Assessing wells for reuse: a probabilistic approach to well integrity using a numerical model and Bayesian belief network

With increasing CO 2 emissions from fossil fuels alongside the push for more sustainable energy systems, the subsurface as a valuable asset for various sustainable energy applications has gained interest. Two primary drawbacks for the use of assets and infrastructure in transition to sustainable energy are (1) the large costs associated with new subsurface infrastructure (e.g. wells, platforms and pipelines), and (2) the detailed integrity assessment of existing infrastructure required for reuse. The concept of reusing existing infrastructure is particularly attractive as it has the potential to facilitate cost-efficient access to the subsurface for sustainable energy applications. Wells are a crucial component for reuse since they generally have a long history of mechanical loads and exposure to formation fluids prior to reuse. A common threat to well integrity is the development of fractures in the cement surrounding the well, or microannuli, at the casing-cement or cement-formation interface that may promote upward migration of fluids. This migration is often difficult to assess with conventional logs but may enable fluid communication from the storage reservoir to the overburden. Such communication is a threat for safe and efficient subsurface energy or CO 2 storage.