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Oruganti, Y.D. (2010) Geologic COR2R Storage: Understanding Pressure Perturbations and Estimating Risk Due to Pressure Buildup. The Faculty of the Graduate School of the University of Texas at Austin in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering.

has been cited by the following article:

• TITLE: Proposing a Meta-Heuristic Algorithm for Enhanced Oil Recovery Using CO2 Injection

  AUTHORS: Mohammadi Raheleh, Hajnajafi Reza

  KEYWORDS: Gas Injection, Gas Storage, Enhanced Oil Recovery, Genetic Optimization Algorithms

  JOURNAL NAME: Open Journal of Yangtze Oil and Gas, Vol.1 No.3, October 30, 2016

  ABSTRACT: With the increased global demand for crude oil, the increased reservoir lifetime, and the need for enhanced oil recovery methods, CO2 injection has become an efficient choice. This paper aimed to determine optimal CO2 injection choices using genetic algorithm, involving both optimized gas storage and enhanced oil recovery. There was no overlap between the objectives. Each was directly optimized and several optimal scenarios were developed at the same time. An advantage of this optimization method is that it is able to modify production scenario according to variations in optimization parameter values.