755 research outputs found
The Open Porous Media Flow Reservoir Simulator
The Open Porous Media (OPM) initiative is a community effort that encourages
open innovation and reproducible research for simulation of porous media
processes. OPM coordinates collaborative software development, maintains and
distributes open-source software and open data sets, and seeks to ensure that
these are available under a free license in a long-term perspective.
In this paper, we present OPM Flow, which is a reservoir simulator developed
for industrial use, as well as some of the individual components used to make
OPM Flow. The descriptions apply to the 2019.10 release of OPM.Comment: 43 pages, 22 figure
Tracing back the source of contamination
From the time a contaminant is detected in an observation well, the question of where and when the contaminant was introduced in the aquifer needs an answer. Many techniques have been proposed to answer this question, but virtually all of them assume that the aquifer and its dynamics are perfectly known. This work discusses a new approach for the simultaneous identification of the contaminant source location and the spatial variability of hydraulic conductivity in an aquifer which has been validated on synthetic and laboratory experiments and which is in the process of being validated on a real aquifer
Parallel software tool for decomposing and meshing of 3d structures
An algorithm for automatic parallel generation of three-dimensional unstructured computational meshes based on geometrical domain decomposition is proposed in this paper. Software package build upon proposed algorithm is described. Several practical examples of mesh generation on multiprocessor computational systems are given. It is shown that developed parallel algorithm enables us to reduce mesh generation time significantly (dozens of times). Moreover, it easily produces meshes with number of elements of order 5 · 107, construction of those on a single CPU is problematic. Questions of time consumption, efficiency of computations and quality of generated meshes are also considered
A NEW GENERATION CHEMICAL FLOODING SIMULATOR Semi-annual Report for the Period
ABSTRACT 4 SUMMARY 4 Task 1: Formulation and development of Solution Scheme
Adaptive machine learning-based surrogate modeling to accelerate PDE-constrained optimization in enhanced oil recovery
In this contribution, we develop an efficient surrogate modeling framework for simulation-based optimization of enhanced oil recovery, where we particularly focus on polymer flooding. The computational approach is based on an adaptive training procedure of a neural network that directly approximates an input-output map of the underlying PDE-constrained optimization problem. The training process thereby focuses on the construction of an accurate surrogate model solely related to the optimization path of an outer iterative optimization loop. True evaluations of the objective function are used to finally obtain certified results. Numerical experiments are given to evaluate the accuracy and efficiency of the approach for a heterogeneous five-spot benchmark problem.publishedVersio
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