International Society for Industrial Process Tomography

State Estimation Approach for Spatio-Temporal Two-Phase Flow Imaging using Dual-Modal Electrical Tomography

Marko Vauhkonen^1*, M. Ziaul Arif¹, Aku Seppänen¹

¹ Department of Technical Physics, University of Eastern Finland, 70211 Kuopio, Finland

^*Email: marko.vauhkonen@uef.fi

ABSTRACT

In this study, we explore the potential of state estimation for dynamic image reconstruction in dual-modal tomography of two-phase oil-water flow. The accurate measurement of two-phase flow quantities is crucial for effective production management across various industries. However, the complexity inherent in two-phase flow poses challenges in accurately estimating the quantities, necessitating the development of reliable techniques. Our approach involves utilizing electromagnetic flow tomography (EMFT) for velocity field estimation and electrical tomography (ET) for determining phase fraction distributions. To account for the contribution of the velocity field to the temporal evolution of the phase fraction distribution, we employ a convection-diffusion model in the state estimation process. Furthermore, the extended Kalman filter (EKF) and fixed-interval Kalman smoother (FIKS) are used for reconstructing the spatio-temporal velocity and phase fraction distributions. The effectiveness of our approach is demonstrated through experimental investigations on a laboratory setup, considering two cases with non-stationary average flow speeds. The results reveal that the proposed approach outperforms conventional stationary reconstructions, highlighting the potential of state estimation for achieving more accurate dynamic image reconstruction in dual-modal tomography of two-phase flow.

Keywords: Dual-modal imaging, Electrical tomography, Electromagnetic flow tomography, State estimation approach, Two-phase flow

Industrial Application: Petroleum and processing industries.