1287 Towards Understanding and Modeling Chronic and Acute Carbon Dioxide Leaks at an Enhanced Oil Recovery Site

Wednesday, 25 January 2017
4E (Washington State Convention Center )
Caitlin Marina Augustin, University of Miami, Miami, FL; and B. T. Galfond, P. K. Swart, and D. D. Riemer

Geologic carbon capture and storage technologies (CCS) –the suite of processes and tools that capture carbon dioxide (CO2) gas and inject the CO2 underground into a subsurface reservoir so that it never reaches the atmosphere– have the potential to help world achieve the global two-degrees-Celsius ceiling on global warming.  Despite investment, there are crucial unknowns that limit the widespread adoption of CCS, specifically the integrity and reactivity of monitoring, measurement, and verification (MMV) tools.  These MMV tools are directly related to the ability to accurately assess carbon credits and to confidently state the safety of the subsurface injection.  This paper advances MMV literature by demonstrating both exceptional meteorological characterization of a prototypical CCS site and thorough assessment of new monitoring devices and post-processing data analysis.  Continuous multi-year measurements showing well-characterized non-natural CO2 release events, clear seasonal and diurnal CO2 flux trends, and coupled CO2/methane (CH4) measurements are presented.  Our results demonstrate that cavity ring-down spectroscopy is a viable high-precision, lower-cost monitoring technology that is capable of detecting small and large-scale fluctuations of CO2 and CH4. Furthermore, these continuous low-level releases are modeled using atmospheric dispersion tools, and these models indicate a potentially larger societal impact from continuous low-level releases than from short-term high volume releases.  In line with much of the atmospheric modeling literature, big data statistical techniques including cluster analysis, hierarchical regression, and mixing models are applied to better interpret limited sampling data to understand the characteristics that would predict non-natural events at the sampling locations. These presented results have immediate implications for CCS monitoring and verification regulations specifically, and climate change mitigation technologies more generally, under programs being discussed as part of the implementation of both U.S. Clean Power Plan and the international Paris Climate Accords (COP 21).
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