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 d1, 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 m2 d1, respectively) and from 28 May 2007 to 4 September 2007 (mean and standard deviation = 12.0 and 28.1 g m2 d1, 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.