Unsupervised Machine Learning for Seismic Facies Classification

Unsupervised Machine Learning for Seismic Facies Classification Applied in Presalt Carbonate Reservoirs of the Búzios Field, Brazil

Seismic data can provide useful information for prospect identification and reservoir characterization. Combining seismic attributes helps identify different patterns, for improved geological characterization. Machine learning applied to seismic interpretation is very useful in assisting with data classification limitations.

This article shows how AspenTech SSE solutions using machine learning technology, were able to differentiate fractured zones associated with build-up facies.

Unsupervised Machine Learning for Seismic Facies Classification Applied in Presalt Carbonate Reservoirs of the Búzios Field, Brazil

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Digital Grid Management

Subsurface Science & Engineering

Unsupervised Machine Learning for Seismic Facies Classification Applied in Presalt Carbonate Reservoirs of the Búzios Field, Brazil

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Unsupervised Machine Learning for Seismic Facies Classification Applied in Presalt Carbonate Reservoirs of the Búzios Field, Brazil

2815841067