Home
Andreas Størksen Stordal's picture

Andreas Størksen Stordal

Associate Professor
  • E-mailAndreas.Stordal@uib.no
  • Phone+47 55 21 28 38
  • Visitor Address
    Realfagbygget, Allégt. 41
  • Postal Address
    Postboks 7803
    5020 Bergen
Academic article
  • Fossum, Kristian; Mannseth, Trond; Stordal, Andreas S. 2020. Assessment of multilevel ensemble-based data assimilation for reservoir history matching. Computational Geosciences.
  • Raanes, Patrick N.; Stordal, Andreas S.; Evensen, Geir. 2019. Revising the stochastic iterative ensemble smoother. Nonlinear processes in geophysics. 325-338.
  • Evensen, Geir; Raanes, Patrick N.; Stordal, Andreas S.; Hove, Joakim. 2019. Efficient Implementation of an Iterative Ensemble Smoother for Data Assimilation and Reservoir History Matching. Frontiers in Applied Mathematics and Statistics. 1-14.
  • Stordal, Andreas S.; Karlsen, Hans. 2017. Large sample properties of the adaptive gaussian mixture filter. Monthly Weather Review. 2533-2553.
  • Magnusson, Jan; Winstral, Adam; Stordal, Andreas S.; Essery, Richard L. H.; Jonas, Tobias. 2017. Improving physically based snow simulations by assimilating snow depths using the particle filter. Water Resources Research. 1125-1143.
  • Lorentzen, Rolf Johan; Stordal, Andreas S.; Hewitt, Neal. 2017. An auxiliary adaptive Gaussian mixture filter applied to flowrate allocation using real data from a multiphase producer. Computers & Geosciences. 34-44.
  • Stordal, Andreas S.; Nævdal, Geir. 2017. A modified randomized maximum likelihood for improved Bayesian history matching. Computational Geosciences. 29-41.
  • Chang, Yuqing; Stordal, Andreas S.; Valestrand, Randi. 2016. Integrated Workflow of Preserving Facies Realism in History Matching: Application to the Brugge Field. SPE Journal.
  • Lorentzen, Rolf Johan; Stordal, Andreas S.; Luo, Xiaodong; Nævdal, Geir. 2016. Estimation of production rates using transient well flow modeling and the auxiliary particle filter – full-scale applications. SPE Production & Operations. 163-175.
  • Stordal, Andreas S.; Elsheikh, Ahmed. 2015. Iterative ensemble smoothers in the annealed importance sampling framework. Advances in Water Resources. 231-239.
  • Luo, Xiaodong; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2015. Iterative Ensemble Smoother as an Approximate Solution to a Regularized Minimum-Average-Cost Problem: Theory and Applications. SPE Journal. 962-982.
  • Stordal, Andreas S. 2015. Iterative Bayesian inversion with Gaussian mixtures: finite sample implementation and large sample asymptotics. Computational Geosciences. 1-15.
  • Sebacher, Bogdan; Stordal, Andreas S.; Hanea, Remus Gabriel. 2015. Complex geology estimation using the iterative adaptive Gaussian mixture filter. Computational Geosciences.
  • Sebacher, Bogdan; Stordal, Andreas S.; Hanea, Remus Gabriel. 2015. Bridging multipoint statistics and truncated Gaussian fields for improved estimation of channelized reservoirs with ensemble methods. Computational Geosciences. 341-369.
  • Stordal, Andreas S.; Szklarz, Slawomir; Leeuwenburgh, Olwijn. 2015. A theoretical look at ensemble-based optimization in reservoir management. Mathematical Geosciences.
  • Luo, Xiaodong; Lorentzen, Rolf; Stordal, Andreas S.; Nævdal, Geir. 2014. Toward an enhanced Bayesian estimation framework for multiphase flow soft-sensing. Inverse Problems.
  • Lorentzen, Rolf; Stordal, Andreas S.; Nævdal, Geir; Karlsen, Hans A; Skaug, Hans J. 2014. Estimation of production rates with transient well-flow modeling and the auxiliary particle filter. SPE Journal. 172-180.
  • Stordal, Andreas S.; Lorentzen, Rolf. 2014. An iterative version of the adaptive Gaussian mixture filter. Computational Geosciences. 579-595.
  • Stordal, Andreas S.; Karlsen, Hans A; Nævdal, Geir; Oliver, Dean; Skaug, Hans J. 2012. Filtering with state space localized Kalman gain. Physica D : Non-linear phenomena. 1123-1135.
  • Valestrand, Randi; Nævdal, Geir; Stordal, Andreas S. 2012. Evaluation of EnKF and variants on the PUNQ-S3 case. Oil & gas science and technology. 841-855.
  • Stordal, Andreas S.; Valestrand, Randi; Karlsen, Hans A; Nævdal, Geir; Skaug, Hans J. 2012. Comparing the adaptive Gaussian mixture filter with the ensemble Kalman filter on synthetic reservoir models. Computational Geosciences. 467-482.
  • Stordal, Andreas S.; Oliver, Dean S. 2011. Characterization of permeability and porosity from nanosensor observations. Advances in Water Resources. 946-956.
  • Stordal, Andreas S.; Karlsen, Hans A; Nævdal, Geir; Skaug, Hans Julius; Vallès, Brice. 2011. Bridging the ensemble Kalman filter and particle filters: the adaptive Gaussian mixture filter. Computational Geosciences. 293-305.
Report
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2014. On an Alternative Implementation of the Iterative Ensemble Smoother and its Application to Reservoir Facies Estimation. .
  • Stordal, Andreas S.; Karlsen, Hans A. 2014. Large sample properties of the Adaptive Gaussian Mixture Filter. .
  • Stordal, Andreas S. 2014. Iterative Bayesian Inversion with Gaussian Mixtures: Finite Sample Implementation and Large Sample Asymptotics. .
  • Stordal, Andreas S.; Elsheikh, Ahmed. 2014. Ensemble Smoothers in the Annealed Importance Sampling Framework. .
  • Stordal, Andreas S.; Sebacher, Bogdan; Hanea, Remus G. 2014. Bridging multipoint statistics and truncated Gaussian fields for improved estimation of channelized reservoirs with ensemble methods. .
Lecture
  • Zhang, Yiteng; Lorentzen, Rolf Johan; Stordal, Andreas S. 2018. Practical Use of the Ensemble-Based Conjugate Gradient Method for Production Optimization in the Brugge Benchmark Study.
  • Zhang, Yiteng; Stordal, Andreas S.; Lorentzen, Rolf Johan; Chang, Yuqing. 2018. A Novel Ensemble-Based Conjugate Gradient Method for Reservoir Management.
  • Stordal, Andreas S. 2017. Iterative Ensemble Smoothers in the Annealed Importance Sampling Framework.
  • Stordal, Andreas S. 2016. Mutation Based Optimization Extensions and Improvements.
  • Stordal, Andreas S. 2016. Iterative Ensemble Smoother in a Probabilistic Framework.
  • Magnusson, Jan; Stordal, Andreas S.; Essery, Richard L. H.; Winstral, Adam; Jonas, Tobias. 2016. Improving physically based snow simulations by assimilating snow depths using the particle filter.
  • Chang, Yuqing; Stordal, Andreas S.; Valestrand, Randi. 2015. Preserving Geological Realism in Reservoir Data Assimilation.
Academic lecture
  • Stordal, Andreas S.; Moraes, Rafael; Raanes, Patrick N.; Evensen, Geir. 2019. Stein Variational Gradient Descent with Application to Data Assimilation.
  • Raanes, Patrick N.; Stordal, Andreas S.; Evensen, Geir. 2019. Revising the Method of Ensemble Randomized Maximum Likelihood.
  • Fossum, Kristian; Mannseth, Trond; Stordal, Andreas S. 2017. Multi-level ensemble based data assimilation.
  • Mannseth, Trond; Fossum, Kristian; Stordal, Andreas S. 2017. Generic approaches to reducing data-assimilation Monte-Carlo error for subsurface applications.
  • Chang, Yuqing; Stordal, Andreas S. 2017. Ensemble-based Methods for Production Optimization.
  • Stordal, Andreas S. 2016. Gradient free production optimization under geological uncertainty.
  • Sebacher, Bogdan; Stordal, Andreas S.; Hanea, Remus Gabriel. 2016. Different parameterizations of the initial ensemble for a channelized reservoir in an Assisted History Matching context.
  • Lorentzen, Rolf; Stordal, Andreas S.; Hewitt, Neal. 2016. An Auxiliary Adaptive Gaussian Mixture Filter Applied to Flowrate Allocation Using Real Data from a Multiphase Producer.
  • Stordal, Andreas S. 2015. particle Filters and Gaussian Mixture Filters.
  • Chang, Yuqing; Stordal, Andreas S.; Valestrand, Randi. 2015. Preserving Geological Realism of Channelized Facies in Complex Reservoir.
  • Chang, Yuqing; Stordal, Andreas S.; Valestrand, Randi. 2015. Preserving Geological Realism for Channelized Facies Estimation on the Brugge Field.
  • Stordal, Andreas S.; Nævdal, Geir. 2015. Generalized Randomized Maximum Likelihood.
  • Chang, Yuqing; Stordal, Andreas S.; Valestrand, Randi. 2015. Facies Parameterization and Estimation for Complex Reservoirs - The Brugge Field.
  • Stordal, Andreas S.; Elsheikh, Ahmed. 2015. Ensemble Smoothers in the Annealed Importance Sampling Framework.
  • Stordal, Andreas S.; Nævdal, Geir. 2015. (Towards a) Generalized Randomized Maximum Likelihood.
  • Luo, Xiaodong; Lorentzen, Rolf; Stordal, Andreas S.; Nævdal, Geir. 2014. Toward an Enhanced Bayesian Estimation Framework for Multiphase Flow Soft-sensing.
  • Fonseca, R.M.; Stordal, Andreas S.; Leeuwenburgh, O; Van Den Hof, P.M.J.; Jansen, J.D. 2014. Robust Ensemble-based Multi-objective Optimization.
  • Chang, Yuqing; Stordal, Andreas S.; Valestrand, Randi. 2014. Preserving Channelized Facies on Brugge Field .
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2014. On an iterative ensemble smoother and its application to a reservoir facies estimation problem.
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2014. On an iterative ensemble smoother and its application to a reservoir facies estimation problem.
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2014. On an Alternative Implementation of the Iterative Ensemble Smoother and its Application to Reservoir Facies Estimation.
  • Stordal, Andreas S.; Nævdal, Geir; Valestrand, Randi; Karlsen, Hans A. 2014. Gaussian Mixtures in data assimilation problems.
  • Nævdal, Geir; Eikrem, Kjersti Solberg; Stordal, Andreas S. 2014. Ensemble based methods for estimation and optimization.
  • Sebacher, B.; Stordal, Andreas S.; Hanea, Remus G. 2014. Complex Geology Estimation Using the Iterative Adaptive Gaussian Mixture (IAGM).
  • Karlsen, Hans A; Stordal, Andreas S. 2014. Asymptotic properties of a broad class of mixture filters.
  • Stordal, Andreas S.; Szklarz, S.P.; Leeuwenburgh, O. 2014. A Closer Look at Ensemble-based Optimization in Reservoir Management.
  • Stordal, Andreas S.; Sklarz, S. P. 2013. Gaussian mutation for optimization and efficient importance sampling.
  • Valestrand, Randi; Nævdal, Geir; Shafieirad, Ali; Stordal, Andreas S.; Dovera, Laura. 2012. Refined Adaptive Gaussian Mixture Filter - Application on a Real Field Case.
  • Stordal, Andreas S.; Lorentzen, Rolf Johan. 2012. Iterative versions of the adaptive Gaussian mixture filter.
  • Stordal, Andreas S.; Sebacher, Bogdan; Hanea, Remus G. 2012. History matching of channelized reservoirs using ensemble based methods.
  • Valestrand, Randi; Nævdal, Geir; Stordal, Andreas S. 2012. Application of the Adaptive Gaussian Mixture Filter to History Match a Real Field Case.
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Lorentzen, Rolf Johan; Stordal, Andreas S.; Nævdal, Geir. 2012. An alternative implementation of the iterative ensemble smoother and some numerical results.
Doctoral dissertation
  • Stordal, Andreas S. 2011. Sequential Data Assimilation in High Dimensional Nonlinear Systems.
Academic chapter/article/Conference paper
  • Zhang, Yiteng; Lorentzen, Rolf Johan; Stordal, Andreas S. 2018. Practical Use of the Ensemble-Based Conjugate Gradient Method for Production Optimization in the Brugge Benchmark Study. 13 pages.
  • Zhang, Yiteng; Stordal, Andreas S.; Lorentzen, Rolf Johan; Chang, Yuqing. 2018. A Novel Ensemble-Based Conjugate Gradient Method for Reservoir Management. 13 pages.
  • Stordal, Andreas S.; Chang, Yuqing; Hanea, Remus G.; Ek, T. 2016. Ensemble Based Optimization Using Importance Sampling and Gaussian Mixtures.
  • Sebacher, Bogdan; Stordal, Andreas S.; Hanea, Remus Gabriel. 2016. Different Parameterizations of the Initial Ensemble for a Channelized Reservoir in an Assisted History matching Context.
  • Lorentzen, Rolf; Stordal, Andreas S.; Neal, Hewitt. 2016. An Auxiliary Adaptive Gaussian Mixture Filter Applied to Flowrate Allocation Using Real Data from a Multiphase Producer.
  • Luo, Xiaodong; Lorentzen, Rolf; Stordal, Andreas S.; Nævdal, Geir. 2014. Toward an Enhanced Bayesian Estimation Framework for Multiphase Flow Soft-sensing.
  • Fonseca, R.M.; Stordal, Andreas S.; Leeuwenburgh, O.; Van Den Hof, P.M.J.; Jansen, P. 2014. Robust Ensemble-based Multi-objective Optimization.
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2014. On an Alternative Implementation of the Iterative Ensemble Smoother and its Application to Reservoir Facies Estimation.
  • Sebacher, B.; Stordal, Andreas S.; Hanea, Remus G. 2014. Complex Geology Estimation Using the Iterative Adaptive Gaussian Mixture (IAGM).
  • Stordal, Andreas S.; Szklarz, S.P.; Leeuwenburgh, O. 2014. A Closer Look at Ensemble-based Optimization in Reservoir Management. 16 pages.
Poster
  • Stordal, Andreas S.; Chang, Yuqing; Hanea, Remus G.; Ek, T. 2016. Ensemble Based Optimization Using Importance Sampling and Gaussian Mixtures.
  • Sebacher, Bogdan; Stordal, Andreas S.; Hanea, Remus Gabriel. 2016. Different parameterizations of the Initial Ensemble for a Channelized Reservoir in an Assisted History Matching Context.
  • Chang, Yuqing; Stordal, Andreas S.; Valestrand, Randi. 2015. Preserving Geological Realism of Facies Estimation on the Brugge Field.
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2014. On an alternative implementation of the iterative ensemble smoother and its application to a reservoir facies estimation problem.
  • Luo, Xiaodong; Chen, Yan; Valestrand, Randi; Stordal, Andreas S.; Lorentzen, Rolf; Nævdal, Geir. 2014. On an alternative implementation of the iterative ensemble smoother and its application to a reservoir facies estimation problem.
Academic literature review
  • Sebacher, Bogdan; Hanea, Remus Gabriel; Stordal, Andreas S. 2017. An adaptive pluri-Gaussian simulation model for geological uncertainty quantification. 494-508.

More information in national current research information system (CRIStin)