• geological carbon sequestration;
  • parameter estimation;
  • monitoring data;
  • inverse problem

[1] This study develops and evaluates an integrated methodology including parameter zonation, efficient global optimization, and multiple aquifer realizations that gives a useful forecast of the pressure distribution and the CO2 plume migration through a heterogeneous storage formation, over time, using only a few monitoring locations in a feasibly short amount of computing time, while dealing with data error. Geological characteristics of the example application are similar to a CO2 sequestration pilot test conducted in a fluvial-deltaic geological setting. In the example, the CO2 injection problem is simulated with the TOUGH2 code, a numerical simulator for multiphase (gas and aqueous), multicomponent flow and transport. The inverse problem is difficult because the GCS optimization estimation problem has multiple local minima and the simulation is computationally expensive. The efficient surrogate response surface global optimization algorithm “Stochastic RBF” (stochastic radial basis function) is used to calibrate the model parameters. Results are averaged over three saline aquifer realizations. In the third numerical experiment using only pressure data, the CO2 plume could be determined with an average correlation coefficient compared to the actual plume of up to R2 = 0.916 (for current plume at t = 1.5 years) and average R2 = 0.80 (for forecasted plume estimated at t = 7.5 years years, using only the first 1.5 years of monitoring data). Adding gas saturation data improved the 6 year forecast somewhat (increasing average R2 = 0.85) but it was not significantly helpful in estimating the current plume. Both our inverse methodology and findings can be broadly applicable to GCS in heterogeneous sedimentary formations.