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Cleyton Carneiro

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Associate Professor

University of Sao Paulo

Brazil

Research Interests

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Professors in Geochemistry

Recent Grants

Grant: Close

Geologia e metalogenia do ouro na Província Aurífera do Tapajós na região de Itaituba (pa): abordagem baseada em imagens aerogeofísicas magnetométricas e gamaespectrométricas

Open Date: 2010-10-01

Close Date: 2013-09-01

Grant: Close

Modelagem espacial de dados geológicos, aerogeofísicos e SAR na identificação de áreas favoráveis a mineralizações na região de Anapu-Tuerê, Pará

Open Date: 2006-09-01

Close Date: 2010-06-01

Grant: Close

Análise dos elementos estruturais que compõem a falha Carajás a partir da interpretação de imagens de sensores remotos

Open Date: 2003-03-01

Close Date: 2005-02-01

Articles (18)

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Professor

University of Sao Paulo

BRAZIL

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Cleyton Carneiro

Research Interests

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Recent Grants

Articles (18)

Image logs classification with convolutional neural networks: A strategic preprocessing routine for obtaining carbonate and volcanic image facies models

Borehole Logging Lithological Classification in Carbonatite‐Hosted Niobium Deposit Integrating Geophysical and Geochemical Data With Self‐Organizing Maps

Mineral prospective mapping for Zn-Pb-Cu-(Ag-Au) through machine learning in the Camaqua Basin, Southern Brazil

Mineral Prospectivity Maps for Critical Metals in the Clean Energy Transition: Examples for Hydrothermal Copper and Nickel Systems in the Carajás Province

Enhanced Gold Ore Classification: A Comparative Analysis of Machine Learning Techniques with Textural and Chemical Data

Investigating formation water variability in the Búzios oilfield (Santos Basin) using cluster analysis and hydrogeochemical modeling

Global enhanced oil recovery assessment: A comprehensive data-driven analysis asing self-organizing maps

Predicting gold accessibility from mineralogical characterization using machine learning algorithms

Model selection for dynamic interfacial tension of dead crude oil/brine to estimate pressure and temperature effects on the equilibrium tension

Enhancing wireline formation testing with explainable machine learning: Predicting effective and non-effective stations

Electrofacies clustering and classification from the Ariri Formation in Santos Basin (southeastern offshore Brazil) involving unsupervised learning algorithms

IntraSOM: A comprehensive Python library for Self-Organizing Maps with hexagonal toroidal maps training and missing data handling

Hybrid mineral model integrating probabilistic and machine learning approaches for the Brazilian pre‐salt carbonate reservoirs

Self-Organizing Maps Analysis of Chemical–Mineralogical Gold Ore Characterization in Support of Geometallurgy

Carbonate lithofacies classification in optical microscopy: a data-centric approach using augmentation and GAN synthetic images

Imputation of Gold Recovery Data from Low Grade Gold Ore Using Artificial Neural Network

Prediction of nuclear magnetic resonance porosity well-logs in a carbonate reservoir using supervised machine learning models

Synthetic Slowness Shear Well-Log Prediction Using Supervised Machine Learning Models

Collaborators (5)

Jean Vicente Ferrari

Rafael Gioria

Lena Monteiro

Marco Antonio Couto Jr

Carina Ulsen

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