Well placement and geosteering technology have been implemented for drilling operations worldwide. These implementations have generally been based on use the of real time (or near real time) downhole measurements that are relevant for horizontal well plac ement decisions in oil & gas reservoirs. Optimal placements will improve the wells productivity as a result of being able to drain from larger hydrocarbon volumes. Recent technology development provides access to ever increasing volumes of downhole measur ements. However, these measurements do not provide direct indications of what lies ahead of the drillbit. Nor do they allow us to directly quantify the uncertainties that are most important for the well placement decisions. Thus research is required on ho w to "translate" the real-time measurements into real time (operational) decision supporting information.A PhD project with basic funding from SBBU "A Bayesian Framework for Real Time Optimization of Well Placement" is focused on this. As?part of this p roject, an extended research visit at the University of Texas (UT) at Austin?in the Department of Operations Research and Industrial Engineering is planned 2012/2013. Professor Eric Bickel at UT will host the PhD student.
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