Publications

  • A Novel Ensemble-Based Conjugate Gradient Method for Reservoir Management

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  • Practical Use of the Ensemble-Based Conjugate Gradient Method for Production Optimization in the Brugge Benchmark Study

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  • Ensemble-based Methods for Production Optimization

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  • An adaptive pluri-Gaussian simulation model for geological uncertainty quantification

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  • Large Sample Properties of the Adaptive Gaussian Mixture Filter

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  • Iterative Ensemble Smoothers in a probabilistic framework

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  • A modified randomized maximum likelihood for improved Bayesian history matching

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  • An auxiliary adaptive Gaussian mixture filter applied to flowrate allocation

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  • Improving physically based snow simulations by assimilating snow depths using the particle filter

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  • Extensions of the Ensemble Based Optimization algorithm

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  • Complex geology estimation using the iterative adaptive Gaussian mixture (IAGM)

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  • Mutation Based Optimization Extensions and Improvements

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  • An Auxiliary Adaptive Gaussian Mixture Filter Applied to Flowrate Allocation Using Real Data

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  • Ensemble Based Optimization using Impor tance Sampling and Gaussian Mixture

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  • An Auxiliary Adaptive Gaussian Mixture Filter Applied to Flowrate Allocation Using Real Data

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  • An Auxiliary Adaptive Gaussian Mixture Filter Applied to Flowrate Allocation Using Real Data

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  • Ensemble Based Optimization using Impor tance Sampling and Gaussian Mixture

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  • Different Parameterizations of the Initial Ensemble for a Channelized Reservoir in an

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  • Integrated Work Flow of Preserving Facies Realism in History Matching: Application to the Brugge Field

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  • Different parameterizations of the initial ensemble for a channelized reservoir in an Assisted History Matching context

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  • Improving physically based snow simulations by assimilating snow depths using the particle filter

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  • Iterative Ensemble Smoothers in a probabilistic framework

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  • Gradient Free Optimization under Uncertainty

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  • Ensemble

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  • Integrated Workflow of Preserving Facies Realism in History Matching: Application to the Brugge Field

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  • Iterative Ensemble Smoother as an Approximate Solution to a Regularized Minimum-Average-Cost Problem: Theory and Applications

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  • Generalized Randomized Maximum Likelihood

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  • Preserving Geological Realism in Reservoir Data Assimilation

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  • User manual. IRIS Filter Toolbox

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  • Ensemble Methods for Reservoir Data Assimilation: Best Practices

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  • Iterative Ensemble Smoothers in the Annealed Importance Sampling Framework

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  • Preser ving Geological Realism of Channelized Facies in Complex Reser voir

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  • Preserving Geological Realism of Facies Estimation on the Brugge Field

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  • Estimation of production rates using transient well flow modeling and the auxiliary particle filter - full-scale applications

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  • Iterative Ensemble Smoother as an Approximate Solution to a Regularized Minimum-Average-Cost Problem: Theory and Applications

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  • Ensemble Smoothers in the Annealed Importance Sampling Framework

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  • (Towards a) Generalized Randomized Maximum Likelihood

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  • An Adaptive Pluri-Gaussian Simulation Model for Geological Uncertainty Quantification

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  • Integrated Workflow of Preserving Facies Realism in History Matching: Application to the Brugge Field

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  • Preserving Geological Realism for Channelized Facies Estimation on the Brugge Field

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  • A Theoretical look at Ensemble-Based Optimization in Reservoir Management

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  • SPE 173872 Facies Parameterization and Estimation for Complex Reservoirs - The Brugge Field

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  • Facies Parameterization and Estimation for Complex Reservoirs - The Brugge Field

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  • Bridging multipoint statistics and truncated Gaussian fields for improved estimation of channelized reservoirs with ensemble methods

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  • Toward an enhanced Bayesian estimation framework for multiphase flow soft-sensing

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  • Large sample properties of the Adaptive Gaussian Mixture Filter

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  • Iterative Bayesian Inversion with Gaussian Mixtures: Finite Sample Implementation and Large Sample Asymptotics

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  • Ensemble Smoothers in the Annealed Importance Sampling Framework

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  • Ensemble based methods for estimation and optimization

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  • On an Alternative Implementation of the Iterative Ensemble Smoother and its Application to

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  • Iterative Bayesian Inversion with Gaussian Mixtures: Finite Sample Implementation and Large Sample Asymptotics

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  • On an iterative ensemble smoother and its application to a reservoir facies estimation problem

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  • A Closer Look at Ensemble-based Optimization in Reservoir Management

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  • Robust Ensemble-based Multi-objective Optimization

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  • Toward an Enhanced Bayesian Estimation Framework for Multiphase Flow Soft-sensing

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  • Complex Geology Estimation Using the Iterative Adaptive Gaussian Mixture (IAGM)

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  • A Closer Look at Ensemble-based Optimization in Reservoir Management

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  • Robust Ensemble-based Multi-objective Optimization

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  • Toward an enhanced Bayesian estimation framework for multiphase flow soft-sensing

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  • Complex Geology Estimation Using the Iterative Adaptive Gaussian Mixture (IAGM)

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  • On an Alternative Implementation of the Iterative Ensemble Smoother and its Application to Reservoir Facies Estimation

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  • Asymptotic properties of a broad class of mixture filters

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  • On an alternative implementation of the iterative ensemble smoother and its application to a reservoir facies estimation problem

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  • On an alternative implementation of the iterative ensemble smoother and its application to a reservoir facies estimation problem

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  • Data Assimilation with Gaussian Mixtures

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  • On an iterative ensemble smoother and its application to a reservoir facies estimation problem

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  • An iterative version of the adaptive Gaussian mixture

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  • Estimation of production rates using transient well flow modeling and the auxiliary particle filter

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  • Rate Allocation Project summary

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  • Rate Allocation – New Theoretical Development

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  • Application of the Adaptive Gaussian Mixture Filter to History Match a Real Field

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  • Iterative versions of the adaptive Gaussian mixture filter

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  • History matching of channelized reservoirs using ensemble based methods

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  • Toward An Expectation-Maximization Method for Parameter Estimation and Its Application to Rate Estimation in Oil Wells

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  • Some Iterative methods for Bayesian estimation in petroleum reservoirs

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  • Gaussian mutation for optimization and efficient importance sampling

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  • Estimation of Flowrates Using Transient Well Flow Modeling and the Auxiliary Particle Filter – Full-Scale Applications

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  • Evaluation of EnKF and Variants on the PUNQ-S3 Case

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  • Estimation of Production Rates Using Transient

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  • Estimation of Production Rates Using Transient Well Flow Modeling and the Auxiliary Particle Filter

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  • Application of the Adaptive Gaussian Mixture Filter to History Match a Real Field Case

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  • Iterative versions of the adaptive Guassian mixture filter

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  • Transient well flow modeling and modern estimation techniques for accurate production allocation

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  • Refined Adaptive Gaussian Mixture Filter - Application on a Real Field Case (SPE 154479)

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  • Transient well flow modeling and modern estimation techniques for accurate production allocation

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  • History Matching a Real Field Case Using the Newest Filter Methods Available

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  • Filtering with state space localized Kalman gain

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  • Comparing the adaptive Gaussian mixture filter with the ensemble Kalman filter on synthetic reservoir models

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  • Characterization of Permeability and Porosity from Nano Sensor Observations

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  • Bridging the ensemble Kalman filter and particle filters: The adaptive Gaussian mixture filter

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  • Comparing the EnKF and the adaptive Gaussian mixture filter

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  • Comparing the Adaptive Gaussian Mixture filter with the EnKF

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  • Bridging the Ensemble Kalman filter and particle filters

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  • Bridging the EnKF and particle filters

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  • Gaussian Mixture filters for high-dimensional dynamic systems

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  • Gaussian Mixture filters for high-dimensional dynamic systems

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International Research Institute of Stavanger
Mailing address:
Visiting address:
P.O. Box 8046, N-4068 Stavanger, Norway
Prof. Olav Hanssensvei 15, 4021 Stavanger


Phone:
Fax:

+47 51 87 50 00
+47 51 87 52 00

General email address: firmapost@iris.no
International Research Institute of Stavanger
Mailing address:
Visiting address:
P.O. Box 8046, N-4068 Stavanger, Norway
Prof. Olav Hanssensvei 15, 4021 Stavanger


Phone:
Fax:

+47 51 87 50 00
+47 51 87 52 00

General email address: firmapost@iris.no
International Research Institute of Stavanger
Mailing address:



Visiting address:
P.O. Box 8046
N-4068 Stavanger
Norway

Prof. Olav Hanssensvei 15 
4021 Stavanger

 
Phone:
Fax:
General email:
+47 51 87 50 00
+47 51 87 52 00
firmapost@iris.no