Reservoir characterization in under-balanced drilling using low-order lumped model. (February 2018) - Nikoofard, Amirhossein; Johansen, Tor Arne; Kaasa, Glenn-Ole
Highlights: Design of the Lyapunov-based adaptive observer based on low-order lumped model for UBD operations. Applying the UKF for estimation of states and parameters of a drift-flux model. Robustness analysis of the adaptive observers in case of uncertainties in the models. The performance of the adaptive observers to detect and track the change in production parameters is investigated. Abstract: Estimation of the production index of oil and gas from the reservoir into the well during under-balanced drilling (UBD) is studied. This paper compares a Lyapunov-based adaptive observer and a joint unscented Kalman filter (UKF) based on a low order lumped (LOL) model and the joint UKF based on the distributed drift-flux model by using real-time measurements of the choke and the bottom-hole pressures. Using the OLGA simulator, it is found that all adaptive observers are capable of identifying the production constants of gas and liquid from the reservoir into the well, with some differences in performance. The results show that the LOL model is sufficient for the purpose of reservoir characterization during UBD operations. Robustness of the adaptive observers is investigated in case of uncertainties and errors in the reservoir and well parameters of the models.