Clustering process for analyzing pressure gradient data
US8918288B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 14, 2011 |
| Grant date | Dec 23, 2014 |
| Priority date | — |
| Expiry date | Feb 15, 2033 |
Classification
- Technology area (CPC E)Fixed Constructions
- CPC primaryE21B47/12
- WIPO fieldCivil engineering
- WIPO sectorOther fields
Abstract
Clustering analysis is used to partition data into similarity groups based on mathematical relationships between the measured variables. These relationships (or prototypes) are derived from the specific correlation required between the measured variables (data) and an environmental property of interest. The data points are partitioned into the prototype-driven groups (i.e., clusters) based on error minimization. Once the data is grouped, quantitative predictions and sensitivity analysis of the property of interest can be derived based on the computed prototypes. Additionally, the process inherently minimizes prediction errors due to the rigorous error minimization during data clustering while avoiding overfitting via algorithm parameterization. The application used to demonstrate the power of the method is pressure gradient analysis.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.