At the well-planning stage target selection usually accounts for drillability. However, during geosteering operations the drilling constraints are not updated and some fixed limits in terms of maximal inclination, dogleg severity, etc., are used instead. We demonstrate a methodology that uses fast physical models of the drilling hydraulics to calculate constraints and costs for geosteering dynamically during an operation.
In field development, many companies have adopted workflows that use ensemble-based methods for decision support. A real-time variation of such a decision support system (DSS) has been recently proposed for geosteering. The DSS is capable of optimization full well trajectories across all realizations of the earth model and can consider multiple objectives and constraints simultaneously. We present a method that makes steady-state hydraulic computations for all possible trajectories ahead-of-bit simultaneously at a low added cost. The output of the computation can provide more precise constraints (geo-pressure margins and cuttings transport) and cost estimates for the DSS.
In this paper we focus on verification and testing of the proposed multi-trajectory hydraulic model (MTHM). Discretization of the model acts as a trade-off between the preciseness of the computation and the computational speed. On our benchmark cases, a simulation that computes the hydraulic parameters for all trajectories with acceptable errors is fast enough for real-time geo-steering applications. Furthermore, we present a case based on data from the Norwegian Continental Shelf for which we demonstrate how hydraulic computations would influence the decisions of steering and stopping. Applying the DSS with the MTHM allows to precisely update the allowed steering interval, thus achieving safe operation while maximizing the expected well profit.
We emphasize that integration of the drilling processes modelling as part of the decision support for the geosteering operation enables better decisions. This is facilitated by the digitalization of the oil industry, but still requires development of new approximate models of the drilling processes. This paper demonstrates the MTHM as an initial step towards integration of drilling and geosteering modelling.