“…The utility of the D N criterion lies in the fact that efficient sequential design algorithms from linearized SED (e.g., Curtis et al, 2004;Stummer et al, 2004;Coles and Morgan, 2009;Coles and Curtis, 2011;Khodja et al, 2010) exist for D optimization (the A N , E N , and T N criteria remarked upon above could also be maximized/minimized using these algorithms). When combined with a linearized sequential design algorithm (LSDA), the D N criterion renders nonlinear Bayesian design computationally feasible for large-scale industrial applications, a feature shared by no other geoscientific nonlinear design technique without recourse to cluster computing or reparameterization of the design space (e.g., Ajo-Franklin, 2009;Guest andCurtis, 2009, 2010).…”