Performance of CO2-EOR and Storage Processes Under Uncertainty

Author:

Ampomah W..1,Balch R. S.1,Cathar M..1,Will R..2,Lee S. Y.2,Dai Z..3

Affiliation:

1. Petroleum Recovery Research Center

2. Schlumberger Carbon Services

3. Los Alamos National Laboratory

Abstract

Abstract This paper presents an optimization approach using a reservoir field scale compositional flow model to co-optimize oil production and CO2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. A geocellular model constructed from geophysical geological and engineering data acquired from the unit was used for the study. An initial history match of primary and secondary recovery constructed was used as basis for CO2 flood study. A scenario based prediction model constructed for FWU (Ampomah et al. 2016a) was used as the baseline case for comparison to study the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO2 storage. A multi objective function that considers both oil recovery and CO2 storage was defined. Initial sensitivity analysis using a Latin-hypercube sampling technique was used to study the effects of operational uncertain variables on a defined objective function. A number of these operational variables were selected as control variables to be included in the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without uncertainty. Vertical permeability anisotropy ratio (Kv/Kh) was selected as the uncertain parameter in optimization, with uncertainty based on experience from the history match. A risk aversion factor was used to represent results at various confidence levels. The simulation results were compared to a baseline case that predicted a CO2 storage of 75% purchased CO2 and oil recovery of 72% original oil in place. The results showed an improved approach for optimizing oil recovery and CO2 storage within FWU. At the end of 21 years of prediction out of the optimal case, more than 94% of purchased CO2 has been stored and nearly 80% of the oil recovered. The sensitivity analysis reduced the number of control variables to lessen computational time. The defined objective function proved to be a robust approach to co-optimize oil recovery and CO2 storage. The Farnsworth CO2 project will serve as a benchmark for future CO2–EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.

Publisher

SPE

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