A Decision Support System for Multi-target Geosteering
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Geosteering is a sequential decision process under uncertainty. The goal of geosteering is to maximize the expected value of the well, which should be defined by an objective value-function for each operation. In this paper we present a real-time decision support system (DSS) for geosteering that aims to approximate the uncertainty with an ensemble of geo-model realizations. As the drilling operation progresses, the ensemble Kalman filter is used to sequentially update the realizations using the data from real-time logging while drilling. At every decision point a discretized dynamic programming algorithm computes all potential well trajectories until the end of the operation and the corresponding value of the well for each realization. Then, the DSS considers all immediate alternatives (continue/steer/stop) and chooses the one that gives the best predicted value across the realizations. This approach works for a variety of objectives and constraints and suggests reproducible decision under uncertainty. Moreover, it has real-time performance. The system is tested on synthetic cases in layer-cake geological environment where the target layer should be selected dynamically based on the prior(pre-drill) model and electromagnetic observations. The numerical closed-loop simulation experiments demonstrate the ability of the DSS to perform successful geosteering and landing of a well for different configurations of targets. Furthermore, the DSS allows to adjust and re-weight the objectives, making the DSS useful before fully-automated geosteering becomes reality.
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