Day 2 Wed, March 29, 2023最新文献

{"title":"Integrating Geomechanics Studies to Shale and Tight Phased Development - Application to Delaware Basin","authors":"O. Khebzegga, Yu-guo Chen, A. Rey, Bin Wang","doi":"10.2118/212224-ms","DOIUrl":"https://doi.org/10.2118/212224-ms","url":null,"abstract":"\u0000 Parent and child wells interference is a major concern in the development of shale and tight reservoirs. Oil and gas operators typically aim to prevent fractures interference during the child well’s stimulation, which connects the parent and child well’s fracture networks. Another aspect of the parent-child well interference lies in the impact of parent-well depletion on child-well stimulation, often leading to the underperformance of child-well production. For these circumstances, reservoir simulation that combines flow and geomechanics is required to predict child-well fractures growth. To achieve this goal, a new workflow combining flow (EDFM), geomechanics (single porosity) and fracturing was developed to predict the reservoir stress change, the growth of the child-well fractures, and the production of the parent and child wells. As one of the applications, this tool was applied to a Delaware basin reservoir and enabled the asset team to better design the pad for the child wells. Multiple scenarios were analyzed for eight child wells located between two parent wells. Using this tool, we were able to predict the asymmetric growth of the fractures in the direction of the parent wells for child wells that were close enough to their parent wells. The impact of this fractures’ asymmetric growth on the production of the child wells was also quantified, based on which a better configuration of child wells was recommended to mitigate the depletion effect of parent wells.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123271920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of Look-Ahead Reservoir Models to Optimize Reservoir Performance.","authors":"P. Crumpton, M. Cancelliere","doi":"10.2118/212259-ms","DOIUrl":"https://doi.org/10.2118/212259-ms","url":null,"abstract":"\u0000 The objective is to use future simulated well behavior to optimize well management within a complex reservoir simulation model. This can be used to increase simulated plateau life and reserves. Traditional well management systems often rely on instantaneous well potential to choose guide rates to determine the well allocation within a group of wells. This has proved to be a very effective strategy. However, for the problem of plateau optimization, one can observe the high instantaneous potential of many wells after the plateau is exhausted; this is because the traditional well management system has no knowledge of future behavior.\u0000 In this work, the future behavior of all the wells and groups with a large and complex giant reservoir simulation model is determined by spawning a coarsened \"Look-Ahead model\" (LAM). This is performed concurrently, while the main model is still running. After a pre-determined simulation time the LAM model is harvested by the main model, and approximate future behavior is integrated into the well management system of the main model. One simple yet effective technique is to evaluate the current potential of the well to be an average of the current instantaneous potential and the future potential, in, for example, 10 years ahead of the current simulations time. Thus wells whose future performance is inhibited because of high GOR or high water cuts will get there current allocation reduced, and wells with future high potential will get allocated more rate.\u0000 The use of LAM models is demonstrated in a water flood problem to increase plateau time of a large and complex reservoir model. The LAM model is automatically constructed by collapsing the grid, maintaining some resolution of the current wells and future wells, and coarsening heavily the areas of the grid with spent wells. By doing so a 10x improvement in elapse time of the LAM model, which enables the frequent spawning of LAM models from the main model, and a subsequently the most up-to-date LAM model is integrated into the main well management system.\u0000 The use of LAM to approximate future behavior of wells, and integrated this behavior into the well management of the reservoir simulator is a novel and practical approach to further optimize the well management system of a reservoir simulator.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130957552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Global-Convergent Newton Optimization Algorithm for the Phase Behavior Calculations with Capillary Pressure Effect for Tight Reservoir Fluids","authors":"Hongbin Jing, Jianqiao Liu, Huanquan Pan, Tie Kuang, Z. Yin, Bensheng Li","doi":"10.2118/212176-ms","DOIUrl":"https://doi.org/10.2118/212176-ms","url":null,"abstract":"\u0000 The thermodynamic behavior of a fluid in a tight reservoir differs from that in the conventional environment. A new phase equilibrium algorithm with capillary pressure is presented and formulated using the laws of thermodynamics. At a given temperature, volume, and moles with capillary pressure, this new algorithm is based on the Newton iteration and line search, which guarantees a global convergence. We obtain the Newton direction by utilizing the modified Cholesky factorization to ensure a descending direction and combine line search to facilitate the iterations in the feasible domain. The initial values of the new algorithm originate from Michelsen's two-sided method. All relevant derivatives are computed analytically and automatically through the Automatically Differentiable Expression Templates Library (ADETL), developed at Stanford University. The new algorithm is based on the Helmholtz free energy, and the corresponding energy surface will not be influenced by the pressure inequality between the liquid and vapor phases. We tested our algorithm on several fluids with different pore radii over a wide range of temperatures and total volumes, and no single calculation breakdown occurred. Meanwhile, the new algorithm can also determine the system phase status at a given temperature and pressure. We compared the results between the given temperature and volume and the given temperature and pressure. There is a dispute in effect of the derivatives of capillary pressure with respect to compositions on the phase equilibrium calculation in literature. We compared the results with and without the derivatives at a given temperature and volume and a given temperature and pressure. These results show that our new algorithm exhibits a good convergent performance and a robust solution even if the pore radius decreases to one nanometer, which indicates the potential of our algorithm for simulating the shale reservoir production process.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133650405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constrained Pressure Residual Preconditioner Including Wells for Reservoir Simulation","authors":"H. Nilsen, E. Ahmed, A. Rasmussen, K. Bao, T. Skille","doi":"10.2118/212172-ms","DOIUrl":"https://doi.org/10.2118/212172-ms","url":null,"abstract":"\u0000 We present a new practical constrained pressure residual (CPR) preconditioner including well degrees of freedom (DOFs).\u0000 The action of the new CPR preconditioner applies only to the reservoir DOFs of the linear system, and includes well-reservoir coupling by solving an extended linear system for the pressure. This extended pressure system is similar to the one proposed in Zhou et al. (Comp. geosci 17(2), 2013). The preconditioner is suitable for a linear system which only includes reservoir DOFs as unknowns and where the effect of the wells is included by Schur complement in the linear operator, without explicit fill-in in the matrix.\u0000 The main feature is that the pressure system is extended to include well DOFs. The full preconditioner then combines block ILU0 on the reservoir matrix as fine smoother with the new extended pressure CPR system, using standard AMG cycles on the latter. The new preconditioner has been implemented in the open-source reservoir simulator OPM Flow. The approach is compared with several different CPR approaches on conceptual and real-field cases including open benchmark cases, looking at accuracy, tolerances, performance and parallel scalability.\u0000 Compared to applying CPR to the reservoir matrix without well fill-in, the new method yields lower linear iteration counts, similar to those that result from applying CPR to the reservoir matrix with well fill-in (explicit Schur complement). However, each iteration is less costly since one avoids the fill-in, which adds k2 extra nonzero matrix elements for a well with k perforations.\u0000 An advantage of the approach is that the structural complexity introduced with the well system is included only in the scalar CPR pressure system in a way suitable for algebraic multigrid (AMG) preconditioning. All other complexity of the wells is handled in the linear operators used in the Krylov solvers.\u0000 The new method can be implemented in reservoir simulators by building on existing preconditioner components, and can improve simulation times for complex cases, in particular those with many wells and perforations.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114494788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling Fault Reactivation Triggered by Fluid Injection","authors":"D. Tran, V. Shrivastava, L. Nghiem","doi":"10.2118/212189-ms","DOIUrl":"https://doi.org/10.2118/212189-ms","url":null,"abstract":"\u0000 With increased focus on CO2 storage, hydraulic fracturing, and steam injection operations in recent years, understanding of fluid induced seismicity has drawn a lot of attention amongst researchers and practicing engineers. Reactivation of existing dormant faults due to injection operations can lead to flow through or along the fault from the reservoir to undesirable zones. It poses a serious challenge that requires careful study so that measures could be taken to avoid such occurrence.\u0000 In this paper, a method is presented where geomechanical response is used to compute the slip tendency when the stress changes in a reservoir due to fluid injection. The slip tendency is considered as the main variable to determine whether the fault is reactivated or not. It is computed based on the effective stress normal to the fault surface, and the tangential stress. When the effective stress on a fault surface is reduced due to the increase of pore pressure in grid-blocks adjacent to the fault, it can potentially make the slip tendency exceed the critical limit. In such a case, the transmissibility of grid-blocks on both sides of the fault are increased to allow the fluid to flow into the fault and subsequently along the fault. When the fluid leaks from the reservoir to another zone through the fault, the effective stress on grid-blocks adjacent to the fault increases as the pore pressures in those grid-blocks decrease. This will in turn reduce the slip tendency. Therefore, the transmissibility in this case will also decrease to a value smaller than the one when the fault reactivated.\u0000 The algorithm allows the fault to be reactivated or deactivated to cope with the pressure change in the reservoir. The slip displacement at the fault is also estimated. The method is implemented in a multidimensional, multiphase flow simulator to demonstrate the advantages of using geomechanics for predicting fault reactivation, which can lead to leakage of fluids from the reservoir to other zones or to the surface. Three examples, two synthetic and one field, are presented to illustrate application of the procedure.\u0000 The proposed method of fault reactivation modeling is suitable for implementing in any fluid flow simulator with geomechanics capability. It is intended for studying and designing of safe injection strategies that avoid undesirable fault reactivation.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123471575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bridging Computational Stratigraphy and Reservoir Simulation for Geologically Realistic High-Resolution Reservoir Modeling","authors":"Boxiao Li, Lewis Li, X. Wen, T. Sun","doi":"10.2118/212244-ms","DOIUrl":"https://doi.org/10.2118/212244-ms","url":null,"abstract":"\u0000 Computational Stratigraphy (CompStrat) is a state-of-the-art earth-modeling method that captures the key heterogeneities in subsurface reservoirs through modeling of the detailed flow and sediment transportation processes in various depositional environments. The method is fully based on physics and generates high-resolution 3D earth models that are much more geologically realistic than those generated by traditional earth-modeling methods. It can accurately predict and preserve those spatially continuous but vertically thin and volumetrically insignificant layers, such as shale layers, thus enabling a much more accurate representation of natural reservoir connectivity.\u0000 In the past few years, CompStrat has been studied mainly within the earth science community and has yet been broadly applied in reservoir simulation research and practices. Our objective is to bridge this gap and allow this frontier technology to offer geologically realistic earth models for reservoir simulation to better understand how various geological features contribute and control subsurface flow patterns and performance, and subsequently leading to a better integration among earth modeling, flow simulation, and more reliable reservoir performance predictions.\u0000 CompStrat models often have large number of cells (hundreds of millions or more). A large proportion of them are related to thin shale layers. These thin cells can often cause convergence difficulties in reservoir simulations. We developed a grid coarsening method to drastically reduce the cell number and the simulation time with minimum altering of overall model connectivity characteristics. The method reduces the cell number by 85% to 93% and the simulation time by 94% to 99.4% with limited loss of accuracy for representative examples. Without this method, the simulation may take impractically long time to run for large models with complex multiphase flow dynamics.\u0000 The successful removal of the computational bottleneck enables the application of this frontier earth-modeling method in high-fidelity reservoir simulation. It also facilitates detailed understanding of the connection between geology and flow to offer valuable insight for reservoir modeling, production forecast uncertainty analysis, and history matching. We developed a method to label, evaluate, and rank geological features based on their influence on flow performance, with shale layers being the specific focus. The labeling is performed semi-automatically and the evaluation and ranking is done efficiently with a reduced-physics solver. The result is statistically consistent across multiple realizations.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121824617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Learning to Solve Parameterized Single-Cell Problems Offline to Expedite Reservoir Simulation","authors":"Abdul-Akeem Olawoyin, R. Younis","doi":"10.2118/212175-ms","DOIUrl":"https://doi.org/10.2118/212175-ms","url":null,"abstract":"\u0000 The reservoir simulation system of residual equations is composed by applying a single parameterized nonlinear function to each cell in a mesh. This function depends on the unknown state variables in that cell as well as on those in the neighboring cells. Anecdotally, the solution of these systems relies on both the level of nonlinearity of this single-cell function as well as on how tightly the cell equations are coupled. This work reformulates this system of equations in an equivalent that is only mildly nonlinear. In an amortized offline regression stage, the single-cell equation is solved over a sampling of possible neighboring states and parameters. A neural network is regressed to this data. An equivalent residual system is formed by replacing the single-cell residual function with the neural network, and we propose three alternative algorithms to solve these preconditioned systems. The first method applies a Picard iteration that does not require Jacobian matrix evaluations or linear solution. The second applies a modified Seidel iteration that additionally infers locality automatically. The third algorithm applies Newton's method to the preconditioned system. The solvers are applied to a one-dimensional incompressible two-phase displacement problem with capillarity and a general two-dimensional two-phase flow model. We investigate the impacts of neural network regression accuracy on the performance of all methods. Reported performance metrics include the number of residual/network evaluations, linear solution iterations, and scalability with time step size. In all cases, the proposed methods significantly improve computational performance relative to the use of standard Newton-based solution methods.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123769447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strongly Coupled Prolongation in Multiscale Pressure Solver for High-Contrast Heterogeneous Reservoir Simulation","authors":"Shingo Watanabe, J. Natvig, P. Tomin","doi":"10.2118/212229-ms","DOIUrl":"https://doi.org/10.2118/212229-ms","url":null,"abstract":"\u0000 The key idea with multiscale methods for reservoir simulation is to construct a set of prolongation operators that interpolate solutions from a coarse spatial resolution to the grid resolution. Efficient multiscale methods need prolongation operators that accurately represent flow at the grid resolution. For high-contrast models, it is especially important that this flow interpolation is confined within high-contrast boundaries. In this paper, we present an improved algorithm to construct multiscale prolongation operators that better capture strong contrasts in geological properties. Specifically, to construct effective prolongation operators, the improved algorithm first finds dominant flow directions by comparing the values of connection transmissibility in a neighborhood, then emphasizes the interpolation along these dominant directions and ignores the interpolation in transverse direction if connection transmissibility is weak.\u0000 The new algorithm is implemented in a commercial reservoir simulator that also provides a commercial implementation of a state-of-the-art multiscale method. The advantage of the new algorithm is demonstrated using synthetic and real reservoir models with high-contrast features. We also analyze the interpolation errors of poorly constructed prolongation operators for such models to identify the root cause of the slow linear solver convergence rate. With the new algorithm, we obtain better linear and nonlinear convergence rates in the pressure solver and shorter simulation time than with a previously published state-of-the-art multiscale method.\u0000 For completeness, we also benchmark our multiscale pressure solver performance against a standard algebraic multigrid (AMG) fine-scale pressure solver, and we highlight differences in linear solver convergence and computational efficiency. Finally, we demonstrate that the new algorithm is beneficial for a real high-contrast heterogeneous field model.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134054097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating Pipe Fractional Flow Theory with Fully Compositional Wellbore Models","authors":"Shuang Zheng, M. Sharma","doi":"10.2118/212226-ms","DOIUrl":"https://doi.org/10.2118/212226-ms","url":null,"abstract":"\u0000 Multi-phase compositional wellbore flow is important in determining the flow and pressure drop in oil, gas, and geothermal wells. These effects become increasingly important in long laterals with multiple locations for fluid influx. Complex hydrocarbon phase behavior such as change in the number of phases, phase flipping, gas slippage can happen in the wellbore because of changes in pressure, temperature and inflow fluid rate and composition along the wellbore. This paper introduces a new wellbore model which integrates fully compositional fluid flow with an energy balance and pipe fractional-flow theory with multiple points of fluid entry along the wellbore.\u0000 Four sets of governing equations: component mass conservation, momentum conservation (pipe fractional flow theory), composition conservation and energy balance are solved fully implicitly along the wellbore. This is then fully implicitly coupled with the flow and energy balance equations in the reservoir and fracture domains. The primary unknowns along the wellbore (total flow rate, hydrocarbon component composition, water saturation, pressure, and temperature) can then be obtained. Flash calculations are used to calculate the hydrocarbon phase saturation, density, viscosity, etc. and the flow rate of each phase is obtained from the fractional flow theory given the local flow rate and saturations.\u0000 In the first case, we study the reservoir-wellbore flow in a gas condensate reservoir with 16 hydrocarbon components. As the pressure drops, an oil phase drops out of the single phase gas condensate, first in the wellbore and then in the reservoir. In a second case, we simulate CO2 flooding in a black-oil reservoir. Reservoir cooling is observed near the injection wellbore and an increased CO2 composition is observed in the produced oil from the production wellbore. In the third case, we study a low permeability volatile oil reservoir with 14 hydrocarbon components. Production from a hydraulically fractured horizontal wellbore is simulated considering the reservoir-fracture-wellbore flow. We observe that as the pressure drops in the wellbore, gas is liberated from the oil phase and this changes the wellbore pressure drop considerably. The lighter component compositions decrease with time while the heavier component compositions increase with time because of the liquid holdup effect. In the fourth case, we showcase a stand-alone wellbore model integrated with point sources.\u0000 This paper fully integrates a pipe-fractional flow formulation with compositional wellbore flow, and an energy balance for the first time. This allows the model to be used directly with compositional reservoir simulators. The wellbore mesh is automatically generated and coupled with the reservoir/fracture mesh to allow for an integrated and seamless simulation from the reservoir to the surface facility. This model allows engineers to accurately account for the pressure drop and phase behavior within the wellbore when simulat","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134639291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Sequentially Coupled THM Model for Fractured Enhanced Geothermal Systems using XFEM and Hybrid EDFM and MINC Models","authors":"Xiangyu Yu, Xia Yan, Cong Wang, Shihao Wang, Yushu Wu","doi":"10.2118/212241-ms","DOIUrl":"https://doi.org/10.2118/212241-ms","url":null,"abstract":"\u0000 The long-term fluid circulation of Enhanced Geothermal Systems (EGS) involves complex coupled Thermal-Hydrological-Mechanical (THM) processes dominated by hydraulic and induced natural fractures. The hydraulic fracture of arbitrary shape in response to pressure changes and thermal strains can be handled by the three-dimensional (3D) eXtended Finite Element Method (XFEM). The induced/natural fractures are incorporated into the model and treated as one continuum of the Multiple INteracting Continua (MINC) for the investigation of their impacts. A TOUGH-code-based program, TOUGH2-EGS, is utilized to simulate the Thermal-Hydrological processes. The 3D Embedded Discrete Fracture Method (EDFM), compatible with the 3D XFEM, is adopted to model the hydraulic fracture. TOUGH2-EGS is then coupled with an XFEM simulator by the sequentially coupled fixed-stress split approach. The convergence performance of this coupling scheme is firstly analyzed by introducing the fracture stiffness coefficient into a single-fracture model. Sensitivity analyses are performed for this model in terms of injection temperature and thermal expansivity. The hybrid EDFM and MINC model is established and analyzed for an EGS with both hydraulic and induced/natural fractures. The convergence performance of the single-fracture model shows that an appropriate stiffness coefficient is essential for this model and different choices of the coefficient value result in distinct performances. The sensitivity analyses for injection temperatures and thermal expansivity are conducted by comparing effective stresses, pressure, temperature, and porosity/permeability distributions, as well as dynamic production temperature, outflow rate, and injection fracture permeability. The results illustrate that the fracture aperture is opened by the cold fluid injection and the reservoir is dominated by the thermal stress/strain. The temperature and pressure distribution are both affected by the thermal-hydrological-mechanical processes through the dynamic porosity, permeability, stress/strain, and fluid viscosity. The thermal breakthrough curves reflect that the conduction contributes the most to heating the fluid while the outflow rates demonstrate the mass loss due to the porosity/permeability altered by thermo-poro-elasticity. In the hybrid model, the enhancement of the natural fracture permeability notably delays the thermal breakthrough by allowing injected fluid to contact more hot reservoirs. Natural fracture spacing, MINC partition numbers are also varied to investigate their influence on the production behavior: the increased spacing delays the thermal breakthrough and needs more MINC partitions for modeling accuracy. Traditional coupled THM models are only applicable under the assumption of infinitesimal strains which does not hold in hydraulically fractured EGS reservoirs. The introduction of fracture stiffness stabilizes the numerical solution. The combined 3D XFEM and EDFM is capable of han","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125874272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}