Day 1 Tue, October 26, 2021最新文献

{"title":"Reduced-Order Modeling for Multiphase Flow Using a Physics-Based Deep Learning","authors":"T. Alsulaimani, M. Wheeler","doi":"10.2118/203965-ms","DOIUrl":"https://doi.org/10.2118/203965-ms","url":null,"abstract":"\u0000 Reservoir simulation is the most widely used tool for oil and gas production forecasting and reservoir management. Solving a large-scale system of nonlinear differential equations every timestep can be computationally expensive. In this work, we present a two-phase physics-constrained deep-learning reduced-order model as a surrogate model for subsurface flow production forecast. The implemented deep learning model is a physics-guided encoder-decoder, constructed based on the Embed-to-Control (E2C) framework. In our implementation, the E2C works in a way analogous to Proper Orthogonal Decomposition combined with Discrete Empirical Interpolation Method (POD-DEIM) or Trajectory Piece-Wise Linearization approach (POD-TPWL). The E2C-Reduced-order model (ROM) involves projecting the system from a high-dimensional space into a low-dimensional subspace using the encoder-decoder, approximating the progression of the system from one timestep to the next using a linear transition model, and finally projecting the system back to high-dimensional space using the encoder-decoder. To guarantee mass conservation, we adopt the Finite Elements Mixed Formulation in the neural network's loss function combined with the original data-based loss function. Training simulations are generated using a full-physics reservoir simulator (IPARS). High-fidelity pressure, velocity, and saturation solution snapshot at constant time intervals are taken as training input to the neural network. After training, the model is tested over large variations of well control settings. Accurate pressure and saturation solutions are predicted along with the injection and production well quantities using the proposed approach. Errors in the predicted quantities of interest are reduced with the increase in the number of training simulations used. Although it required a large number of training simulations for the offline (training) step, the model achieved a significant speedup in the online stage compared to the full physics model. Considering the overall computational cost, this ROM model is proper for cases when a large number of simulations are required like in the case of production optimization and uncertainty assessments. The proposed approach shows the capability of the deep-learning reduced-order model to accurately predict multiphase flow behavior such as well quantities, and global pressure and saturation fields. The model honors mass conservation and the underlying physics laws, which many existing approaches don't take into direct consideration.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73479088","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":"Upscaling of Realistic Discrete Fracture Simulations Using Machine Learning","authors":"N. Andrianov","doi":"10.2118/203962-ms","DOIUrl":"https://doi.org/10.2118/203962-ms","url":null,"abstract":"\u0000 Upscaling of discrete fracture networks to continuum models such as the dual porosity/dual permeability (DPDP) model is an industry-standard approach in modelling of fractured reservoirs. While flow-based upscaling provides more accurate results than analytical methods, the application of flow-based upscaling is limited due to its high computational cost.\u0000 In this work, we parametrize the fine-scale fracture geometries and assess the accuracy of several convolutional neural networks (CNNs) to learn the mapping between this parametrization and the DPDP model closures such as the upscaled fracture permeabilities and the matrix-fracture shape factors. We exploit certain similarities between this task and the problem of image classification and adopt several best practices from the state-of-the-art CNNs used for image classification. By running a sensitivity study, we identify several key features in the CNN structure which are crucial for achieving high accuracy of predictions for the DPDP model closures, and put forward the corresponding CNN architectures.\u0000 Obtaining a suitable training dataset is challenging because i) it requires a dedicated effort to map the fracture geometries; ii) creating a conforming mesh for fine-scale simulations in presence of intersecting fractures typically leads to bad quality mesh elements; iii) fine-scale simulations are time-consuming. We alleviate some of these difficulties by pre-training a suitable CNN on a synthetic random linear fractures’ dataset and demonstrate that the upscaled parameters can be accurately predicted for a realistic fracture configuration from an outcrop data.\u0000 The accuracy of the DPDP results with the predicted model closures is assessed by a comparison with the corresponding fine-scale discrete fracture-matrix (DFM) simulation of a two-phase flow in a realistic fracture geometry. The DPDP results match well the DFM reference solution, while being significantly faster than the latter.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75809601","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 Phase-Field Based Approach for Modeling the Cementation and Shear Slip of Fracture Networks","authors":"M. Jammoul, M. Wheeler","doi":"10.2118/203906-ms","DOIUrl":"https://doi.org/10.2118/203906-ms","url":null,"abstract":"\u0000 Modeling the geomechanical deformations of fracture networks has become an integral part of designing enhanced geothermal systems and recovery mechanisms for unconventional reservoirs. Stress changes in the reservoir can cause large variations in the apertures of fractures resulting in drastic changes in their transmissivities. At the same time, sustained high injection pressures can induce shear slipping along existing fractures and faults and trigger seismic activity.\u0000 In this work, a novel approach is introduced for the simulation of cementation and shear slip of fractures on very general semi-structured grids. Natural fracture networks are represented in large scale reservoirs using the phase-field approach. The fluid flow through fractures is simulated on spatially non-conforming grids using the enhanced velocity mixed finite element method. The geomechanics equations are discretized using the continuous Galerkin finite element method. The single-phase flow and mechanics equations are decoupled using the fixed stress iterative scheme. The model can predict shear slipping and opening/closure of fractures due to induced stresses and poromechanical effects.\u0000 Two synthetic examples are presented to model the effects of injection/production processes on the cementation and shear slip of fractures. The impact of the fractures' orientation and their connectivity on the hydromechanical response of the reservoir is also considered. The examples illustrate the strong impact of the dynamic behavior of fractures and the accompanying poroelastic deformations on the safety and productivity of subsurface projects.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75856432","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":"Injection and Production Optimization for Tengiz Platform Sour Gas Injection by Reactive and Proactive Conformance Completions Control","authors":"Shusei Tanaka, M. Rousset, Y. Ghomian, A. Azhigaliyeva, Chingiz Bopiyev, Ilyas Yechshanov, K. Dehghani","doi":"10.2118/203995-ms","DOIUrl":"https://doi.org/10.2118/203995-ms","url":null,"abstract":"\u0000 Sour gas injection operation has been implemented in Tengiz since 2008 and will be expanded as part of a future growth project. Due to limited gas handling capacity, producing wells at high GOR has been a challenge, resulting in potential well shutdowns. The objective of this study was to establish an efficient optimization workflow to improve vertical/areal sweep, thereby maximizing recovery under operation constraints. This will be enabled through conformance control completions that have been installed in many production/injection wells.\u0000 A Dual-Porosity and Dual-Permeability (DPDK) compositional simulation model with advanced Field Management (FM) logic was used to perform the study. Vertical conformance control was implemented in the model enabling completion control of 4 compartments per well. A model-based optimization workflow was defined to maximize recovery. Objective functions considered were incremental recovery 1) after 5 years, and 2) at the end of concession. Control parameters considered for optimization are 1) injection allocation rate, 2) production allocation rate, 3) vertical completion compartments for injectors and producers. A combination of different optimization techniques e.g., Genetic Algorithm and Machine-Learning sampling method were utilized in an iterative manner.\u0000 It was quickly realized that due to the number of mixed categorical and continuous control parameters and non-linearity in simulation response, the optimization problem became almost infeasible. In addition, the problem also became more complex with multiple time-varying operational constraints. Parameterization of the control variables, such as schedule and/or FM rules optimization were revisited. One observation from this study was that a hybrid approach of considering schedule-based optimization was the best way to maximize short term objectives while rule-based FM optimization was the best alternative for long term objective function improvement. This hybrid approach helped to improve practicality of applying optimization results into field operational guidelines.\u0000 Several optimization techniques were tested for the study using both conceptual and full-field Tengiz models, realizing the utility of some techniques that could help in many field control parameters. However, all these optimization techniques required more than 2000 simulation runs to achieve optimal results, which was not practical for the study due to constraints in computational timing. It was observed that limiting control parameters to around 50 helped to achieve optimal results for the objective functions by conducting 500 simulation runs. These limited number of parameters were selected from flow diagnostics and heavy-hitter analyses from the pool of original 800+ control parameters.\u0000 The novelty of this study includes three folds: 1) The model-based optimization outcome obtained in this study has been implemented in the field operations with observation of increased recovery 2) t","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90389782","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 Collocated Finite Volume Scheme for High-Performance Simulation of Induced Seismicity in Geo-Energy Applications","authors":"A. Novikov, D. Voskov, M. Khait, H. Hajibeygi, J. Jansen, TU Delft","doi":"10.2118/203903-ms","DOIUrl":"https://doi.org/10.2118/203903-ms","url":null,"abstract":"\u0000 We develop a collocated Finite Volume Method (FVM) to study induced seismicity as a result of pore pressure fluctuations. A discrete system is obtained based on a fully-implicit coupled description of flow, elastic deformation, and contact mechanics at fault surfaces on a fully unstructured mesh. The cell-centered collocated scheme leads to convenient integration of the different physical equations, as the unknowns share the same discrete locations on the mesh. Additionally, a multi-point flux approximation is formulated in a general procedure to treat heterogeneity, anisotropy, and cross-derivative terms for both flow and mechanics equations. The resulting system, though flexible and accurate, can lead to excessive computational costs for field-relevant applications. To resolve this limitation, a scalable parallel solution algorithm is developed and presented. Several proof-of-concept numerical tests, including benchmark studies with analytical solutions, are investigated. It is found that the presented method is indeed accurate, stable and efficient; and as such promising for accurate and efficient simulation of induced seismicity.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87638922","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 Cut-Cell Polyhedral Finite Element Model for Coupled Fluid Flow and Mechanics in Fractured Reservoirs","authors":"I. Shovkun, H. Tchelepi","doi":"10.2118/203958-ms","DOIUrl":"https://doi.org/10.2118/203958-ms","url":null,"abstract":"\u0000 Mechanical deformation induced by injection and withdrawal of fluids from the subsurface can significantly alter the flow paths in naturally fractured reservoirs. Modeling coupled fluid-flow and mechanical deformation in fractured reservoirs relies on either sophisticated gridding techniques, or enhancing the variables (degrees-of-freedom) that represent the physics in order to describe the behavior of fractured formation accurately. The objective of this study is to develop a spatial discretization scheme that cuts the \"matrix\" grid with fracture planes and utilizes traditional formulations for fluid flow and geomechanics.\u0000 The flow model uses the standard low-order finite-volume method with the Compartmental Embedded fracture Model (cEDFM). Due to the presence of non-standard polyhedra in the grid after cutting/splitting, we utilize numerical harmonic shape functions within a Polyhedral finite-element (PFE) formulation for mechanical deformation. In order to enforce fracture-contact constraints, we use a penalty approach.\u0000 We provide a series of comparisons between the approach that uses conforming Unstructured grids and a Discrete Fracture Model (Unstructured DFM) with the new cut-cell PFE formulation. The manuscript analyzes the convergence of both methods for linear elastic, single-fracture slip, and Mandel’s problems with tetrahedral, Cartesian, and PEBI-grids. Finally, the paper presents a fully-coupled 3D simulation with multiple inclined intersecting faults activated in shear by fluid injection, which caused an increase in effective reservoir permeability.\u0000 Our approach allows for great reduction in the complexity of the (gridded) model construction while retaining the solution accuracy together with great saving in the computational cost compared with UDFM. The flexibility of our model with respect to the types of grid polyhedra allows us to eliminate mesh artifacts in the solution of the transport equations typically observed when using tetrahedral grids and two-point flux approximation.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85935695","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 Investigation of Unconditionally Stable Sequential Algorithms of Coupled Flow and Geomechanics for Hydraulically Fractured Systems","authors":"Jihoon Kim","doi":"10.2118/203938-ms","DOIUrl":"https://doi.org/10.2118/203938-ms","url":null,"abstract":"\u0000 We investigate unconditionally stable sequential algorithms for coupled hydraulically fractured geomechanics and flow systems, which can account for poromechanics behavior within the fractures. We focus on modifying the concepts of the fixed stress and undrained sequential methods properly for the coupled systems by taking appropriate stabilization terms for stability and convergence with energy analyses. Specifically, an apparent fracture stiffness is used for for numerical stabilization. Because this fracture stiffness depends on the fracture length, the stabilization term needs to be updated dynamically, different from the drained bulk modulus used for typical poromechanics problems. For numerical tests, we take the extended finite element method for geomechanics while the piecewise constant finite element method is used for flow within an existing hydraulic fracture. The numerical results support a priori stability analyses.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86239111","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 GPU-Based, Industrial Grade Compositional Reservoir Simulator","authors":"K. Esler, R. Gandham, L. Patacchini, T. Garipov, P. Panfili, F. Caresani, A. Pizzolato, A. Cominelli","doi":"10.2118/203929-ms","DOIUrl":"https://doi.org/10.2118/203929-ms","url":null,"abstract":"\u0000 Recently, graphics processing units (GPUs) have been demonstrated to provide a significant performance benefit for black-oil reservoir simulation, as well as flash calculations that serve an important role in compositional simulation. A comprehensive approach to compositional simulation based on GPUs had yet to emerge, and some questions remained as to whether the benefits observed in black-oil simulation would persist with a more complex fluid description. We present our positive answer to this question through the extension of a commercial GPU-based black-oil simulator to include a compositional description based on standard cubic equations of state. We describe the motivations for the formulation we select to make optimal use of GPU characteristics, including choice of primary variables and iteration scheme. We then describe performance results on an example sector model and simplified synthetic case designed to allow a detailed examination of scaling with respect to the number of hydrocarbon components and model size, as well as number of processors. We finally show results from two complex asset models (synthetic and real) and examine performance scaling with respect to GPU generation, demonstrating that performance correlates strongly with GPU memory bandwidth.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79105856","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":"Concept Exploration of a Surface Effect Patrol Combatant Using a Multiobjective Synthesis Model","authors":"Harry P. Crosby, Katherine E. Zalegowski, Raphael Christian C. Batto","doi":"10.5957/fast-2021-017","DOIUrl":"https://doi.org/10.5957/fast-2021-017","url":null,"abstract":"This paper demonstrates a concept design methodology for naval SESs that is adapted from modern surface combatant optimization techniques. Similar to current methods, a synthesis model is constructed that uses a variety of discrete and continuous input values to calculate ship characteristics and performance data. The model outputs are generated using a combination of first-principles and exact 3D geometry along with parametrics aggregated from conventional monohulls and SES historical data. A specifically formulated multiobjective genetic algorithm is integrated with the model. The algorithm explores the highly nonlinear and non-convex SES objective space to identify non-dominated design variants. The synthesis model and the associated design space for a patrol boat with a novel SES hullform is detailed. Tradeoffs are evaluated in objective criteria of cost and performance in high-speed littoral operations that include surveillance, reconnaissance, and surface warfare.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75035532","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":"Noise Measurements and Mitigation for a Foil Assisted Catamaran","authors":"K. Karri, N. Koyyapu","doi":"10.5957/fast-2021-021","DOIUrl":"https://doi.org/10.5957/fast-2021-021","url":null,"abstract":"Noise control recommendations and mitigation approaches for a foil-assisted catamaran become very sensitive when it comes to weight tradeoff. While weight control on a fast marine craft is critical, it reaches the uppermost limit when it comes to a foil-assisted catamaran. A foil-assisted catamaran is very sensitive to weight growth as well as the Longitudinal Center of Gravity (LCG) of the vessel in terms of reaching foil-assisted planing speeds. An increase in weight leads to a slow pre-planing speed which does not generate sufficient foil lift to transition the vessel into full planing speed. Whereas incorrect LCG of the vessel leads to wrong foil attack angle and thus leading to insufficient foil lift. This paper covers design philosophy, risk management, onboard measurements, weight management, mitigation approaches, and recommendations associated with the design of a 61 ft foil-assisted catamaran designed to reach 38+ knots and meet specific noise criteria limits at the maximum cruising speed as well as other operational conditions. An initial solution was applied, and the noise reduced at intermediate design speeds, however, at design cruising speeds the noise levels still exceeded the limits. Further computational analyses and mitigation methods such as insulation, mass-loaded vinyl, joiner barriers, viscoelastic coatings, trim adjustment, and floating floors were implemented on a trial-and-error basis to minimize the overall weight added to the vessel while achieving vessel design speed.","PeriodicalId":11146,"journal":{"name":"Day 1 Tue, October 26, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81482148","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}