Abstract
This paper presents results of a screening procedure for chemical EOR methods based on fuzzy-logic and data clustering algorithms. EOR processes considered included combinations of polymer, alkali and surfactant. Reservoir parameters are represented as triangular distributions with validity limits for each EOR process, and a most likely validity value of the distribution. Another triangular distribution was used as a reference for each of the reservoir and fluid parameters. The limits of validity were defined by mining a database and also by using technical limits, e.g. maximum stability temperature for polymers. The most relevant variables were dictated by availability of data and by comparing screening results with reported field cases. Wyoming basins have a long tradition of oil and gas exploitation, so many of the assets are at an advanced stage of maturity. The current energy market has revitalized the opportunities for further exploitation of numerous reservoirs in Wyoming. Enhanced-Oil Recovery (EOR) represents an attractive target for increasing the recovery factor in many of currently underexploited reservoirs, particularly by CO2 and Chemical Flooding. Associated decision-making workflows demand screening procedures, simulation and detailed economic evaluations. Sensible screening procedures are necessary to guide decision-making exercises. In practice, it was not possible to generalize success in field cases. Our results show this simple screening procedure requires a relatively small dataset for each asset, which contains bounds and likely values for the relevant rock and fluid properties. This has been implemented in a way that facilitates its use by final users. Many of the Wyoming reservoirs represent good candidates for processes such as alkaline-polymer or straight-polymer flooding, based on published field experience and our results. This EOR screening strategy is viewed as a significant improvement over go-no go criteria based on look-up table methods, because the developed method yields indicators ranking candidates for chemical EOR strategies. This provides a more assertive search for EOR candidates and allows reservoir types to be grouped on the basis of suitability. A similar philosophy will be developed for screening of CO2 projects, providing a further step in the decision making process and risk management associated with CO2-based EOR projects.
