Data-driven Reservoir Modeling
| Author | : Shahab D. Mohaghegh |
| Publisher | : |
| Total Pages | : 165 |
| Release | : 2017 |
| Genre | : Data mining |
| ISBN | : 9781613995600 |
Data Driven Reservoir Modeling
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Shale Analytics
| Author | : Shahab D. Mohaghegh |
| Publisher | : Springer |
| Total Pages | : 292 |
| Release | : 2017-02-09 |
| Genre | : Technology & Engineering |
| ISBN | : 3319487531 |
This book describes the application of modern information technology to reservoir modeling and well management in shale. While covering Shale Analytics, it focuses on reservoir modeling and production management of shale plays, since conventional reservoir and production modeling techniques do not perform well in this environment. Topics covered include tools for analysis, predictive modeling and optimization of production from shale in the presence of massive multi-cluster, multi-stage hydraulic fractures. Given the fact that the physics of storage and fluid flow in shale are not well-understood and well-defined, Shale Analytics avoids making simplifying assumptions and concentrates on facts (Hard Data - Field Measurements) to reach conclusions. Also discussed are important insights into understanding completion practices and re-frac candidate selection and design. The flexibility and power of the technique is demonstrated in numerous real-world situations.
Data Analytics in Reservoir Engineering
| Author | : Sathish Sankaran |
| Publisher | : |
| Total Pages | : 108 |
| Release | : 2020-10-29 |
| Genre | : |
| ISBN | : 9781613998205 |
Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.
Data-Driven Analytics for the Geological Storage of CO2
| Author | : Shahab Mohaghegh |
| Publisher | : CRC Press |
| Total Pages | : 308 |
| Release | : 2018-05-20 |
| Genre | : Science |
| ISBN | : 1315280795 |
Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of artificial intelligence and machine learning in data-driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of artificial intelligence and machine learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.
Data-Driven Science and Engineering
| Author | : Steven L. Brunton |
| Publisher | : Cambridge University Press |
| Total Pages | : 615 |
| Release | : 2022-05-05 |
| Genre | : Computers |
| ISBN | : 1009098489 |
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
An Introduction to Reservoir Simulation Using MATLAB/GNU Octave
| Author | : Knut-Andreas Lie |
| Publisher | : Cambridge University Press |
| Total Pages | : 677 |
| Release | : 2019-08-08 |
| Genre | : Business & Economics |
| ISBN | : 1108492436 |
Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students. This title is also available as Open Access on Cambridge Core.
Adaptive Approach to Petroleum Reservoir Simulation
| Author | : Stanislav Ursegov |
| Publisher | : Springer Nature |
| Total Pages | : 91 |
| Release | : 2021-01-31 |
| Genre | : Science |
| ISBN | : 3030674746 |
This book presents unique features of the adaptive modeling approach based on new machine learning algorithms for petroleum exploration, development, and production. The adaptive approach helps simulation engineers and geoscientists to create adequate geological and hydrodynamic models. This approach is proven to be a real alternative to traditional techniques, such as deterministic modeling. Currently, machine-learning algorithms grow in popularity because they provide consistency, predictiveness, and convenience. The primary purpose of this book is to describe the theoretical state of the adaptive approach and show some examples of its implementation in simulation and forecasting different reservoir processes.
Reservoir Model Design
| Author | : Philip Ringrose |
| Publisher | : Springer |
| Total Pages | : 260 |
| Release | : 2014-10-03 |
| Genre | : Science |
| ISBN | : 9400754973 |
This book gives practical advice and ready to use tips on the design and construction of subsurface reservoir models. The design elements cover rock architecture, petrophysical property modelling, multi-scale data integration, upscaling and uncertainty analysis. Philip Ringrose and Mark Bentley share their experience, gained from over a hundred reservoir modelling studies in 25 countries covering clastic, carbonate and fractured reservoir types. The intimate relationship between geology and fluid flow is explored throughout, showing how the impact of fluid type, production mechanism and the subtleties of single- and multi-phase flow combine to influence reservoir model design. Audience: The main audience for this book is the community of applied geoscientists and engineers involved in the development and use of subsurface fluid resources. The book is suitable for a range of Master’s level courses in reservoir characterisation, modelling and engineering. · Provides practical advice and guidelines for users of 3D reservoir modelling packages · Gives advice on reservoir model design for the growing world-wide activity in subsurface reservoir modelling · Covers rock modelling, property modelling, upscaling and uncertainty handling · Encompasses clastic, carbonate and fractured reservoirs
Advanced Modeling with the MATLAB Reservoir Simulation Toolbox
| Author | : Knut-Andreas Lie |
| Publisher | : Cambridge University Press |
| Total Pages | : 625 |
| Release | : 2021-11-25 |
| Genre | : Technology & Engineering |
| ISBN | : 1009022490 |
Many leading experts contribute to this follow-up to An Introduction to Reservoir Simulation using MATLAB/GNU Octave: User Guide for the MATLAB Reservoir Simulation Toolbox (MRST). It introduces more advanced functionality that has been recently added to the open-source MRST software. It is however a self-contained introduction to a variety of modern numerical methods for simulating multiphase flow in porous media, with applications to geothermal energy, chemical enhanced oil recovery (EOR), flow in fractured and unconventional reservoirs, and in the unsaturated zone. The reader will learn how to implement new models and algorithms in a robust, efficient manner. A large number of numerical examples are included, all fully equipped with code and data so that the reader can reproduce the results and use them as a starting point for their own work. Like the original textbook, this book will prove invaluable for researchers, professionals and advanced students using reservoir simulation methods. This title is available as Open Access on Cambridge Core.
Computational Science — ICCS 2004
| Author | : Marian Bubak |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 1376 |
| Release | : 2004-05-26 |
| Genre | : Computers |
| ISBN | : 3540221166 |
The International Conference on Computational Science (ICCS 2004) held in Krak ́ ow, Poland, June 6–9, 2004, was a follow-up to the highly successful ICCS 2003 held at two locations, in Melbourne, Australia and St. Petersburg, Russia; ICCS 2002 in Amsterdam, The Netherlands; and ICCS 2001 in San Francisco, USA. As computational science is still evolving in its quest for subjects of inves- gation and e?cient methods, ICCS 2004 was devised as a forum for scientists from mathematics and computer science, as the basic computing disciplines and application areas, interested in advanced computational methods for physics, chemistry, life sciences, engineering, arts and humanities, as well as computer system vendors and software developers. The main objective of this conference was to discuss problems and solutions in all areas, to identify new issues, to shape future directions of research, and to help users apply various advanced computational techniques. The event harvested recent developments in com- tationalgridsandnextgenerationcomputingsystems,tools,advancednumerical methods, data-driven systems, and novel application ?elds, such as complex - stems, ?nance, econo-physics and population evolution.
