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M A Sampaio

Professor

University of Sao Paulo

Brazil

Research Interests

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Professors in Hydrology

Articles (16)

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2026

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2026

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2026

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2026

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2026

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2025

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2025

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2025

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

Collaborators (5)

Rafael Gioria

Assistant Professor

University of Sao Paulo

BRAZIL

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Martin Blunt

Professor of Flow in Porous Media

Imperial College London

UNITED KINGDOM

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Xiaodong Luo

NORCE Norwegian Research Centre

NORWAY

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Eduardo Gildin

UNITED STATES

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Daniel Vieira

Professor

University of Sao Paulo

BRAZIL

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M A Sampaio

Research Interests

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Articles (16)

Enhancing the parameterization of reservoir properties for data assimilation using deep VAE-GAN

Ensemble-Based Assimilation of Pressure Transient Test Data

Covariance scaling: Theory, extension, and applications to ensemble-based history matching

Hybrid forecasting of oil and water production using long short‑term memory networks guided by reservoir simulation outputs

Hybrid Physics-Data-Driven Approach for Pressure Estimation in CO2-Rich Gas Injection Operations

Machine Learning-Based Virtual Sensor for Bottom-Hole Pressure Estimation in Petroleum Wells

Exploring the Synergy of Gas-Integrated Technologies in the B&#250;zios Pre-Salt Field: A Case Study for a Pioneering Strategy in Early Monetization of Deep-Water Offshore Gas

Reservoir characterization based on data incorporation throughout production development

Optimizing CO2 trapping in saline aquifers under geological uncertainty: A case study of the Rio Bonito Formation, Brazil

A Transformer-based approach for anomaly detection in intelligent well completions

Integration between experimental investigation and numerical simulation of alkaline surfactant foam flooding in carbonate reservoirs

A review of carbon storage in saline aquifers: Mechanisms, prerequisites, and key considerations

Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models

Unsupervised machine learning model for predicting anomalies in subsurface safety valves and application in offshore wells during oil production

A System to Detect Oilwell Anomalies Using Deep Learning and Decision Diagram Dual Approach

Hybrid Machine Learning for Modeling the Relative Permeability Changes in Carbonate Reservoirs under Engineered Water Injection

Collaborators (5)

Rafael Gioria

Martin Blunt

Xiaodong Luo

Eduardo Gildin

Daniel Vieira

Make your next move.

M A Sampaio

Research Interests

Make your next move.

Explore related searches

Articles (16)

Enhancing the parameterization of reservoir properties for data assimilation using deep VAE-GAN

Ensemble-Based Assimilation of Pressure Transient Test Data

Covariance scaling: Theory, extension, and applications to ensemble-based history matching

Hybrid forecasting of oil and water production using long short‑term memory networks guided by reservoir simulation outputs

Hybrid Physics-Data-Driven Approach for Pressure Estimation in CO2-Rich Gas Injection Operations

Machine Learning-Based Virtual Sensor for Bottom-Hole Pressure Estimation in Petroleum Wells

Exploring the Synergy of Gas-Integrated Technologies in the B&amp;#250;zios Pre-Salt Field: A Case Study for a Pioneering Strategy in Early Monetization of Deep-Water Offshore Gas

Reservoir characterization based on data incorporation throughout production development

Optimizing CO2 trapping in saline aquifers under geological uncertainty: A case study of the Rio Bonito Formation, Brazil

A Transformer-based approach for anomaly detection in intelligent well completions

Integration between experimental investigation and numerical simulation of alkaline surfactant foam flooding in carbonate reservoirs

A review of carbon storage in saline aquifers: Mechanisms, prerequisites, and key considerations

Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models

Unsupervised machine learning model for predicting anomalies in subsurface safety valves and application in offshore wells during oil production

A System to Detect Oilwell Anomalies Using Deep Learning and Decision Diagram Dual Approach

Hybrid Machine Learning for Modeling the Relative Permeability Changes in Carbonate Reservoirs under Engineered Water Injection

Collaborators (5)

Rafael Gioria

Martin Blunt

Xiaodong Luo

Eduardo Gildin

Daniel Vieira

Make your next move.

Exploring the Synergy of Gas-Integrated Technologies in the Búzios Pre-Salt Field: A Case Study for a Pioneering Strategy in Early Monetization of Deep-Water Offshore Gas