Method and system for estimating in-situ porosity using machine learning applied to cutting analysis
US11649723B2 · kind B2 · utility
1Cited by
5References
20Claims
0Family size
Assignee
Inventor
Key dates
| Filing date | Apr 24, 2019 |
| Grant date | May 16, 2023 |
| Priority date | — |
| Expiry date | Nov 19, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30181
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
A method for estimating in-situ porosity based on cutting images employs a neural network trained with labeled images, the labels indicating wireline porosity values. The method may be used to obtain porosity values along a vertical, deviated or horizontal well, where wireline logging data is not available or unreliable. The method uses machine learning. Training and validating the neural network may be ongoing processes in the sense that any new labeled image that becomes available can be added to the training set and the neural network being retrained to enhance its predictive performance.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.