Gamma Radiation Methods for Cost-Effective Multiphase Flow Metering

The development of a cost-effective multiphase flow meter was investigated through the exploitation of gamma densitometry and pattern recognition signal processing techniques. Two neural network models were developed for comparison: a single multilayer-perceptron and a multilayer hierarchical flow regime dependent model. The pattern recognition systems were trained to map the temporal fluctuations in the multiphase mixture density with the individual phase flow rates using statistical features extracted from the gamma count signals as their inputs. Initial results yielded individual phase flow rate predictions to within ±10% based on flow regime specific correlations.