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Efficient Optimization of Exploration Drilling Campaigns with Convergent Information Bounds
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, Petroleum Geostatistics 2015, Sep 2015, cp-456-00040
- ISBN: 978-94-6282-158-3
Abstract
We discuss a Bayesian Network (BN) with 42 nodes, of which 25 are leaf nodes that represent actual petroleum prospects in the North Sea where we could choose to collect data. We look at the case where the data gathering is carried out as a seasonal campaign with m exploration wells, and the question is: Where should they be drilled? The complexity of the problem is such that for large m or for larger networks, the optimal observation set problem is not computationally feasible through exact calculations. We introduce a method for computing upper and lower bounds inspired by the Junction Tree Algorithm to do a more efficient search for the optimal drilling campaign. Our algorithm improves the bounds until they are sufficiently tight, and our construction of the upper and lower bounds results in an extremely efficient search for the optimal observation set for exploration wells in the North Sea petroleum prospect case.