Performance forecasting for polymer flooding in heavy oil reservoirs

Performance forecasting for polymer flooding in heavy oil reservoirs Fuel 216 (2018) 83–100 Contents lists available at ScienceDirect Fuel journal homepage: www.elsevier.com/locate/fuel Full Length Article Performance forecasting for polymer flooding in heavy oil reservoirs a, b a Ehsan Amirian , Morteza Dejam , Zhangxin Chen Department of Chemical and Petroleum Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada Department of Petroleum Engineering, College of Engineering and Applied Science, University of Wyoming, 1000 E. University Avenue, Laramie, WY 82071-2000, USA GR APHICAL A BSTRACT ARTICLE I NFO ABSTRACT Keywords: As a supply for future fuel and energy demand, 95% of the bitumen deposits in North America are expected to Polymer flooding become a major source. The Steam Assisted Gravity Drainage (SAGD) provides more efficient recovery of un- Heavy oil reservoir conventional oil resources, such as heavy oil and bitumen, as compared to the other thermal recovery methods. Performance forecasting The drawback associated with SAGD or other thermal methods is that they are economically non-profitable Data-driven modeling when applied to the deep and thin reservoirs. Environmental concerns related to land, water, and air also hinder Artificial and computational intelligence the application of the aforementioned methods. These issues have provoked reservoir engineers http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fuel Elsevier

Performance forecasting for polymer flooding in heavy oil reservoirs

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0016-2361
D.O.I.
10.1016/j.fuel.2017.11.110
Publisher site
See Article on Publisher Site

Abstract

Fuel 216 (2018) 83–100 Contents lists available at ScienceDirect Fuel journal homepage: www.elsevier.com/locate/fuel Full Length Article Performance forecasting for polymer flooding in heavy oil reservoirs a, b a Ehsan Amirian , Morteza Dejam , Zhangxin Chen Department of Chemical and Petroleum Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta T2N 1N4, Canada Department of Petroleum Engineering, College of Engineering and Applied Science, University of Wyoming, 1000 E. University Avenue, Laramie, WY 82071-2000, USA GR APHICAL A BSTRACT ARTICLE I NFO ABSTRACT Keywords: As a supply for future fuel and energy demand, 95% of the bitumen deposits in North America are expected to Polymer flooding become a major source. The Steam Assisted Gravity Drainage (SAGD) provides more efficient recovery of un- Heavy oil reservoir conventional oil resources, such as heavy oil and bitumen, as compared to the other thermal recovery methods. Performance forecasting The drawback associated with SAGD or other thermal methods is that they are economically non-profitable Data-driven modeling when applied to the deep and thin reservoirs. Environmental concerns related to land, water, and air also hinder Artificial and computational intelligence the application of the aforementioned methods. These issues have provoked reservoir engineers

Journal

FuelElsevier

Published: Mar 15, 2018

References

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