Shearlets and sparse representation for microresistivity borehole image inpainting
| Autor: | Peter Elkington, Said Assous |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Signal processing
business.industry Wireline 0211 other engineering and technologies Inpainting Borehole 02 engineering and technology Sparse approximation 010502 geochemistry & geophysics 01 natural sciences Image (mathematics) Borehole geophysics Geophysics Geochemistry and Petrology Shearlet Computer vision Artificial intelligence business 021101 geological & geomatics engineering 0105 earth and related environmental sciences Mathematics |
| Zdroj: | GEOPHYSICS. 83:D17-D25 |
| ISSN: | 1942-2156 0016-8033 |
| DOI: | 10.1190/geo2017-0279.1 |
| Popis: | Microresistivity image logs from wireline tools commonly include nonmeasured gaps corresponding to the spaces between electrode-carrying pads in contact with the borehole wall. The missing data impede the development of automated processes that seek to provide objective and reproducible geologic analysis. Geologic features often manifest themselves as curvilinear objects representing a variety of discontinuities, such as layer boundaries and fractures, which lend themselves to sparse representation. Missing data may be inpainted by thresholding or minimizing the norm of their representation in a fitting dictionary. Curvelets have been found to provide good sparse approximation for these features, but shearlets are shown to be more computationally efficient. Results from a mix of synthetic and field image logs indicate more accurate reconstruction of sharp high-contrast edges. |
| Databáze: | OpenAIRE |
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