While the principles of enhanced oil recovery (EOR) are not new, field implementation has been scarce, particularly in the case of dual-porosity naturally fractured reservoirs, where the interaction of two different porous media creates a more complex displacement process. Several approaches to define the screening criteria on dual-porosity reservoirs have been postulated; the evaluation of the matrix-fracture interaction still requires complex models for proper EOR selection.

This paper offers a multidimensional approach to EOR selection in dual-porosity naturally fractured reservoirs, starting with a detailed analysis of the matrix-fracture system and including: transmissivity/storativity ratios, fracture geometry, matrix block size, and dominant recovery mechanisms. Historical observations are used for characterization and identification of areas where one porous media is dominant and to help shortlist the desired EOR methods on an area-by-area basis.

Two levels are considered in the analysis: the first level allows for a qualitative EOR ranking, suitable for reservoirs with limited information. The next level (numerically intensive) provides a quantitative EOR ranking with basic economics. The first-level ranking uses four different criteria for the selection—namely, pore-level displacement efficiency of the matrix-fracture system, EOR agent compatibility, matrix-fracture geometry, and the distribution of moveable hydrocarbons—and an internal advisor-system to achieve the ranking based on the fluid and reservoir properties.

A combination of analytical and numerical models is systematically used to overcome the challenge of estimating pore-level displacement efficiency when the EOR agent contacts matrix and fracture systems simultaneously (including all the relevant recovery mechanisms, such as gravity drainage). An advisor system based on a global EOR project database, merged with in-house EOR engineering expertise, complements the EOR selection. Numerical modeling is used at a later stage to further substantiate and quantify the EOR solution, allowing for a full-cycle comparative evaluation.

It is worth mentioning that the advisory EOR system presented here not only tackles a highly challenging topic but also provides “dynamic engineering guidance” throughout the EOR selection process. The authors believe that combining this reliable engineering process with ever-increasing computation power will help our industry to identify EOR potential easily.

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