A controlled field pilot has been developed in Bozeman, Montana, USA, to study near surface CO 2 transport and detection technologies. A slotted horizontal well divided into six zones was installed in the shallow subsurface. The scale and CO 2 release rates were chosen to be relevant to developing monitoring strategies for geological carbon storage. The field site was characterized before injection, and CO 2 transport and concentrations in saturated soil and the vadose zone were modeled. Controlled releases of CO 2 from the horizontal well were performed in the summers of 2007 and 2008, and collaborators from six national labs, three universities, and the U.S. Geological Survey investigated movement of CO 2 through the soil, water, plants, and air with a wide range of near surface detection techniques. An overview of these results will be presented.

A new field facility was used to study CO2 migration processes and test techniques to detect and quantify potential CO2 leakage from geologic storage sites. For 10 days starting 9 July 2007, and for seven days starting 3 August 2007, 0.1 and 0.3 t CO2 d−1, respectively, were released from a ∼100‐m long, sub‐water table (∼2.5‐m depth) horizontal well. The spatio‐temporal evolution of leakage was mapped through repeated grid measurements of soil CO2 flux (FCO2). The surface leakage onset, approach to steady state, and post‐release decline matched model predictions closely. Modeling suggested that minimal CO2 was taken up by groundwater through dissolution, and CO2 spread out on top of the water table. FCO2 spatial patterns were related to well design and soil physical properties. Estimates of total CO2 discharge along with soil respiration and leakage discharge highlight the influence of background CO2 flux variations on detection of CO2 leakage signals.

Abstract.A field facility located in Bozeman, Montana provides the opportunity to test methods to detect, locate, and quantify potential CO 2 leakage from geologic storage sites. Temporal variations in CO 2 concentrations were correlated with atmospheric and soil temperature, wind speed, atmospheric pressure, rainfall, and CO 2 injection rate.

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We tested the ability of eddy covariance (EC) to detect, locate, and quantify surface CO2 flux leakage signals within a background ecosystem. For 10 days starting on 9 July 2007, and for 7 days starting on 3 August 2007, 0.1 (Release 1) and 0.3 (Release 2) t CO2 d−1, respectively, were released from a horizontal well ∼100 m in length and ∼2.5 m in depth located in an agricultural field in Bozeman, Montana. An EC station measured net CO2 flux (Fc) from 8 June 2006 to 4 September 2006 (mean and standard deviation = −12.4 and 28.1 g m−2 d−1, respectively) and from 28 May 2007 to 4 September 2007 (mean and standard deviation = −12.0 and 28.1 g m−2 d−1, respectively). The Release 2 leakage signal was visible in the Fc time series, whereas the Release 1 signal was difficult to detect within variability of ecosystem fluxes. To improve detection ability, we calculated residual fluxes (Fcr) by subtracting fluxes corresponding to a model for net ecosystem exchange from Fc. Fcr had reduced variability and lacked the negative bias seen in corresponding Fc distributions. Plotting the upper 90th percentile Fcr versus time enhanced the Release 2 leakage signal. However, values measured during Release 1 fell within the variability assumed to be related to unmodeled natural processes. Fcr measurements and corresponding footprint functions were inverted using a least squares approach to infer the spatial distribution of surface CO2 fluxes during Release 2. When combined with flux source area evaluation, inversion results roughly located the CO2 leak, while resolution was insufficient to quantify leakage rate.