An enhanced ensemble Kalman filter scheme incorporating model error in sequential coupling between flow and geomechanics. (12th November 2018)

• Record Type: Journal Article
• Authors: Caballero, Edison; Rochinha, Fernando A.; Borges, Marcio; Murad, Marcio A.
• Is Part Of: International journal for numerical and analytical methods in geomechanics. Volume 43:Number 2(2019)
• Page Start: 482
• Page End: 500
• Publication Date: 2018-11-12
• Subjects: data assimilation -- ensemble Kalman filter -- fixed stress split -- model error approximation -- reservoir geomechanics -- sequential methods; Soil mechanics -- Mathematics -- Periodicals; Rock mechanics -- Mathematics -- Periodicals; 624.1510151
• DOI: 10.1002/nag.2872
• Languages: English
• ISSNs: 0363-9061

Abstract

Summary: In this work, we construct a new methodology for enhancing the predictive accuracy of sequential methods for coupling flow and geomechanics while preserving low computational cost. The new computational approach is developed within the framework of the fixed‐stress split algorithm procedure in conjunction with data assimilation based on the ensemble Kalman filter (EnKF). In this context, we identify the high‐fidelity model with the two‐way formulation where additional source term appears in the flow equation containing the time derivative of total mean stress. The iterative scheme is then interlaced with data assimilation steps, which also incorporate the modeling error inherent to the EnKF framework. Such a procedure gives rise to an "enhanced one‐way formulation, " exhibiting substantial improvement in accuracy compared with the classical one‐way method. The governing equations are discretized by mixed finite elements, and numerical simulation of a 2D slab problem between injection and production wells illustrate the tremendous achievement of the method proposed herein.