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This is a Quantitative Study study.

October 23, 2025OTC Brasil

Data-Driven Deep-Learning Forecasting for Gas Export by FPSO: A Brazilian Pre-Salt Case

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Enhanced forecasting accuracy achieved using deep-learning models compared to baseline methods.
A significant average improvement of up to 10% in forecasting error was noted in gas export predictions.
The approach utilized neural networks with data normalization for improved model stability and accuracy.
Advanced AI techniques address issues related to data drift, aiding practical applications in production environments.

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Implication

Analysis demonstrates improved forecasting accuracy in gas export, using AI and data normalization techniques, suggesting enhanced decision-making for production forecasts.

Cite This Study

Linares et al. (2025) studied this question.

synapsesocial.com/papers/68f9a0eb8ea8f2f37ee94d9b https://doi.org/10.4043/36280-ms

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Implication

Analysis demonstrates improved forecasting accuracy in gas export, using AI and data normalization techniques, suggesting enhanced decision-making for production forecasts.

Data-Driven Deep-Learning Forecasting for Gas Export by FPSO: A Brazilian Pre-Salt Case

Key Points

Discussion

Implication

Cite This Study

Data-Driven Deep-Learning Forecasting for Gas Export by FPSO: A Brazilian Pre-Salt Case

Key Points

Discussion

Implication

Cite This Study

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