Reservoir Simulation - an overview | ScienceDirect Topics
2012年10月5日 · Reservoir simulation is an area of reservoir engineering where computer models are used to predict flow of fluids through porous media. In EnKF method, static parameters like porosity, permeability and dynamic variables are updated to match with real-time production data.
Reservoir Simulations - ScienceDirect
Reservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in reservoir simulation, learning from current experiments and speeding up potential collaboration opportunities in research and technology. This reference explains common terminology, concepts, and equations through multiple ...
Petroleum Reservoir Simulation - ScienceDirect
Petroleum Reservoir Simulation, Second Edition, introduces this novel engineering approach for petroleum reservoir modeling and operations simulations. Updated with new exercises, a new glossary and a new chapter on how to create the data to run a simulation, this comprehensive reference presents step-by-step numerical procedures in an easy to ...
Machine learning to improve natural gas reservoir simulations
2022年1月1日 · Reservoir simulation is a strategy, or set of techniques, by which a numerical model of the geophysical and geological characteristics of a subterranean resource, and the (single phase or multiphase) fluid system is used to investigate and predict how the available fluids flow through a porous and permeable medium into the stock tank.
Importance of reservoir simulation and early reservoir …
2022年11月1日 · Reservoir simulation requires the model to be initialized with various field properties such as relative permeability curves, rock compaction function, PVT data, fluid contacts, initial pressure and temperature. Generally, the reservoir sand is clean and continuous. The porosity values are log-derived, and distributed geo-statistically.
Principles of Applied Reservoir Simulation | ScienceDirect
Reservoir engineers today need to acquire more complex reservoir management and modeling skills. Principles of Applied Reservoir Simulation, Fourth Edition, continues to provide the fundamentals on these topics for both early and seasoned career engineers and researchers. Enhanced with more practicality and with a focus on more modern reservoir ...
Physics-informed neural network-based petroleum reservoir …
2023年12月1日 · Li et al. (2022) introduced a TGNN model that integrates high-fidelity numerical simulation data, fundamental physical laws, boundary conditions, initial conditions, expert knowledge, and engineering control terms in the loss function, enabling the solution of two-phase subsurface flow problems at the reservoir scale beyond the Buckley ...
Reservoir simulation and modeling based on artificial intelligence …
2011年12月1日 · Surrogate Reservoir Model (SRM) is an accurate replica of the traditional numerical reservoir simulation model. It may be questioned that when a numerical reservoir simulation model exists why an AI-based Reservoir Model would be necessary.
A novel methodology for fast reservoir simulation of single-phase …
2022年12月1日 · SETRF = Total Simulation Execution time taken before the application of Machine learning based model Total Simulation Execution time taken after the application of Machine learning based model = 700 s 250 s = 3 From the above table, it is clear that through the application of this novel ML-based reservoir simulator, the simulation execution ...
Modeling and simulating of reservoir operation using the artificial ...
2018年10月1日 · The AI model has the ability to address complex nonlinear prediction problems, which is widely applied in the field of reservoir operation simulation. At present, reports on the performance comparison and analysis of AI models are common, but such reports mainly focus on the global precision comparison analysis of a single time scale.