History Matching With Parameterization Based on the SVD of a Dimensionless Sensitivity Matrix
In this research we develop efficient parameterization algorithms for history matching based on the principal right singular vectors of the dimensionless sensitivity matrix corresponding the maximum a posteriori estimate of reservoir model parameter. The necessary singular vectors can be computed with …
Covariance Localization for Ensemble Kalman Filter
Because of its ease of implementation, computational efficiency and the fact that it generates multiple history-matched models, which conceptually allows one to characterize the uncertainty in reservoir description and future performance predictions, the ensemble Kalman filter (EnKF) provides a highly attractive …
Iterative forms of EnKF and Ensemble Smoother (ES)
The ensemble Kalman filter (EnKF) has become a popular method for history matching production and seismic data in petroleum reservoir models. However, it is well known that EnKF may fail to give acceptable data matches especially for highly nonlinear problems. This …
Combining Ensemble Kalman Filter and Markov Chain Monte Carlo
The ensemble Kalman filter (EnKF) has recently become a popular history-matching tool largely because of its computational efficiency and ease of implementation. While EnKF has improved previous history matches obtained manually in several field cases, and often appears to give reasonable …
EnKF Data Assimilation with Kernel PCA and Discrete Cosine Transform Parameterizations
In this reseach project, we investigate the use of ensemble Kalman filter (EnKF) for production data assimilation with discrete cosine transform (DCT) and kernel principle component analysis (KPCA) parameterization for channelized reservoirs, where the prior geostatistical model is based on multi-point …
Production Optimization Under Linear and Nonlinear Constraints
The production optimization step of the "closed-loop" reservoir management is an optimal well control problem determining optimal operating conditions to maximize hydrocarbon extraction or net present value (NPV) for the remaining expected life of a reservoir. It is an important step …
Derivative-free Production Optimization Algorithms
For large scale production optimization problem, gradient based algorithms seem to be the main feasible approach. However, such algorithms have not been widely performed in practice because of the following shortcomings:(i) it is very complicated to commutate the gradient of the …
Optimal Well Placement
Determination of optimal location for the injection (and production) wells is a critical step in reservoir development plan in order to produce higher hydrocarbon at lower cost. Finding optimal well locations is an optimization problem on discrete variables (well gridblock indices) …
Well Test Data Assimilation Using EnKF
This reseach project investigates the application of the ensemble Kalman filter (EnKF) to the integration of well test data into heterogeneous reservoir models generated from geological and geophysical data. EnKF does not require computing the gradient of an objective function, and …
Uncertainty Quantification of Reservoir Performance Predictions Using a Stochastic Optimization Algorithm
This study presents a modified simultaneous perturbation stochastic approximation (SPSA) algorithm for automatic history matching. The new SPSA algorithm simultaneously perturbs the reservoir model by using unconditional realizations to generate a stochastic search direction. This search direction is always downhill and …