Multiphase coupling of a reservoir simulator and computational fluid dynamics for accurate near-well flow

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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Near-well flow analysis is an important tool for gaining detailed insight of the flow behaviour and for improving well design and production optimization of real reservoirs. One challenge of accurate numerical modelling of the flow field in the vicinity of the well is related to the scale disparity factor in space and time. The numerical scale gap between the reservoir and the wellbore justifies the representation of a well as a point or line sink/source term in traditional reservoir models. However, standard numerical techniques for reservoir simulation are incapable of resolving the near-singular character of the pressure field in the vicinity of the well. Under the assumption that all length scales have impact on flow patterns, we present a proof-of-concept study aimed at improving the quality of the numerical simulation by considering the geometry and fluid flow near the wellbore in a fully connected system, thus accounting for the fine scale phenomena by means of a hybrid Navier-Stokes/Darcy wellbore model coupled with a full scale reservoir model. A weak coupling method based on fixed-point iterations, that preserves the mass flux transport across the coupled interface, while adjusting productivity indices, is demonstrated via numerical experiments. Several different numerical experiments are performed to demonstrate the versatility and the improved well performance insight that the coupled method offers, including horizontal well inflow profile, influence of formation damage and optimal well configuration.
Original languageEnglish
JournalJournal of Petroleum Science and Engineering
Volume178
Pages (from-to)517-527
ISSN0920-4105
DOIs
Publication statusPublished - 2019
CitationsWeb of Science® Times Cited: No match on DOI

    Research areas

  • Multiphase flow, Porous media, CFD, Near-wellbore, Reservoir simulation

ID: 172637662