S34A-06:
Assessment of the Potential for Flux Estimation Using Concentration Data from Mobile Surveys

Wednesday, 17 December 2014: 5:22 PM
Andrew Gyenis1, Christopher Zahasky1, Dylan Michael Moriarty2 and Sally M Benson3, (1)Stanford Earth Sciences, Stanford, CA, United States, (2)Stanford University, Tucson, AZ, United States, (3)Stanford University, Stanford, CA, United States
Abstract:
Carbon capture and storage is a climate change mitigation technology with the potential to serve as a bridge technology as society transitions from a fossil fuel dependent energy system to a renewable energy dominated system. One of the greatest concerns associated with wide-scale adoption of carbon capture and storage technology is the risk of carbon dioxide leakage from sequestration reservoirs. Thus there is a need to develop efficient and effective strategies for monitoring and verification of geologically stored carbon dioxide. To evaluate the potential for estimating leakage fluxes based on mobile surveys, we establish correlations between concentration data and flux measurements made with a flux chamber. These correlations are then used to estimate leakage fluxes over a 70-meter long horizontal well buried approximately 1.8 meters below the surface at the Zero Emissions Research and Technology (ZERT) facility operated by Montana State University. The CO2 had a leakage rate of 0.15 t/d, which is comparable to a small leak in an industrial scale project (0.005% of a 1 Mt/yr storage project). A Picarro gas analyzer was used to measure 12CO2 and 13CO2 at heights of 3 cm above the ground surface. Previous studies (Moriarty, 2014) show that concentration data at this height provides a very high likelihood (>95%) of detecting leaks within a distance of 2.5 m of the leak. Measured concentration data show a noisy but significant correlation with flux measurements, thus providing the possibility to obtain rough estimates of leakage fluxes from mobile measurements.

Moriarty, Dylan, 2014. Rapid Surface Detection of CO2 Leaks from Geologic

Sequestration Sites. MS Thesis, Stanford University.