Data-driven Reservoir Modeling PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data-driven Reservoir Modeling PDF full book. Access full book title Data-driven Reservoir Modeling by Shahab D. Mohaghegh. Download full books in PDF and EPUB format.
Author: Shahab D. Mohaghegh
Publisher:
ISBN: 9781613995600
Category : Data mining
Languages : en
Pages : 165
Get Book Here
Book Description
Author: Shahab D. Mohaghegh
Publisher:
ISBN: 9781613995600
Category : Data mining
Languages : en
Pages : 165
Get Book Here
Book Description
Author: Shahab D. Mohaghegh
Publisher: Springer
ISBN: 3319487531
Category : Technology & Engineering
Languages : en
Pages : 292
Get Book Here
Book Description
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.
Author: Sathish Sankaran
Publisher:
ISBN: 9781613998205
Category :
Languages : en
Pages : 108
Get Book Here
Book Description
Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.
Author: Shahab Mohaghegh
Publisher: CRC Press
ISBN: 1315280795
Category : Science
Languages : en
Pages : 308
Get Book Here
Book Description
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.
Author: Srikanta Mishra
Publisher: Elsevier
ISBN: 0128032804
Category : Science
Languages : en
Pages : 252
Get Book Here
Book Description
Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. - Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains - Written by practitioners for practitioners - Presents an easy to follow narrative which progresses from simple concepts to more challenging ones - Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences - Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications
Author: Knut-Andreas Lie
Publisher: Cambridge University Press
ISBN: 1108492436
Category : Business & Economics
Languages : en
Pages : 677
Get Book Here
Book Description
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.
Author: Marian Bubak
Publisher: Springer Science & Business Media
ISBN: 3540221166
Category : Computers
Languages : en
Pages : 1376
Get Book Here
Book Description
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.
Author: Renji Remesan
Publisher: Springer
ISBN: 3319092359
Category : Science
Languages : en
Pages : 261
Get Book Here
Book Description
This book explores a new realm in data-based modeling with applications to hydrology. Pursuing a case study approach, it presents a rigorous evaluation of state-of-the-art input selection methods on the basis of detailed and comprehensive experimentation and comparative studies that employ emerging hybrid techniques for modeling and analysis. Advanced computing offers a range of new options for hydrologic modeling with the help of mathematical and data-based approaches like wavelets, neural networks, fuzzy logic, and support vector machines. Recently machine learning/artificial intelligence techniques have come to be used for time series modeling. However, though initial studies have shown this approach to be effective, there are still concerns about their accuracy and ability to make predictions on a selected input space.
Author: Stanislav Ursegov
Publisher: Springer Nature
ISBN: 3030674746
Category : Science
Languages : en
Pages : 91
Get Book Here
Book Description
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.
Author: Philip Ringrose
Publisher: Springer
ISBN: 9400754973
Category : Science
Languages : en
Pages : 260
Get Book Here
Book Description
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
