.session D3: Neural networks OIL HEIGHT DETERMINATION FROM CAPACITANCE TOMOGRAPHY MEASUREMENTS USING NEURAL NETWORK
نویسنده
چکیده
This paper presents a "direct" method to gas-oil interface level determination using an artificial neural network approach based on Electrical Capacitance Tomography (ECT) measurements. "Direct" here means that the gas-oil interface levels are obtained directly from the ECT measurements without recourse to image reconstruction. The preliminary work models a separation tank that i~ filled with gas anc:\ oil. An ECT system, attached around the tank is used to obtain ECT measurements. Sets of.ECT measurements together with their corresponding oil heights are fed into a Multi-Layer Perceptron '(MLP) neural' network system for training processes. After being trained, the MLP is tested by giving it sets of independent ECT measurements. The results show that "direct" gas-oil interface level measurement from ECT data is feasible with the use of a neural network system.
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