フォロー
Rafael Pires de Lima
Rafael Pires de Lima
Data Scientist, VerAI Discoveries
確認したメール アドレス: ver-ai.com
タイトル
引用先
引用先
Convolutional neural network for remote-sensing scene classification: Transfer learning analysis
R Pires de Lima, K Marfurt
Remote Sensing 12 (1), 86, 2019
2812019
Deep convolutional neural networks as a geological image classification tool
RP de Lima, A Bonar, DD Coronado, K Marfurt, C Nicholson
The Sedimentary Record 17 (2), 4-9, 2019
752019
Petrographic microfacies classification with deep convolutional neural networks
RP de Lima, D Duarte, C Nicholson, R Slatt, KJ Marfurt
Computers & Geosciences 142, 104481, 2020
692020
Convolutional neural networks as aid in core lithofacies classification
R Pires de Lima, F Suriamin, KJ Marfurt, MJ Pranter
Interpretation 7 (3), 1-50, 2019
612019
Forecasting Megaelectron‐Volt Electrons Inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms
R Pires de Lima, Y Chen, Y Lin
Space Weather 18 (2), e2019SW002399, 2020
402020
Normal or abnormal? Machine learning for the leakage detection in carbon sequestration projects using pressure field data
S Sinha, RP de Lima, Y Lin, AY Sun, N Symons, R Pawar, G Guthrie
International Journal of Greenhouse Gas Control 103, 103189, 2020
392020
Convolutional neural networks as an aid to biostratigraphy and micropaleontology: a test on Late Paleozoic microfossils
R PIRES DE LIMA, KF Welch, JE Barrick, KJ Marfurt, R Burkhalter, ...
Palaios 35 (9), 391-402, 2020
302020
Principal component analysis and K-means analysis of airborne gamma-ray spectrometry surveys
RP de Lima, KJ Marfurt
SEG Technical Program Expanded Abstracts 2018, 2277-2281, 2018
272018
Pretraining Convolutional Neural Networks for Mudstone Petrographic Thin-Section Image Classification
R Pires de Lima, D Duarte
Geosciences 11 (8), 336, 2021
212021
Progress and Challenges in Deep Learning Analysis of Geoscience Images
RP De Lima, K Marfurt, D Duarte, A Bonar
81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019
212019
Deep convolutional neural networks as an estimator of porosity in thin-section images for unconventional reservoirs
D Duarte-Coronado, J Tellez-Rodriguez, R Pires de Lima, K Marfurt, ...
SEG Technical Program Expanded Abstracts 2019, 3181-3184, 2019
132019
Lithofacies identification in cores using deep learning segmentation and the role of geoscientists: Turbidite deposits (Gulf of Mexico and North Sea)
O Falivene, NC Auchter, RP de Lima, L Kleipool, JG Solum, P Zarian, ...
AAPG Bulletin 106 (7), 1357-1372, 2022
102022
Statistical controls on induced seismicity
S Sinha, Y Wen, R Pires De Lima, K Marfurt
Unconventional Resources Technology Conference, Houston, Texas, 23-25 July …, 2018
92018
Generating a labeled data set to train machine learning algorithms for lithologic classification of drill cuttings
D Becerra, R Pires de Lima, H Galvis-Portilla, CR Clarkson
Interpretation 10 (3), SE85-SE100, 2022
82022
Leak Detection in Carbon Sequestration Projects Using Machine Learning Methods: Cranfield Site, Mississippi, USA
S Sinha, R Pires De Lima, Y Lin, A Y Sun, N Symon, R Pawar, G Guthrie
SPE Annual Technical Conference and Exhibition, 2020
82020
Transforming seismic data into pseudo-RGB images to predict CO2 leakage using pre-learned convolutional neural networks weights
R Pires de Lima, Y Lin, KJ Marfurt
SEG Technical Program Expanded Abstracts 2019, 2368-2372, 2019
82019
Geophysical data integration and machine learning for multi-target leakage estimation in geologic carbon sequestration
RP de Lima, Y Lin
SEG Technical Program Expanded Abstracts 2019, 2333-2337, 2019
82019
Comparison of clustering techniques to define chemofacies in mississippian rocks in the STACK Play, Oklahoma
D Duarte, R Lima, R Slatt, K Marfurt
American association of petroleum geologists search and discovery 42523, 2020
62020
Machine learning applications for geoscience problems
RAP LIMA
62019
Seismic Inversion Based SRV and Reserves Estimation for Shale Plays
S Sinha, KJ Marfurt, D Devegowda, R Pires de Lima, S Verma
SPE Annual Technical Conference and Exhibition, 2017
62017
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