Background/Objectives

Carbon capture, utilization, and storage (CCUS) represents an interdisciplinary collection of technologies essential for mitigating anthropogenic CO₂ emissions and combating climate change. Geologic storage of CO₂ has emerged as a pivotal technology for achieving global greenhouse gas reduction goals due to the substantial storage capacity of subsurface formations and existing technology and infrastructure available for injection operations.  However, subsurface heterogeneity presents an inherent challenge for characterizing these potential storage units and geologic systems. We recognize that in CCUS projects, one of the most critical considerations is data and how data deficiencies may impact project viability. In this evolving industry, comprehensive subsurface characterization is essential, demanding the integration of diverse and reliable data. Our key focus is to underscore the influential role of robust subsurface data across the entire CCUS lifecycle, in addition to exploring methods for strengthening subsurface characterizations for the purposes of ensuring successful execution from project inception to completion.

Approach/Activities

Here we strive to unravel the intricate relationship between data deficiencies and CCUS project success.  We identify various data challenges associated with geologic storage of CO₂, consider the techniques and technology used to address them, and identify data collection inconsistencies between active projects. Predictive subsurface models created by interpolation, extrapolation, simulation, and geostatistical processes as they are applied in the oil and gas sector are examined here in the CCUS framework. We emphasize the significance of an integrated subsurface approach, involving predictive modeling, skilled practitioners, and data-driven activities.  We review the publicly available regulatory documents tied to existing CCUS programs within the US, noting a variety of inconsistencies among subsurface data being used by operators (e.g., the absence of advanced/contemporary petrophysical log data, inconsistent seismic data coverage, or missing well test data), a situation that adds to the uncertain nature of these and future projects.  We furthermore assess the utility of publicly available data in strengthening subsurface characterizations and our ability to apply simple statistical methods to these large and complex datasets.   

Results/Lessons Learned

The challenge posed by insufficient data is exacerbated by vague regulatory recommendations and operators striving to cut costs in projects with marginal economics. Here we offer a comprehensive examination of results and lessons learned from how regulators and project operators have tackled data deficiencies in CCUS projects. Drawing on examples from existing programs, we shed light on the consequences of insufficiently characterized subsurface settings. Additionally, we outline the ways in which publicly available data can be used to bolster existing assessments to strengthen subsurface understanding.  The results underscore the importance of robust data acquisition and integration programs in guiding safe CO₂ injection and ensuring the overall viability of CCUS initiatives.

There is no substitute for high quality data and subsurface expertise, and both are necessary to guide our understanding of the storage and confining interval, potential leakage pathways, induced seismicity risk, and other potential hazards.  Without appropriate data collection and integration programs, the nascent CCUS industry may not create the expected impact on atmospheric CO₂ concentrations.  Updating regulatory standards, with a pivot away from general “recommendations” towards specific data requirements could streamline project permits and allow for a re-focus on thorough subsurface characterization.   This evolution is essential for the benefit of operators, regulators, and communities, collectively ensuring the success and safety of CCUS endeavors.