Computer-implemented method of using a non-transitory computer readable memory device with a pre programmed neural network and a trained neural network computer program product for obtaining a true borehole sigma and a true formation sigma

Abstract

A computer-implemented method that uses a preprogrammed neural network and a trained neural network computer program product to predict and then compared borehole and formation sigmas, when using a pulse neutron source and at least three dual-function radiation detectors. These dual-function radiation detectors are used for detecting both neutrons and gamma rays and further pre-programmed to distinguish between neutrons and gamma rays by using pulse shape discrimination techniques. The trained neural network computer program product can be used on above-surface systems, as well as below surface systems like borehole assemblies in logging-while-drilling systems. Once thermal neutron time-decay signals and capture gamma ray time-decay signals are measured by the at least three-dual function radiation detectors, a non-transitory computer readable memory device with the trained neural network computer program product is used to obtain a true borehole sigma and true formation sigma as the measurements are not affected by near-wellbore environments.