Method for optimizing reservoir water injection energy storage before refracturing

Abstract

The invention discloses a reservoir water injection energy storage optimization method before refracturing, which comprises the following steps: S1, establishing a three-dimensional layered heterogeneous finite element model according to reservoir characteristics, and constructing a primary fracturing crack; s2, rock physics and fluid parameters are given to each layer section in the finite element model, and water injection simulation conditions are set; and S3, carrying out simulation calculation on the finite element model, determining the energy complementing efficiency under each displacement, and determining an optimized water injection strategy through a decision index. According to the method, the heterogeneous finite element model is established, accurate changing parameters are given to each grid through a dynamic parameter transmission method, the stratum fracture pressure serves as the safety constraint condition, water injection optimization decision making is conducted through the energy complementing efficiency, and the optimal economic benefit under the water injection energy complementing condition can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil and gas exploitation, in particular to a reservoir water injection energy storage optimization method before repeated fracturing. BACKGROUND

[0002] For oil and gas wells that have undergone fracturing operations, as production progresses, the formation energy (i.e. pore pressure) will be significantly depleted. When the formation pressure is depleted to 50% or less of the original pressure, direct repeated fracturing faces many challenges: on the one hand, the huge bottomhole and formation pressure difference leads to serious fracturing fluid filtration, making it difficult to create fractures and low support agent transport efficiency, and more likely to be damaged by filtrate and pollute the reservoir; on the other hand, the stress field of the reservoir rock changes due to pressure depletion, and the conventional repeated fractures are easily extended along the original fracture path, making it difficult to form a new effective fracture network. Therefore, it is crucial to supplement the formation energy (i.e. "energy storage") before repeated fracturing, which not only supplements the formation energy and optimizes the geostress field, but also achieves the purpose of reducing the flow resistance of crude oil and activating the remaining oil by pre-injection of surface active agents.

[0003] The existing energy storage methods are mostly empirical water injection, lacking precise theoretical guidance. For multi-layer reservoirs, due to the significant differences in physical parameters such as permeability and porosity of each layer, the optimization of injection parameters (displacement, liquid volume) may lead to uneven energy supplement, some layers may not be effectively energized, and some layers may be fractured prematurely due to high injection pressure, causing energy dissipation, and the overall effect of formation water injection energy storage cannot be judged. Therefore, there is an urgent need for an optimization method for water injection energy storage for heterogeneous layers to safely and efficiently restore the formation energy and lay the foundation for the successful implementation of subsequent repeated fracturing. SUMMARY

[0004] The purpose of the present application is to overcome the shortcomings of the prior art and provide a scientific, accurate and safe reservoir water injection energy storage method before repeated fracturing. The method establishes a three-dimensional finite element model to simulate the reservoir pressure recovery under different injection displacement, determines the optimal injection parameters and expected energy storage effect of the reservoir based on the safety constraint of formation fracture pressure, and provides direct and reliable basis for field operations.

[0005] The present application is realized by the following technical scheme, in the first aspect, the present application provides a reservoir water injection energy storage optimization method before repeated fracturing, comprising the following steps:

[0006] S1, a three-dimensional layered heterogeneous finite element model is established according to the reservoir characteristics, and a primary fracturing fracture is constructed;

[0007] S2, rock physics and fluid parameters are assigned to each layer in the finite element model, and injection simulation conditions are set;

[0008] S3, simulate the finite element model to determine the energy compensation efficiency under each displacement , determine the optimal injection strategy through the decision index , wherein

[0009]

[0010]

[0011] wherein V e is the effective energy compensation volume; V is the total volume of the reservoir; is the decision index; Q t is the cumulative injection volume.

[0012] Further, step S1 includes:

[0013] S1.1, determine the length and width of the finite element model according to the well spacing and row spacing of the target well area, and determine the height of the finite element model according to the corresponding formation thickness of the vertical reservoir thickness;

[0014] S1.2, divide the finite element model into different small layers according to the thickness of each vertical reservoir;

[0015] S1.3, construct a rectangle in the geometric center of the finite element model, which penetrates all layers and is perpendicular to the formation plane, and use the rectangle to represent the primary fracturing fracture.

[0016] Further, step S1.3 further includes discretizing the geometric model using the finite element method:

[0017] S1.3.1, divide the overall model using free tetrahedral mesh;

[0018] S1.3.2, perform mesh densification processing near the two-dimensional ellipse representing the intersection of the primary fracturing fracture and the formation plane.

[0019] Further, step S2 further includes:

[0020] S21, use data simulation software to obtain formation dynamic change parameters, and use image data conversion method to assign dynamic change parameters to each grid element of the finite element model;

[0021] S22, define the position of the two-dimensional ellipse surface as the fluid injection inlet, set the initial injection displacement, and gradually increase the injection displacement value;

[0022] S23, when the bottom hole flowing pressure reaches the reservoir fracture pressure, terminate the calculation.

[0023] Further, the formation dynamic change parameters include pressure, porosity, permeability, saturation, and ground stress.

[0024] Further, in step S3, the method for obtaining the effective energy supplement volume is:

[0025] The pore pressure threshold is set as 90% of the original formation pressure, and the total volume of the region in the finite element model in which the pore pressure reaches or exceeds the threshold is calculated by the volume integral algorithm, that is, the effective energy supplement volume V e .

[0026] Further, in step S3, the decision index The injection displacement corresponding to the maximum value is the optimal injection displacement.

[0027] In a second aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the water injection energy storage optimization method according to any one of the embodiments of the present application.

[0028] In a third aspect, the present application provides a storage medium storing computer executable instructions, wherein the computer executable instructions are executed by a computer processor to implement the water injection energy storage optimization method according to any one of the embodiments of the present application.

[0029] In a fourth aspect, the present application provides a computer program product, comprising a computer program executable by a processor to implement the water injection energy storage optimization method according to any one of the embodiments of the present application.

[0030] The water injection energy storage optimization method, electronic device, storage medium and program product provided by the present application have the following beneficial technical effects compared with the prior art:

[0031] (1) Differentiation and precision description of the reservoir, the different heterogeneous reservoir distribution is described in the finite element model, each grid is given a precise change parameter through the dynamic parameter transmission method, and the water injection effect of multi-layer combined injection is described as a whole through the effective energy supplement volume, solving the problems of uneven energy supplement and difficulty in judging whether the water injection effect is achieved.

[0032] (2) Taking the formation fracture pressure as a safety constraint condition, the formation damage and energy loss caused by blind water injection are avoided.

[0033] (3) The water injection optimization decision is made by using the energy supplement efficiency, which can achieve the best economic benefit under the condition of water injection energy supplement. BRIEF DESCRIPTION OF DRAWINGS

[0034] In the drawings, like reference numerals refer to like elements throughout the various drawings. The drawings are not necessarily to scale, the emphasis instead being placed upon illustrating certain principles of the application. It should be understood that the drawings are merely depictions of some embodiments of the application and that no limitations of the scope of the application are intended to be implied therefrom.

[0035] Figure 1 A technical route flowchart is provided for the method of the application;

[0036] Figure 2 A three-dimensional layered finite element model schematic diagram is provided for the embodiments of the application;

[0037] Figure 3 A three-dimensional layered finite element model meshing diagram is provided for the embodiments of the application;

[0038] Figure 4 A reservoir pore pressure distribution cloud chart after simulation calculation is provided for the embodiments of the application. DETAILED DESCRIPTION

[0039] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the application.

[0040] In the following, only some exemplary embodiments are described simply. As can be appreciated by those skilled in the art, the described embodiments can be modified in various different ways without departing from the spirit or scope of the application. Therefore, the drawings and the description are considered to be exemplary in nature rather than limiting.

[0041] In order to optimize water injection and energy storage in a non-homogeneous layer, as shown in the technical route flowchart in the application, the application provides a method for optimizing reservoir water injection and energy storage before repeated fracturing, which comprises the following steps: Figure 1

[0042] S1, a three-dimensional layered non-homogeneous finite element model is established according to the reservoir characteristics, and a primary fracturing fracture is constructed;

[0043] S2, rock physics and fluid parameters are given to each layer in the finite element model, and water injection simulation conditions are set;

[0044] S3, the finite element model is simulated to determine the energy compensation efficiency under each displacement , and the optimal water injection strategy is determined through the decision index , wherein ​

[0045]

[0046]

[0047] Among them, V e V represents the effective energy replenishment volume; V is the total reservoir volume. For decision-making indicators; Q t This represents the cumulative injection volume.

[0048] In step S1, a corresponding three-dimensional layered geomechanics-seepage coupled finite element model needs to be established based on the actual reservoir characteristics of the formation. This model simultaneously considers the interaction between formation deformation under mechanical action and fluid seepage in the porous medium. The two are coupled through the relationship between pore pressure and effective stress. Based on the differences in parameters such as formation thickness, porosity, and permeability, the formation is divided into multiple three-dimensional layered subdomains to ensure that the model can accurately characterize the heterogeneity of different strata.

[0049] Specifically, based on the geological structural characteristics of the target well area, a three-dimensional geometric model is established. The three-dimensional geometric model is defined horizontally as X = L (length) and Y = W (width), corresponding to the well spacing and row spacing of the target well area, respectively; vertically, it consists of n target reservoirs with thicknesses Z... n =H n (n=1, 2, 3, ...), corresponding to the actual formation thickness, with the water injection inlet located at the geometric center of the model. The specific steps are as follows:

[0050] like Figure 2 As shown, create a structure with length L, width W, and height respectively. A cube;

[0051] At a distance from the bottom surface Different faces are created at heights of (n=1, 2, 3, ...) to divide the cube into different layers;

[0052] A rectangle is established at the geometric center of the model, running through all layers and perpendicular to the formation on the xz plane, to represent the primary fracturing fracture. The size of the primary fracturing fracture can be derived from the fracture interpretation of the oilfield.

[0053] After establishing the finite element model, the geometric model is discretized using the finite element method.

[0054] In embodiments of the present invention, such as Figure 3 As shown, in order to improve computational efficiency and accuracy, a non-uniform meshing strategy is adopted. The overall model is divided into free tetrahedral meshes, and the mesh is refined near the two-dimensional ellipse representing the intersection of the initial fracturing fracture and the formation plane in order to accurately capture the intense pressure gradient and fluid flow near the fracture.

[0055] In step S2, in order to accurately obtain the dynamic changes of formation parameters, the calculation results of other numerical software can be imported into the finite element model established in this application, and each grid cell can be assigned accurate reservoir physical property parameters (e.g., initial pore pressure p). n Penetration rate K n Porosity (n=1, 2, 3, ...).

[0056] Taking permeability as an example, a reservoir permeability distribution contour map of the target layer can be exported from the geological modeling software Petrel. Since the contour map is output in RGB color image format, the color gradient represents the spatial variation of permeability values. Therefore, an image-based data conversion method can be applied to reverse-analyze the exported permeability contour map, restoring it to an accurate numerical matrix. The specific steps are as follows:

[0057] The permeability cloud map in RGB format is converted to YUV color space, and its luminance (Y) channel is extracted to obtain a grayscale image representing the permeability distribution.

[0058] An iterative threshold segmentation algorithm is used to automatically segment the grayscale image above, accurately distinguishing regions with different penetration levels;

[0059] Using a pre-defined piecewise linear function, the grayscale value of each pixel in the grayscale image is mapped back to the corresponding actual permeability value, ultimately generating a high-fidelity permeability value matrix that is completely consistent with the original cloud map.

[0060] The permeability numerical matrix obtained from the above steps is mapped and assigned to each mesh element of the three-dimensional finite element model established in this application through a custom interpolation algorithm.

[0061] The same process can be used to process other parameters such as porosity.

[0062] In step S2, in order to construct the seepage mechanics model, the basic properties of the injected fluid can be set, including the fluid density. Viscosity μ f and the rock-fluid compressibility coefficient C r C f etc., to establish a geomechanics-seepage coupling model.

[0063] After assigning the model parameters, the injection conditions and safety constraints can be set. Specifically, the position of the two-dimensional elliptical surface in step S1 is defined as the fluid injection inlet, and an initial water injection rate Q is set. i (e.g., 1 m³ / h), and then the key termination condition for the simulation calculation will be set as: when the monitored bottomhole flowing pressure reaches the fracture pressure P of the reservoir rock.f The calculation automatically terminates at that time. The safety constraints in this invention are the core of ensuring that energy replenishment operations do not fracturing the formation and that safe and controllable energy storage is achieved.

[0064] In step S3, based on the three-dimensional layered geomechanics-seepage coupled finite element model constructed in step S1 and the water injection simulation conditions set in step S2, the dynamic changes of formation pore pressure, the evolution of rock stress and strain, and the seepage law of fluids during the water injection process are simulated. Key data are extracted and output from the calculation results, including bottom hole pressure at different times, formation pore pressure distribution cloud map, volume of area where pore pressure recovers to 90% of the original pressure, and injection volume, laying a data foundation for subsequent energy replenishment parameter analysis.

[0065] In this step, the pore pressure threshold is set to 90% of the original formation pressure. The total volume of the region in the model where the pore pressure reaches or exceeds this threshold is calculated using a volume integral algorithm and denoted as the effective energy replenishment volume V. e The calculation method is as follows:

[0066]

[0067]

[0068] X=P j -P i

[0069] Where m is the total number of all mesh elements in the three-dimensional finite element model; j represents the j-th mesh element in the model; Let be the volume of the j-th grid cell, in m³; The pore pressure value (MPa) of the j-th grid cell at the end of the simulation; Let be the Herveside step function.

[0070] Figure 4 This is an example of a pore pressure distribution cloud map provided in the embodiments of this application, where the highlighted area represents the volume where the pressure has recovered to more than 90% of the original pressure.

[0071] Based on the simulated total injection time and the set displacement, the cumulative injection volume Q at which the safe pressure limit is reached is calculated. t The calculation method is as follows:

[0072] Q t = Q i *t

[0073] Among them, Q i t represents the initial water injection volume; t represents the total injection time.

[0074] The simulation results under different water injection rates were analyzed to determine the optimal combination of water injection parameters. Using the established finite element model, the injection rate was changed (e.g., 0.5 m³ / h, 1.0 m³ / h, 1.5 m³ / h, etc.) to obtain the effective energy replenishment volume V corresponding to different injection rates. e With cumulative injection volume Q t The data set was used to calculate the refueling efficiency for each displacement. .

[0075] Where the energy replenishment efficiency is the effective energy replenishment volume V e The proportion of the total reservoir volume V is calculated using the following formula:

[0076]

[0077]

[0078] Comparative analysis of the cumulative injection volume and energy replenishment efficiency under various displacement schemes, combined with the capacity of the on-site injection equipment and the timeliness requirements of operation, selected the displacement with higher energy replenishment efficiency and controllable operational risks as the optimal water injection displacement Q. o The corresponding cumulative injection volume is the recommended injection volume Q. to .

[0079] During water injection, in order to use the minimum cumulative injection volume while achieving the maximum possible energy replenishment efficiency to meet the oilfield's requirements, decision indicators are used. The optimal water injection strategy is determined, and its calculation formula is as follows:

[0080]

[0081] The physical meaning of the decision indicator is the energy replenishment efficiency that can be obtained per unit of cumulative injection volume. The higher the value, the better the energy replenishment economic benefits of the water injection and discharge scheme.

[0082] In applications, decision indicators are calculated based on different engine displacements. After removing data that does not meet the final requirements for oilfield modification, the remaining different injection rates are used as the x-axis to determine the corresponding decision indicators. Plot a curve showing the relationship between engine displacement and decision-making indicators, with the vertical axis as the ordinate, to visually compare different decision-making indicators. The size of the decision indicator is used to select the decision metric. Maximum injection displacement Q o To determine the optimal injection displacement.

[0083] You can ask questions on site. o Water is injected at a certain flow rate, and the bottom-hole pressure is monitored in real time. When the pressure approaches the formation fracture pressure or the cumulative injection volume reaches Q... to Stop the injection at that time.

[0084] Therefore, this invention provides a method for reservoir water injection and energy storage before repeated fracturing. This method establishes a three-dimensional finite element heterogeneous model to simulate the reservoir pressure recovery under different water injection rates. With the formation fracturing pressure as a safety constraint, it determines the optimal water injection parameters and expected energy storage effect for the reservoir, providing an optimization basis for on-site water injection operations.

[0085] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An optimized method for reservoir water injection and energy storage before repeated fracturing, characterized in that, Includes the following steps: S1. Establish a three-dimensional layered heterogeneous finite element model based on reservoir characteristics and construct the initial hydraulic fracturing fractures; S2. Assign rock physics and fluid parameters to each layer in the finite element model and set water injection simulation conditions; S3. Perform simulation calculations on the finite element model to determine the energy replenishment efficiency for each displacement. Through decision indicators Determine the optimal water injection strategy, among which, Among them, V e V represents the effective energy replenishment volume; V is the total reservoir volume. For decision-making indicators; Q t This represents the cumulative injection volume.

2. The water injection energy storage optimization method according to claim 1, step S1 includes: S1.1 Determine the length and width of the finite element model based on the well spacing and row spacing of the target well area, and determine the height of the finite element model based on the formation thickness corresponding to the vertical reservoir thickness; S1.

2. Divide the finite element model into different sub-layers according to the thickness of each vertical reservoir; S1.3 Construct a rectangle that runs through all layers and is perpendicular to the formation plane at the geometric center of the finite element model, and use the rectangle to represent the initial hydraulic fracturing fracture.

3. The water injection energy storage optimization method according to claim 2, step S1.3 further includes discretizing the geometric model using the finite element method: S1.3.1 The overall model is divided into free tetrahedral meshes; S1.3.

2. The mesh is refined near the two-dimensional ellipse that represents the intersection of the initial fracturing fracture and the formation plane.

4. The water injection energy storage optimization method according to claim 1, further comprising step S2: S21. Use data simulation software to obtain dynamic change parameters of the formation, and use image data conversion method to assign dynamic change parameters to each grid element of the finite element model. S22. Define the position of the two-dimensional elliptical surface as the fluid injection inlet, set the initial water injection rate, and gradually increase the water injection rate value. S23. When the calculated bottom hole flowing pressure reaches the reservoir fracture pressure, the calculation is terminated.

5. The water injection energy storage optimization method according to claim 4, wherein the formation dynamic change parameters include pressure, porosity, permeability, saturation, and geostress.

6. In the water injection energy storage optimization method according to claim 1, the method for obtaining the effective energy replenishment volume in step S3 is as follows: The pore pressure threshold is set to 90% of the original formation pressure. The total volume of the region in the finite element model where the pore pressure reaches or exceeds this threshold is calculated using a volume integral algorithm, which is the effective energy replenishment volume V. e .

7. In the water injection energy storage optimization method according to claim 1, in step S3, the decision index... The injection displacement corresponding to the maximum value is the optimal injection displacement.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the water injection energy storage optimization method as described in any one of claims 1-7.

9. A storage medium storing computer-executable instructions, which, when executed by a computer processor, are used to perform the hydroelectric energy storage optimization method as described in any one of claims 1-7.

10. A computer program product comprising a computer program that, when executed by a processor, implements the water injection energy storage optimization method as described in any one of claims 1-7.

Images