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Inversion of time-dependent nuclear well-logging data using neural networks

The paper presents a fast inversion methodology for the prediction of subsurface formation properties such as porosity, salinity and oil saturation, using time-dependent nuclear well logging data (as opposed to electrokinetic data). This is the first time the technique has been applied to invert pulsed neutron logging tool information and the results are promising. The significance of the technique is due to its speed and accuracy, thus providing a real-time tool for well-logging interpreters to extract formation information in real time and whilst on-site drilling. Verification: Laura Carmine, Drilling Supervisor, Conoco-Philips, Norway (laura.carmine@cop.com)