Day 1 Tue, October 26, 2021最新文献

{"title":"History Matching Complex 3D Systems Using Deep-Learning-Based Surrogate Flow Modeling and CNN-PCA Geological Parameterization","authors":"Meng Tang, Yimin Liu, L. Durlofsky","doi":"10.2118/203924-ms","DOIUrl":"https://doi.org/10.2118/203924-ms","url":null,"abstract":"\u0000 The use of deep-learning-based procedures for geological parameterization and fast surrogate flow modeling may enable the application of rigorous history matching algorithms that were previously considered impractical. In this study we incorporate such methods – specifically a geological parameterization that entails principal component analysis combined with a convolutional neural network (CNN-PCA) and a flow surrogate that uses a recurrent residual-U-Net procedure – into three different history matching procedures. The history matching algorithms considered are rejection sampling (RS), randomized maximum likelihood with mesh adaptive direct search optimization (MADS-RML), and ensemble smoother with multiple data assimilation (ES-MDA). RS is a rigorous sampler used here to provide reference results (though it can become intractable in cases with large amounts of observed data). History matching is performed for a channelized geomodel defined on a grid containing 128,000 cells. The CNN-PCA representation of geological realizations involves 400 parameters, and these are the variables determined through history matching. All flow evaluations (after training) are performed using the recurrent residual-U-Net surrogate model. Two cases, involving different amounts of historical data, are considered. We show that both MADS-RML and ES-MDA provide history matching results in general agreement with those from RS. MADS-RML is more accurate, however, and ES-MDA can display significant error in some quantities. ES-MDA requires many fewer function evaluations than MADS-RML, however, so there is a tradeoff between computational demand and accuracy. The framework developed here could be used to evaluate and tune a range of history matching procedures beyond those considered in this work.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83482068","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":"INSIM-FPT-3D: A Data-Driven Model for History Matching, Water-Breakthrough Prediction and Well-Connectivity Characterization in Three-Dimensional Reservoirs","authors":"Hui Zhao, Wei Liu, Xiang Rao, Guanglong Sheng, H. Li, Zhenyu Guo, Deng Liu, Lin Cao","doi":"10.2118/203931-ms","DOIUrl":"https://doi.org/10.2118/203931-ms","url":null,"abstract":"\u0000 The data-driven interwell simulation model (INSIM) has been recognized as an effective tool for history matching and interwell-connectivity characterization of waterflooding reservoirs. INSIM-FT-3D (FT: front tracking) was recently developed to upgrade the applicationdimension of INSIM series data-driven models from two-dimensional (2D) to three-dimensional (3D). However, INSIM-FT-3D cannot accurately infer the dynamic change of well-connectivity and predict well's bottom-hole pressure (BHP). The main purpose of this study intends to expand the capability of INSIM-FT-3D to empower for the assimilation of BHPs, the reliable prediction of water breakthrough and the characterization of dynamic interwell-connectivities.\u0000 The default setting of well index (WI) in INSIM-FT-3D based on Peaceman's equation does not yield accurate BHP estimates. We derive a WI that can honor the BHPs of a reference model composed of a set of 1D connections. When history matching BHPs of a 3D reservoir, we show that the derived WI is a better initial guess than that obtained from Peaceman's equation. We also develop a flow-path-tracking (FPT) algorithm to calculate the dynamic interwell properties (allocation factors and pore volumes (PVs)). Besides, we discuss the relationship between the INSIM-family methods and the traditional grid-based methods, which indicates that the INSIM-family methods can calculate the transmissibility of the connection between coarse-scale cells in a more accurate manner. As an improvement of INSIM-FT-3D, the newly proposed data-driven model is denoted as INSIM-FPT-3D.\u0000 To verify the correctness of the derived WI, we present a 1D problem and a T-shaped synthetic reservoir simulation model as the reference models. BHPs and oil production rates are obtained as the observed data by running these two reference models with total injection/production-rate controls. An INSIM-FPT-3D model is created by specifying the transmissibilities and PVs that are the same as those in the reference model. By applying the derived WIs in INSIM-FPT-3D, the resulting BHPs and oil rates obtained agree well with the reference model without further model calibration. Applying INSIM-FPT-3D to a synthetic multi-layered reservoir shows that we obtain a reasonable match of both BHPs and oil rates with INSIM-FPT-3D. Compared with the FrontSim model, the INSIM-FPT-3D model after history matching is shown to match the dynamic PVs from FrontSim reasonably well and can correctly predict the timing of water breakthrough.\u0000 By allowing for the assimilation of BHP data, we enable INSIM-FPT-3D to history match a green field with limited production history and forecast the timing of water breakthrough. The improved INSIM-FPT-3D leads to more accurate characterization of the interwell connectivities.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83747618","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":"Intelligent Time-Stepping for Practical Numerical Simulation","authors":"Soham Sheth, François McKee, K. Neylon, Ghazala Fazil","doi":"10.2118/204002-ms","DOIUrl":"https://doi.org/10.2118/204002-ms","url":null,"abstract":"\u0000 We present a novel reservoir simulator time-step selection approach which uses machine-learning (ML) techniques to analyze the mathematical and physical state of the system and predict time-step sizes which are large while still being efficient to solve, thus making the simulation faster. An optimal time-step choice avoids wasted non-linear and linear equation set-up work when the time-step is too small and avoids highly non-linear systems that take many iterations to solve.\u0000 Typical time-step selectors use a limited set of features to heuristically predict the size of the next time-step. While they have been effective for simple simulation models, as model complexity increases, there is an increasing need for robust data-driven time-step selection algorithms. We propose two workflows – static and dynamic – that use a diverse set of physical (e.g., well data) and mathematical (e.g., CFL) features to build a predictive ML model. This can be pre-trained or dynamically trained to generate an inference model. The trained model can also be reinforced as new data becomes available and efficiently used for transfer learning.\u0000 We present the application of these workflows in a commercial reservoir simulator using distinct types of simulation model including black oil, compositional and thermal steam-assisted gravity drainage (SAGD). We have found that history-match and uncertainty/optimization studies benefit most from the static approach while the dynamic approach produces optimum step-sizes for prediction studies. We use a confidence monitor to manage the ML time-step selector at runtime. If the confidence level falls below a threshold, we switch to traditional heuristic method for that time-step. This avoids any degradation in the performance when the model features are outside the training space. Application to several complex cases, including a large field study, shows a significant speedup for single simulations and even better results for multiple simulations. We demonstrate that any simulation can take advantage of the stored state of the trained model and even augment it when new situations are encountered, so the system becomes more effective as it is exposed to more data.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82812519","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 Acid Fracturing Treatments with Multi-Stage Alternating Injection of Pad and Acid Fluids","authors":"Rencheng Dong, M. Wheeler, Hang Su, K. Ma","doi":"10.2118/203985-ms","DOIUrl":"https://doi.org/10.2118/203985-ms","url":null,"abstract":"\u0000 Acid fracturing technique is widely applied to stimulate the productivity of carbonate reservoirs. The acid-fracture conductivity is created by non-uniform acid etching on fracture surfaces. Heterogeneous mineral distribution of carbonate reservoirs can lead to non-uniform acid etching during acid fracturing treatments. In addition, the non-uniform acid etching can be enhanced by the viscous fingering mechanism. For low-perm carbonate reservoirs, by multi-stage alternating injection of a low-viscosity acid and a high-viscosity polymer pad fluid during acid fracturing, the acid tends to form viscous fingers and etch fracture surfaces non-uniformly. To accurately predict the acid-fracture conductivity, this paper developed a 3D acid fracturing model to compute the rough acid fracture geometry induced by multi-stage alternating injection of pad and acid fluids. Based on the developed numerical simulator, we investigated the effects of viscous fingering, perforation design and stage period on the acid etching process. Compared with single-stage acid injection, multi-stage alternating injection of pad and acid fluids leads to narrower and longer acid-etched channels.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89130353","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":"Four Phase Relative Permeability and Capillary Pressure Framework for Surfactant EOR Simulation","authors":"B. Samson, M. Shaykhattarov","doi":"10.2118/203978-ms","DOIUrl":"https://doi.org/10.2118/203978-ms","url":null,"abstract":"\u0000 Consistent set of algorithms to calculate phase relative permeability and capillary pressure values in the four-phase representation suitable for surfactant flooding simulation has been derived. The novel formulation resolves difficulties with applying existing three-phase approaches, and it ensures continuity of transport characteristics at solubilization changes in phase composition.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"98 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77346327","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 Massively Parallel Restriction-Smoothed Basis Multiscale Solver on Multi-Core and GPU Architectures","authors":"A. Manea","doi":"10.2118/203939-ms","DOIUrl":"https://doi.org/10.2118/203939-ms","url":null,"abstract":"\u0000 Due to its simplicity, adaptability, and applicability to various grid formats, the restriction-smoothed basis multiscale method (MsRSB) (Møyne and Lie 2016) has received wide attention and has been extended to various flow problems in porous media. Unlike the standard multiscale methods, MsRSB relies on iterative smoothing to find the multiscale basis functions in an adaptive manner, giving it the ability to naturally adjust to various complex grid orientations often encountered in real-life industrial applications. In this work, we investigate the scalability of MsRSB on various state-of-the-art parallel architectures, including multi-core systems and GPUs. While MsRSB is — like most other multiscale methods — directly amenable to parallelization, the dependence on a smoother to find the basis functions creates unique control- and data-flow patterns. These patterns require careful design and implementation in parallel environments to achieve good scalability. We extend the work on parallel multiscale methods in Manea et al. (2016) and Manea and Almani (2019) to map the MsRSB special kernels to the shared-memory parallel multi-core and GPU architectures. The scalability of our optimized parallel MsRSB implementation is demonstrated using highly heterogeneous 3D problems derived from the SPE10 Benchmark (Christie and Blunt 2001). Those problems range in size from millions to tens of millions of cells. The multi-core implementation is benchmarked on a shared memory multi-core architecture consisting of two packages of Intel's Cascade Lake Xeon® Gold 6246 CPU, while the GPU implementation is benchmarked on a massively parallel architecture consisting of Nvidia Volta V100 GPUs. We compare the multi-core implementation to the GPU implementation for both the setup and solution stages. To the best of our knowledge, this is the first parallel implementation and demonstration of the versatile MsRSB method on the GPU architecture.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87462929","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 Novel Method to Speedup Calibrating Horizontal Well Performance Model with Multi-Stage Fracturing Treatments and Its Applications in Delaware Basin","authors":"Hongjie Xiong, Sangcheol Yoon, Yu Jiang","doi":"10.2118/203935-ms","DOIUrl":"https://doi.org/10.2118/203935-ms","url":null,"abstract":"\u0000 The multi-stage fracture treatments create complex fracture networks with various proppant type, size, and concentration distributed within and along fractures through reservoir rock, where larger size and higher concentrations usually result in higher long-term conductivity. To model the fracture conductivity reduction with depletion, we traditionally use a single monotonic relationship between fracture conductivity and pressure, which is proper for a single proppant concentration but obviously hard to describe the situation in the horizontal wells with complex concentration distributions. This paper is to present a new method to speed-up the calibration process of well performance models with multi-million cells and its two applications in the Wolfcamp reservoir in the Delaware Basin.\u0000 To study well performance and completion effectiveness of 3000 horizontal wells over University Lands acreage in the Permian Basin, we have built a series of well performance models with complex fracture networks (SPE 189855 and 194367). We have used those models to methodically investigate the drivers of well completion parameters and well spacing on well performance and field development value (URTeC 554). In the process of building multiple robust well performance models, we found out it is hard and time-consuming to calibrate a well performance model with multi-million cells based upon a single correlation between fracture conductivity and pressure.\u0000 We first modeled the complex fracture networks and fracture conductivity distributions based upon the historical completion pumping data; we then developed multiple correlations to characterize fracture conductivity reduction and closure behaviors with pressure depletion based upon initial fracture conductivities (as the result of proppant type, size, and concentration) and reservoir geomechanical properties. We found out that this method significantly reduced our model calibration time. We then applied our method to multiple case studies in the Permian Basin to test and improve the method.\u0000 We have thus developed a method to mimic the fracture conductivity reduction and closure behavior in the horizontal wells with complex fracture networks. The paper will layout the theoretical foundation and detail our method to develop the multiple correlations to model fracture conductivity reduction and fracture closure behaviors in the horizontal well performance models in the unconventional reservoirs. We will then show two case studies to illustrate how we have applied our method to speed up the model calibration process.\u0000 Based upon the multiple applications into our model calibration process, we have concluded that the method is very effective to calibrate the well performance model with complex fracture networks.\u0000 The method can be used for engineers to simplify and speedup calibrating horizontal well performance models. Therefore, engineers can more effectively build more robust well performance models to optimize ","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87037304","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 Fast Screening Tool for Assessing the Impact of Poro-Mechanics on Fractured Reservoirs Using Dual-Porosity Flow Diagnostics","authors":"Lesly Gutierrez-Sosa, S. Geiger, F. Doster","doi":"10.2118/203981-ms","DOIUrl":"https://doi.org/10.2118/203981-ms","url":null,"abstract":"\u0000 Accounting for poro-mechanical effects in full-field reservoir simulation studies and uncertainty quantification workflows is still limited, mainly because of their high computational cost. We introduce a new approach that couples hydrodynamics and poro-mechanics with dual-porosity flow diagnostics to analyse how poro-mechanics could impact reservoir dynamics in naturally fractured reservoirs without significantly increasing computational overhead.\u0000 Our new poro-mechanical informed dual-porosity flow diagnostics account for steady-state and singlephase flow conditions in the fractured medium while the fracture-matrix fluid exchange is approximated using a physics-based transfer rate constant which models two-phase flow using an analytical solution for spontaneous imbibition or gravity drainage. The deformation of the system is described by the dualporosity poro-elastic theory, which is based on mixture theory and micromechanics to compute the effective stresses and strains of the rock matrix and fractures. The solutions to the fluid flow and rock deformation equations are coupled sequentially. The governing equations for fluid flow are discretised using a finite volume method with two-point flux-approximation while the governing equations for poro- mechanics are discretised using the virtual element method. The solution of the coupled system considers stress-dependent permeabilities for fractures and matrix. Our framework is implemented in the open source MATLAB Reservoir Simulation Toolbox (MRST).\u0000 We present a case study using a fractured carbonate reservoir analogue to illustrate the integration of poro-mechanics within the dual-porosity flow diagnostics framework. The extended flow diagnostics calculations enable us to quickly screen how the dynamics in fractured reservoirs (e.g. reservoir connectivity, sweep efficiency, fracture-matrix transfer rates) are affected by the complex interactions between poro-mechanics and fluid flow where changes in pore pressure and effective stress modify petrophysical properties and hence impact reservoir dynamics.\u0000 Due to the steady-state nature of the calculations and the effective coupling strategy, these calculations do not incur significant computational overheads. They hence provide an efficient complement to traditional reservoir simulation and uncertainty quantification workflows as they enable us to assess a broader range of reservoir uncertainties (e.g. geological, petrophysical and hydro-mechanical uncertainties). The capability of studying a much broader range of uncertainties allows the comparison and ranking from a large ensemble of reservoir models and select individual candidates for more detailed full-physics reservoir simulation studies without compromising on assessing the range of uncertainties inherent to fractured reservoirs.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"110 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79257381","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":"Acute PEBI Grid Generation for Reservoir Geometries","authors":"Shahid Manzooor, M. Edwards, A. Dogru","doi":"10.2118/203908-ms","DOIUrl":"https://doi.org/10.2118/203908-ms","url":null,"abstract":"\u0000 An unstructured grid generation method is presented that automates control-volume boundary alignment to geological objects and control point alignment to complex wells. The grid generation method is coupled with an iterative acute mesh reconstruction technique, to construct essentially acute triangulations, while satisfying quite general geometric constraints. For well aligned grids control points are constrained to the well trajectory and protection circles are used, whereas for boundary aligned grids halo construction is performed. Unstructured Delaunay triangulations (DT) have the desirable locally orthogonal perpendicular bisectional (PEBI) property, required by the industry standard two-point flux approximation for consistency for isotropic fields. The PEBI property can only be exploited if such grids are comprised of acute simplexes, with circumcentres located inside their respective elements. The method presented enables acute DT layered mesh generation while honoring internal boundaries and wells in a two dimensional space. A dual (Voronoi) grid derived from a feature honored simplicial mesh is then projected in the vertical direction generating 2.5D PEBI grids. Effectiveness of the method to construct acute PEBI grids honoring geological objects and complex wells is demonstrated by meshing representative reservoir geometries. Numerical results are presented that verify consistency of the two-point flux on the resulting boundary-aligned acute PEBI grids. Development of an unstructured grid generation method which 1) Automates interior boundary alignment, 2) Honors features with respect to control point and/or control volume, and 3) Generates acute PEBI grids for reservoir geometries is presented. A unique workflow is presented to generate boundary aligned acute PEBI grids for complex geometries. Development of boundary aligned grids that honor both geological objects and multilateral complex wells, together with mesh reconstruction to ensure circumcenter containment is presented. Further, 3D PEBI grid generation method which can limit refinement to well perforations and geological objects is also described.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88828847","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 3D Coupled Thermal-Hydraulic-Mechanical THM Model Using EDFM and XFEM for Hydraulic-Fracture-Dominated Geothermal Reservoirs","authors":"Xiangyu Yu, Cong Wang, Xia Yan, Shihao Wang, Lei Wang, P. Winterfeld, Yushu Wu","doi":"10.2118/203983-ms","DOIUrl":"https://doi.org/10.2118/203983-ms","url":null,"abstract":"\u0000 Enhanced Geothermal Systems (EGS) are those geothermal reservoirs artificially fractured to create paths for injected low-temperature fluid which is then heated up along the flow path until production for electricity generation. This heat recovery involves three tightly coupled processes: thermal, hydraulic and mechanical which interacts with each other and in turn affects the energy production. The local temperature field would be disturbed by injected fuild, resulting in thermal/poroelastic responses near the hydraulic fractured area which are the dominant factors of fluid flow. In this paper, the three-dimensional (3D) Embedded Discrete Fracture Model (EDFM) was adopted to describe the geometry of the fracture and simulate fluid flow and heat transfer between fractures and the matrix, while mechanics, including displacement of the strong discontinuity (fractures), was solved by the 3D eXtended Finite Element Method (XFEM). With the capability of modeling fractures of arbitrary shapes within a 3D reservoir domain using 3D EDFM-XFEM, a coupled THM model was developed based on the unconditionally stable fixed-stress split sequential-implicit method, where the fluid flow/heat transfer module and mechanics module are solved iteratively until convergence within a time step. Fluid flow/heat transfer and XFEM with internal/external tractions are both validated by comparison with existing simulators. We conducted simulations for two synthetic geothermal reservoir heat recovery cases to investigate the effects of the injection temperature and boundary traction condition on the production temperature and fracture deformation. The results indicate that the fracture aperture and permeability is sensitive to temperature variation and hence impacts the production rate/temperature. Thermal strain might be the dominant factor of rock deformation, especially in the shallow depth where geostress is at a low level.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82529061","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}