Characterization of flow response uncertainty in naturally fractured reservoirs (NFR) through static properties: Connectivity and heterogeneity

L. Belyakova*, Vasily Demyanov, Daniel Arnold

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

Abstract

The aim of this project is to predict uncertainty in the reservoir dynamics based on its static characteristics - connectivity and heterogeneity. Applied workflow includes creation of static models (discreet fracture networks (DFN) models generation based on outcrop data, models upscaling) and dynamic models (dynamic simulation of static models). Both static and dynamic models were clustered (k medoid algorithm) in order to find similarity between groups of models. Data uncertainty is covered by creating an ensemble of DFN models with range of properties. Research results show that there is similarity in models distribution, both static and dynamic one. The proposed approach suggested a CPU time saving and cost effective way to capture the range of dynamic response based on a few dynamic model simulation. Whereas the selected dynamic models are based on the variation of the static properties. The obtained results could be used further in well placement optimization and reservoir recovery prediction.

Original languageEnglish
DOIs
Publication statusPublished - 12 Jun 2017
Event79th EAGE Conference and Exhibition 2017 - Paris, France
Duration: 12 Jun 201715 Jun 2017
http://events.eage.org/en/2017/79th-eage-conference-and-exhibition-2017

Conference

Conference79th EAGE Conference and Exhibition 2017
Country/TerritoryFrance
CityParis
Period12/06/1715/06/17
Internet address

ASJC Scopus subject areas

  • Geochemistry and Petrology
  • Geophysics

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