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Multilevel Monte Carlo methods for computing failure probability of porous media flow systems

F. Fagerlund ; F. Hellman ; Axel Målqvist (Institutionen för matematiska vetenskaper, Tillämpad matematik och statistik) ; A. Niemi
Advances in Water Resources (0309-1708). Vol. 94 (2016), p. 498-509.
[Artikel, refereegranskad vetenskaplig]

We study improvements of the standard and multilevel Monte Carlo method for point evaluation of the cumulative distribution function (failure probability) applied to porous media two-phase flow simulations with uncertain permeability. To illustrate the methods, we study an injection scenario where we consider sweep efficiency of the injected phase as quantity of interest and seek the probability that this quantity of interest is smaller than a critical value. In the sampling procedure, we use computable error bounds on the sweep efficiency functional to identify small subsets of realizations to solve highest accuracy by means of what we call selective refinement. We quantify the performance gains possible by using selective refinement in combination with both the standard and multilevel Monte Carlo method. We also identify issues in the process of practical implementation of the methods. We conclude that significant savings in computational cost are possible for failure probability estimation in a realistic setting using the selective refinement technique, both in combination with standard and multilevel Monte Carlo.

Nyckelord: CDF estimation, Failure probability, Porous media flow simulation, Multilevel Monte Carlo, Selective refinement



Denna post skapades 2016-09-30. Senast ändrad 2017-01-26.
CPL Pubid: 242735

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, Tillämpad matematik och statistikInstitutionen för matematiska vetenskaper, Tillämpad matematik och statistik (GU)

Ämnesområden

Beräkningsmatematik

Chalmers infrastruktur