Estimation of Three-Phase Relative Permeabilities for A WAG Process Using An Improved Ensemble Randomized Maximum Likelihood Algorithm

2017 ◽  
Author(s):  
Zhaoqi Fan ◽  
Yin Zhang ◽  
Daoyong Yang
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Algorithm ◽  
Relative Permeabilities ◽  
Three Phase ◽  
Randomized Maximum Likelihood

Estimation of Three-Phase Relative Permeabilities for a Water-Alternating-Gas Process by Use of an Improved Ensemble Randomized Maximum-Likelihood Algorithm

2016 ◽  
Vol 19 (04) ◽  
pp. 683-693 ◽  
Author(s):  
Zhaoqi Fan ◽  
Yin Zhang ◽  
Daoyong Yang
Keyword(s):  
Maximum Likelihood ◽  
History Matching ◽  
Step Length ◽  
Production Data ◽  
Damping Factor ◽  
Relative Permeabilities ◽  
Reservoir Simulations ◽  
Water Alternating Gas ◽  
Three Phase ◽  
Randomized Maximum Likelihood

Summary In this paper, a modified ensemble randomized maximum-likelihood (EnRML) algorithm has been developed to estimate three-phase relative permeabilities with consideration of the hysteresis effect by reproducing the actual production data. Ensemble-based history matching uses an ensemble of realizations to construct Monte Carlo approximations of the mean and covariance of the model variables, which can acquire the gradient information from the correlation provided by the ensemble. A power-law model is first used to represent the three-phase relative permeabilities, the coefficients of which can be automatically adjusted until production history is matched. A damping factor is introduced as an adjustment to the step length because a reduced step length is commonly required if an inverse problem is sufficiently nonlinear. A recursive approach for determining the damping factor has been developed to reduce the number of iterations and the computational load of the EnRML algorithm. The restart of reservoir simulations for reducing the cost of reservoir simulations is of significant importance for the EnRML algorithm where iterations are inevitable. By comparing a direct-restart method and an indirect-restart method for numerical simulations, we optimize the restart method used for a specific problem. Subsequently, we validate the proposed methodology by use of a synthetic water-alternating-gas (WAG) displacement experiment and then extend it to match laboratory experiments. The proposed technique has proved to efficiently determine the three-phase relative permeabilities for the WAG processes with consideration of the hysteresis effect, whereas history-matching results are gradually improved as more production data are taken into account. The synthetic scenarios demonstrate that the recursive approach saves 33.7% of the computational expense compared with the trial-and-error method when the maximum iteration is 14. Also, the consistency between the production data and model variables has been well-maintained during the updating processes by use of the direct-restart method, whereas the indirect-restart method fails to minimize the uncertainties associated with the model variables representing three-phase relative permeabilities.

A Maximum Likelihood Algorithm for Estimating Damped Sinusoids

1990 ◽  
Vol 23 (1) ◽  
pp. 601-605
Author(s):  
D.R. Farrier ◽  
A.R. Prior-Wandesforde
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Algorithm

Frequency and Phasor Estimations in Three-Phase Systems: Maximum Likelihood Algorithms and Theoretical Performance

2019 ◽  
Vol 10 (3) ◽  
pp. 3248-3258 ◽  
Author(s):  
Vincent Choqueuse ◽  
Adel Belouchrani ◽  
Francois Auger ◽  
Mohamed Benbouzid
Keyword(s):  
Maximum Likelihood ◽  
Three Phase ◽  
Phase Systems ◽  
Theoretical Performance

scholarly journals DIRECTION FINDING FOR BISTATIC MIMO RADAR USING EM MAXIMUM LIKELIHOOD ALGORITHM

2013 ◽  
Vol 141 ◽  
pp. 99-116 ◽  
Author(s):  
Hao Wen Chen ◽  
Degui Yang ◽  
Hong-Qiang Wang ◽  
Xiang Li ◽  
Zhaowen Zhuang
Keyword(s):  
Maximum Likelihood ◽  
Direction Finding ◽  
Mimo Radar ◽  
Maximum Likelihood Algorithm ◽  
Bistatic Mimo Radar
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