Follow
Rafael Pires de Lima
Rafael Pires de Lima
Geoscience researcher, Geological Survey of Brazil
Verified email at cprm.gov.br
Title
Cited by
Cited by
Year
Convolutional neural network for remote-sensing scene classification: Transfer learning analysis
R Pires de Lima, K Marfurt
Remote Sensing 12 (1), 86, 2019
2302019
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
642019
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
632019
Petrographic microfacies classification with deep convolutional neural networks
RP de Lima, D Duarte, C Nicholson, R Slatt, KJ Marfurt
Computers & Geosciences 142, 104481, 2020
482020
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
282020
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
262020
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
252018
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
242020
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
162019
Pretraining Convolutional Neural Networks for Mudstone Petrographic Thin-Section Image Classification
R Pires de Lima, D Duarte
Geosciences 11 (8), 336, 2021
152021
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
112019
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
102018
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
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, R Pires de Lima, L Kleipool, JG Solum, P Zarian, ...
AAPG Bulletin 106 (7), 1357-1372, 2022
7*2022
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
72019
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
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
52022
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
52020
PreMevE Update: Forecasting Ultra-relativistic Electrons inside Earth's Outer Radiation Belt
S Sinha, Y Chen, Y Lin, R Pires de Lima
Space Weather 19 (9), e2021SW002773, 2021
42021
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
32020
The system can't perform the operation now. Try again later.
Articles 1–20