Inversion of electrical capacitance tomography data by simulated annealing: Application to real two-phase gas–oil flow imaging

Abstract

In this work we apply a highly optimized simulated annealing (SA) inversion method to the reconstruction of permittivity images from real two-phase gas–oil flow electrical capacitance tomography (ECT) data. We test the SA inversion method using several flow regimes generated by varying gas and oil flow rates in a test loop facility. The SA-based permittivity inversions have some advantages over other reconstruction approaches based on linear least-squares inversion: they can find good solutions starting with poor initial models, can easily implement complex a priori information, and do not introduce smoothing effects in the final permittivity distribution model. A major disadvantage comes from the fact that SA is computationally very intensive and leads to relatively slow reconstructions when calculation of the forward problem is not very fast. In this work we employ a linearized and numerically improved forward model based on the use of a sensitivity matrix. We find this novel approach to be faster and more accurate than traditional linear methods.