(Ilmumisaeg: 06-Feb-2024, EPUB+DRM, Kirjastus: Taylor & Francis Ltd, ISBN-13: 9781003860228)
This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems. Processing voluminous and complex data sets are the primary...Loe edasi...
(Ilmumisaeg: 06-Feb-2024, PDF+DRM, Kirjastus: Taylor & Francis Ltd, ISBN-13: 9781003860198)
This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems. Processing voluminous and complex data sets are the primary...Loe edasi...
Bhajan Lal, Cornelius Borecho Bavoh, Jai Krishna Sahith Sayani
(Ilmumisaeg: 11-Mar-2023, PDF+DRM, Kirjastus: Springer International Publishing AG, ISBN-13: 9783031242311)
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...Loe edasi...
Bhajan Lal, Cornelius Borecho Bavoh, Jai Krishna Sahith Sayani
(Ilmumisaeg: 11-Mar-2023, EPUB+DRM, Kirjastus: Springer International Publishing AG, ISBN-13: 9783031242311)
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...Loe edasi...
(Ilmumisaeg: 02-Sep-2022, EPUB+DRM, Kirjastus: Taylor & Francis Ltd, ISBN-13: 9781000629552)
Today, raw data on any industry is widely available. With the help of artificial intelligence (AI) and machine learning (ML), this data can be used to gain meaningful insights. In addition, as data is the new raw material for todays world, AI and ML...Loe edasi...
(Ilmumisaeg: 02-Sep-2022, PDF+DRM, Kirjastus: Taylor & Francis Ltd, ISBN-13: 9781000629521)
Today, raw data on any industry is widely available. With the help of artificial intelligence (AI) and machine learning (ML), this data can be used to gain meaningful insights. In addition, as data is the new raw material for todays world, AI and ML...Loe edasi...
Drilling and production wells are becoming more digitalized as oil and gas companies continue to implement machine learning andbig data solutions to save money on projects while reducing energy and emissions. Up to now there has not been one cohesive...Loe edasi...
Drilling and production wells are becoming more digitalized as oil and gas companies continue to implement machine learning andbig data solutions to save money on projects while reducing energy and emissions. Up to now there has not been one cohesive...Loe edasi...
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, specificall...Loe edasi...
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, specificall...Loe edasi...
Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas oper...Loe edasi...
Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas oper...Loe edasi...
2D/3D Boundary Element Programming in Petroleum Engineering and Geomechanics, Volume 72, is designed to make it easy for researchers, engineers and students to begin writing boundary element programs. This reference covers the fundamentals, theoretic...Loe edasi...
2D/3D Boundary Element Programming in Petroleum Engineering and Geomechanics, Volume 72, is designed to make it easy for researchers, engineers and students to begin writing boundary element programs. This reference covers the fundamentals, theoretic...Loe edasi...
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, cov...Loe edasi...
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, cov...Loe edasi...
Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses o...Loe edasi...
Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses o...Loe edasi...
Petroleum Production Engineering, Second Edition, updates both the new and veteran engineer on how to employ day-to-day production fundamentals to solve real-world challenges with modern technology. Enhanced to include equations and references with t...Loe edasi...
Petroleum Production Engineering, Second Edition, updates both the new and veteran engineer on how to employ day-to-day production fundamentals to solve real-world challenges with modern technology. Enhanced to include equations and references with t...Loe edasi...
