Identification of CO₂ Sequestration Opportunities: CO₂ Miscible Flooding Guidelines

Abstract

Carbon dioxide (CO2) flooding has been demonstrated as an economically feasible technique for carbon capture and storage (CCS) via enhanced oil recovery (EOR). In the oil industry, most of the CO2-EOR projects were implemented in miscible phase (CO2 miscible flooding), and it has become the most productive EOR method in the United States since 2012. Successful implementation of CO2 miscible flooding requires comprehensive guidelines about where CO2 can be applied. With the development of new technology, the suitable conditions for CO2-EOR have changed. Therefore, updating the guidelines for CO2-EOR is necessary. In this study, we updated the guidelines for field CO2 miscible applications in the United States by collecting valuable information from about 100 publications. Significant parameters for CO2 miscible flooding such as minimum miscibility pressure (MMP) and pay zone net thickness were considered for the first time in comparison with existing research studies. After data processing/cleaning, 207 projects have remained in the dataset. Combination plots were created to explore the ranges, distributions, and cumulative frequencies of each property. Meanwhile, descriptive values were calculated based on statistical methods. The guidelines for CO2 miscible flooding were presented with important parameters, including porosity, permeability, depth, reservoir temperature, net thickness, oil saturation, oil gravity, oil viscosity, and MMP. The analyzed results show that the reservoir pressure should be greater than 1020 psi to achieve miscibility, and CO2 miscible flooding project could be successfully applied in a reservoir with an oil gravity greater than 25 °API, oil viscosity less than 4 cp, and a reservoir temperature less than 120 °F.

Department(s)

Geosciences and Geological and Petroleum Engineering

Keywords and Phrases

CO2 miscible flooding; Field applications; Minimum miscibility pressure; Screening guidelines; Statistical analysis

International Standard Serial Number (ISSN)

0016-2361

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2019 Elsevier Ltd, All rights reserved.

Publication Date

01 Apr 2019

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