Day 1 Tue, October 26, 2021最新文献

{"title":"Automatic Calibration of a Geomechanical Model from Sparse Data for Estimating Stress in Deep Geological Formations","authors":"O. Andersen, M. Kelley, V. Smith, S. Raziperchikolaee","doi":"10.2118/204006-ms","DOIUrl":"https://doi.org/10.2118/204006-ms","url":null,"abstract":"\u0000 In this study, we demonstrate geomechanical modeling with fully automatic parameter calibration to estimate the full geomechanical stress fields of a prospective US CO2 storage site, based on sparse measurement data. The goal is to compute full stress tensor field estimates (principal stresses and orientations) that are maximally compatible with observations within the constraints of the model assumptions, thereby extending point-wise, incomplete partial stress measurement to a simulated full formation stress field, as well as a rough assessment of the associated error. We use the Perch site, located in Otsego Country, Michigan, as our case study. Input data consists of partial stress tensor information inferred from in-situ borehole tests, geophysical well logs and processing of seismic data. A static earth model of the site was developed, and geomechanical simulation functionality of the open-source MATLAB Reservoir Simulation Toolbox (MRST) used to model the stress field. Adjoint-based nonlinear optimization was used to adjust boundary conditions and material properties to calibrate simulated results to observations. Results were interpreted through a Bayesian framework.\u0000 The focus of this article is to demonstrate how the fully automatic calibration procedure works and discuss the results obtained but does not attempt a detailed analysis of the stress field in the context of the proposed CO2 storage initiatives. Our work is part of a larger effort to non-invasively determine in-situ stresses in deep formations considered for CO2 storage. Guided by previously published research on geomechanical model calibration, our work presents a novel calibration approach supporting a potentially large number of linear or nonlinear calibration parameters, in order to produce results optimally agreeing with available measurements and thus extend partial point-wise estimates to full tensor fields compatible with the physics of the site.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76278788","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":"Coupled Poroelastic Modeling to Characterize the 4.18-Magnitude Earthquake Due to Hydraulic Fracturing in the East Shale Basin of Western Canada","authors":"Gang Hui, Shengnan Chen, F. Gu","doi":"10.2118/203921-ms","DOIUrl":"https://doi.org/10.2118/203921-ms","url":null,"abstract":"\u0000 Recently, the elevated levels of seismicity activities in Western Canada have been demonstrated to be linked to hydraulic fracturing operations that developed unconventional resources. The underlying triggering mechanisms of hydraulic fracturing-induced seismicity are still uncertain. The interactions of well stimulation and geology-geomechanical-hydrological features need to be investigated comprehensively. The linear poroelasticity theory was utilized to guide coupled poroelastic modeling and to quantify the physical process during hydraulic fracturing. The integrated analysis is first conducted to characterize the mechanical features and fluid flow behavior. The finite-element simulation is then conducted by coupling Darcy's law and solid mechanics to quantify the perturbation of pore pressure and poroelastic stress in the seismogenic fault zone. Finally, the Mohr-coulomb failure criterion is utilized to determine the spatial-temporal faults activation and reveal the trigger mechanisms of induced earthquakes. The mitigation strategy was proposed accordingly to reduce the potential seismic hazards near this region. A case study of ML 4.18 earthquake in the East Shale Basin was utilized to demonstrate the applicability of the coupled modeling and numerical simulation. Results showed that one inferred fault cut through the Duvernay formation with the strike of NE20°. The fracture half-length of two wells owns an average value of 124 m. The brittleness index deriving from the velocity logging data was estimated to be a relatively higher value in the Duvernay formation, indicating a geomechanical bias of stimulated formation for the fault activation. The coupled poroelastic simulation was conducted, showing that the hydrologic connection between seismogenic faults and stimulated well was established by the end of the 38th stage completion for the east horizontal well. The simulated coulomb failure stress surrounding the fault reached a maximum of 4.15 MPa, exceeding the critical value to cause the fault slip. Hence the poroelastic effects on the inferred fault were responsible for the fault activation and triggered the subsequent ML 4.18 earthquake. It is essential to optimize the stimulation site selection near the existing faults to reduce risks of future seismic hazards near the East Shale Basin.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"114 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74851350","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":"Bayesian Long-Short Term Memory for History Matching in Reservoir Simulations","authors":"R. Santoso, Xupeng He, M. AlSinan, H. Kwak, H. Hoteit","doi":"10.2118/203976-ms","DOIUrl":"https://doi.org/10.2118/203976-ms","url":null,"abstract":"\u0000 History matching is critical in subsurface flow modeling. It is to align the reservoir model with the measured data. However, it remains challenging since the solution is not unique and the implementation is expensive. The traditional approach relies on trial and error, which are exhaustive and labor-intensive. In this study, we propose a new workflow utilizing Bayesian Markov Chain Monte Carlo (MCMC) to automatically and accurately perform history matching. We deliver four novelties within the workflow: 1) the use of multi-resolution low-fidelity models to guarantee high-quality matching, 2) updating the ranges of priors to assure convergence, 3) the use of Long-Short Term Memory (LSTM) network as a low-fidelity model to produce continuous time-response, and 4) the use of Bayesian optimization to obtain the optimum low-fidelity model for Bayesian MCMC runs.\u0000 We utilize the first SPE comparative model as the physical and high-fidelity model. It is a gas injection into an oil reservoir case, which is the gravity-dominated process. The coarse low-fidelity model manages to provide updated priors that increase the precision of Bayesian MCMC. The Bayesian-optimized LSTM has successfully captured the physics in the high-fidelity model. The Bayesian-LSTM MCMC produces an accurate prediction with narrow uncertainties. The posterior prediction through the high-fidelity model ensures the robustness and precision of the workflow. This approach provides an efficient and high-quality history matching for subsurface flow modeling.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86849083","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 Gridding Method for Capturing Geological Complexity and Uncertainty","authors":"Xu Yifei, Priyesh Srivastava, Xiao Ma, Karan Kaul, Hao Huang","doi":"10.2118/203902-ms","DOIUrl":"https://doi.org/10.2118/203902-ms","url":null,"abstract":"\u0000 In this paper, we introduce an efficient method to generate reservoir simulation grids and modify the fault juxtaposition on the generated grids. Both processes are based on a mapping method to displace vertices of a grid to desired locations without changing the grid topology. In the gridding process, a grid that can capture stratigraphical complexity is first generated in an unfaulted space. The vertices of the grid are then displaced back to the original faulted space to become a reservoir simulation grid. The resulting reversely mapped grid has a mapping structure that allows fast and easy fault juxtaposition modification. This feature avoids the process of updating the structural framework and regenerating the reservoir properties, which may be time-consuming. To facilitate juxtaposition updates within an assisted history matching workflow, several parameterized fault throw adjustment methods are introduced. Grid examples are given for reservoirs with Y-faults, overturned bed, and complex channel-lobe systems.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90336672","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":"GEOSX: A Multiphysics, Multilevel Simulator Designed for Exascale Computing","authors":"H. Gross, A. Mazuyer","doi":"10.2118/203932-ms","DOIUrl":"https://doi.org/10.2118/203932-ms","url":null,"abstract":"\u0000 Evaluating large basin-scale formations for CO2 sequestration is one of the most important challenges for our industry. The technical complexity and the quantification of risks associated with these operations call for new reservoir engineering and reservoir simulation tools. The impact of multiple coupled physical phenomena, the century timescale, and basin-sized models in these operations force us to completely take apart and revisit the numerical backbone of existing simulation tools. We need a reservoir simulation tool designed for scalability and portability on high-performance computing architectures.\u0000 To achieve this, we are proposing a new, open-source, multiphysics, and multilevel physics simulation tool called GEOSX. This tool is jointly created by Lawrence Livermore National Laboratory, Stanford University, and Total. It is designed for scalability on multiple CPUs and multiple GPUs and offers a suite of physical solvers that can be extended easily while achieving a balance between performance and portability. GEOSX is initially targeting multiphysics simulations with coupled geomechanics, flow, and transport mechanics but with its open architecture, it allows access to high-performance physical solvers as building blocks of other multiphysics problems and provides users with a suite of tools for numerical optimization across platforms.\u0000 In this paper, we introduce GEOSX, expose its fundamental architecture principles, and show an example of geological sequestration of CO2 modeling on real data. We demonstrate our ability to simulate fluid and rock poromechanical interactions over long periods and basin-scale dimensions. GEOSX demonstrates its usefulness for such complex and large problems and proves to be scalable and portable across multiple high-performance systems.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"206 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80418444","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":"Distributed GPU Based Matrix Power Kernel for Geoscience Applications","authors":"A. Sedrakian, T. Guignon","doi":"10.2118/203947-ms","DOIUrl":"https://doi.org/10.2118/203947-ms","url":null,"abstract":"\u0000 High-performance computing is at the heart of digital technology which allows to simulate complex physical phenomena. The current trend for hardware architectures is toward heterogeneous systems with multi-core CPUs accelerated by GPUs to get high computing power. The demand for fast solution of Geoscience simulations coupled with new computing architectures drives the need for challenging parallel algorithms. Such applications based on partial differential equations, requires to solve large and sparse linear system of equations. This work makes a step further in Matrix Powers Kernel (MPK) which is a crucial kernel in solving sparse linear systems using communication-avoiding methods. This class of methods deals with the degradation of performances observed beyond several nodes by decreasing the gap between the time necessary to perform the computations and the time needed to communicate the results. The proposed work consists of a new formulation for distributed MPK kernels for the cluster of GPUs where the pipeline communications could be overlapped by the computation. Also, appropriate data reorganization decreases the memory traffic between processors and accelerators and improves performance. The proposed structure is based on the separation of local and external components with different layers of interface nodes-due to the MPK algorithm-. The data is restructured in a way where all the data required by the neighbor process comes contiguously at the end, after the local one. Thanks to an assembly step, the contents of the messages for each neighbor are determined. Such data structure has a major impact on the efficiency of the solution, since it permits to design an appropriate communication scheme where the computation with local data can occur on the GPUs and the external ones on the CPUs. Moreover, it permits more efficient inter-process communication by an effective overlap of the communication by the computation in the asynchronous pipeline way. We validate our design through the test cases with different block matrices obtained from different reservoir simulations : fractured reservoir dual-medium, black-oil two phase-flow, and three phase-flow models. The experimental results demonstrate the performance of the proposed approach compared to state of the art. The proposed MPK running on several nodes of the GPU cluster provides a significant performance gain over equivalent Sparse Matrix Vector product (SpMV) which is already optimized and provides better scalability.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"152 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80946299","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":"Theoretical and Numerical Investigation of Supersonic Multiphase Gas Injection","authors":"Da Zhu, M. Sivagnanam, I. Gates","doi":"10.2118/203911-ms","DOIUrl":"https://doi.org/10.2118/203911-ms","url":null,"abstract":"\u0000 Supersonic gas injection can help deliver gas uniformly to a reservoir, regardless of reservoir conditions. This technology has played a key role in enhanced oil recovery (EOR) and in particular, thermal enhanced oil recovery operations. Most previous studies have focused on single phase gas injection whereas in most field applications, multiphase and multicomponent situations occur.\u0000 In the research documented in this paper, we report on results of evaluations of compressible multiphase supersonic gas flows in which gas is the continuous phase is seeded with dispersed liquid droplets or solid particles. Theoretical derivation and numerical simulations with and without relative motions between continuous and disperse phases are examined first. The results illustrate that the shock wave structures and flow properties associated with the multiphase gas flows are different than that of single-phase isentropic flows. The existence and importance of relaxation zones after the normal shock wave in multiphase flow is described. Numerical computational fluid dynamics (CFD) simulations are conducted to show how the multiphase multicomponent flow affects gas phase injection under different conditions. The impact of solid/liquid mass loading on flow performance is discussed. Finally, the practical application of the findings is discussed.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"78 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83744455","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":"Efficient Drill Sequence Optimization Using a Heuristic Priority Function","authors":"Zhenzhen Wang, Jincong He, Shusei Tanaka, X. Wen","doi":"10.2118/203986-ms","DOIUrl":"https://doi.org/10.2118/203986-ms","url":null,"abstract":"\u0000 Drill sequence optimization is a common challenge faced in the oil and gas industry and yet it cannot be solved efficiently by existing optimization methods due to its unique features and constraints. For many fields, the drill queue is currently designed manually based on engineering heuristics. In this paper, a heuristic priority function is combined with traditional optimizers to boost the optimization efficiency at a lower computational cost to speed up the decision-making process.\u0000 The heuristic priority function is constructed to map the individual well properties such as well index and inter-well distance to the well priority values. As the name indicates, wells with higher priority values will be drilled earlier in the queue. The heuristic priority function is a comprehensive metric of inter-well communication & displacement efficiency. For example, injectors with fast support to producers or producers with a better chance to drain the unswept region tend to have high scores. It contains components that weigh the different properties of a well. These components are then optimized during the optimization process to generate the beneficial drill sequences. Embedded with reservoir engineering heuristics, the priority function helps the optimizer focus on exploring scenarios with promising outcomes.\u0000 The proposed heuristic priority function, combined with the Genetic Algorithm (GA), has been tested through drill sequence optimization problems for the Brugge field and Olympus field. Optimizations that are directly performed on the drill sequence are employed as reference cases. Different continu- ous/categorical parameterization schemes and various forms of heuristic priority functions are also investigated. Our exploration reveals that the heuristic priority function including well type, constraints, well index, distance to existing wells, and adjacent oil in place yields the best outcome. The proposed approach was able to achieve a better optimization starting point (∼5-18% improvement due to more reasonable drill sequence rather than random guess), a faster convergence rate (results stabilized at 12 vs. 30 iterations), and a lower computational cost (150-250 vs. 1,300 runs to achieve the same NPV) over the reference methods. Similar performance improvement was also observed in another application to a North Sea type reservoir. This demonstrated the general applicability of the proposed method.\u0000 The employment of the heuristic priority function improves the efficiency and reliability of drill sequence optimization compared to the traditional methods that directly optimize the sequence. It can be easily embedded in either commercial or research simulators as an independent module. In addition, it is also an automatic process that fits well with iterative optimization algorithms.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"63 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82153204","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":"Comparison of Various Discretization Schemes for Simulation of Large Field Case Reservoirs Using Unstructured Grids","authors":"Samier Pierre, Raguenel Margaux, Darche Gilles","doi":"10.2118/203949-ms","DOIUrl":"https://doi.org/10.2118/203949-ms","url":null,"abstract":"\u0000 Solving the equations governing multiphase flow in geological formations involves the generation of a mesh that faithfully represents the structure of the porous medium. This challenging mesh generation task can be greatly simplified by the use of unstructured (tetrahedral) grids that conform to the complex geometric features present in the subsurface. However, running a million-cell simulation problem using an unstructured grid on a real, faulted field case remains a challenge for two main reasons. First, the workflow typically used to construct and run the simulation problems has been developed for structured grids and needs to be adapted to the unstructured case. Second, the use of unstructured grids that do not satisfy the K-orthogonality property may require advanced numerical schemes that preserve the accuracy of the results and reduce potential grid orientation effects. These two challenges are at the center of the present paper. We describe in detail the steps of our workflow to prepare and run a large-scale unstructured simulation of a real field case with faults. We perform the simulation using four different discretization schemes, including the cell-centered Two-Point and Multi-Point Flux Approximation (respectively, TPFA and MPFA) schemes, the cell- and vertex-centered Vertex Approximate Gradient (VAG) scheme, and the cell- and face-centered hybrid Mimetic Finite Difference (MFD) scheme. We compare the results in terms of accuracy, robustness, and computational cost to determine which scheme offers the best compromise for the test case considered here.","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":"87880389","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":"Unified Reservoir And Seismic Simulation With Explicit Representation Of Fractures And Faults","authors":"Z. Han, G. Ren, R. Younis","doi":"10.2118/203979-ms","DOIUrl":"https://doi.org/10.2118/203979-ms","url":null,"abstract":"\u0000 In the context of remote sensing, the vast disparity in characteristic scales between seismic deformation (e.g. milliseconds) and transient flow (e.g. hours) allows a \"two-model paradigm\" for geophysics and reservoir simulation. In the context of flow-induced geohazard risk mitigation and micro-seismic data integration, this paradigm breaks down. Under micro-seismic deformation, events occur with high-frequency, and over sustained duration during which the rock-fluid coupling is significant. In risk mitigation scenarios, the onset of seismic deformation is directly tied to quasi-static coupling periods. This work develops an approach to reservoir simulation modeling that allows simultaneous resolution of transient (inertial) poromechanics and multiphase fluid flow in the presence of fracture.\u0000 A mixed discretization scheme combining the extended finite element method (XFEM) and the embedded discrete fracture model (EDFM) is extended using a second-order implicit Newmark time integration scheme for the inertial mechanics. A Lagrange multiplier method is developed to model pressure-dependent contact traction in fractures. The contact constraints are adapted to accommodate fracture opening. Slip-weakening fracture friction models are incorporated. Finally, a time-step controller is proposed to combine local discretization error with contact traction and slip-rate control along the fractures. This strategy allows automatic adaptation to resolve quasi-static, inter-seismic triggering, and co-seismic spontaneous rupture periods within one model. The model is verified to simulate complete induced earthquake sequences, including inter-seismic and dynamic rupture phases. The performance of the adaptive model is illustrated for cases with various set-ups of production and injection periods in a fractured reservoir with explicit fracture representation.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":"124 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88008433","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}