Unconventional Hydrocarbon Resources: Prediction and Modeling Using Artificial Intelligence Approaches

Unconventional Hydrocarbon Resources: Prediction and Modeling Using Artificial Intelligence Approaches PDF Author: Sid-Ali Ouadfeul
Publisher: John Wiley & Sons
ISBN: 1119389372
Category : Science
Languages : en
Pages : 324

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Book Description
Unconventional Hydrocarbon Resources Enables readers to save time and effort in exploring and exploiting shale gas and other unconventional fossil fuels by making use of advanced predictive tools Unconventional Hydrocarbon Resources highlights novel concepts and techniques for the geophysical exploration of shale and other tight hydrocarbon reservoirs, focusing on artificial intelligence approaches for modeling and predicting key reservoir properties such as pore pressure, water saturation, and wellbore stability. Numerous application examples and case studies present real-life data from different unconventional hydrocarbon fields such as the Barnett Shale (USA), the Williston Basin (USA), and the Berkine Basin (Algeria). Unconventional Hydrocarbon Resources explores a wide range of reservoir properties, including modeling of the geomechanics of shale gas reservoirs, petrophysics analysis of shale and tight sand gas reservoirs, and prediction of hydraulic fracturing effects, fluid flow, and permeability. Sample topics covered in Unconventional Hydrocarbon Resources include: Calculation of petrophysical parameter curves for non-conventional reservoir modeling and characterization Comparison of the Levenberg-Marquardt and conjugate gradient learning methods for total organic carbon prediction in the Barnett shale gas reservoir Use of pore effective compressibility for quantitative evaluation of low resistive pays and identifying sweet spots in shale reservoirs Pre-drill pore pressure estimation in shale gas reservoirs using seismic genetic inversion Using well-log data to classify lithofacies of a shale gas reservoir Unconventional Hydrocarbon Resources is a valuable resource for researchers and professionals working on unconventional hydrocarbon exploration and in geoengineering projects.

Unconventional Hydrocarbon Resources: Prediction and Modeling Using Artificial Intelligence Approaches

Unconventional Hydrocarbon Resources: Prediction and Modeling Using Artificial Intelligence Approaches PDF Author: Sid-Ali Ouadfeul
Publisher: John Wiley & Sons
ISBN: 1119389372
Category : Science
Languages : en
Pages : 324

Get Book

Book Description
Unconventional Hydrocarbon Resources Enables readers to save time and effort in exploring and exploiting shale gas and other unconventional fossil fuels by making use of advanced predictive tools Unconventional Hydrocarbon Resources highlights novel concepts and techniques for the geophysical exploration of shale and other tight hydrocarbon reservoirs, focusing on artificial intelligence approaches for modeling and predicting key reservoir properties such as pore pressure, water saturation, and wellbore stability. Numerous application examples and case studies present real-life data from different unconventional hydrocarbon fields such as the Barnett Shale (USA), the Williston Basin (USA), and the Berkine Basin (Algeria). Unconventional Hydrocarbon Resources explores a wide range of reservoir properties, including modeling of the geomechanics of shale gas reservoirs, petrophysics analysis of shale and tight sand gas reservoirs, and prediction of hydraulic fracturing effects, fluid flow, and permeability. Sample topics covered in Unconventional Hydrocarbon Resources include: Calculation of petrophysical parameter curves for non-conventional reservoir modeling and characterization Comparison of the Levenberg-Marquardt and conjugate gradient learning methods for total organic carbon prediction in the Barnett shale gas reservoir Use of pore effective compressibility for quantitative evaluation of low resistive pays and identifying sweet spots in shale reservoirs Pre-drill pore pressure estimation in shale gas reservoirs using seismic genetic inversion Using well-log data to classify lithofacies of a shale gas reservoir Unconventional Hydrocarbon Resources is a valuable resource for researchers and professionals working on unconventional hydrocarbon exploration and in geoengineering projects.

Unconventional Hydrocarbon Resources: Prediction and Modeling Using Artificial Intelligence Approaches

Unconventional Hydrocarbon Resources: Prediction and Modeling Using Artificial Intelligence Approaches PDF Author: Sid-Ali Ouadfeul
Publisher: John Wiley & Sons
ISBN: 1119389364
Category : Science
Languages : en
Pages : 324

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Book Description
Unconventional Hydrocarbon Resources Enables readers to save time and effort in exploring and exploiting shale gas and other unconventional fossil fuels by making use of advanced predictive tools Unconventional Hydrocarbon Resources highlights novel concepts and techniques for the geophysical exploration of shale and other tight hydrocarbon reservoirs, focusing on artificial intelligence approaches for modeling and predicting key reservoir properties such as pore pressure, water saturation, and wellbore stability. Numerous application examples and case studies present real-life data from different unconventional hydrocarbon fields such as the Barnett Shale (USA), the Williston Basin (USA), and the Berkine Basin (Algeria). Unconventional Hydrocarbon Resources explores a wide range of reservoir properties, including modeling of the geomechanics of shale gas reservoirs, petrophysics analysis of shale and tight sand gas reservoirs, and prediction of hydraulic fracturing effects, fluid flow, and permeability. Sample topics covered in Unconventional Hydrocarbon Resources include: Calculation of petrophysical parameter curves for non-conventional reservoir modeling and characterization Comparison of the Levenberg-Marquardt and conjugate gradient learning methods for total organic carbon prediction in the Barnett shale gas reservoir Use of pore effective compressibility for quantitative evaluation of low resistive pays and identifying sweet spots in shale reservoirs Pre-drill pore pressure estimation in shale gas reservoirs using seismic genetic inversion Using well-log data to classify lithofacies of a shale gas reservoir Unconventional Hydrocarbon Resources is a valuable resource for researchers and professionals working on unconventional hydrocarbon exploration and in geoengineering projects.

Unconventional Hydrocarbon Resources

Unconventional Hydrocarbon Resources PDF Author: Reza Barati
Publisher: John Wiley & Sons
ISBN: 1119420490
Category : Science
Languages : en
Pages : 608

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Book Description
A comprehensive textbook presenting techniques for the analysis and characterization of shale plays Significant reserves of hydrocarbons cannot be extracted using conventional methods. Improvements in techniques such as horizontal drilling and hydraulic fracturing have increased access to unconventional hydrocarbon resources, ushering in the “shale boom” and disrupting the energy sector. Unconventional Hydrocarbon Resources: Techniques for Reservoir Engineering Analysis covers the geochemistry, petrophysics, geomechanics, and economics of unconventional shale oil plays. The text uses a step-by-step approach to demonstrate industry-standard workflows for calculating resource volume and optimizing the extraction process. Volume highlights include: Methods for rock and fluid characterization of unconventional shale plays A workflow for analyzing wells with stimulated reservoir volume regions An unconventional approach to understanding of fluid flow through porous media A comprehensive summary of discoveries of massive shale resources worldwide Data from Eagle Ford, Woodford, Wolfcamp, and The Bakken shale plays Examples, homework assignments, projects, and access to supplementary online resources Hands-on teaching materials for use in petroleum engineering software applications The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

Shale Analytics

Shale Analytics PDF Author: Shahab D. Mohaghegh
Publisher: Springer
ISBN: 3319487531
Category : Technology & Engineering
Languages : en
Pages : 287

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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.

Applications of Artificial Intelligence Techniques in the Petroleum Industry

Applications of Artificial Intelligence Techniques in the Petroleum Industry PDF Author: Abdolhossein Hemmati-Sarapardeh
Publisher: Gulf Professional Publishing
ISBN: 0128223855
Category : Science
Languages : en
Pages : 324

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Book Description
Applications of Artificial Intelligence Techniques in the Petroleum Industry gives engineers a critical resource to help them understand the machine learning that will solve specific engineering challenges. The reference begins with fundamentals, covering preprocessing of data, types of intelligent models, and training and optimization algorithms. The book moves on to methodically address artificial intelligence technology and applications by the upstream sector, covering exploration, drilling, reservoir and production engineering. Final sections cover current gaps and future challenges. Teaches how to apply machine learning algorithms that work best in exploration, drilling, reservoir or production engineering Helps readers increase their existing knowledge on intelligent data modeling, machine learning and artificial intelligence, with foundational chapters covering the preprocessing of data and training on algorithms Provides tactics on how to cover complex projects such as shale gas, tight oils, and other types of unconventional reservoirs with more advanced model input

Machine Learning and Flow Assurance in Oil and Gas Production

Machine Learning and Flow Assurance in Oil and Gas Production PDF Author: Bhajan Lal
Publisher: Springer Nature
ISBN: 3031242319
Category : Technology & Engineering
Languages : en
Pages : 179

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Book Description
This book is useful to flow assurance engineers, students, and industries who wish to be flow assurance authorities in the twenty-first-century oil and gas industry. The use of digital or artificial intelligence methods in flow assurance has increased recently to achieve fast results without any thorough training effectively. Generally, flow assurance covers all risks associated with maintaining the flow of oil and gas during any stage in the petroleum industry. Flow assurance in the oil and gas industry covers the anticipation, limitation, and/or prevention of hydrates, wax, asphaltenes, scale, and corrosion during operation. Flow assurance challenges mostly lead to stoppage of production or plugs, damage to pipelines or production facilities, economic losses, and in severe cases blowouts and loss of human lives. A combination of several chemical and non-chemical techniques is mostly used to prevent flow assurance issues in the industry. However, the use of models to anticipate, limit, and/or prevent flow assurance problems is recommended as the best and most suitable practice. The existing proposed flow assurance models on hydrates, wax, asphaltenes, scale, and corrosion management are challenged with accuracy and precision. They are not also limited by several parametric assumptions. Recently, machine learning methods have gained much attention as best practices for predicting flow assurance issues. Examples of these machine learning models include conventional approaches such as artificial neural network, support vector machine (SVM), least square support vector machine (LSSVM), random forest (RF), and hybrid models. The use of machine learning in flow assurance is growing, and thus, relevant knowledge and guidelines on their application methods and effectiveness are needed for academic, industrial, and research purposes. In this book, the authors focus on the use and abilities of various machine learning methods in flow assurance. Initially, basic definitions and use of machine learning in flow assurance are discussed in a broader scope within the oil and gas industry. The rest of the chapters discuss the use of machine learning in various flow assurance areas such as hydrates, wax, asphaltenes, scale, and corrosion. Also, the use of machine learning in practical field applications is discussed to understand the practical use of machine learning in flow assurance.

Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python PDF Author: Hoss Belyadi
Publisher: Elsevier
ISBN: 0128219297
Category : Computers
Languages : en
Pages : 476

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Book Description
Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. Helps readers understand how open-source Python can be utilized in practical oil and gas challenges Covers the most commonly used algorithms for both supervised and unsupervised learning Presents a balanced approach of both theory and practicality while progressing from introductory to advanced analytical techniques

Handbook of Energy Transitions

Handbook of Energy Transitions PDF Author: Muhammad Asif
Publisher: CRC Press
ISBN: 1000689433
Category : Technology & Engineering
Languages : en
Pages : 525

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Book Description
The global energy scenario is undergoing an unprecedented transition. In the wake of enormous challenges—such as increased population, higher energy demands, increasing greenhouse gas emissions, depleting fossil fuel reserves, volatile energy prices, geopolitical concerns, and energy insecurity issues—the energy sector is experiencing a transition in terms of energy resources and their utilization. This modern transition is historically more dynamic and multidimensional compared to the past considering the vast technological advancements, socioeconomic implications and political responses, and ever-evolving global policies and regulations. Energy insecurity in terms of its critical dimensions—access, affordability, and reliability—remains a major problem hindering the socioeconomic progress in developing countries. The Handbook of Energy Transitions presents a holistic account of the 21st-century energy transition away from fossil fuels. It provides an overview of the unfolding transition in terms of overall dimensions, drivers, trends, barriers, policies, and geopolitics, and then discusses transition in terms of particular resources or technologies, such as renewable energy systems, solar energy, hydropower, hydrogen and fuel cells, electric vehicles, energy storage systems, batteries, digitalization, smart grids, blockchain, and machine learning. It also discusses the present energy transition in terms of broader policy and developmental perspectives. Further, it examines sustainable development, the economics of energy and green growth, and the role of various technologies and initiatives like renewables, nuclear power, and electrification in promoting energy security and energy transition worldwide. Key Features Includes technical, economic, social, and policy perspectives of energy transitions Features practical case studies and comparative assessments Examines the latest renewable energy and low-carbon technologies Explains the connection between energy transition and global climate change

Artificial Intelligence and Cognitive Computing

Artificial Intelligence and Cognitive Computing PDF Author: Miltiadis D. Lytras
Publisher: MDPI
ISBN: 303651161X
Category : Technology & Engineering
Languages : en
Pages : 278

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Book Description
Artificial intelligence (AI) is a subject garnering increasing attention in both academia and the industry today. The understanding is that AI-enhanced methods and techniques create a variety of opportunities related to improving basic and advanced business functions, including production processes, logistics, financial management and others. As this collection demonstrates, AI-enhanced tools and methods tend to offer more precise results in the fields of engineering, financial accounting, tourism, air-pollution management and many more. The objective of this collection is to bring these topics together to offer the reader a useful primer on how AI-enhanced tools and applications can be of use in today’s world. In the context of the frequently fearful, skeptical and emotion-laden debates on AI and its value added, this volume promotes a positive perspective on AI and its impact on society. AI is a part of a broader ecosystem of sophisticated tools, techniques and technologies, and therefore, it is not immune to developments in that ecosystem. It is thus imperative that inter- and multidisciplinary research on AI and its ecosystem is encouraged. This collection contributes to that.

Onshore Unconventional Hydrocarbon Development

Onshore Unconventional Hydrocarbon Development PDF Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309474272
Category : Science
Languages : en
Pages : 101

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Book Description
Oil and gas well completion and stimulation technologies to develop unconventional hydrocarbon resources in the United States have evolved over the past several decades, particularly in relation to the development of shale oil and shale gas. Shale oil and shale gas resources and the technology associated with their production are often termed "unconventional" because the oil and gas trapped inside the shale or other low-permeability rock formation cannot be extracted using conventional technologies. Since about 2005, the application of these technologies to fields in the U.S. have helped produce natural gas and oil in volumes that allowed the country to reduce its crude oil imports by more than 50% and to become a net natural gas exporter. The regional and national economic and energy advances gained through production and use of these resources have been accompanied, however, by rapid expansion of the infrastructure associated with the development of these fields and public concern over the impacts to surface- and groundwater, air, land, and communities where the resources are extracted. The intent of the first day of the workshop of the National Academies of Sciences, Engineering, and Medicine's Roundtable on Unconventional Hydrocarbon Development was to discuss onshore unconventional hydrocarbon development in the context of potential environmental impacts and the ways in which the risks of these kinds of impacts can be managed. Specifically, the workshop sought to examine the lifecycle development of these fields, including decommissioning and reclamation of wells and related surface and pipeline infrastructure, and the approaches from industry practice, scientific research, and regulation that could help to ensure management of the operations in ways that minimize impacts to the environment throughout their active lifetimes and after operations have ceased. This publication summarizes the presentations and discussions from the workshop.