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Justin Granek
Justin Granek
Xtract AI
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Multiresolution neural networks for tracking seismic horizons from few training images
B Peters, J Granek, E Haber
Interpretation 7 (3), SE201-SE213, 2019
692019
Neural networks for geophysicists and their application to seismic data interpretation
B Peters, E Haber, J Granek
The Leading Edge 38 (7), 534-540, 2019
522019
Application of machine learning algorithms to mineral prospectivity mapping
J Granek
University of British Columbia, 2016
292016
Data mining for real mining: A robust algorithm for prospectivity mapping with uncertainties
J Granek, E Haber
Proceedings of the 2015 SIAM international conference on data mining, 145-153, 2015
232015
An adaptive mesh method for electromagnetic inverse problems
E Haber, D Oldenburg, C Schwarzbach, R Shekhtman, E Holtham, ...
SEG International Exposition and Annual Meeting, SEG-2012-0828, 2012
182012
Using machine learning to interpret 3D airborne electromagnetic inversions
E Haber, J Fohring, M McMillan, J Granek
ASEG Extended Abstracts 2019 (1), 1-4, 2019
92019
Machine learning systems and methods for document matching
EM Holtham, A Shafaei, J Granek
US Patent App. 15/903,344, 2018
82018
Advanced geoscience targeting via focused machine learning applied to the QUEST project dataset, British Columbia
J Granek, E Haber
Geoscience BC Summary of Activities 2011, 2016
72016
3D inversion of DC/IP data using adaptive OcTree meshes
E Haber, D Oldenburg, R Shekhtman, J Granek, D Marchant, E Holtham
SEG International Exposition and Annual Meeting, SEG-2012-1438, 2012
72012
Computing geologically consistent models from geophysical data
J Granek
University of British Columbia, 2011
72011
Orogenic gold prospectivity mapping using machine learning
M McMillan, J Fohring, E Haber, J Granek
ASEG Extended Abstracts 2019 (1), 1-4, 2019
52019
Automatic classification of geologic units in seismic images using partially interpreted examples
B Peters, J Granek, E Haber
81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019
52019
Multiresolution neural networks for tracking seismic horizons from few training images: Interpretation, 7
B Peters, J Granek, E Haber
SE201–SE213, 2019
52019
Does shallow geological knowledge help neural-networks to predict deep units?
B Peters, E Haber, J Granek
SEG International Exposition and Annual Meeting, D033S038R002, 2019
22019
Resource Management through Machine Learning
J Granek, E Haber, E Holtham
ASEG Extended Abstracts 2016 (1), 1-5, 2016
12016
Sensor systems and methods for facility operation management
JS Granek, EM Holtham
US Patent App. 17/330,971, 2022
2022
Ultra High-resolution Imaging of Brachiopod Shells: Assessing Their Robustness as Paleo-environmental Indicators
JS Granek
Acadia University, 2009
2009
Advanced Geoscience Targeting via Focused Machine Learning
J Granek, E Haber
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