A least-squares support vector machine approach to predict temperature drop accompanying a given pressure drop for the natural gas production and processing systems-Reference-Cited by-同舟云学术

A least-squares support vector machine approach to predict temperature drop accompanying a given pressure drop for the natural gas production and processing systems

Published:2015-07-03 Issue:2 Volume:38 Page:122-129
ISSN:0143-0750
Container-title:International Journal of Ambient Energy
language:en
Short-container-title:International Journal of Ambient Energy

Author:

Ahmadi Mohammad-Ali¹²,Hasanvand Mahdi Zeinali³,Bahadori Alireza⁴

Affiliation:

1. Department of Petroleum Engineering, Ahwaz Faculty of Petroleum Engineering, Petroleum University of Technology (PUT), Ahwaz, Iran

2. EOR/IOR Institute, Tehran, Iran

3. Research Institute of Petroleum Industry (RIPI), Tehran, Iran

4. School of Environment, Science and Engineering, Southern Cross University, Post Box 157, Lismore, NSW 2480, Australia

Publisher

Informa UK Limited

Subject

Building and Construction,Renewable Energy, Sustainability and the Environment

Link

https://www.tandfonline.com/doi/pdf/10.1080/01430750.2015.1055515

Reference43 articles.

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4. Connectionist model predicts the porosity and permeability of petroleum reservoirs by means of petro-physical logs: Application of artificial intelligence

5. A LSSVM approach for determining well placement and conning phenomena in horizontal wells

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