Using a dynamic model of technological processes to reduce the cost of heavy oil extraction

DOI

10.2991/itoec-16.2016.78How to use a DOI?

Keywords

oil and gas industry, heavy oil, the substitution of import, decision support systems, digital oilfield.

Abstract

The article considers the problem of reducing the cost of heavy oil productions. A new approach, based on the intelligent analysis of successful events' historical data of qualitative EOR application, is proposed. Based on database info analysis, the synthesis of a model, targeted to automated search of wells for EOR application, is worked out. The main data processing tool is a novel technology, based on neural network analysis techniques and evolutionary algorithms implementation. This approach allows selecting EOR in fuzzy, hardly formalized oilfield conditions and reduces the dependence on the human factor.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Dr. Iakov S. Korovin
AU  - Dr. Anatoly I. Kalyaev
AU  - Dr. Maxim V. Khisamutdinov
PY  - 2016/05
DA  - 2016/05
TI  - Using a dynamic model of technological processes to reduce the cost of heavy oil extraction
BT  - Proceedings of the 2nd Information Technology and Mechatronics Engineering Conference (ITOEC 2016)
PB  - Atlantis Press
SP  - 408
EP  - 411
SN  - 2352-5401
UR  - https://doi.org/10.2991/itoec-16.2016.78
DO  - 10.2991/itoec-16.2016.78
ID  - Korovin2016/05
ER  -