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Data Analytics in Reservoir Engineering
Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.
Machine Learning in the Oil and Gas Industry
Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanation...
Formulas and Calculations for Petroleum Engineering
Formulas and Calculations for Petroleum Engineering unlocks the capability for any petroleum engineering individual, experienced or not, to solve problems and locate quick answers, eliminating non-productive time spent searching for that right calculation. Enhanced with lab data experiments, practice examples, and a complimentary online software toolbox, the book presents the most convenient and practical reference for all oil and gas phases of a given project. Covering the full spectrum, this reference gives single-point reference to all critical modules, including drilling, production, reservoir engineering, well testing, well logging, enhanced oil recovery, well completion, fracturing, fluid flow, and even petroleum economics. - Presents single-point access to all petroleum engineering equations, including calculation of modules covering drilling, completion and fracturing - Helps readers understand petroleum economics by including formulas on depreciation rate, cashflow analysis, and the optimum number of development wells
Routledge Handbook of the Digital Environmental Humanities
The Routledge Handbook of the Digital Environmental Humanities explores the digital methods and tools scholars use to observe, interpret, and manage nature in several different academic fields. Employing historical, philosophical, linguistic, literary, and cultural lenses, this handbook explores how the digital environmental humanities (DEH), as an emerging field, recognises its convergence with the environmental humanities. As such, it is empirically, critically, and ethically engaged in exploring digitally mediated, visualised, and parsed framings of past, present, and future environments, landscapes, and cultures. Currently, humanities, geographical, cartographical, informatic, and comput...
Sustainable Materials for Oil and Gas Applications
Sustainable Materials for Oil and Gas Applications, a new release in the Advanced Materials and Sensors for the Oil and Gas Industry series, comprises a list of processes across the upstream and downstream sectors of the industry and the latest research on advanced nanomaterials. Topics include enhanced oil recovery mechanisms of nanofluids, health and safety features related to nanoparticle handling, and advanced materials for produced water treatments. Supplied from contributing experts in both academic and corporate backgrounds, the reference contains developments, applications, advantages and challenges. Located in one convenient resource, the book addresses real solutions as oil and gas companies try to lower emissions. As the oil and gas industry are shifting and implementing innovative ways to produce oil and gas in an environmentally friendly way, this resource is an ideal complement to their work.
Machine Learning Applications in Subsurface Energy Resource Management
The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy). Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and pred...
Sustainable Materials for Oil and Gas Applications
Sustainable Materials for Oil and Gas Applications, a new release in the Advanced Materials and Sensors for the Oil and Gas Industry series, comprises a list of processes across the upstream and downstream sectors of the industry and the latest research on advanced nanomaterials. Topics include enhanced oil recovery mechanisms of nanofluids, health and safety features related to nanoparticle handling, and advanced materials for produced water treatments. Supplied from contributing experts in both academic and corporate backgrounds, the reference contains developments, applications, advantages and challenges. Located in one convenient resource, the book addresses real solutions as oil and gas...
Recent Innovative Trends in Interdisciplinary Research Areas Vol. 1
An edited book is a compilation of academic chapters produced by several authors to share their perspectives and experiences on a certain subject. The chapters of the edited book, which are written by many writers, go through a peer-reviewing procedure to confirm their quality. The volume editor next manages the uniformity of style and material flow. The chapters in the edited book should be the author's own unpublished original works. If they are carefully planned and edited well, edited volumes can be excellent books. A successful edited book is more than just a longer version of a journal issue with a similar theme; it is also a complete intellectual undertaking that should be treated as such from the outset.
