Method for determining preferred drill bit design parameters and drilling parameters using a trained artificial neural network, and methods for training the artificial neural network
US6424919B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 26, 2000 |
| Grant date | Jul 23, 2002 |
| Priority date | — |
| Expiry date | Jun 26, 2020 |
Classification
- Technology area (CPC E)Fixed Constructions
- CPC primaryE21B2200/22
- WIPO fieldCivil engineering
- WIPO sectorOther fields
Abstract
A method for selecting a design parameter for a drill bit is disclosed. The method includes entering a value of at least one property of an earth formation to be drilled into a trained neural network. The neural network is trained by selecting data from drilled wellbores. The data comprise values of the formation property for formations through which the drilled wellbores have penetrated. Corresponding to the values of formation property are values of at least one drilling operating parameter, the drill bit design parameter, and values of a rate of penetration and a rate of wear of a drill bit used on each of the formations. Data from the wellbores are entered into the neural network to train it, and the design parameter is then selected based on output of the trained neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.