Download or read book Unconventional Hydrocarbon Resources Prediction and Modeling Using Artificial Intelligence Approaches written by Sid-Ali Ouadfeul and published by John Wiley & Sons. This book was released on 2023-08-02 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Unconventional Hydrocarbon Resources Prediction and Modeling Using Artificial Intelligence Approaches written by Sid-Ali Ouadfeul and published by John Wiley & Sons. This book was released on 2023-08-22 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Unconventional Hydrocarbon Resources written by Reza Barati and published by John Wiley & Sons. This book was released on 2020-11-11 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Shale Analytics written by Shahab D. Mohaghegh and published by Springer. This book was released on 2017-02-09 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Applications of Artificial Intelligence Techniques in the Petroleum Industry written by Abdolhossein Hemmati-Sarapardeh and published by Gulf Professional Publishing. This book was released on 2020-08-26 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Machine Learning and Flow Assurance in Oil and Gas Production written by Bhajan Lal and published by Springer Nature. This book was released on 2023-03-11 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning Guide for Oil and Gas Using Python written by Hoss Belyadi and published by Elsevier. This book was released on 2021-04-13 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Handbook of Energy Transitions written by Muhammad Asif and published by CRC Press. This book was released on 2022-10-14 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry written by Kingshuk Srivastava and published by CRC Press. This book was released on 2023-11-20 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies. Features: Provides an understanding of the basics of IT technologies applied in the oil and gas sector Includes deep comparison between different artificial intelligence techniques Analyzes different simulators in the oil and gas sector as well as discussion of AI applications Focuses on in-depth experimental and applied topics Details different case studies for upstream and downstream This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.

Download or read book Artificial Intelligence and Cognitive Computing written by Miltiadis D. Lytras and published by MDPI. This book was released on 2021-09-10 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Onshore Unconventional Hydrocarbon Development written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-07-23 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Alternative Energy Sources written by Andrzej L.Wasiak and published by MDPI. This book was released on 2021-05-20 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: The search for alternative sources of energy is an attempt to solve two of the main problems facing the modern world. Today's resources are mainly based on fossil flammable substances such as coal, oil, and natural gas. The first problem is related to the expected and observed depletion of deposits, not only those available but also less accessible. Another is related to global warming from emissions of greenhouse gases (mainly carbon dioxide) as well as emissions of other pollutants in the atmosphere. Mitigating the harmful effects of fossil fuel use is an obvious challenge for mankind. This Special Issue includes articles on the search for new raw materials and new technologies for obtaining energy, such as those existing in nature, methane hydrates, biomass, etc., new more efficient technologies for generating electricity, as well as analyses of the possibilities and conditions of use of these resources for practical applications.

Download or read book Enhance Oil and Gas Exploration with Data Driven Geophysical and Petrophysical Models written by Keith R. Holdaway and published by John Wiley & Sons. This book was released on 2017-10-09 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Artificial Intelligence and Data Analytics for Energy Exploration and Production written by Fred Aminzadeh and published by John Wiley & Sons. This book was released on 2022-09-21 with total page 613 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICAL INTELLIGENCE AND DATA ANALYTICS FOR ENERGY EXPLORATION AND PRODUCTION This groundbreaking new book is written by some of the foremost authorities on the application of data science and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field. The book provides an in-depth treatment of the foundations of Artificial Intelligence (AI) Machine Learning, and Data Analytics (DA). It also includes many of AI-DA applications in oil and gas reservoirs exploration, development, and production. The book covers the basic technical details on many tools used in “smart oil fields”. This includes topics such as pattern recognition, neural networks, fuzzy logic, evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural language processing, data analytics and next-generation visualization. While theoretical details will be kept to the minimum, these topics are introduced from oil and gas applications viewpoints. In this volume, many case histories from the recent applications of intelligent data to a number of different oil and gas problems are highlighted. The applications cover a wide spectrum of practical problems from exploration to drilling and field development to production optimization, artificial lift, and secondary recovery. Also, the authors demonstrate the effectiveness of intelligent data analysis methods in dealing with many oil and gas problems requiring combining machine and human intelligence as well as dealing with linguistic and imprecise data and rules.

Download or read book Adaptive Approach to Petroleum Reservoir Simulation written by Stanislav Ursegov and published by Springer Nature. This book was released on 2021-01-31 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Reservoir Geomechanics written by Mark D. Zoback and published by Cambridge University Press. This book was released on 2010-04-01 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This interdisciplinary book encompasses the fields of rock mechanics, structural geology and petroleum engineering to address a wide range of geomechanical problems that arise during the exploitation of oil and gas reservoirs. It considers key practical issues such as prediction of pore pressure, estimation of hydrocarbon column heights and fault seal potential, determination of optimally stable well trajectories, casing set points and mud weights, changes in reservoir performance during depletion, and production-induced faulting and subsidence. The book establishes the basic principles involved before introducing practical measurement and experimental techniques to improve recovery and reduce exploitation costs. It illustrates their successful application through case studies taken from oil and gas fields around the world. This book is a practical reference for geoscientists and engineers in the petroleum and geothermal industries, and for research scientists interested in stress measurements and their application to problems of faulting and fluid flow in the crust.

Download or read book Artificial Intelligent Approaches in Petroleum Geosciences written by Constantin Cranganu and published by Springer. This book was released on 2015-04-20 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents several intelligent approaches for tackling and solving challenging practical problems facing those in the petroleum geosciences and petroleum industry. Written by experienced academics, this book offers state-of-the-art working examples and provides the reader with exposure to the latest developments in the field of intelligent methods applied to oil and gas research, exploration and production. It also analyzes the strengths and weaknesses of each method presented using benchmarking, whilst also emphasizing essential parameters such as robustness, accuracy, speed of convergence, computer time, overlearning and the role of normalization. The intelligent approaches presented include artificial neural networks, fuzzy logic, active learning method, genetic algorithms and support vector machines, amongst others. Integration, handling data of immense size and uncertainty, and dealing with risk management are among crucial issues in petroleum geosciences. The problems we have to solve in this domain are becoming too complex to rely on a single discipline for effective solutions and the costs associated with poor predictions (e.g. dry holes) increase. Therefore, there is a need to establish a new approach aimed at proper integration of disciplines (such as petroleum engineering, geology, geophysics and geochemistry), data fusion, risk reduction and uncertainty management. These intelligent techniques can be used for uncertainty analysis, risk assessment, data fusion and mining, data analysis and interpretation, and knowledge discovery, from diverse data such as 3-D seismic, geological data, well logging, and production data. This book is intended for petroleum scientists, data miners, data scientists and professionals and post-graduate students involved in petroleum industry.