Oil production uncertainty assessment by predicting reservoir production curves and confidence intervals from arbitrary proxy responses

Autor: Pierre Biver, Philippe Renard, Gaétan Bardy, Guillaume Caumon
Přispěvatelé: GeoRessources, Institut national des sciences de l'Univers (INSU - CNRS)-Centre de recherches sur la géologie des matières premières minérales et énergétiques (CREGU)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), TOTAL-Scientific and Technical Center Jean Féger (CSTJF), TOTAL FINA ELF, Ecole Nationale Supérieure de Géologie (ENSG), Université de Lorraine (UL), Université de Neuchâtel (UNINE), Total (CIFRE)
Rok vydání: 2019
Předmět:
Zdroj: Journal of Petroleum Science and Engineering
Journal of Petroleum Science and Engineering, Elsevier, 2019, 176, pp.116-125. ⟨10.1016/j.petrol.2019.01.035⟩
ISSN: 0920-4105
1873-4715
DOI: 10.1016/j.petrol.2019.01.035
Popis: International audience; Underground fluid flow in hydrocarbon reservoirs (or aquifers) is difficult to predict accurately due to geological and petrophysical uncertainties. To quantify that uncertainty, several spatial statistical methods are often used to generate an ensemble of subsurface models representing and sampling these uncertainties. However, to predict the uncertainties in terms of flow responses, one needs to run a forward flow simulator (often multiphase flow in transient state) on every model of this ensemble and this generally entails intractable computational costs. Approximate solutions (flow proxies) can help addressing this challenge but introduce physical simplifications whose impact on the uncertainty quantification is difficult to characterize. This paper proposes a workflow to assess the dynamic reservoir behavior uncertainties from an input ensemble of realizations sampling geological and geophysical uncertainties. Analytical reservoir production curves are estimated from proxy distances computed between all ensemble members and from a few accurate flow responses computed on a subset of the ensemble. A randomization process accounting for proxy quality and for model selection is used to assess confidence intervals about reservoir production quantile curves. The process can use both static and dynamic proxies and also permits to compare their efficiency. A case study on a real turbiditic reservoir shows the applicability of the method, and highlights the value of even a simple proxy to increase the confidence about future reservoir production
Databáze: OpenAIRE
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