Ensemble-Based Closed-Loop Optimization Applied to Brugge Field

2010 ◽  
Vol 13 (01) ◽  
pp. 56-71 ◽  
Author(s):  
Yan Chen ◽  
Dean S. Oliver
Keyword(s):  
Relative Permeability ◽  
Large Scale ◽  
Closed Loop ◽  
Net Present Value ◽  
Real Field ◽  
Test Case ◽  
Management Scenarios ◽  
Water Contact ◽  
Loop Optimization ◽  
Benchmark Study

Summary In this paper, ensemble-based closed-loop optimization is applied to a large-scale SPE benchmark study. The Brugge field, a synthetic reservoir, is designed as a common platform to test different closed-loop reservoir management methods. The problem was designed to mimic real field management scenarios and, as a result, is by far the largest and most complex test case on closed-loop optimization. The Brugge field model consists of nine layers with a total of 44,550 active cells. It has one internal fault and seven rock regions with different relative permeability and capillary pressure functions. There are 20 producers and 10 injectors in the field. Noise corrupted production data are provided monthly. Each well has three different completions that can be controlled independently. The producing life of the reservoir is 30 years, and the objective of optimization is to maximize the net present value (NPV) at the end of 30 years. Because of the complexity of this test case, several advanced techniques are used in order to improve the solution of the ensemble-based closed-loop optimization. First, covariance localization was used to obtain good model updates with a relatively small ensemble of reservoir models. Localization alleviated the effect of spurious correlations and made it possible to incorporate large amounts of data. Second, covariance inflation was used to compensate for the tendency of small ensembles to lose variability too quickly. When covariance inflation was used together with localization, variability in the ensemble was maintained. Third, regularization was also used in the ensemble-based optimization to reduce the effect of spurious correlations and to smooth the optimized control parameters. Fourth, normalized saturations were used in the state vector because different rock regions had different relative permeability endpoint saturations. Finally, the addition of global parameters such as relative permeability curves and initial oil/water contact (IOWC) reduced the tendency for overshoot. The resulting combination of ensemble-based data assimilation and optimization performed very well on the benchmark study, achieving an NPV within 1% of the value obtained by the test organizers with known geology.

Comparison of Various Discretization Schemes for Simulation of Large Field Case Reservoirs Using Unstructured Grids

2021 ◽  
Author(s):  
Samier Pierre ◽  
Raguenel Margaux ◽  
Darche Gilles
Keyword(s):  
Large Scale ◽  
Unstructured Grids ◽  
Computational Cost ◽  
Large Field ◽  
Real Field ◽  
Test Case ◽  
Generation Task ◽  
Field Case ◽  
Flux Approximation ◽  
Discretization Schemes

Abstract 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.

Localization of Ensemble-Based Control-Setting Updates for Production Optimization

SPE Journal ◽  
2011 ◽  
Vol 17 (01) ◽  
pp. 122-136 ◽  
Author(s):  
Yan Chen ◽  
Dean S. Oliver
Keyword(s):  
Net Present Value ◽  
Production Optimization ◽  
Test Case ◽  
Ensemble Size ◽  
Control Variables ◽  
Loop Optimization ◽  
Localization Method ◽  
Steepest Ascent ◽  
Control Setting ◽  
Improved Performance

Summary In the ensemble-based approach to production optimization (EnOpt), a steepest-ascent direction is computed from an ensemble of controls to iteratively improve a set of control settings. The method was shown to work well in maximizing field net present value (NPV) with an ensemble size of 104 on the Brugge SPE comparative test case for closed-loop optimization that had 84 controllable completion intervals (and 3,360 control variables), but performance of the method with smaller ensemble size or on larger problems might be difficult. Without regularization, the crosscovariance between control variables and the objective function is often likely to be dominated by spurious correlations. Because the update to the control variables is proportional to the covariance, spurious correlations will result in poor control settings. We propose a localization method that updates the control setting to optimize the field production while reconciling information from each individual well. The proposed localization method reduces the effect of spurious correlations for improved performance. The Brugge test case is used as an example to show that with covariance localization, greater efficiency could be achieved through the use of a smaller ensemble, or that for a given ensemble size, the optimization results can be improved.

scholarly journals Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance Evaluation

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 218
Author(s):  
Ala’ Khalifeh ◽  
Khalid A. Darabkh ◽  
Ahmad M. Khasawneh ◽  
Issa Alqaisieh ◽  
Mohammad Salameh ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Experimental Evaluation ◽  
Large Scale ◽  
Performance Metrics ◽  
Smart Cities ◽  
Field Tests ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Real Field

The advent of various wireless technologies has paved the way for the realization of new infrastructures and applications for smart cities. Wireless Sensor Networks (WSNs) are one of the most important among these technologies. WSNs are widely used in various applications in our daily lives. Due to their cost effectiveness and rapid deployment, WSNs can be used for securing smart cities by providing remote monitoring and sensing for many critical scenarios including hostile environments, battlefields, or areas subject to natural disasters such as earthquakes, volcano eruptions, and floods or to large-scale accidents such as nuclear plants explosions or chemical plumes. The purpose of this paper is to propose a new framework where WSNs are adopted for remote sensing and monitoring in smart city applications. We propose using Unmanned Aerial Vehicles to act as a data mule to offload the sensor nodes and transfer the monitoring data securely to the remote control center for further analysis and decision making. Furthermore, the paper provides insight about implementation challenges in the realization of the proposed framework. In addition, the paper provides an experimental evaluation of the proposed design in outdoor environments, in the presence of different types of obstacles, common to typical outdoor fields. The experimental evaluation revealed several inconsistencies between the performance metrics advertised in the hardware-specific data-sheets. In particular, we found mismatches between the advertised coverage distance and signal strength with our experimental measurements. Therefore, it is crucial that network designers and developers conduct field tests and device performance assessment before designing and implementing the WSN for application in a real field setting.

scholarly journals A large-scale 2005–2012 flood map record derived from ENVISAT-ASAR data: United Kingdom as a test case

2021 ◽  
Vol 256 ◽  
pp. 112338
Author(s):  
Jie Zhao ◽  
Ramona Pelich ◽  
Renaud Hostache ◽  
Patrick Matgen ◽  
Wolfgang Wagner ◽  
...  
Keyword(s):  
United Kingdom ◽  
Large Scale ◽  
Test Case ◽  
Envisat Asar

Accelerating Large-Format Metal Additive Manufacturing: How Controls R&D Is Driving Speed, Scale, and Efficiency

2020 ◽  
Author(s):  
Brian T. Gibson ◽  
Paritosh Mhatre ◽  
Michael C. Borish ◽  
Justin L. West ◽  
Emma D. Betters ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Large Scale ◽  
Closed Loop ◽  
Size Control ◽  
Pool Size ◽  
Large Format ◽  
Layer Height ◽  
Melt Pool ◽  
The Impact ◽  
Melt Pool Size

Abstract This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.

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