Multisensor drill core logging integrating XRF and SWIR sensors to support machine learning

P. Teixeira Mendes; P. Barnabé; P. Koch; E. Pirard; C. Garcia Pina; L. Rybok; C. Bachmann; J.M. Pons Perez; J.C. Videira Vazquez

doi:10.3997/2214-4609.202089037

oa Multisensor drill core logging integrating XRF and SWIR sensors to support machine learning
Authors P. Teixeira Mendes¹, P. Barnabé¹, P. Koch¹, E. Pirard¹, C. Garcia Pina², L. Rybok³, C. Bachmann³, J.M. Pons Perez⁴, J.C. Videira Vazquez⁴
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Affiliations: ¹ University Of Liege ² DMT ³ Bachmann ⁴ MATSA
Publisher: European Association of Geoscientists & Engineers
Source: Conference Proceedings, Mineral Exploration Symposium, Sep 2020, Volume 2020, p.1 - 3
DOI: https://doi.org/10.3997/2214-4609.202089037

Abstract

Summary

An innovative computer assisted drill core logging system has been developed based on the integration of a SWIR spectral imaging system and a systematic XRF analytical probe. The system has been trained on mineralisations from the Iberian Pyrite Belt. The use of deep learning algorithms allows to obtain consistent logging results

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2020-09-17

2024-04-20

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References

Almodóvar, G. R., Yesares, L., Sáez, R., Toscano, M., González, F., & Pons, J. M.
[2019]. Massive Sulfide Ores in the Iberian Pyrite Belt: Mineralogical and Textural Evolution.Minerals, 9(11), 653.
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Multisensor drill core logging integrating XRF and SWIR sensors to support machine learning

Conference Proceedings 2020, 1 (2020); https://doi.org/10.3997/2214-4609.202089037

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oa Multisensor drill core logging integrating XRF and SWIR sensors to support machine learning

Abstract

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The natural combination of full and image‐based waveform inversion

Poststack diffraction imaging using reverse‐time migration

Characterizing the effect of elastic interactions on the effective elastic properties of porous, cracked rocks

Fracture detection by Gaussian beam imaging of seismic data and image spectrum analysis

Laboratory measurements of guided‐wave propagation within a fluid‐saturated fracture