Implementation And Interpretation Of Machine And Deep Learning To Applied Subsurface Geological Problems
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Implementation And Interpretation Of Machine And Deep Learning To Applied Subsurface Geological Problems
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Author : David A. Wood
language : en
Publisher: Elsevier
Release Date : 2025-02-18
Implementation And Interpretation Of Machine And Deep Learning To Applied Subsurface Geological Problems written by David A. Wood and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-18 with Technology & Engineering categories.
Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information explores machine and deep learning models for subsurface geological prediction problems commonly encountered in applied resource evaluation and reservoir characterization tasks. The book provides insights into how the performance of ML/DL models can be optimized—and sparse datasets of input variables enhanced and/or rescaled—to improve prediction performances. A variety of topics are covered, including regression models to estimate total organic carbon from well-log data, predicting brittleness indexes in tight formation sequences, trapping mechanisms in potential sub-surface carbon storage reservoirs, and more.Each chapter includes its own introduction, summary, and nomenclature sections, along with one or more case studies focused on prediction model implementation related to its topic. - Addresses common applied geological problems focused on machine and deep learning implementation with case studies - Considers regression, classification, and clustering machine learning methods and how to optimize and assess their performance, considering suitable error and accuracy metric - Contrasts the pros and cons of multiple machine and deep learning methods - Includes techniques to improve the identification of geological carbon capture and storage reservoirs, a key part of many energy transition strategies
Advances In Subsurface Data Analytics
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Author : Shuvajit Bhattacharya
language : en
Publisher: Elsevier
Release Date : 2022-05-18
Advances In Subsurface Data Analytics written by Shuvajit Bhattacharya and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-18 with Science categories.
Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume. - Covers fundamentals of simple machine learning and deep learning algorithms, and physics-based approaches written by practitioners in academia and industry - Presents detailed case studies of individual machine learning algorithms and optimal strategies in subsurface characterization around the world - Offers an analysis of future trends in machine learning in geosciences
Rock Physics Of Unconventional Reservoirs Volume Ii
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Author : Qiaomu Qi
language : en
Publisher: Frontiers Media SA
Release Date : 2024-10-07
Rock Physics Of Unconventional Reservoirs Volume Ii written by Qiaomu Qi and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-07 with Science categories.
Unconventional resources with commercial interest in the world mainly include heavy oils, shales, coalbed methane, and tight gas sands. The production and development of these resources has changed the global energy supply pattern. Quantitative interpretation of geophysical data in the exploration, well-logging, and engineering development of unconventional resources requires a comprehensive understanding of physical properties of rocks and their relationships. The research of rock physics provides an interdisciplinary treatment of physical properties, whether related to geological, geophysical, or geomechanical methodologies. The development of new rock physics methods is essential when integrating core, well-log, seismic data to improve the accuracy of formation evaluation and reservoir characterization. The composition, internal structure, and thermodynamic environment of reservoir rocks are complex and vary with different regions. This becomes particularly evident for unconventional reservoirs with strong macro- and micro-scopic heterogeneities. The diversity of exploration targets and complexity of reservoir characteristics pose great challenges to the applicability of existing rock physics experiments and theories. There are potential risks in directly using existing empirical relations and physical models to guide geophysical interpretation since spurious results may occur. Therefore, it is imperative to explore more applicable rock physics methods according to the petrophysical nature of actual reservoirs.
Applications Of Machine Learning In Volcanology
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Author : Bellina Di Lieto
language : en
Publisher: Frontiers Media SA
Release Date : 2025-04-29
Applications Of Machine Learning In Volcanology written by Bellina Di Lieto and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-29 with Science categories.
The characterization of volcano state is not a simple task due the complexity of physics processes underway. Understanding their evolution prior to and during eruptions is a critical point for identifying transitions in volcanic state. Permanent monitoring networks are developed for such a purpose. With the increase of the number of monitoring sites, the amount of available continuous data coming from different sources (infrasonic, seismic, GPS, geochemical, etc.) has increased exponentially and extracting the huge amount of information this data brings, represents a non-trivial task for researchers, who are always more often looking at the potentiality of computer algorithms to find correlations among them. Recent developments in the field of Machine Learning (ML) have proven to be very useful and efficient for automatic discrimination, decision, prediction, clustering and information extraction in many fields, including volcanology. In recent times, Deep Learning has seen rapid growth in its popularity along with other supervised strategies, such as Support Vectors Machines and Recurrent neural networks (RNN), which have consistently been applied with success to broader and broader sets of applications and fields. However, supervised machine learning requires labels for training, and obtaining these labels for large volumes of seismic and volcanic data is a very demanding and challenging task. Therefore, semi-supervised and unsupervised methods, such as Self-organized Maps, have been applied with success, to extract relevant information from huge amounts of unlabelled data. In seismic and deformative data processing, these techniques are used for waveform inversion, automatic picking of first arrivals, and interpretation of peculiar characteristics of transients. ML is helpful in the discrimination of magmatic complexes, in distinguishing tectonic settings of volcanic rocks, in the evaluation of correlations between volcanic signals and the chemico-physical composition of erupted materials. Other applications of ML in volcanology include the analysis and classification of geological, geochemical and petrological “static” data to infer for example, the possible source and mechanism of observed deposits, the analysis of satellite imagery to quickly classify vast regions difficult to investigate on the ground or, again, to detect changes that could indicate an unrest. The results obtained with the help of these algorithms would otherwise represent for researchers’ tasks hard to be solved with the usual standard methodologies.
Proceedings Of The Rocscience International Conference 2023 Ric2023
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Author : Reginald E. Hammah
language : en
Publisher: Springer Nature
Release Date : 2023-11-06
Proceedings Of The Rocscience International Conference 2023 Ric2023 written by Reginald E. Hammah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-06 with Technology & Engineering categories.
This is an open access book. Rocscience is delighted to announce the Rocscience International Conference 2023 (RIC2023), an in-person gathering to be held from April 24–26, 2023, in Toronto, Canada. RIC2023's primary objective is to bring geotechnical professionals together to meet and exchange ideas on important issues and developments in geotechnical engineering, particularly combinations of emerging and mature technologies. The geotechnical industry is rapidly evolving. Engineers are more connected through technology, technology is becoming more integrated than ever, and methods combining these technologies are becoming more prevalent. This movement towards combining technologies led us to the conference theme, “Synergy in Geotechnical Engineering – Success Beyond Individual Technologies.” We believe the time is right to highlight how far the industry has come with various technologies and continues to develop. The conference aims to create an environment that fosters new perspectives and helps attendees delve deeper into innovative approaches. During RIC2023, Rocscience will award the 2023 Lifetime Achievement Medal to Dr. Norbert Morgenstern, an internationally recognized authority in the engineering community. As both a practitioner and educator, Dr. Morgenstern’s contributions to the geotechnical community continue to benefit engineers worldwide, and he will give an address on his career. In addition to keynotes by Dr. Morgernstern and four other distinguished speakers, there will be several technical and networking sessions.
Introduction To Modeling Simulation And Optimization Of Co2 Sequestration In Various Types Of Reservoirs
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Author : Ramesh Agarwal
language : en
Publisher: Elsevier
Release Date : 2024-11-23
Introduction To Modeling Simulation And Optimization Of Co2 Sequestration In Various Types Of Reservoirs written by Ramesh Agarwal and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-23 with Technology & Engineering categories.
Carbon capture and sequestration has become an essential technology for addressing the mitigation of global warming and adverse climate change due to increasing CO2 emissions from fossil fuel combustion worldwide. However, the scientific/engineering community still lacks thorough and practical knowledge about various types of reservoirs capable of effective long-term CO2 sequestration. Introduction to Modeling, Simulation, and Optimization of CO2 Sequestration in Various Types of Reservoirs pulls together the relevant basic scientific knowledge and applications to help reservoir engineering practitioners learn and utilize the potential of CO2 sequestration in saline, oil, gas, shale, basalt, and geothermal reservoirs. After presenting the fundamental properties of various reservoirs, the authors describe each type of reservoir and explain basic parameters, benchmark cases, experimental data, optimization strategies for CO2 sequestration, prospects, and outlook. Rounding out the text with a glossary and consideration of future developments, this book delivers the necessary tools for engineers to better understand carbon sequestration and advance the energy transition. - Introduces the physical characteristics of saline, oil, gas, shale, basalt, and geothermal reservoirs - Describes the physics and chemistry of CO2 sequestration in different types of reservoirs and their modeling - Applies numerical simulation and optimization methodology to various reservoirs with real-world examples - Reviews machine learning applications to carbon capture and sequestration
Seismicity In Volcanic Areas
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Author : Derek Keir
language : en
Publisher: Frontiers Media SA
Release Date : 2022-11-04
Seismicity In Volcanic Areas written by Derek Keir and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-04 with Science categories.
Bulletin Of The Atomic Scientists
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Author :
language : en
Publisher:
Release Date : 1970-12
Bulletin Of The Atomic Scientists written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970-12 with categories.
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Bulletin Of The Atomic Scientists
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Author :
language : en
Publisher:
Release Date : 1972-10
Bulletin Of The Atomic Scientists written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1972-10 with categories.
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
A Primer On Machine Learning In Subsurface Geosciences
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Author : Shuvajit Bhattacharya
language : en
Publisher: Springer Nature
Release Date : 2021-05-03
A Primer On Machine Learning In Subsurface Geosciences written by Shuvajit Bhattacharya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-03 with Technology & Engineering categories.
This book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences. It explores the fundamentals of data science and machine learning, and how their advances have disrupted the traditional workflows used in the industry and academia, including geology, geophysics, petrophysics, geomechanics, and geochemistry. It then presents the real-world applications and explains that, while this disruption has affected the top-level executives, geoscientists as well as field operators in the industry and academia, machine learning will ultimately benefit these users. The book is written by a practitioner of machine learning and statistics, keeping geoscientists in mind. It highlights the need to go beyond concepts covered in STAT 101 courses and embrace new computational tools to solve complex problems in geosciences. It also offers practitioners, researchers, and academics insights into how to identify, develop, deploy, and recommend fit-for-purpose machine learning models to solve real-world problems in subsurface geosciences.