Cost-optimal design of pressure-based monitoring networks for carbon sequestration projects, with consideration of geological uncertainty

Abstract

Leakage from geologic faults and abandoned wells represents one of the major risks to industrial-scale carbon capture and storage (CCS) projects. Current CCS regulations and best practice guidance suggest that operators emplace risk-informed monitoring, verification, and accounting (MVA) plans to protect public safety and reduce property and environmental damage. Deep subsurface pressure monitoring is regarded as one of the most cost-effective technologies for early leakage detection in CCS projects. In practice, however, the number of deep pressure monitoring wells that an operator can deploy often remains limited because of the high costs associated with drilling, instrumenting, and operating these wells. Thus, optimal design of the pressure monitoring network is essential to minimizing monitoring and liability costs and gaining public support. In this work, we present a general, binary integer programming approach to solve an optimal monitoring well network design problem under multiple constraints. Specifically, our approach helps a CCS operator to design a cost-optimal monitoring network that covers all potentially leaky locations (in a worst-case-scenario sense) while satisfying a prescribed carbon dioxide (CO2) storage performance criterion and considering geological uncertainty. Instead of using cost surrogates as has been done in many other studies, our formulation allows the user to directly assess total costs in terms of monitoring costs and potential economic losses associated with brine and CO2 leakage. Our numerical examples demonstrate that a cost-optimal monitoring network may save millions of dollars in total costs, including well construction and leakage costs. Factors exerting the most impact on the cost-optimal monitoring network design are unit leakage damage costs, pressure threshold for leakage detection, and geological uncertainty.