Contribution of the Process-Based Modeling to Pluri-gaussian Simulation in the Case of Meandering Channelized Reservoirs
Simulating deposits associated to meandering channels with statistical methods is still a challenge due to the complex forms of the sedimentary bodies (eg point bar deposits, crevasse splays, oxbow lakes). Several conditional methods have been proposed to reproduce these geometries at the reservoir scale such as object-based models, Boolean or multi point statistics. Nevertheless, these methods need first to define a synthetic shape of individual sedimentary bodies and then to arrange these in the desired architecture.
Another way to simulate more accurately the sedimentary bodies and their internal structures is proposed through the use of process-based-stochastic models, such as Flumy that is conditioned to well data. However when the number of constraining data increases the conditioning is less efficient.
We propose to combine the benefits of the realistic simulation of sedimentary bodies of Flumy in simulations performed with PGS that is adapted to conditioning of large data set.
Analysis of well data provides us with the necessary parameters (channel max depth, sand body extension, net to gross) to perform several process-based simulations which characteristics correspond to the field to be modeled. Statistics are then performed on these multiple realizations, to obtain more accurate relationship to be used in the PGS simulation (lithofacies, spatial distribution of the facies proportion) calibrating the PGS from the results of a genetic simulation.
By this way, the final conditional simulations produced with PGS are conditioned to as many well data as needed and take also into account the spatial relationship of the different types of sedimentary bodies.
The method is illustrated through a field data set. This dataset has been collected over the Loranca Basin in Spain. Results are presented for two units with different N/G and sand body extension, illustrating the potential of the method.
AAPG Search and Discovery Article #90142 © 2012 AAPG Annual Convention and Exhibition, April 22-25, 2012, Long Beach, California