A method and system for predicting the evolution path of a super-large true triaxial hydraulic fracturing fracture

Abstract

The present application relates to the technical field of oil and gas field development, and discloses a prediction method and system for fracture evolution path of super-large true triaxial hydraulic fracturing, wherein the prediction method comprises the following steps: a coupling geomechanics model integrating micro, macro and wellbore flow scales is constructed; the model is initialized and initial fracture expansion simulation is performed; construction data are collected in real time, and model parameters are dynamically optimized through a data assimilation algorithm; advanced prediction of fracture evolution is performed by using the updated model; and optimized decisions are generated based on the prediction results and fed back to the construction site. The present application realizes the fusion of multi-scale physical mechanism and real-time dynamic prediction, and can accurately predict and actively control the fracture expansion under super-large true triaxial conditions.

Description

Technical Field

[0001] This invention relates to the field of oil and gas field development technology, specifically to a method and system for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures. Background Technology

[0002] Hydraulic fracturing technology, as a core method in the stimulation and development of unconventional oil and gas reservoirs, significantly improves the extraction efficiency of these reservoirs by increasing oil and gas flow channels. Hydraulic fracturing utilizes a surface high-pressure pump unit to inject a large amount of high-viscosity fluid into the reservoir through the wellbore, creating high pressure at the bottom of the well. When the pressure exceeds the reservoir's tolerance, the reservoir fractures, forming fracture channels. These fracture channels increase the contact area between the horizontal well and the reservoir, enhancing the ability of oil and gas to migrate to distant parts of the reservoir, thus achieving the goal of increasing production in unconventional oil and gas reservoirs.

[0003] On the one hand, hydraulic fracturing involves a variety of mechanical problems involving the coupling of physical fields, such as rock deformation, fluid flow within the fracture, fluid loss within the fracture, fracture formation and propagation, and flow in porous media. Due to the complexity of geological structures, including the constitutive properties of rocks, non-uniform material distribution, and the presence of natural fractures and weak interfaces, research on hydraulic fracturing faces enormous challenges.

[0004] On the other hand, hydraulic fracturing technology requires expensive experimental equipment, and there are significant differences between manual coring and underground reservoirs. Therefore, numerical simulation and theoretical analysis have become important methods for hydraulic fracturing research. As a key factor affecting the productivity of unconventional oil and gas reservoirs, fractures in hydraulic fracturing cause the fracture network in the rock to continuously expand and connect under the action of liquid pressure, forming a complex fracture network structure. This complexity is not only reflected in the geometry of the fractures but also in the spatial relationships, directionality, and size distribution between them.

[0005] Therefore, accurately modeling and describing the hydraulic fracturing fracture network is of great significance for optimizing fracturing design and improving oil and gas extraction efficiency. Based on an accurate hydraulic fracturing fracture network model, the hydraulic fracturing design scheme can be optimized. Establishing a reasonable hydraulic fracturing fracture model is the key to simulating and evaluating the fluidity of fractured reservoirs, and thus evaluating the fracturing effect. It can better evaluate the fracturing effect, provide guidance for reservoir stimulation, improve oil and gas extraction efficiency, and reduce production costs.

[0006] In view of this, the present invention is hereby proposed. Summary of the Invention

[0007] To address the aforementioned problems, this invention proposes a method and system for predicting the evolution path of fractures in ultra-large true triaxial hydraulic fracturing operations. Specifically, the following technical solution is adopted:

[0008] A method for predicting the evolution path of fractures in ultra-large true triaxial hydraulic fracturing operations includes:

[0009] Step S1: For the target reservoir, establish a multi-scale coupled geomechanical numerical model for cross-scale data interaction through a fluid-structure interaction framework. The model covers the microscale of rock materials, the macroscale of rock strata, and the flow scale of the wellbore and near-wellbore zone.

[0010] Step S2: Based on geological exploration, well logging and core test data, assign initialization parameters to the multi-scale coupled geomechanical model, set true triaxial boundary conditions, set fracturing fluid injection conditions in the multi-scale coupled geomechanical model, simulate the initial propagation of fractures, and predict the fracture initiation location, initial propagation path and morphology.

[0011] Step S3: During the actual fracturing operation, real-time monitoring data is collected. The monitoring data includes at least bottom hole pressure, wellhead discharge rate, microseismic events, downhole strain, or acoustic emission signals. The real-time collected monitoring data is input into a data assimilation algorithm and compared with the model prediction results of step S2 to dynamically invert and optimize the key uncertainty parameters in the model.

[0012] Step S4: Based on the optimized parameters in step S3, update the multi-scale coupled geomechanical model in real time; run the updated multi-scale coupled geomechanical model to make advanced predictions and obtain prediction results on the evolution path, propagation speed, fracture network complexity, and interaction with natural fractures and bedding interfaces in the future time period.

[0013] As an optional embodiment of the present invention, a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, wherein the construction of a multi-scale coupled geomechanical model in step S1 includes:

[0014] A microscale model of rock material was constructed using the discrete element method to simulate the deformation of the rock matrix, microcrack initiation, and interparticle interactions.

[0015] Macroscopic rock strata-scale models were constructed using the extended finite element method or the cohesive element method to simulate the initiation and three-dimensional propagation of hydraulic fractures.

[0016] Computational fluid dynamics or a one-dimensional pipe flow model are used to construct a flow scale model of the wellbore and near-wellbore zone to simulate the flow and pressure transmission of fracturing fluid in the wellbore and the opened fractures.

[0017] The microscale model of the rock material, the macroscale model of the rock strata, and the flow scale model of the wellbore and near-wellbore zone are dynamically coupled through a fluid-structure interaction calculation framework to realize the transmission of cross-scale mechanical and fluid information.

[0018] As an optional embodiment of the present invention, the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures in step S3 is a data assimilation algorithm of ensemble Kalman filtering or particle filtering algorithm; the key uncertainty parameters include at least one of reservoir local in-situ stress field, spatial distribution of rock fracture toughness, opening pressure of natural fractures and filtration coefficient.

[0019] As an optional embodiment of the present invention, the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures in step S3 further includes: temperature and strain profile data along the wellbore obtained through distributed optical fiber sensing technology, and / or near-wellbore fracture imaging data obtained through downhole television or measurement-while-drilling tools.

[0020] As an optional embodiment of the present invention, the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures of the present invention further includes step S4: based on the prediction results of the advanced prediction, assessing the engineering risks of uncontrolled fracture height, asymmetric expansion of fracture network, and communication with non-target layers or adjacent wells.

[0021] As an optional embodiment of the present invention, a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, and assessing engineering risks, includes:

[0022] Set a risk threshold and trigger a height runaway warning when the predicted crack propagation height exceeds the constraint range of the top or bottom boundary of the producing layer.

[0023] When the asymmetry of the predicted crack propagation path in the horizontal direction exceeds a preset ratio, an abnormal crack mesh morphology warning is triggered.

[0024] When the predicted fracture is less than the safe distance from the known adjacent well trajectory or water layer / gas cap, an early warning of inter-well interference or communication risk is triggered.

[0025] As an optional embodiment of the present invention, a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures includes:

[0026] Step S5: Based on the assessment results of the engineering risks, generate optimization decision instructions;

[0027] The decision instructions include recommended schemes for adjusting fracturing operation parameters, which at least include displacement, sand ratio, slug combination, or temporary plugging strategy; the decision instructions are fed back to the on-site fracturing control system or operators to guide or automatically adjust the current and subsequent fracturing operations.

[0028] As an optional embodiment of the present invention, a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, wherein the generation of optimization decision instructions includes:

[0029] Based on the updated multi-scale coupled geomechanical model, multi-scenario simulations are performed, with different discharge rates, liquid viscosities, or temporary plugging schemes as input variables.

[0030] With the optimization objectives of maximizing the effective modification volume, minimizing engineering risks, or optimizing the complexity of the crack network, the optimal combination of construction parameters is selected from the results of multi-scenario simulations using optimization algorithms to form the decision instructions.

[0031] As an optional embodiment of the present invention, a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, wherein the initial propagation simulation of the fracture is performed in step S2 or the advanced prediction based on the updated model is performed in step S4, is executed through the following numerical simulation steps:

[0032] Initial equilibrium solution: After applying true triaxial boundary conditions and initial injection conditions, a single-step steady-state or quasi-static solution is first performed to calculate the initial geostress distribution of the multi-scale coupled geomechanical model and to verify the numerical convergence to ensure computational stability.

[0033] Incremental loading solution: The fracturing process is simulated by incremental loading, gradually increasing the fluid pressure load; in each incremental solution step, the failure area, fracture tip stress intensity factor and fracture tip cracking angle of the multi-scale coupled geomechanical model are calculated and updated;

[0034] Crack propagation monitoring and calculation: Real-time monitoring and calculation of crack propagation path, length, width, and total volume change of the crack network.

[0035] This invention also provides a prediction system for the evolution path of ultra-large true triaxial hydraulic fracturing fractures, used to implement the prediction method described above. The system includes:

[0036] The multi-scale coupled modeling and simulation module is used to build, initialize, and run the multi-scale coupled geomechanical model.

[0037] The real-time data acquisition and communication module is used to receive and standardize various monitoring data from field sensors;

[0038] The data assimilation and parameter inversion module is used to execute data assimilation algorithms and dynamically optimize model parameters;

[0039] The real-time risk prediction and assessment module is used to perform advanced prediction of fracture propagation and quantitative risk assessment based on the updated multi-scale coupled geomechanical model.

[0040] The intelligent decision-making and instruction generation module is used to generate decision instructions that optimize fracturing construction parameters based on risk prediction and assessment results.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] This invention provides a method for predicting the evolution path of fractures in ultra-large true triaxial hydraulic fracturing. A multi-scale coupled geomechanical numerical model combines the mechanical properties of rocks at different scales, more realistically reflecting fracture propagation behavior in actual environments. Numerical simulation methods predict fracture propagation paths and cracking modes, thus providing guidance for hydraulic fracturing design. By predicting fracture propagation paths, cracking modes, and interactions between fractures, the design of hydraulic fracturing parameters, such as injection pressure and injection rate, can be optimized, thereby improving fracture permeability and optimizing the extraction of oil, gas, or geothermal resources. Real-time monitoring data feedback (such as stress, fracture morphology, and fracturing fluid flow) allows the model to be dynamically adjusted based on field conditions. The prediction of fracture propagation path is corrected based on actual conditions; this feedback mechanism can significantly improve the accuracy of fracture evolution prediction and reduce prediction errors. By accurately predicting the fracture propagation path and its interactions, the risk of uncontrolled fracture propagation can be effectively avoided. For example, it can prevent fractures from entering unwanted areas or affecting other wells, reducing negative environmental impacts. High-precision fracture propagation simulation and real-time monitoring data feedback can provide field operators with more scientific decision-making basis, ensuring the smooth progress of the hydraulic fracturing process and improving overall operational efficiency. Overall, the prediction of fracture evolution path can help to better understand and control the fracture propagation process, optimize resource extraction, reduce risks, and improve the economy and safety of operations. Attached Figure Description

[0043] Figure 1 A flowchart of a method for predicting the evolution path of fractures in ultra-large true triaxial hydraulic fracturing according to an embodiment of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0045] Therefore, the following detailed description of embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely illustrates some embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0046] It should be noted that, unless otherwise specified, the embodiments and features and technical solutions in the present invention can be combined with each other.

[0047] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0048] In the description of this invention, it should be noted that the terms "upper," "lower," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use, or the orientation or positional relationship commonly understood by those skilled in the art. These terms are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. In addition, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0049] See Figure 1 As shown, this embodiment of the invention provides a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, including:

[0050] Step S1: For the target reservoir, establish a multi-scale coupled geomechanical numerical model for cross-scale data interaction through a fluid-structure interaction framework. The model covers the microscale of rock materials, the macroscale of rock strata, and the flow scale of the wellbore and near-wellbore zone.

[0051] Step S2: Based on geological exploration, well logging and core test data, assign initialization parameters to the multi-scale coupled geomechanical model, set true triaxial boundary conditions, set fracturing fluid injection conditions in the multi-scale coupled geomechanical model, simulate the initial propagation of fractures, and predict the fracture initiation location, initial propagation path and morphology.

[0052] Step S3: During the actual fracturing operation, real-time monitoring data is collected. The monitoring data includes at least bottom hole pressure, wellhead discharge rate, microseismic events, downhole strain, or acoustic emission signals. The real-time monitoring data is input into a data assimilation algorithm and compared with the model prediction results of step S2 to dynamically invert and optimize the key uncertainty parameters in the model.

[0053] Step S4: Based on the optimized parameters in step S3, update the multi-scale coupled geomechanical model in real time; run the updated multi-scale coupled geomechanical model to make advanced predictions and obtain prediction results on the evolution path, propagation speed, fracture network complexity, and interaction with natural fractures and bedding interfaces in the future time period.

[0054] In this invention, "ultra-large" refers to a physical scale in which the simulation or construction far exceeds the conventional scale. This includes not only long fracture lengths (e.g., horizontal well sections exceeding 1500 meters), but more importantly, a large simulation range. It requires the model to cover a range from the near-wellbore area of ​​a single well to the distant reservoir, and may even involve an entire well group or block spanning square kilometers.

[0055] Traditional small-scale core experiments or local numerical models cannot reflect the stress shadowing effect, far-field interference between fractures, macroscopic manifestations of reservoir heterogeneity, and overall behavior of fluid loss and pressure transmission at such a large scale.

[0056] In this invention, "true triaxial" refers to the geostress state. It requires the model to apply and consider a complex three-dimensional stress field where the principal stresses in the three directions are unequal (σ1>σ2>σ3). This represents the true state of deep underground reservoirs. The difference from "pseudo-triaxial" or "plane strain" models is that "pseudo-triaxial" experiments or simplified models often assume σ2=σ3, or simplify it to a two-dimensional problem, which greatly simplifies the fracture propagation behavior.

[0057] Under true triaxial stress, crack propagation is no longer a simple planar problem. The crack surface tends to extend along the direction of the maximum principal stress, but is simultaneously constrained by the intermediate principal stress and the minimum principal stress, which may lead to extremely complex spatial morphologies such as crack torsion, non-planar bending, and multi-branch competition.

[0058] When the embodiments of this invention combine "ultra-large" with "true triaxial" dimensions, a series of complex challenges arise where 1+1>2, specifically including:

[0059] (1) The extreme complexity and unpredictability of crack morphology.

[0060] In large-scale true triaxial stress fields, cracks may no longer be single main cracks, but rather form complex three-dimensional crack networks affected by local stress variations and natural cracks. The difficulty of predicting their paths and morphologies increases exponentially.

[0061] (2) Macroscopic effects of multi-crack interference and stress shadow.

[0062] In ultra-large-scale fracturing (such as multi-stage and multi-cluster fracturing), a strong stress shadowing effect can occur between multiple fractures that are generated simultaneously or sequentially. This effect is amplified and complicated in a true triaxial background, which may cause subsequent fractures to change direction drastically, be inhibited, or propagate asymmetrically, directly affecting the overall fracturing volume.

[0063] (3) The computational model is contradictory to its massive nature and real-time nature.

[0064] Simulating large-scale fractures (due to numerous meshes) and characterizing complex fracture behavior under true triaxial conditions (due to model complexity and slow computation) presents a significant computational challenge. However, for real-time on-site decision-making, the model must provide predictions within an acceptable timeframe. This presents a contradiction that traditional methods struggle to resolve.

[0065] (4) The overall requirements of risk control.

[0066] On a large scale, if fractures get out of control, the consequences are more severe (such as connecting to distant water layers or disturbing adjacent wells). True triaxial conditions further make this runaway path more difficult to predict. Therefore, a method is needed that can proactively predict risks and guide interventions, rather than relying on post-hoc analysis.

[0067] Therefore, embodiments of the present invention provide a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures:

[0068] The contradiction between accuracy and efficiency in "ultra-large" projects is addressed by using a "multi-scale coupled geomechanical numerical model".

[0069] Microscopic models of rock materials capture local fracture mechanisms, while macroscopic rock strata-scale models grasp overall expansion. By coupling these models, key physical processes are not lost while ensuring a certain level of computational efficiency. This is the core idea behind solving large-scale computations.

[0070] The "true triaxial boundary conditions" and the "multi-scale coupled geomechanical model" directly address the mechanical complexity.

[0071] Clearly applying the boundary condition σ1≠σ2≠σ3 and using the multi-scale coupled geomechanical model that can simulate cracking along arbitrary three-dimensional paths is the technical basis for accurately simulating the complex morphology of cracks under true triaxial conditions.

[0072] The problem of inaccurate prediction and risk control is solved by using "real-time data feedback and dynamic optimization".

[0073] Faced with extremely high uncertainties in ultra-large true triaxial scenarios, the multi-scale coupled geomechanical model is continuously modified by real-time monitoring data (microseismic, pressure, etc.), making it "localized" and "real-time," thereby significantly improving prediction accuracy and enabling risk warning and parameter optimization guidance. This constitutes a leap from static analysis to dynamic control.

[0074] In summary, this invention provides a method for predicting the evolution path of fractures in ultra-large true triaxial hydraulic fracturing. The multi-scale coupled geomechanical numerical model combines the mechanical properties of rocks at different scales, more realistically reflecting the propagation behavior of fractures in actual environments. Numerical simulation methods predict fracture propagation paths and cracking modes, thus providing guidance for hydraulic fracturing design. By predicting fracture propagation paths, cracking modes, and the interactions between fractures, the design of hydraulic fracturing parameters, such as injection pressure and injection rate, can be optimized, thereby improving fracture permeability and optimizing the extraction of oil, gas, or geothermal resources. Real-time monitoring of data feedback (such as stress, fracture morphology, and fracturing fluid flow) allows the model to be dynamically adjusted. The predicted fracture propagation path is corrected based on the actual site conditions. This feedback mechanism can significantly improve the accuracy of fracture evolution prediction and reduce prediction errors. By accurately predicting the fracture propagation path and its interactions, the risk of uncontrolled fracture propagation can be effectively avoided. For example, it can prevent fractures from entering unwanted areas or affecting other wells, reducing negative environmental impacts. High-precision fracture propagation simulation and real-time monitoring data feedback can provide on-site operators with a more scientific basis for decision-making, ensuring the smooth progress of the hydraulic fracturing process and improving overall operational efficiency. Overall, the prediction of fracture evolution paths can help to better understand and control the fracture propagation process, optimize resource extraction, reduce risks, and improve the economy and safety of operations.

[0075] In the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures in this embodiment, the construction of a multi-scale coupled geomechanical model in step S1 includes: defining the research objectives and scale range, and determining the scale range to be covered, including mineral level, fracture level, pore level, and large-scale rock strata level.

[0076] Furthermore, the construction of the multi-scale coupled geomechanical model in step S1 of this embodiment includes: collecting rock mechanical properties, obtaining information such as mineral composition, microcracks, pore structure, and crystal structure, which can be obtained by scanning electron microscopy; obtaining information such as macroscopic deformation behavior, stress-strain relationship, and crack distribution of rocks through simulation experiments and field data; and obtaining the overall stress field, porosity, permeability, and other properties of the formation, which are then analyzed through geological exploration and drilling data.

[0077] Furthermore, the construction of the multi-scale coupled geomechanical model in step S1 of this embodiment includes:

[0078] Numerical simulation methods were used to simulate the deformation and fracture behavior of rocks at the microscale, obtain local material properties, and construct a microscale model of rock materials using the discrete element method to simulate the deformation of the rock matrix, microcrack initiation and interparticle interactions.

[0079] Based on experimental and field data, a macroscopic rock stratum scale model was constructed using the extended finite element method or the cohesive element method to simulate the initiation and three-dimensional propagation of hydraulic fractures.

[0080] Computational fluid dynamics or a one-dimensional pipe flow model are used to construct a flow scale model of the wellbore and near-wellbore zone to simulate the flow and pressure transmission of fracturing fluid in the wellbore and the opened fractures.

[0081] The microscale model of the rock material, the macroscale model of the rock strata, and the flow scale model of the wellbore and near-wellbore zone are dynamically coupled through a fluid-structure interaction calculation framework to realize the transmission of cross-scale mechanical and fluid information.

[0082] Specifically, in this embodiment, a multi-scale coupled geomechanical model is constructed, and an appropriate numerical simulation method is selected to solve problems at different scales. The finite element method (FEM) is used for simulation.

[0083] This embodiment verifies the constructed multi-scale coupled geomechanical model. The model is validated using rock mechanics experiments and field monitoring data. The consistency between simulation results and fracture propagation experimental results is compared. Real-time field monitoring data (such as stress, displacement, and fracture distribution) are used for comparison. Sensitivity analysis is performed on the model to examine the impact of different parameters on the model's prediction results, ensuring the model's stability and reliability under different conditions.

[0084] This embodiment presents a method for predicting the evolution path of fractures in ultra-large true triaxial hydraulic fracturing. Step S3 involves simulating fracture propagation. Step S2 involves constructing a multi-scale coupled geomechanical model to simulate fractures based on known rock mechanical properties. Utilizing the known physical and mechanical properties of the rock, as well as the characteristics of injection conditions, injection pressure, and injection fluid, the finite element method is used to simulate fracture propagation during hydraulic fracturing. The simulation simulates fracture initiation modes under different stress fields and pore structures, predicts parameters such as fracture propagation direction, fracture depth, and fracture width, and considers the mutual influence between multiple fractures, including common behavior, mutual interference, and merging phenomena.

[0085] In step S3 of this embodiment, during the actual fracturing process, the multi-scale coupled geomechanical model is dynamically updated through real-time monitoring of data such as stress, displacement, fracture morphology, and fracturing fluid flow. Based on feedback from on-site monitoring data, the model parameters are dynamically adjusted using an optimization algorithm (Bayesian optimization) to improve the accuracy of fracture propagation prediction.

[0086] In the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures in this embodiment, the data assimilation algorithm in step S3 is an ensemble Kalman filter or a particle filter algorithm; the key uncertainty parameters include at least one of the following: reservoir local in-situ stress field, spatial distribution of rock fracture toughness, opening pressure of natural fractures, and filtration coefficient.

[0087] In this embodiment of the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, step S3, which involves real-time acquisition and input of monitoring data, further includes: temperature and strain profile data along the wellbore obtained through distributed fiber optic sensing technology, and / or near-wellbore fracture imaging data obtained through downhole television or measurement-while-drilling tools. In this embodiment of the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, step S4 further includes: based on the prediction results of the advanced prediction, assessing the engineering risks of uncontrolled fracture height, asymmetric fracture network propagation, and communication with non-target layers or adjacent wells.

[0088] Specifically, the assessment of engineering risks includes:

[0089] Set a risk threshold and trigger a height runaway warning when the predicted crack propagation height exceeds the constraint range of the top or bottom boundary of the producing layer.

[0090] When the asymmetry of the predicted crack propagation path in the horizontal direction exceeds a preset ratio, an abnormal crack mesh morphology warning is triggered.

[0091] When the predicted fracture is less than the safe distance from the known adjacent well trajectory or water layer / gas cap, an early warning of inter-well interference or communication risk is triggered.

[0092] This embodiment of a method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures includes:

[0093] Step S5: Based on the assessment results of the engineering risks, generate optimization decision instructions;

[0094] The decision instructions include recommended schemes for adjusting fracturing operation parameters, which at least include displacement, sand ratio, slug combination, or temporary plugging strategy; the decision instructions are fed back to the on-site fracturing control system or operators to guide or automatically adjust the current and subsequent fracturing operations.

[0095] This embodiment visualizes the prediction results of step S4 in three dimensions, showing the path of fracture propagation, fracturing fluid flow, fracture interaction, and other behaviors. Combined with the prediction results of the multi-scale coupled geomechanical model, it provides decision support for on-site fracturing operations, optimizes fracturing design, reduces risks, and improves production efficiency.

[0096] Specifically, the instructions for generating optimization decisions include:

[0097] Based on the updated multi-scale coupled geomechanical model, multi-scenario simulations are performed, with different discharge rates, liquid viscosities, or temporary plugging schemes as input variables.

[0098] With the optimization objectives of maximizing the effective modification volume, minimizing engineering risks, or optimizing the complexity of the crack network, the optimal combination of construction parameters is selected from the results of multi-scenario simulations using optimization algorithms to form the decision instructions.

[0099] In this embodiment of the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures, step S2 involves simulating the initial propagation of the fracture, or step S4 involves making an advance prediction based on the updated model. This is performed through the following numerical simulation steps:

[0100] Initial equilibrium solution: After applying true triaxial boundary conditions and initial injection conditions, a single-step steady-state or quasi-static solution is first performed to calculate the initial geostress distribution of the multi-scale coupled geomechanical model and to verify the numerical convergence to ensure computational stability.

[0101] Incremental loading solution: The fracturing process is simulated by incremental loading, gradually increasing the fluid pressure load; in each incremental solution step, the failure area, fracture tip stress intensity factor and fracture tip cracking angle of the multi-scale coupled geomechanical model are calculated and updated;

[0102] Crack propagation monitoring and calculation: Real-time monitoring and calculation of crack propagation path, length, width, and total volume change of the crack network.

[0103] The above-described technical solution in this embodiment, through a structured numerical simulation process, produces the following significant technical effects when performing initial crack propagation simulation or advanced prediction:

[0104] (1) Ensure the physical authenticity and numerical stability of the simulation to lay a reliable foundation for prediction.

[0105] The "initial equilibrium solution" step prioritizes the calculation and stabilization of the model's initial geostress field after applying complex true triaxial boundary conditions. This process eliminates numerical oscillations or non-convergence caused by sudden loading of boundary conditions, ensuring that the entire simulation begins in a physically reasonable and numerically stable initial state. This is like laying a solid and flat "foundation" for subsequent dynamic simulations, fundamentally avoiding prediction biases caused by incorrect initial conditions, and is the primary guarantee for obtaining reliable results.

[0106] (2) To achieve a refined and mechanistic simulation of the dynamic propagation process of cracks.

[0107] The "incremental loading solution" step employs a progressive pressure loading method, accurately replicating the physical process of gradually increasing fluid pressure in actual fracturing. In each tiny incremental step, the model does not perform "black box" calculations, but explicitly calculates and tracks two core fracture mechanics parameters: the stress intensity factor (SIF) at the fracture tip and the fracture initiation angle. This ensures that each fracture extension has a clear mechanical criterion (such as the maximum circumferential stress criterion) as a basis, achieving a mechanistic mapping from "stress field" to "fracture behavior." This method can finely characterize the complex behaviors of fractures in heterogeneous stress fields, such as turning and bifurcation, significantly outperforming simulation methods based solely on preset paths or empirical formulas.

[0108] (3) Provide full-cycle, quantitative crack evolution data to support precise analysis and decision-making.

[0109] Through the "crack propagation monitoring and calculation" step, this solution can output and record in real time the continuous changes in crack propagation path, geometric dimensions (length and width), and network volume. This forms a complete spatiotemporal dataset of crack evolution. Its effect is that it not only provides the final morphology of the crack but also reveals its dynamic development process, speed, and patterns in a panoramic way. This provides engineers with extremely valuable and accurate data support for analyzing the timing of the interaction between cracks and natural cracks, assessing the formation stage of crack network complexity, and conducting subsequent quantitative analysis of the effects of construction parameters.

[0110] In summary, the combined effects of these technologies elevate numerical simulation from a static, result-oriented analytical tool into a dynamic, process-controllable, and mechanistically transparent "digital twin" experimental platform. This significantly enhances the accuracy, reliability, and practical value of prediction results, providing a solid and reliable core engine for subsequent model-based real-time risk warning and construction parameter optimization.

[0111] This embodiment also provides a prediction system for the evolution path of ultra-large true triaxial hydraulic fracturing fractures, used to implement the prediction method described above. The system includes:

[0112] The multi-scale coupled modeling and simulation module is used to build, initialize, and run the multi-scale coupled geomechanical model.

[0113] The real-time data acquisition and communication module is used to receive and standardize various monitoring data from field sensors;

[0114] The data assimilation and parameter inversion module is used to execute data assimilation algorithms and dynamically optimize model parameters;

[0115] The real-time risk prediction and assessment module is used to perform advanced prediction of fracture propagation and quantitative risk assessment based on the updated multi-scale coupled geomechanical model.

[0116] The intelligent decision-making and instruction generation module is used to generate decision instructions that optimize fracturing construction parameters based on risk prediction and assessment results.

[0117] Example 1

[0118] This embodiment presents a specific example of a method for predicting the fracture evolution path in ultra-large true triaxial hydraulic fracturing, using a case study of an ultra-large true triaxial hydraulic fracturing process. Key construction parameters are: injection pressure 45 MPa, injection rate 30 m³ / min, and fracturing fluid type: water-based fluid (containing chemical additives).

[0119] Step S1: Construct a multi-scale coupled geomechanical numerical model.

[0120] The modeling area was determined to be at the experimental core scale, and geological data of the target reservoir were imported, including: stratigraphic profiles based on drilling logging and seismic exploration data, and initial fracture distribution based on microseismic monitoring and CT scan data.

[0121] Based on the geological data, a geometric model was created using 3D modeling software and then imported into finite element analysis software.

[0122] The geometric model is divided using a hexahedral mesh. Local mesh refinement is performed in the preset potential crack propagation area to accurately calculate the stress concentration at the crack tip and to check the mesh quality.

[0123] Constructing a multi-scale coupled geomechanical numerical model:

[0124] Microscale model of rock materials: constructed using the discrete element method to simulate the interaction between rock particles and microcracks.

[0125] Macroscopic rock strata scale model: Constructed using a cohesive element model, with key rock mechanics parameters input: elastic modulus, Poisson's ratio, tensile strength, compressive strength, and fracture toughness.

[0126] Flow scale model in wellbore and near-wellbore zone: A one-dimensional pipe flow model is used for construction, with key input parameters: permeability, porosity, and fracturing fluid viscosity.

[0127] By dynamically coupling the three scale models mentioned above through a fluid-structure interaction computational framework, cross-scale transfer of mechanical and fluid information can be achieved.

[0128] Step S2: Model initialization and initial crack propagation simulation.

[0129] Model initialization: Parameters are assigned to the multi-scale coupled geomechanical model. The fracturing fluid injection pressure is set to 45 MPa, and the injection rate to 30 m³ / min. Based on drilling data, true triaxial boundary conditions are applied: maximum horizontal principal stress σ1 = 60 MPa, intermediate principal stress σ2 = 40 MPa, and minimum horizontal principal stress σ3 = 20 MPa. Horizontal stress is applied to constrain the wellbore boundary and to the far-field formation.

[0130] Initial crack propagation simulation: Run the model to simulate the initial crack propagation, which is performed through the following numerical simulation steps:

[0131] Initial equilibrium solution: Perform a single-step steady-state solution to calculate the equilibrium state of the model under the initial geostress field, ensuring numerical convergence and stability.

[0132] Incremental loading solution: An incremental loading method is used to gradually increase the fluid pressure load to simulate the fracturing process. In each incremental step, the changes in the failure region, the stress intensity factor at the crack tip, and the crack initiation angle are calculated.

[0133] Crack propagation monitoring and calculation: Real-time monitoring and calculation of crack propagation path, length, width and morphological changes.

[0134] This simulation predicted the crack initiation location, initial propagation direction, and early crack morphology.

[0135] Step S3: Real-time data assimilation and dynamic model update (simulation demonstration).

[0136] This embodiment demonstrates the process of assimilating real-time data. It assumes that microseismic events and bottom-hole pressure data are monitored in real-time during actual construction. An ensemble Kalman filter algorithm is used to compare and analyze this real-time monitoring data with the model prediction results from step S2, dynamically inverting and optimizing the local fracture toughness parameters of the reservoir.

[0137] Step S4: Model update and advance prediction.

[0138] Update the optimized parameters from step S3 into the model.

[0139] The updated model was run to make advanced predictions. Simulation results show that under continuous injection conditions, the cracks will predominantly propagate along the direction of maximum principal stress, while interacting with pre-defined natural cracks to form a complex crack network. The predictions yielded the crack propagation rate, crack network complexity, and final modification volume over future time periods.

[0140] Risk prediction: Based on the prediction results, the assessment shows that the fracture extension height is within the producing layer range and has not triggered a height runaway warning; the fracture morphology is basically symmetrical and has not triggered a morphological anomaly warning; the distance to the adjacent well is greater than the safe distance and has not triggered an inter-well interference warning.

[0141] Verification and Results: The final simulated crack morphology of this embodiment was compared with CT scan experimental data under the same conditions. The error was within the allowable range, verifying the accuracy of the prediction by this method.

[0142] Example 2

[0143] This embodiment presents a specific example of applying the method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures under another set of geological and construction parameters (lower stress, higher discharge rate) to demonstrate its universality. Key parameters: injection pressure 20 MPa, injection rate 60 m³ / min, fracturing fluid type is low viscosity water-based fluid.

[0144] Step S1: Construct a multi-scale coupled geomechanical numerical model.

[0145] The modeling process is the same as in Example 1, except that the geological data comes from a different target reservoir.

[0146] Step S2: Model initialization and initial crack propagation simulation.

[0147] Model initialization: The fracturing fluid injection pressure was set to 20 MPa, and the injection rate to 60 m³ / min. The applied true triaxial stress field was: σ1 = 30 MPa, σ2 = 25 MPa, σ3 = 15 MPa. Rock mechanics parameters and flow parameters were set based on new reservoir data.

[0148] Simulation of initial crack propagation: The same numerical simulation steps as in Example 1 (initial equilibrium solution, incremental loading solution, crack propagation monitoring and calculation) were used for simulation. The prediction showed that under lower geostress and higher displacement, cracks initiated earlier, and the initial propagation morphology exhibited a more obvious multi-branching trend.

[0149] Steps S3 / S4, data assimilation and advance prediction (simulation demonstration).

[0150] The real-time data assimilation process was simulated, and the filtration coefficient of natural fractures was optimized using simulated wellhead displacement and downhole strain data via a particle filter algorithm. The updated model was then used for forward prediction. Results show that high displacement promotes rapid fracture network formation, but also increases the risk of fracture deflection at weak interfaces. The predictions successfully predicted the tendency for fractures to extend significantly at a specific bedding interface.

[0151] Comparison and explanation: Example 2 shows that even under conditions of low ground stress and large differences in construction parameters, the present invention can still achieve accurate prediction of crack evolution path and risk warning through the same multi-scale coupled model framework and real-time data assimilation process, verifying the robustness and wide applicability of the method of the present invention.

[0152] The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described herein. Although the present invention has been described in detail with reference to the above embodiments, the present invention is not limited to the specific embodiments described above. Therefore, any modifications or equivalent substitutions to the present invention, as well as all technical solutions and improvements that do not depart from the spirit and scope of the invention, are covered within the scope of the claims of the present invention.

Claims

1. A method for predicting the evolution path of fractures in ultra-large true triaxial hydraulic fracturing operations, characterized in that, include: Step S1: For the target reservoir, establish a multi-scale coupled geomechanical numerical model for cross-scale data interaction using a fluid-structure interaction framework. This model encompasses the microscale of rock materials, the macroscale of rock strata, and the flow scale of the wellbore and near-wellbore zone. The multi-scale coupled geomechanical model includes: constructing a microscale model of rock materials using the discrete element method to simulate the deformation of the rock matrix, microcrack initiation, and interparticle interactions; constructing a macroscale model of rock strata using the extended finite element method or cohesive element method to simulate the initiation and three-dimensional propagation of hydraulic fractures; constructing a flow scale model of the wellbore and near-wellbore zone using computational fluid dynamics or a one-dimensional pipe flow model to simulate the flow and pressure transmission of fracturing fluid in the wellbore and existing fractures; and dynamically coupling the microscale rock material model, the macroscale rock strata model, and the flow scale model of the wellbore and near-wellbore zone through the fluid-structure interaction computational framework to achieve cross-scale mechanical and fluid information transmission. Step S2: Based on geological exploration, well logging and core test data, assign initialization parameters to the multi-scale coupled geomechanical model, set true triaxial boundary conditions, set fracturing fluid injection conditions in the multi-scale coupled geomechanical model, simulate the initial propagation of fractures, and predict the fracture initiation location, initial propagation path and morphology. Step S3: During the actual fracturing operation, real-time monitoring data is collected. The monitoring data includes at least bottom hole pressure, wellhead discharge rate, microseismic events, downhole strain, or acoustic emission signals. The real-time collected monitoring data is input into a data assimilation algorithm and compared with the model prediction results of step S2 to dynamically invert and optimize the key uncertainty parameters in the model. Step S4: Based on the optimized parameters in step S3, update the multi-scale coupled geomechanical model in real time; run the updated multi-scale coupled geomechanical model to make advanced predictions and obtain prediction results on the evolution path, propagation speed, fracture network complexity, and interaction with natural fractures and bedding interfaces in the future time period.

2. The method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures according to claim 1, characterized in that, The data assimilation algorithm in step S3 is either an ensemble Kalman filter or a particle filter algorithm; the key uncertainty parameters include at least one of the following: local reservoir stress field, spatial distribution of rock fracture toughness, opening pressure of natural fractures, and filtration coefficient.

3. The method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures according to claim 1, characterized in that, The real-time acquisition and input of monitoring data in step S3 also includes: temperature and strain profile data along the wellbore obtained through distributed fiber optic sensing technology, and / or near-wellbore fracture imaging data obtained through downhole television or measurement-while-drilling tools.

4. The method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures according to claim 1, characterized in that, Step S4 further includes: assessing the engineering risks of uncontrolled fracture height, asymmetric fracture network expansion, and communication between non-target layers or adjacent wells based on the prediction results of the advanced prediction.

5. The method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures according to claim 4, characterized in that, Assessing project risks includes: Set a risk threshold and trigger a height runaway warning when the predicted crack propagation height exceeds the constraint range of the top or bottom boundary of the producing layer. When the asymmetry of the predicted crack propagation path in the horizontal direction exceeds a preset ratio, an abnormal crack mesh morphology warning is triggered. When the predicted fracture is less than the safe distance from the known adjacent well trajectory or water layer / gas cap, an early warning of inter-well interference or communication risk is triggered.

6. The method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures according to claim 4, characterized in that, include: Step S5: Based on the assessment results of the engineering risks, generate optimization decision instructions; The decision instructions include recommended schemes for adjusting fracturing operation parameters, which include at least displacement, sand ratio, slug combination, or temporary plugging strategy; the decision instructions are fed back to the on-site fracturing control system or operators to guide or automatically adjust the current and subsequent fracturing operations.

7. The method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures according to claim 6, characterized in that, The generated optimization decision instructions include: Based on the updated multi-scale coupled geomechanical model, multi-scenario simulations are performed, with different discharge rates, liquid viscosities, or temporary plugging schemes as input variables. With the optimization objectives of maximizing the effective modification volume, minimizing engineering risks, or optimizing the complexity of the crack network, the optimal combination of construction parameters is selected from the results of multi-scenario simulations using optimization algorithms to form the decision instructions.

8. The method for predicting the evolution path of ultra-large true triaxial hydraulic fracturing fractures according to claim 1, characterized in that, The initial crack propagation simulation in step S2 or the advanced prediction based on the updated model in step S4 is performed through the following numerical simulation steps: Initial equilibrium solution: After applying true triaxial boundary conditions and initial injection conditions, a single-step steady-state or quasi-static solution is first performed to calculate the initial geostress distribution of the multi-scale coupled geomechanical model and to verify the numerical convergence to ensure computational stability. Incremental loading solution: The fracturing process is simulated by incremental loading, gradually increasing the fluid pressure load; in each incremental solution step, the failure area, fracture tip stress intensity factor and fracture tip cracking angle of the multi-scale coupled geomechanical model are calculated and updated; Crack propagation monitoring and calculation: Real-time monitoring and calculation of crack propagation path, length, width, and total volume change of the crack network.

9. A prediction system for the evolution path of fractures in ultra-large true triaxial hydraulic fracturing, characterized in that, The system for implementing the prediction method according to any one of claims 1-8 comprises: The multi-scale coupled modeling and simulation module is used to build, initialize, and run the multi-scale coupled geomechanical model. The real-time data acquisition and communication module is used to receive and standardize various monitoring data from field sensors; The data assimilation and parameter inversion module is used to execute data assimilation algorithms and dynamically optimize model parameters; The real-time risk prediction and assessment module is used to perform advanced prediction of fracture propagation and quantitative risk assessment based on the updated multi-scale coupled geomechanical model. The intelligent decision-making and instruction generation module is used to generate decision instructions that optimize fracturing construction parameters based on risk prediction and assessment results.

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