Abstract: A borehole logging tool having a pair of spaced-apart detectors records intensity signals representing the die-away of nuclear radiation in a subsurface formation. Weighted moments of the intensity signals as well as of a model are produced. Corresponding weighted intensity and model moments are equated and simultaneously solved to obtain values for a borehole decay constant, a formation decay constant, and a formation-to-borehole amplitude ratio for each of the pair of detectors. From these values a trained neural network produces intrinsic values of a formation macroscopic thermal neutron absorption cross section, a formation porosity, and a borehole fluid cross section. A log is generated of these intrinsic values versus depth as the logging tool traverses the borehole.

Abstract: A borehole logging tool is lowered into a borehole traversing a subsurface formation and a neutron detector measures the die-away of nuclear radiation in the formation. A model of the die-away of nuclear radiation is produced using exponential terms varying as the sum of borehole, formation and thermal neutron background components. Exponentially weighted moments of both the die-away measurements and die-away model are determined and equated. The equated moments are solved for the ratio of the borehole to formation amplitude components of the measurements. The formation decay constant is determined from at least the formation and thermal neutron background terms of the weighted measurement and model moments. An epithermal neutron lifetime is determined from the formation decay constant. This epithermal neutron lifetime and the amplitude ratio are used by a trained neural network to determine a lifetime correction and an apparent standoff.

Abstract: A borehole logging tool is lowered into a borehole traversing a subsurface formation and a neutron detector measures the die-away of nuclear radiation in the formation. Intensity signals are produced representing the die-away of nuclear radiation as the logging tool traverses the borehole A signal processor, employing at least one neural network, processes the intensity signals and produces a standoff-corrected epithermal neutron lifetime signal to correct for standoff from the borehole wall encountered by the detector as the logging tool traverses the borehole. The signal processor further generates a porosity signal from the standoff-corrected epithermal neutron lifetime signal derived from measurements in borehole models at known porosities and conditions of detector standoff. A log is generated of such porosity signal versus depth as the logging tool traverses the borehole.

Abstract: A borehole logging tool is lowered into a borehole traversing a subsurface formation and a neutron detector measures the die-away of nuclear radiation in the formation. A model of the die-away of nuclear radiation is produced using exponential terms varying as the sum of borehole, formation and thermal neutron background components. Exponentially weighted moments of both the die-away measurements and die-away model are determined and equated. The equated moments are solved for the ratio of the borehole to formation amplitude components of the measurements. The formation decay constant is determined from at least the formation and thermal neutron background terms of the weighted measurement and model moments. The determined borehole to formation amplitude ratio is used to correct the determined formation decay constant for the effects of detector standoff from the borehole wall.