the reservoir with a short development time or in the reservoir development evaluation stage, the reservoir with a higher degree of structural and sedimentary adjacent development is selected as the optimized design model area by analogy.

3. The reservoir numerical simulation grid design method according to claim 1, characterized in that: In step 2, the optimized model area data is used to establish reservoir geological models with different grid steps, and the reservoir numerical simulation technology is used to perform numerical simulation on the models with different grid steps.

4. The reservoir numerical simulation grid design method according to claim 1, characterized in that: In step 3, the influence of grid step size on the reservoir geological body, heterogeneity, fitting rate and other dynamic and static data matching rate and calculation efficiency is fully considered, and a reservoir model grid step size evaluation parameter library is established.

5. The reservoir numerical simulation grid design method according to claim 1, characterized in that: In step 3, according to the characteristics of unconformity reservoirs and data, three types of evaluation parameters are selected: geological body geometric parameters, fitting parameters and other parameters.

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