Day 2 Wed, March 29, 2023最新文献

{"title":"Multiscale Reservoir Simulation of High-Resolution Models","authors":"J. Natvig, Daniel Dias, F. Bratvedt, Shingo Watanabe, Zhuoyi Li, Antonina Kozlova, P. Tomin, Jiamin Jiang, Xundan Shi","doi":"10.2118/212231-ms","DOIUrl":"https://doi.org/10.2118/212231-ms","url":null,"abstract":"\u0000 To quantify the uncertainty in reservoir performance, it is common to build ensembles of models that sample the space of possible reservoirs that are consistent with the available data. To evaluate the spread of possible outcomes, simulations experiments are run for each model in the ensemble to calculate for instance recovery factor. The geoscreening workflow is a common way to do this systematically and in a reasonable time. It can work as follows: First, run simulations with simplified physics to calculate recovery factor for every model in the ensemble. Then, use recovery factor (and other quantities) to rank and select representative models for high, medium, and low performance scenarios that can be used for full field simulations.\u0000 In this paper we present an application of the multiscale sequential fully implicit (MS SFI) framework to simulate extremely complex high-resolution models with simplified physics. This enables us to perform fast evaluations of geological uncertainty, such as in the geoscreening workflow. The multiscale SFI method computes each timestep in two steps: First, it solves a nonlinear equation for pressure (and flow). Then, it solves a nonlinear equation for saturations and mole fractions. The pressure equation is solved iteratively using a multiscale approach.\u0000 The MS SFI method has recently been made generally available in a commercial reservoir simulator and can easily be benchmarked with a state-of-the-art fully implicit (FI) method. The MS SFI method was used to successfully simulate a realistic high-resolution geological model in a practical time frame, achieving approximately 10 times speedup in CPU time compared to the FI method. This demonstrates the ability of the MS SFI method to effectively deal with extremely complex models, enabling fast quantification of geological uncertainty with a shorter turnaround time. In many instances the MS SFI method enables simulation of large models at the original geological resolutions without the need for upscaling.\u0000 Finally, we demonstrate how the MS SFI method benefits a geology screening workflow and discuss future use of the MS SFI framework to create fit-for-purpose simulation engines for other workflows.","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":"131350708","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":"Deep Learning-Based Disentangled Parametrization for Model Calibration Under Multiple Geologic Scenarios","authors":"Junjie Yu, B. Jafarpour","doi":"10.2118/212177-ms","DOIUrl":"https://doi.org/10.2118/212177-ms","url":null,"abstract":"\u0000 Parametrization is widely used to improve the solution of ill-posed subsurface flow model calibration problems. Traditional low-dimensional parameterization methods consist of spatial and transform-domain methods with well-established mathematical properties that are mostly amenable to interpretation. More recent deep learning-based parametrization approaches exhibit strong performance in representing complex geological patterns but lack interpretability, making them less suitable for systematic updates based on expert knowledge. We present a disentangled parameterization approach with variational autoencoder (VAE) architecture to enable improved representation of complex spatial patterns and provide some degree of interpretability by allowing certain spatial features and attributes of a property map to be controlled by a single latent variable (generative factor), while remaining relatively invariant to changes in other latent factors. The existence of disentangled latent variables brings extra controllability to incorporate expert knowledge in making updates to the model. We explore two different approaches to achieve disentangled parameterization. In the first approach, we use β-VAE to learn disentangled factors in unsupervised learning manner, while in the second approach we apply the conditional VAE to represent discrete disentangled factors through supervised learning. By encoding the geologic scenarios into discrete latent codes, the parameterization enables automated scenario selection during inverse modeling and assisted updates on the spatial maps by experts. We present preliminary results using a single-phase pumping test example to show how model calibration can benefit from the proposed disentangled parameterization.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"62 2 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":"128015525","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":"Phase-Field Simulation of Near-Wellbore Nucleation and Propagation of Hydraulic Fractures in Enhanced Geothermal Systems (EGS)","authors":"F. Fei, A. Costa, J. Dolbow, R. Settgast, M. Cusini","doi":"10.2118/212251-ms","DOIUrl":"https://doi.org/10.2118/212251-ms","url":null,"abstract":"\u0000 Enhanced geothermal systems (EGS) rely on the artificial creation of fractures (i.e., hydraulic fractures) to enhance the permeability of the formation which would, otherwise, be too low to allow for fluid circulation. Hydraulic fracturing involves complex nucleation and propagation processes, which are key to the analysis and prediction of well productivity. Numerical simulations are commonly employed to understand the specific mechanisms behind nucleation and propagation of hydraulic fractures. However, most numerical approaches face tremendous challenges in tracking and accommodating the evolving fracture geometry, especially when curved and branched fractures occur. The phase-field method can overcome this obstacle, as it can model fracture propagation without the need for tracking the fracture tip nor for remeshing. However, the most common phase-field formulation is unable to accurately capture fracture nucleation. In this work, we develop a new phase-field approach for hydraulic fracturing that accounts for fracture nucleation due to the strengths of geologic material and the existence of small defects. Verification examples show that the proposed formulation can accurately predict near-wellbore nucleation and propagation of hydraulic fractures and the wellbore breakdown pressure. Simulation of a three-dimensional wellbore problem further demonstrates the efficiency of the proposed phase-field method in handling fracture nucleation and propagation.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"9 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":"115780692","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":"Accurate Production Forecast and Productivity Decline Analysis Using Coupled Full-Field and Near-Wellbore Poromechanics Modeling","authors":"Yan Li, Bin Wang, Jiehao Wang, K. Zaki, Ruiting Wu, Bradley Barnum, Peggy Rijken, B. Guyaguler","doi":"10.2118/212200-ms","DOIUrl":"https://doi.org/10.2118/212200-ms","url":null,"abstract":"\u0000 Productivity Index (PI) decline is caused by different mechanisms in both the wellbore region and the far field. The damages in the wellbore region can be simulated by detailed wellbore modeling. To incorporate field pressure evolution and impact on well productivity, a newly developed full-field and near-wellbore poromechanics coupling scheme is used to model PI degradation against time. Near wellbore damages, field and well interactions are identified when applying the coupling scheme for a deep water well. History matching, production forecast and safe drawdown limits are derived for operation decisions.\u0000 The coupling scheme is applied in a deep water well for history matching and drawdown strategy evaluation. The field model containing reservoir properties and operation conditions is coupled to multiple near-wellbore models which have completion and detailed wellbore geometry. During history matching, the field model is explicitly coupled with near-wellbore models. Field pressure is dynamically mapped into near-wellbore models and the PI multiplier in the field model for the given well(s) is updated based on near wellbore flow paths simulated in the near-wellbore models. Well productivity changes are accurately represented in the reservoir model for history matching and the production forecast.\u0000 Using the coupling scheme, we successfully history matched well production and the PI trend. PI decline damage mechanisms, such as perforation efficiency, fines migration, fracture connectivity, fracture conductivity, compaction, are modeled in the coupling scheme. At each coupling step, well productivity calculated in near-wellbore model(s) is updated as a PI multiplier for the well(s) in the field model. History matching results showed the dominant PI decline factors are perforation efficiency, fines migration, and fracture conductivity. Near wellbore perforation collapse reduces flowing area and changes flow path. Fines migration is observed at the high velocity region. It damages the permeability around high velocity flow path and the damage accumulates with time. Maintaining perforation efficiency and conducting a stimulation job to remove fines damage could mitigate PI decline.\u0000 Production forecast is performed with different drawdown rates. Results showed that there is no further PI decline with low drawdown. For high drawdown rate, PI could continue to decline and PI decline slope is related with drawdown pressure.","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":"122761858","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":"Dissipation-Based Nonlinear Solver for Efficient Implicit Simulation of Compositional and Discrete Fracture Models","authors":"Jiamin Jiang, Huanquan Pan","doi":"10.2118/212219-ms","DOIUrl":"https://doi.org/10.2118/212219-ms","url":null,"abstract":"\u0000 The solution of nonlinear equation-system resulting from the Fully Implicit Method (FIM) remains a challenge for numerically simulating multi-phase flow in subsurface fracture media. The Courant numbers can vary orders of magnitude across discrete fracture- matrix (DFM) models because of the high contrasts in the permeability and length-scale between matrix and fracture. The standard Newton solver is usually unable to converge for big timestep sizes or poor initial guesses.\u0000 Limited research has been conducted on nonlinear solver techniques for multi-phase compositional flow-transport in fractured media. We make an extension of a new dissipation-based continuation (DBC) algorithm to compositional and DFM models. Our goal is to prevent time-step cuttings and sustain efficient time-stepping for FIM. The DBC algorithm builds a homotopy of the discretized conservation equations through the addition of numerical dissipation terms. We introduce a continuation parameter for controlling the dissipation and ensuring that accuracy of the computed solution will not be reduced. Under the nonlinear framework of DBC, general dissipation operators and adaptive methods are developed to provide the optimal dissipation matrix for multiphase compositional hyperbolic systems.\u0000 We assess the new nonlinear solver through multiple numerical examples. Results reveal that the damped-Newton solver suffers from serious restrictions on timestep sizes and wasted iterations. In contrast, the DBC solver provides excellent computational performance. The dissipation operators are able to successfully resolve the main convergence difficulties. We also investigate the impact of star-delta transformation which removes the small cells at fracture intersections. Moreover, we demonstrate that an aggressive time-stepping does not affect the solution accuracy.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"29 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":"128816434","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":"Water Injection Optimization to Prevent Reservoir Souring","authors":"B. Izgec","doi":"10.2118/212253-ms","DOIUrl":"https://doi.org/10.2118/212253-ms","url":null,"abstract":"\u0000 This paper presents a three-stage integrated workflow using thermal/ geomechanical and thermal/ chemical simulation models to prevent reservoir souring during high concentration sulphate water injection. Reservoir souring takes place when sulphate reducing bacteria (SRB) is activated by cold injection water and gains access to high concentrations of sulphate along with volatile fatty acids (VFA) and/ or hydrocarbons (BTEX) as nutrients.\u0000 In the first stage a thermal/ chemical reservoir simulation model is history matched to quantify the changes in nutrient distribution around the injector. Earlier in the life of the well high volumes of low sulphate content water injection washes away the VFA/ BTEX in the near wellbore area creating a nutrient depleted zone for SRB.\u0000 In the second stage, a detailed wellbore model is coupled with a thermal/ geomechanical reservoir simulator and history matched to predict the downhole injection water temperature. Because the size of the cooled region changes with injection induced fractures extending from the wellbore into the formation, a thermal/ geomechanical simulation model is preferred.\u0000 The final stage of the workflow takes place later in the life of the injector when injection water has high sulphate concentrations. During this stage, the size of the formation cooling around the wellbore is constrained within the nutrient depleted zone with dynamic injection rate optimization to stop bacterial activity and accordingly reservoir souring.\u0000 Case studies from deepwater Gulf of Mexico reservoirs demonstrate how the workflow has been successfully operationalized to eliminate reservoir souring during high concentration sulphate water injection. Four years after the initiation of high sulphate concentration water injection, lack of sour gas production from the fields points to the robustness of the method. As suggested by the simulation models SRB activity is not promoted if cooling is only limited to the nutrient depleted zone.\u0000 This method helps quantify an upper limit for the sulphate concentration in injection water that will not cause reservoir souring. Chemical injections and/ or adjustments to the existing facility design is not required.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"28 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":"124609908","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":"Matrix Formulation for Simultaneous Calculations of Pressure and Temperature in Wells and Pipelines","authors":"I. N. Alves, R. Islam, José Savio Alves de Sousa Segundo","doi":"10.2118/212252-ms","DOIUrl":"https://doi.org/10.2118/212252-ms","url":null,"abstract":"\u0000 This paper presents a novel approach to calculate pressure and temperature profile in a pipe. An implicit formulation is implemented in this model using a combined system of the three conservation equations (mass, momentum, and energy), and using the change of enthalpy and pressure to calculate the change of temperature.\u0000 The derivation of the equations for temperature and pressure profile calculation uses the traditional approach of applying the mass, momentum and energy balance equations to a control volume of the pipe. For a pipe, usually the pressure and temperature values at one end are known. Due to the non-linearity of balance equation, an iterative process is required to calculate the values at the other end of the pipe. In the model proposed in this paper the system of equations was arranged in a matrix and vector form, all pressure and temperature for all the nodes are calculated in one calculation step, different from the traditional approach.\u0000 The proposed model is used with both Black oil table correlations and a fully compositional model for calculating P-T profiles. It can be applied over the entire inclination angle range from horizontal to vertical. Conventionally, marching algorithm is used to calculate pressure from first cell to second cell until the end of the pipe is reached. The final form of energy balance is expressed in terms of enthalpy; therefore, P-H flash is used to calculate temperature profile. The calculation process is faster as all of it is done in one step and more accurate than the traditional approach.\u0000 Traditionally the coupling of the mechanical energy and heat balance equation, uses a marching algorithm to determine pressure and temperature profile in a pipe, using a nested pair of loops, usually the external one for temperature and an internal for pressure. The proposed method applies a novel matrix formulation using a vectorized procedure to determine simultaneously pressure and temperature using their natural connection the enthalpy through the balance equations. This method aims to determine pressure-temperature profiles in a fast and accurate way. Vector and matrices approach is a tool that improves the performance of a code and utilizing it for pipeline calculation is unique, it opens a door for also coupling with reservoir simulators in an integrated approach. Since most flow assurance problems i.e. paraffin, hydrate are related to pressure and temperature dependent, the proper calculation of the P-T profile is a must. The proposed model provides a fast and precise calculation organizing the problem in a structured manner.","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":"114373480","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":"Smooth Formulation for Three-Phase Black-Oil Simulation with Superior Nonlinear Convergence","authors":"Jiamin Jiang, X. Wen","doi":"10.2118/212261-ms","DOIUrl":"https://doi.org/10.2118/212261-ms","url":null,"abstract":"\u0000 Black-oil simulations with phase changes are challenging, because of the complex interactions between the different components and the equilibrium behavior of the phases. The common method for solving this type of nonlinear problem is to use a fully-implicit approach. However, the conventional black-oil model can lead to difficulties with converging using Newton's method. Discontinuities in discrete system can occur when a phase transition happens, which can lead to oscillations or even failure of the Newton iterations. The goal is to design a smoothing formulation that eliminates any sudden changes in properties or discontinuities that occur during phase transitions.\u0000 We first employ a compositional formulation based on K-values to describe the standard black-oil model. Next, the coupled system is reformulated such that the discontinuities are carried over to the phase equilibrium model. In this manner, a single, succinct non-smooth equation is obtained, which allows for deriving a smoothing approximation. A mixed complementarity problem (MCP) for phase-equilibrium in the area of chemical process modeling served as the foundation for the reformulation. The new formulation is non-intrusive and simple to implement, requiring minor changes to current black-oil simulator frameworks.\u0000 We analyze and demonstrate that phase changes lead to the changes of fluid-properties and discrete system, under the conventional black-oil formulation. By comparison, the newly proposed formulation uses a smoothing parameter to ensure smooth transitions of variables between the phase regimes. It also generates unique solutions that are valid for all three phases. Several complex heterogeneous problems are tested. The conventional black-oil model experiences many time-step cuttings and wasting nonlinear iterates. On the contrary, the smoothing model exhibits excellent convergence behaviors. Overall, the new formulation addresses the issues with convergence caused by phase-changes, while barely affecting solution results.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"18 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":"122574392","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":"High Performance Integrated Asset Modeling: A Giant Gas Field Case Study","authors":"Andrea Rosa, K. Wiegand, K. Mukundakrishnan, A. Pizzolato, P. Panfili, A. Cominelli, Silvia Picone, Rosario Ruffino, L. Patacchini","doi":"10.2118/212246-ms","DOIUrl":"https://doi.org/10.2118/212246-ms","url":null,"abstract":"\u0000 We present the development of a field-scale simulation tool coupling the model of Zohr, a super giant deepwater gas reservoir requiring a multi-million active cells grid with dual porosity/dual permeability formulation, to its gathering network. Deepwater field development often relies on a complex subsea gathering infrastructure, possibly evolving over time and leading to a complex topology. Here, facilities route the multiphase production stream to an onshore compression plant throughout a network with bifurcations.\u0000 To perform integrated modeling of such assets, we have developed a Facility Network Solver (FNS) with flexible topology, whose formulation relies on a graph representation with continuity equations at nodes and tabulated constitutive equations at edges. FNS was designed to be integrated with the industrial grade GPU-based reservoir simulator used in the company, both jointly developed by Eni and Stone Ridge Technology, with emphasis on preserving usability and simulation performance.\u0000 The correctness of FNS results in the presence of bifurcations was thoroughly assessed in standalone mode, through benchmarking against what is today considered a reference commercial network solver. FNS integration with the reservoir simulator enables forecasts where the back-pressure is taken into account. Engineers can better assess the viability of different development scenarios, including dynamic upgrades to the network topology, using reservoir simulation workflows they are well accustomed to. In particular, a single tool replaces often heterogeneous associations of third-party software, without impacting simulation time.\u0000 Sensitivity analyses were performed on both coupling frequency and location. It was concluded that periodic coupling at the well-head was a satisfactory setting, yielding negligible performance overhead with respect to standalone reservoir simulations, thus enabling the integrated model to be used routinely as the sole simulation model.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"38 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":"128088462","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":"Successful Application of an Ensemble Modeling Workflow for a Deepwater Field in US Gulf of Mexico","authors":"Vivek Peraser, Eugene Shen, Will Dugat, M. Sweatman, Gerardo Cedillo","doi":"10.2118/212173-ms","DOIUrl":"https://doi.org/10.2118/212173-ms","url":null,"abstract":"\u0000 A Deepwater field in the Gulf of Mexico is currently in its mid-production life and undergoing development optimization, which was underpinned by a robust evaluation using multiple geologic scenarios that were history matched to observed field data. This challenge was addressed using an ensemble modeling workflow that has been guided by BP's Top-Down Reservoir Modeling (TDRMTM) (1) principles. The ensemble contained 27 distinct geologic scenarios and was used to evaluate water injection, field expansion, and infills.\u0000 For a wide range of geologic scenarios covering alternate structural and stratigraphic models, a workflow called \"forced boxing\" was executed along with the assisted history matching algorithm, PSO-MADS (2, 3), to fully history match historical rates and pressures for more than 27 distinct combinations of geologic scenarios. These scenarios covered a wide range of oil-in place, connectivity, aquifer strength, and relative permeability behavior. The final calibrated ensemble of 1000s of models was then down sampled to ~100 distinct models to use for the probabilistic evaluation of water injection, field expansion, and infills.\u0000 The \"forced boxing\" technique was successful at finding high quality history matches for 25 of the 27 distinct geologic scenarios. The history matching workflow considered well-level production rates, including water cut, as well as reservoir pressure measurements (MDTs). A match quality acceptance workflow was set up to find acceptable models out of each geologic scenario. The resulting ensemble of models contained over 20,000 distinct simulation cases. A methodology was used to down sample those cases to a final ensemble of ~100 models covering the 25 geologic scenarios. This workflow is an improvement to conventional history matching and uncertainty workflows because this workflow ensures multiple geologic scenarios are matched and included in the ensemble and the final set of models gives a probabilistic view of the predictive outcomes. The ~100 model ensemble was then utilized to explore different field development opportunities and included the successful selection of an economic infill producer target.\u0000 The \"forced boxing\" approach, which entailed history matching distinct static parameter combinations, was built to ensure diversity of scenarios/outcomes as opposed to traditional workflows that focus on finding the best history matches. Given the importance of cross-fault communication between different reservoir sands, the parameterization of fault throws as a variable controlled in the optimization process was also a novel addition to the history matching workflow.","PeriodicalId":205933,"journal":{"name":"Day 2 Wed, March 29, 2023","volume":"37 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":"133909005","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}