Generalized functionals for qualification of geological carbon storage injection sites

Abstract

Many nations have pledged to achieve carbon neutrality by 2050 through the implementation of geological carbon storage (GCS) as a pivotal technology within the carbon capture, utilization, and storage (CCUS) framework, thus spearheading the Net Zero initiative. The CCUS goal is to capture carbon dioxide (CO2) emissions, recycling them or transporting them through pipelines to underground geological formations for permanent storage. Despite global success in GCS projects, driven by the oil and gas sector, large-scale GCS initiatives are still in their early stages in Brazil. Databases for potential storage sites, including saline aquifers and depleted reservoirs, are in development, as with the regulatory structure. This thesis introduces mathematical models for the systematic selection and ranking of underground CO2 storage sites. The research explores a family of mathematical functionals, each with distinct weighting functions, achieving two main objectives. Firstly, it clarifies non-linear interactions between rock and fluid properties using quality indicators. Secondly, it evaluates geographical regions, considering structural traps in caprocks. This methodology is a valuable resource for identifying suitable injection and storage locations. The models were implemented using the Matlab Reservoir Simulation Toolbox (MRST), and a case study using the UNISIM-I-D model for the Namorado Field in the Campos Basin, Brazil, indicates the influence of permeability and porosity as well as sigmoid, exponential or hybrid curves on different interpretations of ideal storage locations, with surpluses that range up to 66% in the best case. The vertical equilibrium model was used to reduce computational cost and Sobol sensitivity analysis to study the individual influence of each parameter. Simulation results corroborate the theoretical analyses. The ultimate objective of the study is to establish a fundamental knowledge base for future GCS projects in Brazil, leveraging legacy well infrastructures.