Efficient screening of enhanced oil recovery methods and predictive economic analysis

Abstract Oil demand for economic development around the world is rapidly increasing. Moreover, oil production rates are getting a peak in mature reservoirs and tending to decline in the near future, which has led to considerable researches on enhanced oil recovery (EOR) methods. Therefore, an efficient technical and economical screening to appropriate selection of EOR methods can make savings in time and cost. The purpose of this communication is to present a method to select an efficient EOR process and investigate its economic parameters. A database of reservoir parameters of rock and fluid properties along with successful EOR techniques has been collected and analyzed. First, an artificial neural network (ANN) was developed to classify the EOR methods technically. Then, an economical EOR screening model was designed, and then, future cash flows on the use of EOR methods were predicted. The results show that the ANN system can select proper EOR methods and classify them. Moreover, the obtained results indicate that the economic analysis performed in this study is efficient and useful to predict future cash flows.

[1]  Edward S. Rubin,et al.  The effect of high oil prices on EOR project economics , 2009 .

[2]  Yasin,et al.  [Society of Petroleum Engineers Production and Operations Symposium - (2007.03.31-2007.04.3)] Proceedings of Production and Operations Symposium - Intelligent Prediction of Reservoir Fluid Viscosity , 2007 .

[3]  Baojun Bai,et al.  Recent Developments and Updated Screening Criteria of Enhanced Oil Recovery Techniques , 2010 .

[4]  W. J. Parkinson,et al.  Using an expert system to explore enhanced oil recovery methods , 1994 .

[5]  Nasir Mehranbod,et al.  Bayesian Network Analysis as a Tool for Efficient EOR Screening , 2011 .

[6]  Turgay Ertekin,et al.  A New Screening Tool for Improved Oil Recovery Methods Using Artificial Neural Networks , 2012 .

[7]  F. D. Martin,et al.  EOR Screening Criteria Revisited—Part 2: Applications and Impact of Oil Prices , 1997 .

[8]  Rais Khisamov,et al.  Application And Method Based On Artificial Intelligence For Selection Of Structures And Screening Of Technologies For Enhanced Oil Recovery , 2002 .

[9]  Petri Koistinen,et al.  Using additive noise in back-propagation training , 1992, IEEE Trans. Neural Networks.

[10]  ELRADI ABASS,et al.  ARTIFICIAL INTELLIGENCE SELECTION WITH CAPABILITY OF EDITING A NEW PARAMETER FOR EOR SCREENING CRITERIA , 2011 .

[11]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

[12]  Ridha Gharbi,et al.  Application of an expert system to optimize reservoir performance , 2005 .

[13]  Adam P. Piotrowski,et al.  A comparison of methods to avoid overfitting in neural networks training in the case of catchment runoff modelling , 2013 .

[14]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[15]  Baojun Bai,et al.  Analysis of EOR Projects and Updated Screening Criteria , 2011 .

[16]  E. M. El-M. Shokir,et al.  Selection and Evaluation EOR Method Using Artificial Intelligence , 2002 .

[17]  Ridha Gharbi,et al.  An expert system for selecting and designing EOR processes , 2000 .

[18]  Jong-Se Lim,et al.  Selection and Evaluation of Enhanced Oil Recovery Method Using Artificial Neural Network , 2011 .

[19]  Abdulrazag Y. Zekri,et al.  Economic Evaluation of Enhanced Oil Recovery , 2000 .

[20]  Zhen Zhu,et al.  Optimized Approximation Algorithm in Neural Networks Without Overfitting , 2008, IEEE Transactions on Neural Networks.

[21]  Eduardo Manrique,et al.  Selection of EOR/IOR Opportunities Based on Machine Learning , 2002 .

[22]  Jasper Lane Dickson,et al.  Development Of Improved Hydrocarbon Recovery Screening Methodologies , 2010 .

[23]  Yasin Hajizadeh.  Intelligent prediction of reservoir fluid viscosity , 2007 .

[24]  J. J. Taber,et al.  Technical Screening Guides for the Enhanced Recovery of Oil , 1983 .

[25]  R. Seright,et al.  EOR Screening Criteria Revisited - Part 1: Introduction to Screening Criteria and Enhanced Recovery Field Projects , 1997 .

[26]  Dominique Guerillot.  EOR Screening With an Expert System , 1988 .