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Uncertainty Quantification on the Inversion of Geosteering Measurements using Deep Learning
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 3rd EAGE/SPE Geosteering Workshop, Nov 2021, Volume 2021, p.1 - 5
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Abstract
Summary
We propose the use of a Deep Learning (DL) algorithm for the real-time inversion of electromagnetic measurements acquired during geosteering operations. Moreover, we show that when the DL algorithm is equipped with a properly designed two-step loss function without regularization, it is possible to recover an uncertainty quantification map by analyzing certain cross-plots. We illustrate these ideas with a synthetic example based on piecewise 1D earth models.
The resulting uncertainty quantification map could be used to design better measurement acquisition systems for geosteering operations.
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