Artificial Intelligent Approaches in Petroleum Geosciences Editor
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Bester Preis: Fr. 5.52 (€ 5.64)¹ (vom 23.10.2019)Artificial Intelligent Approaches in Petroleum Geosciences (2016)
ISBN: 9783319359922 bzw. 3319359924, in Deutsch, Springer International Publishing AG, neu, Nachdruck.
New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Artificial Intelligent Approaches in Petroleum Geosciences (2016)
ISBN: 9783319359922 bzw. 3319359924, in Deutsch, Springer International Publishing AG, neu, Nachdruck.
New Book. Delivered from our US warehouse in 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND.Established seller since 2000.
Artificial Intelligent Approaches in Petroleum Geosciences (2016)
ISBN: 9783319359922 bzw. 3319359924, in Deutsch, Springer International Publishing AG, Taschenbuch, neu.
bol.com.
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 benc... 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.Taal: Engels;Afmetingen: 16x235x155 mm;Gewicht: 468,00 gram;Verschijningsdatum: november 2016;ISBN10: 3319359924;ISBN13: 9783319359922; Engelstalig | Paperback | 2016.
Artificial Intelligent Approaches in Petroleum Geosciences
ISBN: 9783319359922 bzw. 3319359924, vermutlich in Englisch, Springer Shop, Taschenbuch, neu.
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. Soft cover.
/ Luchian / Breaban | Artificial Intelligent Approaches in Petroleum Geosciences | Springer | Softcover reprint of the original 1st ed. 2015
ISBN: 9783319359922 bzw. 3319359924, vermutlich in Englisch, Springer, Taschenbuch, neu.
Artificial Intelligent Approaches in Petroleum Geosciences Constantin Cranganu Editor
ISBN: 9783319359922 bzw. 3319359924, vermutlich in Englisch, Springer International Publishing, Taschenbuch, neu.
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.
Artificial Intelligent Approaches in Petroleum Geosciences (2016)
ISBN: 9783319359922 bzw. 3319359924, in Deutsch, Springer, Taschenbuch, neu.
9783319359922 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher.
Artificial Intelligent Approaches in Petroleum Geosciences (2016)
ISBN: 9783319359922 bzw. 3319359924, in Deutsch, Springer, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, English-Book-Service Mannheim [1048135], Mannheim, Germany.
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