Friday, 16:15 - 16:40 h, Room: H 3003A


Andrew Conn
Simulation-based optimization: Integrating seismic and production data in history matching

Coauthors: Sippe Douma, Lior Horesh, Eduardo Jimenez, Gijs van Essen


We present two recent complementary approaches to mitigate the ill-posedness of this problem: Joint inversion - the development of a virtual sensing formulation for efficient and consistent assimilation of 4D time-lapse seismic data; Flow relevant geostatistical sampling - despite conscientious efforts to minimize the undeterminedness of the solution space, through joint inversion or through regularization, the distribution of the unknown parameters conditional on the historical data, often remains illusive. This is typically accounted for through extensive sampling. We propose a reduced space hierarchical clustering of flow-relevant indicators for determining representatives of these samples. This allows us to identifying model characteristics that affect the dynamics.
The effectiveness of both methods are demonstrated both with synthetic and real field data.
Time permitting we will discuss the ramifications for the optimization and the numerical linear algebra.


Talk 3 of the invited session Fri.3.H 3003A
"Novel applications of derivative-free and simulation-based optimization" [...]
Cluster 6
"Derivative-free & simulation-based optimization" [...]


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