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A stochastic well-test analysis on transient pressure data using iterative ensemble Kalman filter
, Article Neural Computing and Applications ; 2017 , Pages 1-17 ; 09410643 (ISSN) ; Adibifard, M ; Sharif University of Technology
Abstract
Accurate estimation of the reservoir parameters is crucial to predict the future reservoir behavior. Well testing is a dynamic method used to estimate the petro-physical reservoir parameters through imposing a rate disturbance at the wellhead and recording the pressure data in the wellbore. However, an accurate estimation of the reservoir parameters from well-test data is vulnerable to the noise at the recorded data, the non-uniqueness of the obtained match, and the accuracy of the optimization algorithm. Different stochastic optimization methods have been applied to this address problem in the literature. In this study, we apply the recently developed iterative ensemble Kalman filter in the...
A stochastic well-test analysis on transient pressure data using iterative ensemble Kalman filter
, Article Neural Computing and Applications ; Volume 31, Issue 8 , 2019 , Pages 3227-3243 ; 09410643 (ISSN) ; Adibifard, M ; Sharif University of Technology
Springer London
2019
Abstract
Accurate estimation of the reservoir parameters is crucial to predict the future reservoir behavior. Well testing is a dynamic method used to estimate the petro-physical reservoir parameters through imposing a rate disturbance at the wellhead and recording the pressure data in the wellbore. However, an accurate estimation of the reservoir parameters from well-test data is vulnerable to the noise at the recorded data, the non-uniqueness of the obtained match, and the accuracy of the optimization algorithm. Different stochastic optimization methods have been applied to this address problem in the literature. In this study, we apply the recently developed iterative ensemble Kalman filter in the...