Mathematical Methods And Modelling In Hydrocarbon Exploration And Production
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Mathematical Methods And Modelling In Hydrocarbon Exploration And Production
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Author : Armin Iske
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-01-27
Mathematical Methods And Modelling In Hydrocarbon Exploration And Production written by Armin Iske and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-01-27 with Mathematics categories.
Hydrocarbon exploration and production incorporate great technology challenges for the oil and gas industry. In order to meet the world's future demand for oil and gas, further technological advance is needed, which in turn requires research across multiple disciplines, including mathematics, geophysics, geology, petroleum engineering, signal processing, and computer science. This book addresses important aspects and fundamental concepts in hydrocarbon exploration and production. Moreover, new developments and recent advances in the relevant research areas are discussed, whereby special emphasis is placed on mathematical methods and modelling. The book reflects the multi-disciplinary character of the hydrocarbon production workflow, ranging from seismic data imaging, seismic analysis and interpretation and geological model building, to numerical reservoir simulation. Various challenges concerning the production workflow are discussed in detail. The thirteen chapters of this joint work, authored by international experts from academic and industrial institutions, include survey papers of expository character as well as original research articles. Large parts of the material presented in this book were developed between November 2000 and April 2004 through the European research and training network NetAGES, "Network for Automated Geometry Extraction from Seismic". The new methods described here are currently being implemented as software tools at Schlumberger Stavanger Research, one of the world's largest service providers to the oil industry.
Modern Engineering Mathematics
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Author : Abul Hasan Siddiqi
language : en
Publisher: CRC Press
Release Date : 2017-12-22
Modern Engineering Mathematics written by Abul Hasan Siddiqi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-22 with Mathematics categories.
This book is a compendium of fundamental mathematical concepts, methods, models, and their wide range of applications in diverse fields of engineering. It comprises essentially a comprehensive and contemporary coverage of those areas of mathematics which provide foundation to electronic, electrical, communication, petroleum, chemical, civil, mechanical, biomedical, software, and financial engineering. It gives a fairly extensive treatment of some of the recent developments in mathematics which have found very significant applications to engineering problems.
Introduction To Geological Uncertainty Management In Reservoir Characterization And Optimization
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Author : Reza Yousefzadeh
language : en
Publisher: Springer Nature
Release Date : 2023-04-08
Introduction To Geological Uncertainty Management In Reservoir Characterization And Optimization written by Reza Yousefzadeh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-08 with Technology & Engineering categories.
This book explores methods for managing uncertainty in reservoir characterization and optimization. It covers the fundamentals, challenges, and solutions to tackle the challenges made by geological uncertainty. The first chapter discusses types and sources of uncertainty and the challenges in different phases of reservoir management, along with general methods to manage it. The second chapter focuses on geological uncertainty, explaining its impact on field development and methods to handle it using prior information, seismic and petrophysical data, and geological parametrization. The third chapter deals with reducing geological uncertainty through history matching and the various methods used, including closed-loop management, ensemble assimilation, and stochastic optimization. The fourth chapter presents dimensionality reduction methods to tackle high-dimensional geological realizations. The fifth chapter covers field development optimization using robust optimization, including solutions for its challenges such as high computational cost and risk attitudes. The final chapter introduces different types of proxy models in history matching and robust optimization, discussing their pros and cons, and applications. The book will be of interest to researchers and professors, geologists and professionals in oil and gas production and exploration.
Enhance Oil And Gas Exploration With Data Driven Geophysical And Petrophysical Models
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Author : Keith R. Holdaway
language : en
Publisher: John Wiley & Sons
Release Date : 2017-10-09
Enhance Oil And Gas Exploration With Data Driven Geophysical And Petrophysical Models written by Keith R. Holdaway and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-09 with Business & Economics categories.
Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration. Recent and continual advances in machine learning are driving a rapid increase in empirical modeling capabilities. This book shows you how these new tools and methodologies can enhance geophysical and petrophysical data analysis, increasing the value of your exploration data. Apply data-driven modeling concepts in a geophysical and petrophysical context Learn how to get more information out of models and simulations Add value to everyday tasks with the appropriate Big Data application Adjust methodology to suit diverse geophysical and petrophysical contexts Data-driven modeling focuses on analyzing the total data within a system, with the goal of uncovering connections between input and output without definitive knowledge of the system's physical behavior. This multi-faceted approach pushes the boundaries of conventional modeling, and brings diverse fields of study together to apply new information and technology in new and more valuable ways. Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models takes you beyond traditional deterministic interpretation to the future of exploration data analysis.
Advances In Geophysics
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Author : Cedric Schmelzbach
language : en
Publisher: Academic Press
Release Date : 2018-11-13
Advances In Geophysics written by Cedric Schmelzbach and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-13 with Science categories.
Advances in Geophysics is a highly-respected publication in the field of geophysics. Since 1952, each volume has been eagerly awaited, frequently consulted, and praised by researchers and reviewers alike. Now with over 50 volumes, the series contains much material still relevant today – truly an essential publication for researchers in all fields of geophysics. Provides high-level reviews of the latest innovations in geophysics Written by recognized experts in the field Presents an essential publication for researchers in all fields of geophysics
Quantitative Geosciences Data Analytics Geostatistics Reservoir Characterization And Modeling
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Author : Y. Z. Ma
language : en
Publisher: Springer
Release Date : 2019-07-15
Quantitative Geosciences Data Analytics Geostatistics Reservoir Characterization And Modeling written by Y. Z. Ma and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-15 with Technology & Engineering categories.
Earth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosciences in three parts. Part 1 presents data analytics using probability, statistical and machine-learning methods. Part 2 covers reservoir characterization using several geoscience disciplines: including geology, geophysics, petrophysics and geostatistics. Part 3 treats reservoir modeling, resource evaluation and uncertainty analysis using integrated geoscience, engineering and geostatistical methods. As the petroleum industry is heading towards operating oil fields digitally, a multidisciplinary skillset is a must for geoscientists who need to use data analytics to resolve inconsistencies in various sources of data, model reservoir properties, evaluate uncertainties, and quantify risk for decision making. This book intends to serve as a bridge for advancing the multidisciplinary integration for digital fields. The goal is to move beyond using quantitative methods individually to an integrated descriptive-quantitative analysis. In big data, everything tells us something, but nothing tells us everything. This book emphasizes the integrated, multidisciplinary solutions for practical problems in resource evaluation and field development.
Algorithms For Approximation
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Author : Armin Iske
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-12-13
Algorithms For Approximation written by Armin Iske and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-12-13 with Mathematics categories.
Approximation methods are vital in many challenging applications of computational science and engineering. This is a collection of papers from world experts in a broad variety of relevant applications, including pattern recognition, machine learning, multiscale modelling of fluid flow, metrology, geometric modelling, tomography, signal and image processing. It documents recent theoretical developments which have lead to new trends in approximation, it gives important computational aspects and multidisciplinary applications, thus making it a perfect fit for graduate students and researchers in science and engineering who wish to understand and develop numerical algorithms for the solution of their specific problems. An important feature of the book is that it brings together modern methods from statistics, mathematical modelling and numerical simulation for the solution of relevant problems, with a wide range of inherent scales. Contributions of industrial mathematicians, including representatives from Microsoft and Schlumberger, foster the transfer of the latest approximation methods to real-world applications.
Shared Earth Modeling
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Author : Michel Perrin
language : en
Publisher: Editions TECHNIP
Release Date : 2013
Shared Earth Modeling written by Michel Perrin and has been published by Editions TECHNIP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Computer simulation categories.
Over the last two decades, earth modeling has become a major investigative tool for evaluating the potential of hydrocarbon reservoirs. Earth modelling must now face new challenges since petroleum exploration no longer consists in only investigating newly identified resources, but also in re-evaluating the potential of previously investigated reservoirs in the light of new prospecting data and of revised interpretations. Earth models incorporate a variety of different interpretations made on various types of data at successive steps of the modeling process. However, current modeling procedures provide no way to link a range of data and interpretations with a final earth model. For this reason, sharing and exchanging information about the model building process is at present a major difficulty. Recently, the term “Shared Earth Modeling” has been used for expressing the idea that earth models should be built in such a way that experts and end users can have access, at any time, to all the information incorporated into the model. This information does not only concern the data, but also the knowledge that geoscientists produce by interpreting these data. Accordingly, practical solutions must be studied for operating a knowledge-driven approach of Shared Earth Modeling. This is the goal of this book. This study of earth subsurface modeling is intended for several categories of readers. It concerns in the first place geologists, engineers and managers involved in the study and evaluation of subsurface reservoirs and hydrocarbon exploration. Relying on recent progress in various fields of computer sciences, the authors present innovative solutions for solving the critical issue of knowledge exchange at key steps of the modeling process. This book will also be of interest to researchers in computer science and, more generally, to engineers, researchers and students who wish to apply advanced knowledge-based techniques to complex engineering problems. Contents : Part I. Earth Models. 1. Earth models as subsurface representations. 2. Earth models for underground resource exploration and estimation. 3. Earth models used in petroleum industry: current practice and future challenges. Part II. Knowledge oriented solutions. 4. Knowledge based approach of a data intensive problem: seismic interpretation. 5. Individual surface representations and optimization. 6. Geological surface assemblage. 7. 3D Meshes for structural, stratigraphy and reservoir frameworks. 8. The data extension issue: geological constraints applied in geostatistical processes. Part III. Knowledge formalization. 9. Ontologies and their use for geological knowledge formalization. 10. Ontologies for Interpreting geochronological relationships. 11. Building ontologies for analyzing data expressed in natural language. 12. Ontology-based rock description and interpretation. Part IV. Knowledge management & applications. 13. Ontology integration and management within data intensive engineering systems. 14. Earth modeling using web services. 15. Full scale example of a knowledge-based method for building and managing an earth model. Part V. Conclusion. Appendix. Glossary.
Advanced Digital Signal Processing Of Seismic Data
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Author : Wail A. Mousa
language : en
Publisher: Cambridge University Press
Release Date : 2020-01-16
Advanced Digital Signal Processing Of Seismic Data written by Wail A. Mousa and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-16 with Business & Economics categories.
Presents an advanced overview of Digital Signal Processing and its applications to exploration seismology, for electrical engineers, geophysicists and petroleum professionals.
Adaptive Approach To Petroleum Reservoir Simulation
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Author : Stanislav Ursegov
language : en
Publisher: Springer Nature
Release Date : 2021-01-31
Adaptive Approach To Petroleum Reservoir Simulation written by Stanislav Ursegov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-31 with Science categories.
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.