Dual-mode capacitance and gamma-ray tomography using the Landweber reconstruction algorithm

A dual-mode tomography system based on electrical capacitance and gamma-ray tomography has been developed at the Department of Physics and Technology, University of Bergen. The objective of the dual-mode tomograph is to acquire cross-sectional images, i.e. tomograms, of hydrocarbon flow comprising oil, water and gas constituents. The capacitance tomograph utilizes an eight-electrode sensor set-up mounted around a PVC pipe structure which is sensitive to the electrical permittivity epsilon(r) of the fluid. By using the capacitance tomograph, the produced water constituent can be separated from the gas and crude oil constituents, assuming that the liquid phase is oil continuous. The high-speed gamma-ray tomograph comprises five 500 mCi Am-241 gamma-ray sources, each at a principal energy of 59.5 keV, which corresponds to five detector modules, each consisting of 17 CdZnTe detectors mounted around the same pipe section as the capacitance sensor. The gamma-ray tomograph discriminates between the gas and the liquid phase, since these have different photon attenuation properties. As a result, the gamma-ray tomograph is able to distinguish the gas phase from the liquid phase of the hydrocarbon flow. Consequently, the dual-mode capacitance and gamma-ray tomography set-up is able to distinguish the oil, water and gas constituents of hydrocarbon flow. This paper presents the work that has been performed related to static characterization of the dual-mode tomograph using the Landweber reconstruction algorithm on polypropylene phantoms. The objective of the work has been to quantitatively evaluate the static imaging performance of the dual-mode tomograph with respect to relative spatial measurement errors, i.e. root mean square errors of the reconstructed tomograms compared to that of the phantom. The work shows that dual-mode tomography using electrical capacitance and gamma-ray sensors is feasible on hydrocarbon flow components using a pixel-to-pixel fusion procedure on separately reconstructed tomograms based on the Landweber reconstruction algorithm.