Rafael Pires de Lima

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Linking image processing and numerical modeling to identify potential geohazards

Rafael Pires de Lima, 2017 .

Petrographic microfacies classification with deep convolutional neural networks

Rafael Pires de Lima, David Duarte, Charles D. Nicholson, 2020, Comput. Geosci..

Quantifying fault connectivity drilling hazards through simple flow computations

Kurt J. Marfurt, Rafael Pires de Lima, 2017 .

Convolutional neural networks as aid in core lithofacies classification

Kurt J. Marfurt, Rafael Pires de Lima, Fnu Suriamin, 2019 .

Deep convolutional neural networks as a geological image classification tool

Kurt J. Marfurt, Charles Nicholson, Rafael Pires de Lima, 2019, The Sedimentary Record.

Statistical Controls on Induced Seismicity

Saurabh Sinha, Kurt J. Marfurt, Rafael Pires de Lima, 2018 .

Deep convolutional neural networks as an estimator of porosity in thin-section images for unconventional reservoirs

Kurt J. Marfurt, Roger M. Slatt, Rafael Pires de Lima, 2019 .

Convolutional Neural Network for Remote-Sensing Scene Classification: Transfer Learning Analysis

Rafael Pires de Lima, Kurt Marfurt, K. Marfurt, 2019, Remote. Sens..

Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms

Rafael Pires de Lima, Youzuo Lin, Yue Chen, 2019, Space Weather.

Data for: Petrographic analysis with deep convolutional neural networks

Roger M. Slatt, Rafael Pires de Lima, David Duarte, 2020 .

URTeC : 2897507 Statistical Controls on Induced Seismicity

Rafael Pires de Lima, K. Marfurt, Yunjie Wen, 2018 .

This is the title of an example SEG abstract using Microsoft Word 11-point bold type

Rafael Pires de Lima, K. Marfurt, R. Slatt, 2006 .