Oil Well Prediction Tools Using Deep Learning

Deep Learn Oil is a collection of deep learning tools for predicting oil well data, created by akashlevy. The repository is associated with Harvard and was last updated in September 2021. Specific dataset details like row count and features are not provided.

Use Cases

• Predicting oil well production rates using historical well data and operational features.
• Classifying well performance categories from geological and engineering parameters.
• Forecasting equipment failure or maintenance needs from time-series sensor data.
• Estimating reservoir properties from well log measurements using neural networks.

Strengths

• Repository is associated with Harvard, suggesting an academic or research context.
• Tools are built with established deep learning frameworks like Keras.

Limitations

• No dataset size, specific features, or sample data are available for evaluation.
• The tools and any associated data were last updated in 2021, which may limit applicability to current methods.

Provenance

Source

GitHub repository by author akashlevy.

Collection Method

Developed as deep learning tools for oil well data prediction; specific data gathering method is unknown.

Freshness

Last updated 2021-09-29.