The impact of hard data uncertainty in reservoirs modelling

2017-01-01
Fadlelmula, M.m.
Akın, Serhat
Duzgun, H.s.
Predicting and estimating real world conditions presents one of the major ways in which uncertainty is introduced to reservoir modelling, with errors often occurring due to the scarcity of subsurface geological information. The inherently random nature of physical phenomena is another source of uncertainty. While uncertainty due to physical phenomena cannot be reduced - because it is a state of nature - developing more accurate models and collecting additional data can help decrease estimation uncertainty. These uncertainties affect the output of reservoir models, but to what extent? This study provides a systematic way to investigate the propagation of hard data uncertainty through the estimate of original oil in place (OOIP) and recoverable oil in place (ROIP) for a given reservoir model. The reservoir is modelled using a multiple-point statistics (MPS) methodology. The results show that the projected OOIP and ROIP values are very sensitive to hard data uncertainty. © 2017 European Association of Geoscientists and Engineers EAGE. All rights reserved.
2nd EAGE Workshop on Well Injectivity and Productivity in CarbonatesVolume 2017-December, 2017

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Citation Formats
M. m. Fadlelmula, S. Akın, and H. s. Duzgun, “The impact of hard data uncertainty in reservoirs modelling,” presented at the 2nd EAGE Workshop on Well Injectivity and Productivity in CarbonatesVolume 2017-December, 2017, Doha; Qatar, 2017, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85048869041&origin=inward.