Qualitative risk assessment of legacy wells based on publicly available data for class VI well permit applications—Illinois basin case study.

• Step-by-step procedure to develop the tabulation and map component of UIC class VI permit. • Qualitative risk assessment methodology for all types of wells within AoR penetrating the confining zones. • Highlights the need for crossflow modelling of CO 2 leakage through improperly plugged wells. • Generalized categorization of legacy wells based on geologic penetrations and protections. Carbon Capture & Storage (CCS) refers to capturing the anthropogenic carbon dioxide (CO 2) at a source followed by injecting and storing it safely in the subsurface. The success of the CCS projects therefore heavily relies on how efficiently the confining zones (containment seals) prevent migration of the CO 2 to the surface and/or to the underground sources of drinking water (USDW) through leakage pathways. CCS projects requires drilling of Underground Injection Control (UIC) Class VI wells for permanent storage of CO 2 in subsurface. Detailed information of all the wells within the Area of Review (AoR) is needed to develop the map and tabulation components of the Class VI well permit application. This paper discusses the generic process that can be used by permit applicants to develop the dataset necessary for preparing the map and tabulation components of the Class VI permit application and perform qualitative risk assessment of all the wells within the AoR. This methodology directs the corrective action plans as well as monitoring plans to some extent. Results of the application of the newly developed methodology for wells in Illinois basin is discussed in detail. This methodology can be applied to all wells including orphaned wells, abandoned wells, active oil and gas wells, stratigraphic wells, disposal wells, etc. This methodology generalized categorization of legacy wells that will help in easier comparison of different CCS projects across the globe. The qualitative risk assessment methodology discussed in this paper is a good starting point for developing crossflow modeling. [ABSTRACT FROM AUTHOR]