Abstract
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.
