Unconventional Hydrocarbon Resources Prediction And Modeling Using Artificial Intelligence Approaches

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 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.

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.

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 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

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. A workshop on December 1 and 2, 2016 at the National Academy of Sciences in Washington, DC, explored the management of risk related to the development of onshore unconventional oil and gas resources such as shale oil and shale gas. The second part of the workshop, on December 2, addressed issues associated with induced seismicity and managing the risk of induced seismic events associated with development of oil and gas fields. This publication summarizes the presentations and discussions from this second day of the workshop.

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.

Unconventional Oil and Gas Resources Handbook: Evaluation and Development is a must-have, helpful handbook that brings a wealth of information to engineers and geoscientists. Bridging between subsurface and production, the handbook provides engineers and geoscientists with effective methodology to better define resources and reservoirs. Better reservoir knowledge and innovative technologies are making unconventional resources economically possible, and multidisciplinary approaches in evaluating these resources are critical to successful development. Unconventional Oil and Gas Resources Handbook takes this approach, covering a wide range of topics for developing these resources including exploration, evaluation, drilling, completion, and production. Topics include theory, methodology, and case histories and will help to improve the understanding,integrated evaluation, and effective development of unconventional resources. Presents methods for a full development cycle of unconventional resources, from exploration through production Explores multidisciplinary integrations for evaluation and development of unconventional resources and covers a broad range of reservoir characterization methods and development scenarios Delivers balanced information with multiple contributors from both academia and industry Provides case histories involving geological analysis, geomechanical analysis, reservoir modeling, hydraulic fracturing treatment, microseismic monitoring, well performance and refracturing for development of unconventional reservoirs

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

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.