Dual-gradient drilling (DGD) solutions have been developed to work with greater margins while drilling in deep water environments by mirroring hydrostatic pressure conditions that are closer to the natural ones. Recent attempts have been undertaken to use DGD to actively control the downhole pressure and therefore turning them into managed pressure drilling (MPD) solutions. The pressure control strategy requires the knowledge of how pressure will change along the borehole as a function of the drilling parameters and therefore needs to use numerical hydraulic models. However, the accuracy of the prediction of pressure calculations depends on a certain number of parameters that are not necessarily well known. Some of those significant factors are well defined but are not necessarily measured as extensively as it would have been required. Others are subject to the actual downhole conditions and may change with time. Therefore, they are, in many instances, difficult to assess with enough certainty. As a result, it is necessary to constantly calibrate the downhole pressure calculations in order to match observed values at controlled positions. This calibration process is usually done manually by a human operator, leaving the possibility for possible misinterpretations of the actual calibration data and consequently a potentially erroneous control of the downhole pressure by the MPD control algorithm.

In this paper, we review the sources of uncertainties that can affect the accuracy of the downhole pressure calculations. Thereafter, we explain how automatic calibration of the numerical models can be made in order to match reference measurements. The proposed method also allows for an evaluation of the accuracy by which the downhole pressure calculations can be made. In conjunction with the required precision to control the downhole pressure during a drilling operation, it is possible to assess whether additional measurements or working procedures should be implemented prior to an MPD dual-gradient operation with tight constraints.

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