Field development optimization of waterflooding process using data assimilation methods

Abstract

The application of data assimilation methods for field development optimization has been the subject of intense investigation during the past 10 years. Lately has seen remarkable progress in the ability of data assimilation approach in reservoir characterization and based on this, improvements of field development optimization. In this review paper, we have summarized key achievements in field development optimization of waterflooding process with data assimilation approach and review many of the achievements of the past time, including developments in the field of search for modifications of Ensemble Kalman Filter (EnKF) and Ensemble Smoothers (ES). An attempt has been made to discuss different data assimilation methods and to identify possible limitations of each. Current challenges and future research opportunities for improved data assimilation methods for field development optimization of waterflooding process are also discussed.