TY - JOUR
T1 - Impact of modelling decisions and rock typing schemes on oil in place estimates in a giant carbonate reservoir in the Middle East
AU - Al Breiki, Mohamed
AU - Geiger, Sebastian
AU - Corbett, Patrick
N1 - Funding Information:
Acknowledgements The authors would like to thank Abu Dhabi National Oil Company (ADNOC) for providing access to data and the scholarship for Mohamed. Sebastian acknowledges support from Energi Simulation for his Chair in Carbonate Reservoir Simulation. We are also grateful to Schlumberger for access to Petrel and to Vicki and Dan O’Meara for access to Geo2Flow.
Publisher Copyright:
© 2021 The Author(s).
PY - 2022/2
Y1 - 2022/2
N2 - We demonstrate how modelling decisions for a giant carbonate reservoir with a thick transition zone in the Middle East, most notably the approach to reservoir rock typing and modelling the initial fluid saturations, impact the hydrocarbon distributions and oil-in-place estimates in the reservoir. Rather than anchoring our model around a single base case with an upside and downside, we apply a comprehensive 3D multiple deterministic scenario workflow to compare-and-contrast how modelling decisions and geological uncertainties influence the volumetric estimates. We carry out a detailed analysis which shows that the variations in STOIIP estimates can be as high as 28% depending on the preferred modelling decision, which could potentially mask the impact of other geological uncertainties. These models were validated through repeated and randomised blind tests. We hence present a quantitative approach that helps us to assess if the static models are consistent in terms of the integration of geological and petrophysical data. Ultimately, the decision which of the different modelling options should be applied does not only influence STOIIP estimates, but also subsequent history matching & forecasts.
AB - We demonstrate how modelling decisions for a giant carbonate reservoir with a thick transition zone in the Middle East, most notably the approach to reservoir rock typing and modelling the initial fluid saturations, impact the hydrocarbon distributions and oil-in-place estimates in the reservoir. Rather than anchoring our model around a single base case with an upside and downside, we apply a comprehensive 3D multiple deterministic scenario workflow to compare-and-contrast how modelling decisions and geological uncertainties influence the volumetric estimates. We carry out a detailed analysis which shows that the variations in STOIIP estimates can be as high as 28% depending on the preferred modelling decision, which could potentially mask the impact of other geological uncertainties. These models were validated through repeated and randomised blind tests. We hence present a quantitative approach that helps us to assess if the static models are consistent in terms of the integration of geological and petrophysical data. Ultimately, the decision which of the different modelling options should be applied does not only influence STOIIP estimates, but also subsequent history matching & forecasts.
UR - http://www.scopus.com/inward/record.url?scp=85125653227&partnerID=8YFLogxK
U2 - 10.1144/petgeo2021-028
DO - 10.1144/petgeo2021-028
M3 - Article
AN - SCOPUS:85125653227
SN - 1354-0793
VL - 28
JO - Petroleum Geoscience
JF - Petroleum Geoscience
IS - 1
M1 - petgeo2021-028
ER -