Inverse sequential simulation: A new approach for the characterization of hydraulic conductivities demonstrated on a non-Gaussian field

Inverse sequential simulation (iSS) is a new inverse modeling approach for the characterization of hydraulic conductivity fields based on sequential simulation. It is described and demonstrated in a synthetic aquifer with non‐Gaussian spatial features, and compared against the normal‐score ensemble Kalman filter (NS‐EnKF). The new approach uses the sequential simulation paradigm to generate realizations borrowing from the ensemble Kalman filter the idea of using the experimental nonstationary cross‐covariance between conductivities and piezometric heads computed on an ensemble of realizations. The resulting approach is fully capable of retrieving the non‐Gaussian patterns of the reference field after conditioning on the piezometric heads with results comparable of those obtained by the NS‐EnKF. Key Points: A new algorithm is developed for inverse stochastic conditional simulation The algorithm is applied for the generation of non‐Gaussian parameter fields The algorithm compares very well against its benchmark, the normal‐score EnKF