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: 73.13 GBP
Availability: InStock

AI & Machine Learning

This is the usual price. Wait for it to drop, or tell us your number.

£73 today · usual range £0–£0 · best ever £13

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 639 days • 639 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 639 days • 3 price ranges

Days at Price

Current Price

Price Analysis

Most common range: £70-85 (402 days, 62.9%)

Price range: £13 - £85

Price levels: 3 price ranges over 639 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

This is the usual price. Wait for it to drop, or tell us your number.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Artificial Intelligent Approaches in Petroleum Geosciences

Artificial Intelligence for Subsurface Characterization and Monitoring

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

Geophysical Characterization of Gas Hydrates: 14 (Geophysical Developments)

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

Wiley Unconventional Hydrocarbon Resources AI Modeling Book

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

Remote Sensing for Hydrocarbon Exploration (Springer Remote Sensing/Photogrammetry)

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

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications

Oil and Gas Exploration: Methods and Application: 72 (Special Publications)

Geomechanics, Fluid Dynamics and Well Testing, Applied to Naturally Fractured Carbonate Reservoirs: Extreme Naturally Fractured Reservoirs (Springer Theses)

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

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

Practical Petroleum Geochemistry for Exploration and Production

Machine Learning for Subsurface Characterization

Surface Geochemistry in Petroleum Exploration

Surface Geochemistry in Petroleum Exploration

Elements of Petroleum Geology

Correlation in Hydrocarbon Exploration: Proceedings of the conference Correlation in Hydrocarbon Exploration organized by the Norwegian Petroleum Society and held in Bergen, Norway, 3–5 October 1988

Geosciences of Azerbaijan: Volume II: Economic Geology and Applied Geophysics (Regional Geology Reviews)

Heavy Oils: Reservoir Characterization and Production Monitoring: 13 (Geophysical Developments)

Petroleum Geoscience, 2nd Edition

Data-Driven Reservoir Modeling