Tuning of Computer Model Parameters in Managed Pressure Drilling Applications Using an Unscented Kalman Filter Technique
- Jan Einar Gravdal (Rogaland Research Centre) | Rolf Johan Lorentzen (RF-Rogaland Research) | Kjell Kaare Fjelde (RF-Rogaland Research) | Erlend Heggelund Vefring (RF-Rogaland Research)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 9-12 October, Dallas, Texas
- Publication Date
- Document Type
- Conference Paper
- 2005. Society of Petroleum Engineers
- 1.6.1 Drilling Operation Management, 1.7.2 Managed Pressure Drilling, 1.12.1 Measurement While Drilling, 1.11 Drilling Fluids and Materials, 1.7.5 Well Control, 1.6 Drilling Operations, 1.12.6 Drilling Data Management and Standards, 4.3.4 Scale, 1.7.7 Cuttings Transport, 1.10.1 Drill string components and drilling tools (tubulars, jars, subs, stabilisers, reamers, etc), 4.1.5 Processing Equipment, 4.1.2 Separation and Treating, 5.3.2 Multiphase Flow, 1.7.1 Underbalanced Drilling, 4.2 Pipelines, Flowlines and Risers
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In order to manage the annular pressure profile during Managed Pressure Drilling (MPD) operations, simulations performed with advanced computer models are needed. To obtain a high degree of accuracy in these simulations it is crucial that all parameters describing the system are as correct as possible. A new methodology for real time updating of key parameters in a well flow model by taking into account real time measurements, including measuring uncertainty, is presented. Key model parameters are tuned using a recently developed estimation technique based on the traditional Kalman Filter.
The presented methodology leads to a more accurate prediction of well flow scenarios. Although the present study is motivated by applications in MPD, the idea of tuning model parameters should be of great importance in a wide area of applications.
The performance of the filter is studied, both using synthetic data and real measurements from a North Sea High-Pressure-High-Temperature (HPHT) drilling operation. Benefits by this approach are seen by more accurate downhole pressure predictions which are of major importance for safety and economic reasons during MPD operations.
Drilling technology has advanced significantly over the last years, allowing drilling of complex multi-lateral and extended reach wells. A safe and successful conventional, low-head or underbalanced drilling operation requires control of downhole pressure. Throughout the last decades, the development of appropriate well flow models has improved the well design process and given the drilling engineers better tools for making the right decisions. However, flow models are only approximations of reality and improvements are still needed. In this paper, focus is on how real time data can be used for improving the accuracy of the flow model predictions.
For a well flow model to calculate a reliable downhole pressure profile, accurate friction pressure loss calculations are essential. To obtain this, model input need to be as correct as possible. It is important that e.g. flow regime and eccentricity in the model is representative for the actual conditions and that drilling fluid parameters are as correct as possible at all time. Density, rheology and thermal conditions change as a function of pressure and temperature. However, even state of the art well flow models developed for calculation of downhole pressure do not take into account the time effects on rheology for non-Newtonian liquids. It is a well known phenomenon that during the first hours of circulation a relatively large decrease in bottom hole pressure can be observed. Figure 2 shows an example of this in a North Sea HPHT well during a circulation sweep. A gradually decrease in viscosity during circulation followed by a gradually recovery when circulation is ended is caused by thixotropy . The rheology of a thixotropic fluid changes with time until reaching equilibrium. In fact, most drilling fluids exhibit thixotropy, which is necessary for fast drilling, efficient cuttings transport and to support weight material when mud flow stops.
Continuous transmitting of real time measurements is getting more and more common. Data processing capabilities are improving and automatic control of the drilling process is soon a possibility. The technology development may allow us to go from passive/reactive drilling to active/proactive drilling control. In order to reach this target, a systematic analysis of combining real time measurements, flow models and control loops has to be performed. An important step in this direction is to develop methodology for continuous updating of well flow and drilling mechanical models.
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