The overall objective of this project is to develop a Pressure-based Inversion and Data Assimilation System (PIDAS) for detecting CO2 leakage from storage formations.
Carbon capture, utilization, and sequestration (CCUS) has the potential to enable deep reductions in global carbon emissions if high storage efficiency can be achieved. A major hurdle to industrial-scale implementation of geological carbon sequestration (GCS) projects is the potential migration of fluids (brine or CO2) from the storage formations and the resulting legal and financial liabilities. The capability to accurately identify leakage pathways by which stored CO2 could leak, has leaked, or is leaking from the targeted storage zone is thus of paramount importance to site licensees and regulators. Although many MVA techniques have been devised, pressure-based monitoring technology remains the most sensitive and reliable technique for early detection. It has consistently received the highest score in terms of benefit/cost ratio and it provides the greatest potential for leakage detection with broad areal coverage. Although much has been done in the area of forward modeling of leakage, the more challenging pressure inversion problems need further theoretical, experimental, and field studies.
The proposed PIDAS tool will expand and strengthen existing pressure-based techniques for leakage detection in GCS repositories. The major research objectives are to perform integrated theoretical and numerical analysis, laboratory experiments, and field tests and develop effective data assimilation and inversion algorithms for identifying leakage pathways.