Ensemble Kalman Filter For History Matching

Speaker: Dr. Dean Oliver, Professor and Director,
Mewbourne School of Petroleum and Geology Engineering
The University of OklahomaThe problem of reservoir characterization through automatic history matching has been extensively studied in recent years. Efficient applications have, however, required either an adjoint or a gradient simulator method to compute the gradient of the objective function or a sensitivity coefficient matrix for the minimization. Both computations are expensive when the number of model parameters or the number of observation data is large. The codes for gradient-based history matching methods are also complex and time-consuming to write.This talk reports the use of the Ensemble Kalman Filter (EnKF) for automatic history matching. EnKF is a Monte Carlo method, in which a collection of reservoir models is used to estimate various relationships for history matching. An estimate of uncertainty in future reservoir performance can also be obtained from the ensemble.Unlike traditional history matching, the source code of the reservoir simulator is not required, which allows this method to be used with any reservoir simulator. Also, the assimilation of the data in EnKF is done sequentially rather than simultaneously as in traditional history matching. By so doing the reservoir models are always kept up-to-date, which may be important when the frequency of data is fairy high.In this talk, the application of the EnKF to the problem of history matching the PUNQ-S3 test modelwill be described. It is a small (19x28x5) three-phase reservoir engineering model that was developed by research units in the European Union to compare methods for quantifying uncertainty assessment in history matching. The model is also tested on a synthetic problem in which the locations of geologic facies must be determined. In both cases, the EnKF provided satisfactory history matching results while requiring less computation than traditional methods.

Location: Hedco Pertroleum and Chemical Engineering Building (HED) - CO 116

Audiences: The Scientific Community is Cordially Invited

Contact: Takimoto Idania