Applications of Artificial Intelligence Techniques in the Petroleum Industry Books

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Applications of Artificial Intelligence Techniques in the Petroleum Industry


Applications of Artificial Intelligence Techniques in the Petroleum Industry
  • Author : Abdolhossein Hemmati Sarapardeh
  • Publisher : Gulf Professional Publishing
  • Release : 2020-08-26
  • ISBN : 9780128223857
  • Language : En, Es, Fr & De
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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

Artificial Intelligent Approaches in Petroleum Geosciences


Artificial Intelligent Approaches in Petroleum Geosciences
  • Author : Constantin Cranganu
  • Publisher : Springer
  • Release : 2015-04-20
  • ISBN : 9783319165318
  • Language : En, Es, Fr & De
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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 Intelligence in the Petroleum Industry


Artificial Intelligence in the Petroleum Industry
  • Author : Bertrand Braunschweig
  • Publisher : Editions TECHNIP
  • Release : 1995
  • ISBN : 2710806886
  • Language : En, Es, Fr & De
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Machine Learning in the Oil and Gas Industry


Machine Learning in the Oil and Gas Industry
  • Author : Yogendra Narayan Pandey
  • Publisher : Apress
  • Release : 2020-11-03
  • ISBN : 1484260937
  • Language : En, Es, Fr & De
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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 explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering. Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will Learn Understanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industry Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used Study interesting industry problems that are good candidates for being solved by machine and deep learning Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.

Artificial Intelligence in the Petroleum Industry


Artificial Intelligence in the Petroleum Industry
  • Author : Bertrand Braunschweig
  • Publisher : Editions TECHNIP
  • Release : 1996
  • ISBN : 2710807033
  • Language : En, Es, Fr & De
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