logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Datadriven Analytics For The Geological Storage Of Co2 First Edition Shahab Mohaghegh

  • SKU: BELL-7160076
Datadriven Analytics For The Geological Storage Of Co2 First Edition Shahab Mohaghegh
$ 31.00 $ 45.00 (-31%)

5.0

48 reviews

Datadriven Analytics For The Geological Storage Of Co2 First Edition Shahab Mohaghegh instant download after payment.

Publisher: CRC Press
File Extension: PDF
File size: 22.8 MB
Pages: 280
Author: Shahab Mohaghegh
ISBN: 9781315280790, 9781315280806, 9781315280813, 1315280795, 1315280809, 1315280817
Language: English
Year: 2018
Edition: First edition

Product desciption

Datadriven Analytics For The Geological Storage Of Co2 First Edition Shahab Mohaghegh by Shahab Mohaghegh 9781315280790, 9781315280806, 9781315280813, 1315280795, 1315280809, 1315280817 instant download after payment.

Data driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of Artificial Intelligence and Machine Learning in data driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of Artificial Intelligence and Machine Learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.

Related Products