Abstract

Carbon sequestration in subsurface geological formations has massive potential for emission reduction of greenhouse gases in the coming decades. To accurately identify a geological prospect for carbon dioxide CO2 storage requires a play-based exploration scenario analogous to hydrocarbon exploration. The process requires a multi-faceted approach incorporating geological, geophysical, and well-engineering datasets for CO2 storage screening potential of a depleted oil and gas reservoir and/or saline aquifers. An automated Python script-based user interface (UI) is developed for identifying necessary data sources when planning CO2 storage screening of any geological sites in a minimum amount of time. UI takes multiple varied file inputs (.las, .csv, .pdf, .txt, .xlsx, .sgy) and searches them for the necessary data which is required for CO2 storage screening potential such as porosity, lithology, permeability, temperature, pore pressure, etc. It further generates a detailed report of the geological site in terms of data priority listing and feasibility of CO2 screening program. The application is proven to be efficient in reducing time and cost during the early planning phase of the storage site selection program. It is tested on a small amount of data from Ichthys field, Browse Basin, Western Australia for CO2 storage screening and has enormous scope to improve further.