2017_EJRNL_PP_LIANG_XUE_1.pdf
Terbatas Suharsiyah
» ITB
Terbatas Suharsiyah
» ITB
Reservoir simulations always involve a large number of parameters to characterize the
properties of formation and fluid, many of which are subject to uncertainties owing to spatial
heterogeneity and insufficient measurements. To provide solutions to uncertainty-related issues in
reservoir simulations, a general package called GenPack has been developed. GenPack includes
three main functions required for full stochastic analysis in petroleum engineering, generation of
random parameter fields, predictive uncertainty quantifications and automatic history matching.
GenPack, which was developed in a modularized manner, is a non-intrusive package which can
be integrated with any existing commercial simulator in petroleum engineering to facilitate its
application. Computational efficiency can be improved both theoretically by introducing a surrogate
model-based probabilistic collocation method, and technically by using parallel computing. A series
of synthetic cases are designed to demonstrate the capability of GenPack. The test results show that the
random parameter field can be flexibly generated in a customized manner for petroleum engineering
applications. The predictive uncertainty can be reasonably quantified and the computational efficiency
is significantly improved. The ensemble Kalman filter (EnKF)-based automatic history matching
method can improve predictive accuracy and reduce the corresponding predictive uncertainty by
accounting for observations.