Rafael Augusto Pires de Lima

Pós-doutorado

Formação complementar

Idiomas

Áreas de atuação

Produções bibliográficas

• DA SILVA, ADOLFO BARBOSA ; PIRES DE LIMA, RAFAEL ; LA MARCA, KARELIA . Decomposing and recovering airborne radiometric data through principal component analysis applied on flight-line data: An alternative to reduce noise. Interpretation-A Journal of Subsurface Characterization , v. 11, p. T523-T535, 2023.

• DUARTE, DAVID ; PIRES DE LIMA, RAFAEL ; TELLEZ, JAVIER ; PRANTER, MATTHEW J. . Spatial variability of petrofacies using supervised machine learning and geostatistical modeling: Sycamore Formation, Sho-Vel-Tum Field, Oklahoma, USA. Interpretation-A Journal of Subsurface Characterization , v. 11, p. T289-T302, 2023.

• PIRES DE LIMA, RAFAEL ; KARIMZADEH, MORTEZA . Model Ensemble With Dropout for Uncertainty Estimation in Sea Ice Segmentation Using Sentinel-1 SAR. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING , v. 61, p. 1-15, 2023.

• PIRES DE LIMA, RAFAEL ; VAHEDI, BEHZAD ; HUGHES, NICK ; BARRETT, ANDREW P. ; MEIER, WALTER ; KARIMZADEH, MORTEZA . Enhancing sea ice segmentation in Sentinel-1 images with atrous convolutions. INTERNATIONAL JOURNAL OF REMOTE SENSING , v. 44, p. 5344-5374, 2023.

• BECERRA, DANIELA ; PIRES DE LIMA, RAFAEL ; GALVIS-PORTILLA, HENRY ; CLARKSON, CHRISTOPHER R. . Generating a labeled data set to train machine learning algorithms for lithologic classification of drill cuttings. Interpretation-A Journal of Subsurface Characterization , v. 10, p. SE85-SE100, 2022.

• FALIVENE, ORIOL ; AUCHTER, NEAL C. ; PIRES DE LIMA, RAFAEL ; KLEIPOOL, LUUK ; SOLUM, JOHN G. ; ZARIAN, PEDRAM ; CLARK, RACHEL W. ; ESPEJO, IRENE . Lithofacies identification in cores using deep learning segmentation and the role of geoscientists: Turbidite deposits (Gulf of Mexico and North Sea). AAPG BULLETIN , v. 106, p. 1357-1372, 2022.

• BECERRA, DANIELA ; CLARKSON, CHRISTOPHER R. ; GHANIZADEH, AMIN ; PIRES DE LIMA, RAFAEL ; TABASINEJAD, FARSHAD ; ZHANG, ZHENZIHAO ; TRIVEDI, AJESH ; SHOR, ROMAN . Evaluation of Reservoir Quality and Forecasted Production Variability along a Multi-Fractured Horizontal Well. Part 1: Reservoir Characterization. Energies , v. 14, p. 6154, 2021.

• PIRES DE LIMA, RAFAEL ; DUARTE, DAVID . Pretraining Convolutional Neural Networks for Mudstone Petrographic Thin-Section Image Classification. Geosciences , v. 11, p. 336, 2021.

• SINHA, SAURABH ; CHEN, YUE ; LIN, YOUZUO ; PIRES DE LIMA, RAFAEL . PreMevE Update: Forecasting Ultra-Relativistic Electrons Inside Earth's Outer Radiation Belt. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS , v. 19, p. e2021SW002773, 2021.

• PIRES DE LIMA, RAFAEL ; MARFURT, KURT . Convolutional Neural Network for Remote-Sensing Scene Classification: Transfer Learning Analysis. Remote Sensing , v. 12, p. 86, 2020.

• PIRES DE LIMA, RAFAEL ; CHEN, YUE ; LIN, YOUZUO . Forecasting Megaelectron-Volt Electrons inside Earth's Outer Radiation Belt: PreMevE 2.0 Based on Supervised Machine Learning Algorithms. SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS , v. 18, p. e2019SW002399, 2020.

• PIRES DE LIMA, RAFAEL ; DUARTE, DAVID ; NICHOLSON, CHARLES ; SLATT, ROGER ; MARFURT, KURT J. . Petrographic microfacies classification with deep convolutional neural networks. COMPUTERS & GEOSCIENCES , v. 142, p. 104481, 2020.

• PIRES DE LIMA, RAFAEL ; WELCH, KATIE F. ; BARRICK, JAMES E. ; MARFURT, KURT J. ; BURKHALTER, ROGER ; CASSEL, MURPHY ; SOREGHAN, GERILYN S. . CONVOLUTIONAL NEURAL NETWORKS AS AN AID TO BIOSTRATIGRAPHY AND MICROPALEONTOLOGY: A TEST ON LATE PALEOZOIC MICROFOSSILS. PALAIOS , v. 35, p. 391-402, 2020.

• SINHA, SAURABH ; DE LIMA, RAFAEL PIRES ; LIN, YOUZUO ; SUN, ALEXANDER Y. ; SYMONS, NEILL ; PAWAR, RAJESH ; GUTHRIE, GEORGE . Normal or abnormal? Machine learning for the leakage detection in carbon sequestration projects using pressure field data. International Journal of Greenhouse Gas Control , v. 103, p. 103189, 2020.

• PIRES DE LIMA, RAFAEL ; SURIAMIN, FNU ; MARFURT, KURT J. ; PRANTER, MATTHEW J. . Convolutional neural networks as aid in core lithofacies classification. Interpretation-A Journal of Subsurface Characterization , v. 7, p. SF27-SF40, 2019.

• PIRES DE LIMA, RAFAEL ; BONAR, ALICIA ; CORONADO, DAVID DUARTE ; MARFURT, KURT ; NICHOLSON, CHARLES ; BIRGENHEIER, LAUREN P. ; HARPER, HOWARD . Deep convolutional neural networks as a geological image classification tool. The Sedimentary Record , v. 17, p. 4-9, 2019.

• PIRES DE LIMA, RAFAEL ; SURIAMIN, FNU . Chapter 5 - Convolutional neural networks: core interpretation with instance segmentation models. In: Shuvajit Bhattacharya; Haibin Di. (Org.). Advances in Subsurface Data Analytics. 1ed.: , 2022, v. 1, p. 117-140.

• PIRES DE LIMA, RAFAEL ; SURIAMIN, F. ; MARFURT, KURT ; PRANTER, M. ; SOREGHAN, G. . Convolutional Neural Networks: If they can identify an oncoming car, can they identify lithofacies in core?. AAPG Explorer, Tulsa, OK, EUA, 01 out. 2018.

• SINHA, SAURABH ; PIRES DE LIMA, RAFAEL ; LIN, YOUZUO ; Y. SUN, ALEXANDER ; SYMON, NEILL ; PAWAR, RAJESH ; GUTHRIE, GEORGE . Leak Detection in Carbon Sequestration Projects Using Machine Learning Methods: Cranfield Site, Mississippi, USA. In: SPE Annual Technical Conference and Exhibition, 2020, Virtual. SPE Annual Technical Conference and Exhibition, 2020.

• SINHA, SAURABH ; WEN, YUNJIE ; DE LIMA, RAFAEL PIRES ; MARFURT, KURT . Statistical Controls on Induced Seismicity. In: Unconventional Resources Technology Conference, 2018, Houston. Proceedings of the 6th Unconventional Resources Technology Conference. Tulsa: American Association of Petroleum Geologists, 2018.

• SINHA, SAURABH ; MARFURT, KURT J. ; DEVEGOWDA, DEEPAK ; PIRES DE LIMA, RAFAEL ; VERMA, SUMIT . Seismic Inversion Based SRV and Reserves Estimation for Shale Plays. In: SPE Annual Technical Conference and Exhibition, 2017, San Antonio. SPE Annual Technical Conference and Exhibition, 2017.

• WANG, ZHONGYING ; DE LIMA, RAFAEL PIRES ; CROOKS, JAMES L. ; REGAN, ELIZABETH ANNE ; KARIMZADEH, MORTEZA . Increasing the Spatial Coverage of Atmospheric Aerosol Depth Measurements using Random Forest and Mean Filters. In: IGARSS 2023 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023, Pasadena. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023. p. 3928.

• KARIMZADEH, MORTEZA ; DE LIMA, RAFAEL PIRES . Deep Learning on SAR Imagery: Transfer Learning Versus Randomly Initialized Weights. In: IGARSS 2023 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023, Pasadena. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023. p. 1983.

• DE LIMA, RAFAEL PIRES ; VAHEDI, BEHZAD ; KARIMZADEH, MORTEZA . Comparison of Cross-Entropy, Dice, and Focal Loss for Sea Ice Type Segmentation. In: IGARSS 2023 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023, Pasadena. IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023. p. 145.

• LA MARCA, KARELIA ; BEDLE, HEATHER ; STRIGHT, LISA ; PIRES DE LIMA, RAFAEL ; MARFURT, KURT J. . Quantifying uncertainty in unsupervised machine learning methods for seismic facies using outcrop-derived 3D models and synthetic seismic data. In: Second International Meeting for Applied Geoscience & Energy, 2022, Houston. Second International Meeting for Applied Geoscience & Energy, 2022. p. 1312.

• PIRES DE LIMA, RAFAEL ; FERREIRA, MARCOS ; COSTA, IAGO . A step towards the automatization of predictive geological mapping. In: Second International Meeting for Applied Geoscience & Energy, 2022, Houston. Second International Meeting for Applied Geoscience & Energy, 2022. p. 1437.

• DUARTE-CORONADO, DAVID ; TELLEZ-RODRIGUEZ, JERSON ; PIRES DE LIMA, RAFAEL ; MARFURT, KURT ; SLATT, ROGER . Deep convolutional neural networks as an estimator of porosity in thin-section images for unconventional reservoirs. In: SEG Technical Program Expanded Abstracts 2019, 2019, San Antonio. SEG Technical Program Expanded Abstracts 2019, 2019. p. 3181.

• DE LIMA, RAFAEL PIRES ; LIN, YOUZUO ; MARFURT, KURT J. . Transforming seismic data into pseudo-RGB images to predict CO2 leakage using pre-learned convolutional neural networks weights. In: SEG Technical Program Expanded Abstracts 2019, 2019, San Antonio. SEG Technical Program Expanded Abstracts 2019, 2019. p. 2368.

• DE LIMA, RAFAEL PIRES ; LIN, YOUZUO . Geophysical data integration and machine learning for multi-target leakage estimation in geologic carbon sequestration. In: SEG Technical Program Expanded Abstracts 2019, 2019, San Antonio. SEG Technical Program Expanded Abstracts 2019, 2019. p. 2333.

• PIRES DE LIMA, R. ; MARFURT, K. ; DUARTE, D. ; BONAR, A. . Progress and Challenges in Deep Learning Analysis of Geoscience Images. In: 81st EAGE Conference and Exhibition 2019, 2019, London, 2019.

• SINHA, SAURABH ; DE LIMA, RAFAEL PIRES ; QI, JIE ; INFANTE-PAEZ, LENNON ; MARFURT, KURT . Well-log attributes to map upward-fining and upward-coarsening parasequences. In: SEG Technical Program Expanded Abstracts 2018, 2018, Anaheim. SEG Technical Program Expanded Abstracts 2018. p. 3337.

• DE LIMA, RAFAEL PIRES ; MARFURT, KURT J. . Principal component analysis and K-means analysis of airborne gamma-ray spectrometry surveys. In: SEG Technical Program Expanded Abstracts 2018, 2018, Anaheim. SEG Technical Program Expanded Abstracts 2018. p. 2277.

• DE LIMA, RAFAEL AUGUSTO PIRES ; MARFURT, KURT . Quantifying fault connectivity drilling hazards through simple flow computations. In: SEG Technical Program Expanded Abstracts 2017, 2017, Houston. SEG Technical Program Expanded Abstracts 2017, 2017. p. 2345.

• Yue Chen ; SINHA, SAURABH ; PIRES DE LIMA, RAFAEL ; Yuouzuo Lin . PreMevE: A Machine-Learning Based Predictive Model for Relativistic Electrons inside Earth?s Outer Van Allen Belt. In: AGU Fall Meeting, 2021, New Orleans. AGU Fall Meeting 2021, 2021.

• Yue Chen ; PIRES DE LIMA, RAFAEL ; SINHA, SAURABH ; LIN, YOUZUO . PreMevE: A Machine-Learning Based Predictive Model for MeV Electrons inside Earth?s Outer Radiation Belt. In: EGU General Assembly, 2021, Online. EGU General Assembly 2021, 2021.

• DUARTE, D. ; PIRES DE LIMA, R. ; SLATT, R. ; MARFURT, KURT J. . Comparison of Clustering Techniques to Define Chemofacies: Case Study for Mississippian Rocks in the STACK Play, Oklahoma. In: AAPG Annual Convention and Exhibition, 2019, San Antonio. AAPG Annual Convention and Exhibition, 2019.

• PIRES DE LIMA, R. ; Yue Chen ; Yuouzuo Lin . PreMevE 2.0: Neural Network Based Predictive Model for MeV Electrons in Earth?s Outer Radiation Belt. In: AGU Fall Meeting, 2019, São Francisco, Califórnia, EUA. AGU Fall Meeting, 2019.

• PIRES DE LIMA, RAFAEL ; MARFURT, KURT . Program fault_connectivity 2017 (Documentação de software).

Outras produções

Projetos de pesquisa

• 2010 - 2011

  Medidas de propriedades termofísicas controladas por microcomputador, Descrição: objetivo deste projeto de pesquisa é desenvolver um sistema automático de aquisição de dados para medidas de condutibilidade térmica, de coeficiente de difusão térmica. As medidas de temperatura, tanto no caso de determinações de condutibilidade térmica e de coeficiente de difusão térmica, serão feitas utilizando-se o método da fonte linear de calor. O projeto consiste em construir uma interface para controlar todo o processo de aquisição de dados, desde o acionamento da fonte de calor, coleta da série de medidas de temperatura necessárias para a determinação das duas propriedades térmicas até o cálculo dessas propriedades. O programa de controle da interface também será desenvolvido. , Situação: Concluído; Natureza: Pesquisa. , Alunos envolvidos: Graduação: (2) . , Integrantes: Rafael Augusto Pires de Lima - Integrante / Fernando Brenha Ribeiro - Coordenador / André Defendi Arelaro - Integrante., Financiador(es): Universidade de São Paulo - Bolsa.

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