Methods and apparatuses for modeling shale characteristics in wellbore servicing fluids using an artificial neural network
US9117169B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 24, 2012 |
| Grant date | Aug 25, 2015 |
| Priority date | — |
| Expiry date | Aug 31, 2033 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An apparatus and method for determining a formation/fluid interaction of a target formation and a target drilling fluid is described herein. The method may include training an artificial neural network using a training data set. The training data set may include a formation characteristic of a source formation and a fluid characteristic of a source drilling fluid and experimental data on source formation/fluid interaction. Once the artificial neural network is trained, a formation characteristic of the target formation and fluid characteristic of target drilling fluid may be input. The formation characteristic of the target formation may correspond to the formation characteristic of the source formation. The fluid characteristic of the target drilling fluid may correspond to the fluid characteristic of the source drilling fluid. A formation/fluid interaction of the target formation and the target drilling fluid may be determined using a value output by the artificial neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.