System and method of predicting gas saturation of a formation using neural networks
US8898045B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 21, 2009 |
| Grant date | Nov 25, 2014 |
| Priority date | — |
| Expiry date | Jul 8, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01V5/125
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Predicting gas saturation of a formation using neural networks. At least some of the illustrative embodiments include obtaining a gamma count rate decay curve one each for a plurality of gamma detectors of a nuclear logging tool (the gamma count rate decay curves recorded at a particular borehole depth), applying at least a portion of each gamma count rate decay curve to input nodes of a neural network, predicting a value indicative of gas saturation of a formation (the predicting by the neural network in the absence of a formation porosity value supplied to the neural network), and producing a plot of the value indicative of gas saturation of the formation as a function of borehole depth.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.