An Initial Approach of Multiple Linear Regression in CO2-water Relative Permeability Prediction for Carbon Storage Projects

Ying Yu

doi:10.20944/preprints202406.1849.v1

Preprint Concept Paper Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 25 June 2024 / Approved: 26 June 2024 / Online: 26 June 2024 (11:35:26 CEST)

This work discusses the feasibility of multiple linear regression in predicting water/CO₂ relative permeability using training and testing datasets from two nearby wells, separately, of the Lower Cretaceous Lakota Sandstone, Jurassic Hulett Sandstone, and Pennsylvanian Minnelusa Formation at the Dry Fork Station site. The outcome is promising as the predicted and measured relative permeability data are decently comparable. Yet, whether this approach could be generally applicable needs more delicate models and larger training datasets to be determined.

CCUS; Relative permeability; Supervised learning

Environmental and Earth Sciences, Geophysics and Geology

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An Initial Approach of Multiple Linear Regression in CO₂-water Relative Permeability Prediction for Carbon Storage Projects

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