In this work we present a systematic geosteering workflow that automatically integrates a priori information and the real-time measurements for updating of geomodel with uncertainties, and uses the latest model predictions in a Decision Support System (DSS). The DSS supports geosteering decisions by evaluating production potential versus drilling and completion risks.
In our workflow, the uncertainty in the geological interpretation around the well is represented via multiple realizations of the geology. The realizations are updated using EnKF (Ensemble Kalman Filter) in real-time when new LWD measurements become available, providing a modified prediction of the geology ahead of the bit. For every geosteering decision, the most recent representation of the geological uncertainty is used as input for the DSS. It suggests steering correction or stopping, considering complete well trajectories ahead-of-the-bit against the always updated representation of key uncertainties. The optimized well trajectories and the uncertainties are presented to the users of the DSS via a GUI. This interface enables interactive adjustment of decision criteria and constraints, which are applied in a matter of seconds using advanced dynamic programming algorithms yielding consistently updated decision suggestions.
To illustrate the benefits of the DSS, we consider synthetic cases for which we demonstrate the model updating and the decision recommendations. The DSS is particularly advantageous for unbiased high-quality decision making when navigating in complex reservoirs with several potential targets and significant interpretation uncertainty. The initial results demonstrate statistically optimal landing and navigating of the well in such a complex reservoir. Furthermore, the capability to adjust and re-weight the objectives provides the geosteering team with the ability to change the selected trade-offs between the objectives as they drill. Under challenging conditions, model-based results as input to a decision process that is traditionally much based on human intuition and judgement is expected to yield superior decisions.
The novel DSS offers a new paradigm for geosteering where the geosteering experts control the input to the DSS by choosing decision criteria. At the same time, the DSS identifies the optimal decisions through multi-objective optimization under uncertainty. It bridges the gap between developments in formation evaluation and reservoir mapping on one side, and automation of the drilling process on the other. Hence, the approach creates value based on the existing instrumentation and technology.