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Abstract This case study involves a well drilled in the Erbil area of the Kurdish Region of Iraq, a region characterized by challenging geological conditions for drilling. To achieve the key drilling objectives, the drilling mud was made less dense by the addition of nitrogen into the mud column. In order to get a full understanding of the downhole conditions using this mud, the complete drilling process was modelled in real-time. The model was driven using a real-time WITSML data feed. This transient modeling software calculates downhole pressures, temperatures, torque and drag and cuttings density at all depths in the well bore in real- time, including the depths where there are no physical measurements. The transient model is continuously updated in real-time to reflect the drilling processes undertaken on the rig (e.g. pipe movement, mud pump activity, thermodynamics). Surface system variables including virtual mud pit levels are also calculated in real-time. The modelled data is then continuously compared to the sparse data points that are being recorded in real-time, allowing both a continuous calibration of the model with the "as drilled" well operation. The calculation of important drilling parameters such as sliding friction, rotational friction, and hydraulic friction is performed in real-time. The paper will present the key observations upon the matches between the modelled data and the "as drilled" data and summarise the key lessons learned during the well operations and the real-time modelling processes.
Summary During a drilling operation, a real-time analysis of surface and downhole measurements can give indications of poor hole cleaning. However, it is not always intuitive to understand how and where the cuttings are settling in the borehole because the transportation of cuttings and the formation of cuttings beds are largely influenced by the series of actions performed during the operation. With a transient cuttings-transport model, it is possible to get a continuously updated prognosis of the distribution of cuttings in suspension and in beds along the annulus. This information can be of prime importance for making decisions to deal with and prevent poor hole-cleaning conditions. A transient cuttings-transport model has been obtained by integrating closure laws for cuttings transport into a transient drilling model that accounts for both fluid transport and drillstring mechanics. This paper presents how this model was used to monitor two different drilling operations in the North Sea: one using conventional drilling and one using managed-pressure drilling (MPD). Some unknown parameters within the model (e.g., the size of the cuttings particles) were calibrated to obtain a better match with the top-side measurements (cuttings-flow rate, active pit reduction as a result of cuttings removal). With the calibrated model, the prediction of cuttings-bed locations was confirmed by actual drilling incidents such as packoffs and overpulls while tripping out of hole. On the basis of the calibrated transient cuttings-transport model, it is thereby possible to evaluate the adjustments of the drilling parameters that are necessary to stop and possibly remove the cuttings beds, thus giving the drilling team the opportunity to take remedial and preventive actions on the basis of quantitative evaluations, rather than solely on the intuition and experience of the decision makers.
Abstract During a drilling operation, real-time analysis of surface and downhole measurements can give indications of poor hole cleaning. However, it is not always intuitive to understand how and where the cuttings are settling in the borehole, because the transportation of cuttings and the formation of cuttings beds are largely influenced by the series of actions performed during the operation. Using a transient cuttings transport model, it is possible to get a continuously updated prognosis of the distribution of cuttings in suspension and in beds along the annulus. This information can be of prime importance for taking decisions to deal with and prevent poor hole cleaning conditions. A transient cuttings transport model has been obtained by integrating closure laws for cuttings transport into a transient drilling model that accounts for both fluid transport and drill-string mechanics. This paper presents how this model was used to monitor two different drilling operations in the North Sea: one using conventional drilling and one using MPD (Managed Pressure Drilling). Some unknown parameters within the model (e.g. the size of the cuttings particles) were calibrated in order to obtain a better match with the top side measurements (cuttings flowrate, active pit reduction due to cuttings removal). Using the calibrated model, the prediction of cuttings bed locations were confirmed by actual drilling incidents like pack-offs and overpulls while tripping out of hole. Based on the calibrated transient cuttings transport model, it is thereby possible to evaluate what adjustments of the drilling parameters are necessary to stop and possibly remove the cuttings beds, therefore giving the drilling team the opportunity to take remedial and preventive actions based on quantitative evaluations, rather than solely upon the intuition and experience of the decision makers.
Summary Current topside and downhole instrumentation at the wellsite has been developed to manually conduct drilling operations. The emergence of automatic drilling-analysis software shows the limitations of today's measurement capabilities. It is therefore time to analyze the requirements for on-site instrumentation to implement new, efficient drilling-automation technologies. On one hand, drilling is facing more and more difficult conditions with narrow geopressure windows, deepwater, or high-pressure/high-temperature (HP/HT) conditions. On the other hand, unconventional hydrocarbon reserves may require a considerable amount of wells to be profitable. Drilling automation, by means of smart safeguards, automatic safety triggers, managed-pressure drilling (MPD), and ultimately complete or semiautonomous drilling rigs, can provide the solution to safely construct wells in these challenging settings. The common denominator for the vast majority of drilling-automation solutions is the use of physical models of the drilling process in the form of heat-transfer, mechanical, and hydraulic models. By analyzing the requirements of those models for necessary boundary conditions, it is possible to derive which measurements should be made both at surface and downhole to obtain stable and accurate calculations. This analysis also provides a way to estimate the necessary accuracy of the boundary conditions to ensure reaching the target control tolerance. By use of the boundary-condition analysis, it is possible to derive precisely which measurements should be performed and where they should be performed. As a result, a typical organization of sensors that is compatible with the implementation of drilling-automation solutions is derived.
Abstract 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.