A New CO2-EOR Methods Screening Model Based on Interdependency Parameters

Abstract

The successful implementation of carbon dioxide-enhanced oil recovery (CO2-EOR) is crucial in increasing oil production and reducing carbon emissions. For this reason, screening criteria are needed for the initial characterization of a suitable CO2-EOR reservoir. The existing screening model treats the screening parameters independently. Therefore, each parameter has its criteria limit and does not relate to the others. However, in reality, several screening parameters are interdependent, so we need a method that treats the interdependent parameters simultaneously. This research develops a new simultaneous screening model using the interdependency of the parameters. Quantitative and actual data were collected from CO2-EOR field documentation worldwide with a comprehensive analysis. A statistical approach with a correlation analysis method was used to determine the interconnected screening parameters. The results were synchronized with the expert domain to match actual physical conditions. The limit of simultaneous screening criteria was acquired by multivariate quality control (MQC) based on the principal component analysis (PCA) method. The proposed screening model was compared with 13 actual projects, and demonstrated improvements to previous models. The results match actual operations and follow the expert domain rules. If the miscible CO2-EOR is met, then the immiscible should also be appropriate but not vice versa. Nevertheless, four different immiscible projects are predicted to be slightly optimistic as miscible or immiscible.