ES-PhD: Ensemble Smoother - Patrick Raanes

Research on the ‘Ensemble Smoother’ (ES) method for parameter estimation (history matching) and model conditioning.

Objectives

The ensemble smoother (ES) is a promising method that has potential applications in a number of research areas and problems related to computational geosciences. The purpose of this project is to develop experience with ES with different dynamic models and examples, and maturing the method for further operational use in history matching. The project is expected to lead to spin-off applications in several fields.

Project Summary

Project tasks include:

  • Evaluation of ES for parameter estimation in a number of known test problems of varying complexity to evaluate ES performance with respect to other traditional methods
  • Evaluation, implementation and testing of recently proposed iterative smoother algorithms
  • Development, implementation and testing of new iterative smoother algorithms
  • Application and demonstration of smoother algorithms in agree field examples.
 
Project Details
Acronym: 
ES-PhD
Funding Agency: 
Statoil E&P
NERSC Principal Investigator: 
Laurent Bertino
Project Deputy Leader at NERSC: 
Alberto Carrassi
Coordinating Institute: 
Nansen Environmental and Remote Sensing Center
Project Status: 
Completed