A prediction method for the law of repeated fracturing crack propagation and related equipment

Abstract

The present invention relates to the fields of tight oil development and rock mechanics, and discloses a method for predicting the fracture propagation law of refracturing and related equipment. The method includes determining the geological characteristics and rock mechanical characteristics of the formation where the primary fracture is located; determining the in-situ stress state of the formation where the reservoir fracturing fracture is located; determining the primary fracture network through the geological characteristics, rock mechanical characteristics and the in-situ stress state; determining the refracturing fracture propagation characteristics; and predicting the refracturing fracture propagation law according to the geological characteristics, rock mechanical characteristics, in-situ stress state, primary fracture network and the refracturing fracture propagation characteristics. The present invention increases the influence of in-situ stress evolution on the propagation of new fractures, improves the accuracy of fracture propagation prediction of oil wells, improves the efficiency and effect of the refracturing technology of oil wells, and provides innovative technical support for the efficient development of tight oil reservoirs.

Description

Technical Field

[0001] The present invention relates to the fields of tight oil development and rock mechanics, and specifically provides a method for predicting the fracture propagation law of refracturing and related equipment. Background Art

[0002] In the field of tight oil exploitation, refracturing technology, as an important means to improve the productivity of oil and gas wells, has received extensive attention in recent years. Although refracturing technology has shown remarkable effects in increasing the production of developed oil and gas wells, it still faces many challenges in practical applications. Among them, the influence of in-situ stress on fracture propagation is a key issue. In-situ stress not only affects the formation and direction of fractures, but also determines the final shape, distribution and conductivity of fractures, thereby affecting oil and gas productivity and well group production. Common refracturing technologies often ignore the complex effects of heterogeneous in-situ stress on fracture propagation, which leads to difficulties in predicting fracture behavior and optimizing fracturing design.

[0003] Currently, traditional fracture propagation prediction methods often deviate from the actual situation, unable to accurately predict the fracture morphology and distribution of refracturing after the initial fracture network is put into production, affecting the design of refracturing parameters and resulting in suboptimal fracturing effects. In addition, existing methods also have deficiencies in dealing with the complexity and uncertainty of geological data, and it is difficult to adapt to the changing reservoir pressure and stress states. Therefore, it is necessary to develop a new prediction method that can comprehensively consider the influence of in-situ stress, accurately simulate and predict the fracture propagation law in refracturing. This method should be able to handle complex in-situ stress states, provide a scientific basis for the design and optimization of oil well refracturing, and ultimately increase the production and economic benefits of oil wells. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for predicting the fracture propagation law of refracturing and related equipment, so as to solve the technical problem of how to accurately predict the influence law of in-situ stress on fracture propagation in oil well refracturing.

[0005] The present invention is realized through the following technical solutions:

[0006] In a first aspect, the present invention provides a method for predicting the fracture propagation law of refracturing, including the following steps

[0007] Determine the geological characteristics and rock mechanical characteristics of the formation where the initial fracturing fractures are located;

[0008] Determine the in-situ stress state of the formation where the reservoir fracturing fractures are located;

[0009] Determine the initial fracture network based on the geological characteristics, rock mechanical characteristics and the in-situ stress state;

[0010] Determine the fracture propagation characteristics of refracturing;

[0011] Predict the repeated fracturing crack propagation law according to the geological characteristics, rock mechanical characteristics, in-situ stress state and the initial fracture network in combination with the repeated fracturing crack propagation characteristics.

[0012] Preferably, in the steps of determining the geological characteristics and rock mechanical characteristics of the formation where the initial fracturing cracks are located, determine the rock mineral composition by X-ray diffraction, analyze the geological characteristics and rock mechanical characteristics based on the rock mineral composition using seismic data and well logging data, and create a three-dimensional geological model of the reservoir according to the geological characteristics and rock mechanical characteristics, where the parameters of the three-dimensional geological model include lithology, porosity and permeability.

[0013] Preferably, in the process of determining the in-situ stress state of the formation where the reservoir fracturing cracks are located, the specific process is as follows:

[0014] Use downhole measurement data and rock mechanical experiments on cores to determine the original in-situ stress, where the downhole measurement data includes formation breakdown test data and imaging logging data;

[0015] Based on the original in-situ stress, combine the elastic-plastic constitutive equation and the Mohr-Coulomb criterion to determine the in-situ stress state of the formation where the reservoir fracturing cracks are located.

[0016] Preferably, in the process of determining the initial fracture network through the geological characteristics, rock mechanical characteristics and the in-situ stress state, forward model the initial fracture morphology by the fracture mechanics method, and process the convex sample set and non-convex sample set through the density-based clustering algorithm of microseismic data to form the inversion morphology of the initial fracturing fracture network; combine the forward modeled initial fracture morphology and the inversion morphology of the initial fracturing fracture network to determine the initial fracture network.

[0017] Furthermore, determine the pore pressure and in-situ stress change characteristics caused by the production of the initial fracture network, and analyze the pore pressure and in-situ stress change characteristics to characterize the reservoir fluid-solid coupling characteristics induced by the pressure reduction production of the initial fracture network. The calculation formula of the reservoir fluid-solid coupling characteristics is as follows:

[0018] Seepage state: u = -k / μ * ∇p

[0019] Solid mechanics constitutive: σ = C * (ε - α * ∇p)

[0020] Fluid continuity equation: ∂p / ∂t - ∇p * (k * ∇p) = Q

[0021] Among them, u is the velocity with the unit of m / s; k is the permeability with the unit of m²; μ is the viscosity with the unit of Pa·s; ∇p is the pressure gradient with the unit of Pa / m; σ is the total stress with the unit of Pa; C is the drainage elastic stiffness parameter with the unit of Pa; ε is the total strain tensor, α is the effective stress coefficient, t is the time with the unit of s; Q is the fluid inflow or outflow parameter with the unit of m³ / s·m³.

[0022] Preferably, in the step of determining the characteristics of refracturing fracture propagation, the specific process is as follows:

[0023] Simulate the propagation behavior of fractures in the evolved complex stress field through fracture mechanics and extended finite element method;

[0024] Describe the fracture network based on the propagation behavior in the complex stress field, where nodes and edges are used to represent fracture intersections and fracture segments, and analyze the connectivity and distribution characteristics of the fracture network;

[0025] Determine the characteristics of refracturing fracture propagation according to the fracture network.

[0026] Preferably, in the process of predicting the refracturing fracture propagation law by combining the refracturing fracture propagation characteristics with the geological characteristics, rock mechanical characteristics, in-situ stress state and primary fracture network, the specific process is as follows:

[0027] Compare and calibrate the geological characteristics, rock mechanical characteristics, in-situ stress state and primary fracture network to determine the propagation effect and fracturing quality;

[0028] Predict the refracturing fractures based on the propagation effect and fracturing quality to determine the optimal refracturing fracture morphology and fracturing parameters.

[0029] In the second aspect, the present invention also provides a prediction system for the refracturing fracture propagation law, including:

[0030] The first data determination module is used to determine the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing fractures are located;

[0031] The second data determination module is used to determine the in-situ stress state of the formation where the reservoir fracturing fractures are located;

[0032] The first data processing module is used to determine the primary fracture network based on the geological characteristics, rock mechanical characteristics and the in-situ stress state;

[0033] The third data determination module is used to determine the characteristics of refracturing fracture propagation;

[0034] The second data processing module is used to predict the refracturing fracture propagation law by combining the geological characteristics, rock mechanical characteristics, in-situ stress state and primary fracture network with the characteristics of refracturing fracture propagation.

[0035] In a third aspect, the present invention further provides a mobile terminal, characterized by comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the prediction method for the repeated fracturing crack propagation law as described above is implemented.

[0036] In a fourth aspect, the present invention further provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the prediction method for the repeated fracturing crack propagation law as described above is implemented.

[0037] Compared with the prior art, the present invention has the following beneficial technical effects:

[0038] The present invention provides a prediction method for the repeated fracturing crack propagation law. Based on actual reservoir data, the initial fracture network, and the initial fracture network productivity data, the repeated fracturing process of oil wells in tight oil reservoirs is simulated. Well sections with similar in-situ stress states, fracture network morphologies, and productivity distributions are classified and quantified, and then repeated fracturing crack prediction is carried out. On this basis, the influence of in-situ stress evolution on the propagation of new fractures is increased, the accuracy of fracture propagation prediction for oil wells is improved, the efficiency and effect of the repeated fracturing technology for oil wells are improved, and innovative technical support is provided for the efficient development of tight oil reservoirs.

[0039] Furthermore, by combining actual reservoir data, the initial fracture network, and productivity data, the present invention can more accurately simulate the repeated fracturing process, and thus more accurately predict the crack propagation law. This prediction method based on actual data has higher accuracy and reliability compared with traditional theoretical models or empirical formulas.

[0040] Furthermore, the present invention classifies and quantifies well sections with similar in-situ stress states, fracture network morphologies, and productivity distributions. This classification method helps to identify the commonalities and differences between different well sections, and thus formulate more specific fracturing strategies and optimization schemes for different types of well sections. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flowchart of the prediction method for the repeated fracturing crack propagation law in the present invention;

[0042] Figure 2 is an effect diagram of repeated fracturing cracks under the action of the stress field in the present invention;

[0043] Figure 3 is a schematic diagram showing the prediction of the repeated fracturing crack morphology in the present invention in a strip form;

[0044] Figure 4Schematic structural diagram of the prediction system for the repeated fracturing crack propagation law of the present invention;

[0045] In the figure: 1 - First data determination module; 2 - Second data determination module; 3 - First data processing module; 4 - Third data determination module; 5 - Second data processing module. Detailed implementation manners

[0046] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0047] The present invention will be further described in detail below in conjunction with the accompanying drawings:

[0048] The purpose of the present invention is to provide a method and related equipment for predicting the repeated fracturing crack propagation law, so as to solve the technical problem of how to accurately predict the influence law of in-situ stress on crack propagation in oil well repeated fracturing.

[0049] Refer to Figure 1 and Figure 2 , the present invention provides a method for predicting the repeated fracturing crack propagation law, including the following steps

[0050] Step 1, determine the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing crack is located;

[0051] Specifically, in the step of determining the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing crack is located, the rock mineral composition is determined by X-ray diffraction, and based on the rock mineral composition, the geological characteristics and rock mechanical characteristics are analyzed by using seismic data and well logging data, and a three-dimensional geological model of the reservoir is created according to the geological characteristics and rock mechanical characteristics, wherein the parameters of the three-dimensional geological model include lithology, porosity and permeability.

[0052] Among them, X-ray diffraction is an effective means for analyzing the rock mineral composition. When X-rays irradiate a rock sample, diffraction occurs, forming a specific diffraction pattern. By analyzing these patterns, the mineral components and their contents in the rock can be determined.

[0053] In the fusion analysis of seismic and well logging data, seismic data can provide large-scale structural information of the formation, such as structural features such as faults and folds. This information is crucial for understanding the overall structure and stress distribution of the formation.

[0054] Well logging data can reveal small-scale features of the formation, such as reservoir parameters like porosity and permeability. These parameters directly affect the propagation of fractures and the flow of oil and gas.

[0055] By fusing and analyzing seismic data and well logging data, a more comprehensive understanding of the geological and rock mechanical characteristics of the formation can be obtained, providing accurate basic data for subsequent creation of 3D geological models and prediction of fracture propagation.

[0056] Among them, the 3D geological model can visually display the spatial distribution and key parameters of the formation. In the prediction of fracture propagation, this model can be used to simulate the fracture propagation process and analyze key parameters such as the propagation direction, length, and width of the fractures.

[0057] By comparing the fracture propagation under different parameters, the fracturing strategy and construction parameters can be optimized to improve the fracturing effect and oil and gas recovery rate.

[0058] Step 2, determine the in-situ stress state of the formation where the reservoir fracturing fractures are located;

[0059] Specifically, in the process of determining the in-situ stress state of the formation where the reservoir fracturing fractures are located, the specific process is as follows:

[0060] Use downhole measurement data and rock mechanics experiments on core samples to determine the original in-situ stress, where the downhole measurement data includes breakdown experiment data and imaging well logging data;

[0061] Based on the original in-situ stress, combine the elastoplastic constitutive equation and the Mohr-Coulomb criterion to determine the in-situ stress state of the formation where the reservoir fracturing fractures are located.

[0062] In the present invention, the downhole measurement data includes breakdown experiment data and imaging well logging data. The breakdown experiment data is obtained by conducting specific pressure tests downhole, observing and recording the pressure values when the rock fractures, and thus inferring the original in-situ stress of the formation. The imaging well logging data is obtained by scanning the formation with well logging instruments to acquire information such as the formation structure and fracture distribution, and these information can also indirectly reflect the stress state of the formation.

[0063] In the rock mechanics experiments on core samples in the present invention, core samples are taken from the formation using a coring tool, and then rock mechanics experiments such as uniaxial compression experiments and triaxial compression experiments are conducted under laboratory conditions to measure rock mechanical parameters such as elastic modulus, Poisson's ratio, and compressive strength. These parameters can be used to infer the original in-situ stress of the formation.

[0064] The elastoplastic constitutive equation used in the present invention is a mathematical equation for the stress-strain relationship of materials during the stress application process. For formation rocks, their stress application process often includes both elastic deformation and plastic deformation, so the elastoplastic constitutive equation is needed to describe their stress-strain relationship.

[0065] A criterion for judging whether a rock undergoes shear failure through the Mohr-Coulomb criterion. Based on parameters such as the tensile strength, compressive strength, and internal friction angle of the rock, the failure conditions of the rock under specific stress states can be deduced.

[0066] By combining the original in-situ stress with the elastoplastic constitutive equation and the Mohr-Coulomb criterion, the stress distribution and changes during the fracturing process of the formation can be calculated, thereby determining the in-situ stress state of the formation where the reservoir fracturing cracks are located.

[0067] Step 3, determine the primary fracture network based on the described geological characteristics, rock mechanical characteristics, and the in-situ stress state;

[0068] During the process of determining the primary fracture network based on the described geological characteristics, rock mechanical characteristics, and the in-situ stress state, the forward modeling of the primary fracture morphology is carried out by the fracture mechanics method, and the inversion morphology of the primary fracture network is formed by processing the convex sample set and non-convex sample set based on the density clustering algorithm of microseismic data; combine the forward modeled primary fracture morphology and the inversion morphology of the primary fracture network to determine the primary fracture network.

[0069] Specifically, in the forward modeling of the primary fracture morphology by the fracture mechanics method, the geological characteristics, rock mechanical characteristics, and in-situ stress state are used as input parameters.

[0070] Apply fracture mechanics theories, such as the K-I opening mode or K-II sliding mode fracture mechanics models, to calculate the propagation path, morphology, and size of the fractures under specific stress conditions.

[0071] The results of the forward simulation provide a prediction of the primary fracture morphology, that is, a preliminary understanding of how the fractures are distributed and propagated underground.

[0072] Specifically, the method for determining the inversion morphology of the fracture network is as follows:

[0073] Determine the directly related density of a certain point: δ(x) = |{p ∈ X | dist(x, p) ≤ ε}|

[0074] This formula calculates the directly reachable density of point x, that is, the number of points within its ε neighborhood.

[0075] Determine the core points: C(x) = {p ∈ X | δ(p) ≥ minPts}

[0076] This formula defines the core points as the points whose directly reachable density is greater than or equal to minPts.

[0077] Determine the boundary points: B(x) = {p ∈ X | ∃q ∈ C(x) such that dist(x, q) ≤ ε}

[0078] This formula defines boundary points as points within the ε-neighborhood of core points, but not the core points themselves.

[0079] Quantization noise: N = X \ (C(X) ∪ B(X))

[0080] This formula defines noise as the set of points that are neither core points nor boundary points. These points are considered not to belong to any cluster.

[0081] Reachability characterization: reach(p, q) =∀r ∈ X between p and q, δ(r) ≥ minPts

[0082] This formula defines the reachability between two points p and q. If there is a path between q and p, and every point on the path is either a core point or directly reachable from a core point, then q can be reached from p.

[0083] Determine cluster: cluster(p) = {q ∈ X | reach(p, q) ∨ reach(q, p)}

[0084] This formula identifies the cluster to which point p belongs. All points that are reachable from p or from which p is reachable are considered part of the same cluster.

[0085] Among them, determine the characteristics of pore pressure and in-situ stress changes caused by the initial fracture network production, and analyze the characteristics of pore pressure and in-situ stress changes to characterize the reservoir fluid-solid coupling characteristics induced by the initial fracture network pressure reduction production. The calculation formula for the reservoir fluid-solid coupling characteristics is as follows:

[0086] Seepage state: u = -k / μ * ∇p

[0087] Solid mechanics constitutive: σ = C * (ε - α * ∇p)

[0088] Fluid continuity equation: ∂p / ∂t - ∇p * (k * ∇p) = Q

[0089] Among them, u is the velocity, unit m / s; k is the permeability, unit m²; μ is the viscosity, unit Pa·s; ∇p is the pressure gradient, unit Pa / m; σ is the total stress, unit Pa; C is the drained elastic stiffness parameter, unit Pa; ε is the total strain tensor, α is the effective stress coefficient, t is the time, unit s; Q is the fluid inflow or outflow parameter, unit m³ / s·m³.

[0090] Step 4, determine the characteristics of repeated fracturing crack propagation;

[0091] Specifically, in the steps of determining the characteristics of refracturing fracture propagation, the specific process is as follows:

[0092] Analyze the propagation behavior of fractures in the evolved complex stress field through fracture mechanics and extended finite element simulation;

[0093] Among them, using fracture mechanics theories, such as linear elastic fracture mechanics or elastoplastic fracture mechanics, to analyze the propagation behavior of fractures in the complex stress field. This includes calculating parameters such as the stress intensity factor and J-integral at the fracture tip to evaluate the propagation trend and stability of fractures.

[0094] Apply the extended finite element method (XFEM) to simulate the propagation process of fractures. XFEM is a powerful numerical simulation method that can simulate the propagation of static and dynamic cracks, taking into account the nonlinearity of materials and damage evolution. Through XFEM, the propagation path, morphology, and velocity of fractures in the complex stress field can be visually observed.

[0095] Describe the fracture network based on the propagation behavior in the complex stress field, where nodes and edges are used to represent fracture intersections and fracture segments, and analyze the connectivity and distribution characteristics of the fracture network;

[0096] Among them, nodes and edges are used to represent fracture intersections and fracture segments. Nodes represent the intersection points or endpoints of fractures, while edges represent fracture segments, that is, the connecting parts between two nodes.

[0097] Analyze the connectivity and distribution characteristics of the fracture network. Connectivity describes the connection relationship between each fracture segment in the fracture network, such as whether they intersect or are parallel. The distribution characteristics describe the distribution of the fracture network in space, such as the density, direction, and length of fractures.

[0098] Determine the characteristics of refracturing fracture propagation based on the fracture network.

[0099] Among them, based on the description and analysis of the fracture network, determine the characteristics of refracturing fracture propagation. These characteristics may include the propagation direction of fractures, propagation velocity, fracture morphology (such as planar propagation, non-planar propagation, vertical propagation, etc.), the complexity and connectivity of the fracture network, etc.

[0100] By comparing the fracture propagation characteristics under different conditions, the fracturing effect can be evaluated, and the fracturing strategy and construction parameters can be optimized to improve the oil and gas recovery rate.

[0101] In the present invention, fracture propagation simulation is carried out. Through fracture mechanics methods and extended finite element methods, the propagation behavior of fractures in the evolved complex stress field is simulated. On this basis, fracture network analysis is carried out, and the graph theory method in complex network theory is applied to describe the fracture network: nodes and edges are used to represent fracture intersections and fracture segments, and their connectivity and distribution characteristics are analyzed.

[0102] The specific process is as follows:

[0103] Using the extended finite element method, enrich the standard finite element approximation by including additional functions that capture the behavior near the fracture tip.

[0104] Define the position of the crack through the level set function and use it to determine the enrichment domain.

[0105] Use a unified partition to ensure a smooth blend of the enriched displacement field and the standard displacement field.

[0106] The weak form of the balance equation is used to derive the system of equations for solving the nodal displacements.

[0107] Use the fracture mechanics crack propagation criterion to judge the crack propagation timing and path. Judge the crack propagation based on the energy release rate at the fracture tip.

[0108] The level set function is updated at each time step to reflect the current propagation state of the refracturing crack.

[0109] Step 5, predict the refracturing crack propagation law according to the geological characteristics, rock mechanics characteristics, in-situ stress state, and primary fracture network in combination with the refracturing crack propagation characteristics.

[0110] Specifically, in the process of predicting the refracturing crack propagation law according to the geological characteristics, rock mechanics characteristics, in-situ stress state, and primary fracture network in combination with the refracturing crack propagation characteristics, the specific process is as follows:

[0111] Compare and calibrate the geological characteristics, rock mechanics characteristics, in-situ stress state, and primary fracture network to determine the propagation effect and fracturing quality;

[0112] Based on the propagation effect and fracturing quality, predict the refracturing crack, and determine the optimal refracturing crack morphology and fracturing parameters.

[0113] Example 1

[0114] Taking a well in the X tight oil reservoir as an example, this example provides a method for predicting the refracturing crack propagation law, and the specific implementation steps are as follows:

[0115] S1: Determine the three-dimensional distribution of minerals, porosity, permeability, saturation, and rock mechanics parameters of the reservoir in the work area to form an initial state three-dimensional model. Taking this modeling as an example:

[0116] The layered porosity sequence is: [0.0334, 0.1131, 0.1239, 0.0587, 0.0854, 0.0873, 0.0650, 0.0939, 0.0222, 0.0236];

[0117] The layered permeability sequence is: [7.49, 2.26, 5.33, 4.80, 3.18, 4.28, 3.80, 6.72, 3.78, 5.17];

[0118] The layered saturation sequence is: [0.85, 0.81, 0.78, 0.76, 0.75, 0.76, 0.87, 0.77, 0.81, 0.80];

[0119] The layered elastic modulus sequence is: [35.19, 32.49, 33.21, 30.26, 39.04, 39.93, 36.87, 41.69, 40.93, 29.22];

[0120] The layered brittleness sequence is: [0.74, 0.61, 0.75, 0.66, 0.79, 0.64, 0.80, 0.73, 0.60, 0.66].

[0121] S2: Establish a in-situ stress model, collect a total of 1 well times of 20 groups of rock mechanics experimental data of core samples and borehole imaging logging data of adjacent wells in the work area, establish an initial in-situ stress model for the work area (with a thickness of 100 m and an area of 10 km²), and determine that the stress mechanism in the work area is a strike-slip fault stress mechanism.

[0122] S3: Through inversion of the primary fracturing construction data and microseismic data, characterize the size and extent of the primary fracture network, as shown in Table 1;

[0123]

[0124] Table 1 Characterization of the size and extent of the primary fracture network

[0125] S4: Collect the production history data of a certain well in the X tight oil reservoir, and characterize the degree and range of pressure drop and in-situ stress changes in combination with the reservoir fluid-solid coupling model.

[0126] S5: Determine the time of refracturing and the position of stage clusters, conduct refracturing fracture prediction, and evaluate the fracturing effect, as Figure 3 shown.

[0127] S6: Compare and calibrate the propagation path and shape of the refracturing fractures with the rock mechanics and geomechanics models to clarify the propagation effect and fracturing quality.

[0128] S7: Repeat the refracturing fracture prediction in S5, finally determine the optimal refracturing fracture shape and fracturing parameters, and the final in-situ stress results are shown in Table 2.

[0129]

[0130] Table 2 In-situ stress results

[0131] In summary, this embodiment provides a method for predicting the fracture propagation law of refracturing. Based on actual reservoir data, the initial fracture network, and the productivity data of the initial fracture network, the refracturing process of oil wells in tight oil reservoirs is simulated. Wells with similar in-situ stress states, fracture network morphologies, and productivity distributions are classified and quantified, and then the refracturing fracture prediction is carried out. On this basis, the influence of in-situ stress evolution on the propagation of new fractures is added to improve the accuracy of fracture propagation prediction for oil wells, enhance the efficiency and effect of the oil well refracturing technology, and provide innovative technical support for the efficient development of tight oil reservoirs.

[0132] Embodiment 2

[0133] According to Figure 4 As shown, this embodiment also provides a prediction system for the fracture propagation law of refracturing, including:

[0134] The first data determination module 1 is used to determine the geological characteristics and rock mechanical characteristics of the formation where the initial fracturing fractures are located;

[0135] The second data determination module 2 is used to determine the in-situ stress state of the formation where the reservoir fracturing fractures are located;

[0136] The first data processing module 3 is used to determine the initial fracture network based on the geological characteristics, rock mechanical characteristics, and the in-situ stress state;

[0137] The third data determination module 4 is used to determine the fracture propagation characteristics of refracturing;

[0138] The second data processing module 5 is used to predict the fracture propagation law of refracturing according to the geological characteristics, rock mechanical characteristics, in-situ stress state, and the initial fracture network in combination with the fracture propagation characteristics of refracturing.

[0139] Embodiment 3

[0140] The present invention also provides a mobile terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, such as a prediction program for the fracture propagation law of refracturing.

[0141] When the processor executes the computer program, the steps of the above-mentioned method for predicting the fracture propagation law of refracturing are implemented, such as:

[0142] Determine the geological characteristics and rock mechanical characteristics of the formation where the initial fracturing fractures are located;

[0143] Determine the in-situ stress state of the formation where the reservoir fracturing fractures are located;

[0144] Determine the initial fracture network based on the geological characteristics, rock mechanical characteristics, and the in-situ stress state;

[0145] Determine the characteristics of repeated fracturing crack propagation;

[0146] Predict the law of repeated fracturing crack propagation based on the geological characteristics, rock mechanical characteristics, in-situ stress state, and primary fracture network in combination with the characteristics of repeated fracturing crack propagation.

[0147] Alternatively, when the processor executes the computer program, it realizes the functions of each module in the above system. For example:

[0148] The first data determination module 1 is used to determine the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing cracks are located;

[0149] The second data determination module 2 is used to determine the in-situ stress state of the formation where the reservoir fracturing cracks are located;

[0150] The first data processing module 3 is used to determine the primary fracture network through the geological characteristics, rock mechanical characteristics, and the in-situ stress state;

[0151] The third data determination module 4 is used to determine the characteristics of repeated fracturing crack propagation;

[0152] The second data processing module 5 is used to predict the law of repeated fracturing crack propagation based on the geological characteristics, rock mechanical characteristics, in-situ stress state, and primary fracture network in combination with the characteristics of repeated fracturing crack propagation.

[0153] Exemplarily, the computer program can be divided into one or more modules / units. The one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units can be a series of computer program instruction segments capable of performing specific functions, and these instruction segments are used to describe the execution process of the computer program in the mobile terminal.

[0154] For example, the computer program can be divided into the first data determination module 1, the second data determination module 2, the first data processing module 3, the third data determination module 4, and the second data processing module 5. The specific functions of each module are as follows:

[0155] The first data determination module 1 is used to determine the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing cracks are located;

[0156] The second data determination module 2 is used to determine the in-situ stress state of the formation where the reservoir fracturing cracks are located;

[0157] The first data processing module 3 is used to determine the primary fracture network through the geological characteristics, rock mechanical characteristics, and the in-situ stress state;

[0158] The third data determination module 4 is configured to determine the characteristics of repeated fracturing crack propagation;

[0159] The second data processing module 5 is configured to predict the law of repeated fracturing crack propagation according to the geological characteristics, rock mechanical characteristics, in-situ stress state, and the primary fracture network in combination with the characteristics of repeated fracturing crack propagation.

[0160] The mobile terminal may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The mobile terminal may include, but is not limited to, a processor and a memory.

[0161] The processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the mobile terminal, connecting various parts of the entire mobile terminal through various interfaces and lines.

[0162] The memory may be used to store the computer programs and / or modules. The processor realizes various functions of the mobile terminal by running or executing the computer programs and / or modules stored in the memory, and by calling the data stored in the memory.

[0163] The memory may mainly include a program storage area and a data storage area. Among them, the program storage area may store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area may store data created according to the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0164] Embodiment 4

[0165] The present invention also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the method for predicting the propagation law of repeated fracturing fractures are implemented.

[0166] If the modules / units integrated in the mobile terminal are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.

[0167] Based on such understanding, all or part of the processes in the above method of the present invention can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the method for predicting the propagation law of repeated fracturing fractures can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc.

[0168] The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0169] It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0170] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific implementation manners of the present invention, and any modification or equivalent replacement without departing from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A prediction method for the law of repeated fracturing crack propagation, characterized in that, The method includes the following steps: Determine the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing fractures are located; Determine the in-situ stress state of the formation where the reservoir fracturing fractures are located; Determine the primary fracture network based on the geological characteristics, rock mechanical characteristics and in-situ stress state; Among them, the forward modeling of the primary fracture morphology is carried out by the fracture mechanics method, and the inversion morphology of the primary fracturing fracture network is formed by processing the convex sample set and non-convex sample set based on the density of the microseismic data; the primary fracture network is determined by combining the forward modeling of the primary fracture morphology and the inversion morphology of the primary fracturing fracture network; Among them, determine the characteristics of pore pressure and in-situ stress changes caused by the production of the primary fracture network, and analyze the characteristics of pore pressure and in-situ stress changes to characterize the fluid-solid coupling characteristics of the reservoir induced by the pressure reduction production of the primary fracture network. The calculation formula of the fluid-solid coupling characteristics of the reservoir is as follows: Seepage state: Constitutive relations of solid mechanics: Fluid continuity equation: Among them, u is the velocity with the unit of m / s; k is the permeability with the unit of m 2 ; μ is the viscosity with the unit of Pa·s; the pressure gradient with the unit of Pa / m; σ is the total stress with the unit of Pa; C is the drainage elastic stiffness parameter with the unit of Pa; ε is the total strain tensor, α is the effective stress coefficient, t is the time with the unit of s; Q is the fluid inflow or outflow parameter with the unit of m 3 / s; Determine the characteristics of the repeated fracturing fracture propagation; Based on the geological characteristics, rock mechanical characteristics, in-situ stress state and primary fracture network, predict the repeated fracturing fracture propagation law in combination with the characteristics of the repeated fracturing fracture propagation.

2. The prediction method for the repeated fracturing crack propagation law according to claim 1, characterized in that In the step of determining the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing fractures are located, the rock mineral composition is determined by X-ray diffraction, and the geological characteristics and rock mechanical characteristics are analyzed based on the rock mineral composition by using seismic data and well logging data, and a three-dimensional geological model of the reservoir is created according to the geological characteristics and rock mechanical characteristics. The parameters of the three-dimensional geological model include lithology, porosity and permeability.

3. A prediction method for the propagation law of repeated fracturing cracks according to claim 1, characterized in that In the process of determining the in-situ stress state of the formation where the reservoir fracturing fractures are located, the specific process is as follows: Determine the original in-situ stress by using downhole measurement data and rock mechanical experiments on cores, where the downhole measurement data includes formation breakdown test data and imaging logging data; Based on the original in-situ stress, combine the elastoplastic constitutive equation and the Mohr-Coulomb criterion to determine the in-situ stress state of the formation where the reservoir fracturing fractures are located.

4. A prediction method for the propagation law of repeated fracturing cracks according to claim 1, characterized in that, In the step of determining the characteristics of the repeated fracturing fracture propagation, the specific process is as follows: Simulate the propagation behavior of fractures in the evolved complex stress field by fracture mechanics and extended finite element; Describe the fracture network based on the propagation behavior in the complex stress field, where nodes and edges are used to represent fracture intersections and fracture segments, and analyze the connectivity and distribution characteristics of the fracture network; Determine the characteristics of the repeated fracturing fracture propagation according to the fracture network.

5. The prediction method for the repeated fracturing crack propagation law according to claim 1, characterized in that In the process of predicting the repeated fracturing fracture propagation law based on the geological characteristics, rock mechanical characteristics, in-situ stress state and primary fracture network in combination with the characteristics of the repeated fracturing fracture propagation, the specific process is as follows: Carry out comparative calibration on the geological characteristics, rock mechanical characteristics, in-situ stress state and primary fracture network to determine the propagation effect and fracturing quality; Predict the repeated fracturing fractures based on the propagation effect and fracturing quality, and determine the optimal repeated fracturing fracture morphology and fracturing parameters.

6. A prediction system for the fracture propagation law of refracturing, based on the prediction method for the fracture propagation law of refracturing according to any one of claims 1-5, characterized in that It includes: The first data determination module is used to determine the geological characteristics and rock mechanical characteristics of the formation where the primary fracturing fractures are located; The second data determination module is used to determine the in-situ stress state of the formation where the reservoir fracturing fractures are located; The first data processing module is used to determine the primary fracture network based on the geological characteristics, rock mechanical characteristics and the in-situ stress state; The third data determination module is used to determine the characteristics of repeated fracturing crack propagation; The second data processing module is used to predict the law of repeated fracturing crack propagation according to the geological characteristics, rock mechanical characteristics, in-situ stress state, and the primary fracture network in combination with the characteristics of repeated fracturing crack propagation.

7. A mobile terminal, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the prediction method of the repeated fracturing crack propagation law according to any one of claims 1-5 is implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the prediction method of the repeated fracturing crack propagation law according to any one of claims 1-5 is implemented.

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