Methods of analyzing cement integrity in annuli of a multiple-cased well using machine learning
US11493659B2 · kind B2 · utility
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25Claims
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Key dates
| Filing date | Oct 25, 2018 |
| Grant date | Nov 8, 2022 |
| Priority date | — |
| Expiry date | Oct 25, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01V2210/62
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A sonic tool is activated in a well having multiple casings and annuli surrounding the casing. Detected data is preprocessed using slowness time coherence (STC) processing to obtain STC data. The STC data is provided to a machine learning module which has been trained on labeled STC data. The machine learning module provides an answer product regarding the states of the borehole annuli which may be used to make decision regarding remedial action with respect to the borehole casings. The machine learning module may implement a convolutional neural network (CNN), a support vector machine (SVM), or an auto-encoder.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.