Estimate ore content based on spatial geological data through 3D convolutional neural networks
US12236329B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 5, 2018 |
| Grant date | Feb 25, 2025 |
| Priority date | — |
| Expiry date | Mar 7, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/045
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An ore content prediction system is provided. The system receives structured geological data that is derived based on spatial geological information that is associated with an input region. The received structured geological data includes a plurality of multidimensional tensors that are derived from spatial geological information of a plurality of sub-regions of the input region. The spatial geological information includes one or more types of data. The system trains a prediction model to produce a prediction output based on an average grade of an ore of a target mineral type at a target region by using the received structured geological data. The system identifies a relationship of the structured geological data to the prediction output and determines a revised input region based on the identified relationship.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.