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Convergence of the undrained split iterative scheme for coupling flow with geomechanics in heterogeneous poroelastic media.

Authors :
Almani, T.
Manea, A.
Kumar, K.
Dogru, A. H.
Source :
Computational Geosciences. Apr2020, Vol. 24 Issue 2, p551-569. 19p.
Publication Year :
2020

Abstract

Recently, an accurate coupling between subsurface flow and reservoir geomechanics has received more attention in both academia and industry. This stems from the fact that incorporating a geomechanics model into upstream flow simulation is critical for accurately predicting wellbore instabilities and hydraulic fracturing processes. One of the recently introduced iterative coupling algorithms to couple flow with geomechanics is the undrained split iterative coupling algorithm as reported by Kumar et al. (2016) and Mikelic and Wheeler (Comput. Geosci. 17: 455–461 2013). The convergence of this scheme is established in Mikelic and Wheeler (Comput. Geosci. 17:455–461 2013) for the single rate iterative coupling algorithm and in Kumar et al. (2016) for the multirate iterative coupling algorithm, in which the flow takes multiple finer time steps within one coarse mechanics time step. All previously established results study the convergence of the scheme in homogeneous poroelastic media. In this work, following the approach in Almani et al. (2017), we extend these results to the case of heterogeneous poroelastic media, in which each grid cell is associated with its own set of flow and mechanics parameters for both the single rate and multirate schemes. Second, following the approach in Almani et al. (Comput. Geosci. 21:1157–1172 2017), we establish a priori error estimates for the single rate case of the scheme in homogeneous poroelastic media. To the best of our knowledge, this is the first rigorous and complete mathematical analysis of the undrained split iterative coupling scheme in heterogeneous poroelastic media. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14200597
Volume :
24
Issue :
2
Database :
Academic Search Index
Journal :
Computational Geosciences
Publication Type :
Academic Journal
Accession number :
142793777
Full Text :
https://doi.org/10.1007/s10596-019-09860-5