Artificial Intelligent Approaches in Petroleum Geosciences - Image 1

£73.13

Springer Artificial Intelligent Approaches in Petroleum Geosciences

Name: Artificial Intelligent Approaches in Petroleum Geosciences
Brand: Springer
Price: 67.77 GBP
Availability: InStock

AI & Machine Learning

Price History & Forecast

Last 44 days • 44 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 44 days • 6 price levels

Days at Price

Current Price

Price Analysis

Most common price: £73 (12 days, 27.3%)

Price range: £67 - £79

Price levels: 6 different prices over 44 days

Description

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.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 3319165305
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 04 May 2015
Listed Since: 12 February 2015

Barcode

No barcode data available

Springer Artificial Intelligent Approaches in Petroleum Geosciences

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Artificial Intelligent Approaches in Petroleum Geosciences

Wiley AI and Data Analytics for Energy Exploration and Production

Artificial Intelligence for Subsurface Characterization and Monitoring

Intelligent Systems in Oil Field Development under Uncertainty: 183 (Studies in Computational Intelligence, 183)

Wiley Unconventional Hydrocarbon Resources AI Modeling Book

Geophysical Applications of Artificial Neural Networks and Fuzzy Logic: 21 (Modern Approaches in Geophysics, 21)

Geophysical Applications of Artificial Neural Networks and Fuzzy Logic: 21 (Modern Approaches in Geophysics, 21)

Data-Driven Reservoir Modeling

Elsevier AI in Mining and Geotechnical Engineering Book

Applications of Artificial Intelligence Techniques in the Petroleum Industry

Borehole Acoustic Logging – Theory and Methods (Petroleum Engineering)

Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling

Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences

Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis

Geomechanics of Oil and Gas Wells (Advances in Oil and Gas Exploration & Production)

Applied Techniques to Integrated Oil and Gas Reservoir Characterization: A Problem-Solution Discussion with Geoscience Experts

Advances in Subsurface Data Analytics: Traditional and Physics-Based Machine Learning

Geostatistical Methods for Reservoir Geophysics (Advances in Oil and Gas Exploration & Production)

Seismic Reservoir Modeling: Theory, Examples, and Algorithms

Intelligent Systems and Technologies: Methods and Applications: 217 (Studies in Computational Intelligence, 217)

Intelligent Digital Oil and Gas Fields: Concepts, Collaboration, and Right-Time Decisions

Artificial Intelligence and Data Mining Approaches in Security Frameworks: Advances and Challenges (Advances in Data Engineering and Machine Learning)

Intelligent Data Analytics for Terror Threat Prediction: Architectures, Methodologies, Techniques, and Applications