… iterations to converge to an acceptable minimum. In this manuscript we describe a new iterative
ensemble smoother (… of the iterative smoother with the two non-iterative methods and the …

… by the theory of the iterative ensemble Kalman smoother (IEnKS). … idea of the randomized
maximum likelihood method. Section 3 … obtained with various iterative ensemble smoothers. …

… The iterative methods are compared with the standard Ensemble Smoother (ES) to improve
… Finally, we have examined the smoother methods with a highly nonlinear model to examine …

… In Chen and Oliver [6], the LM ensemble randomized maximum likelihood (LM-EnRML) is
proposed where the regularization parameter is chosen heuristically as a way to balance the …

… iterative forms of ES were proposed in the past few years, most of which combine ideas from
random maximum likelihood (RML) and ensemble-… randomized version of objective function …

… on the modified LM method, LM-ensemble randomized maximum likelihood (LM-… ensemble
approximation to a sequential form of the randomized maximum likelihood (RML) method …

… based smoother with multiple data assimilation (ES-MDA). ES-MDA has an easy … on the
number of iterations that will be used. An iterative ensemble smoother algorithm based on the …

… can be chosen so that the resulting schemes coincide with the standard randomized maximum
likelihood (RML) and the ensemble smoother (ES), respectively. Therefore, the proposed …

… implementation of the iterative-ensemble smoother (iES). We show that iteration formulae
similar to … In the Levenberg-Marquardt ensemble randomized maximumlikelihood (LM-EnRML) …

… approach (randomized maximum likelihood, RML), an iterative ensemble smoother (IES), …
The three approximate sampling methods are applied to a linear-Gaussian inverse problem …