AI Fault Prediction Results for Ultra-Deepwater OBN Seismic Data in Santos Basin

An AI-driven fault prediction framework applied to Ocean Bottom Node seismic data from the Santos Basin's pre-salt carbonate reservoirs. The dataset was authored by Siwen Wang and last updated on May 11, 2026. It demonstrates a workflow that reduces structural interpretation cycles from months to hours.

Use Cases

• Benchmark AI fault detection models based on the described structure-oriented filtering and HR-Net framework.
• Validate automated 3D fault model generation workflows based on the described progressive post-processing steps.
• Analyze fault geometries in carbonate reservoirs based on the described Y-shaped fault resolution.
• Compare seismic interpretation methods based on the described performance against traditional towed-streamer systems.

Strengths

• The dataset is associated with a specific, described application in the Santos Basin's pre-salt carbonate reservoirs.
• The described methodology includes a multi-step AI and post-processing workflow for fault model generation.
• The dataset is licensed under CC-BY-4.0, allowing for open sharing and modification.

Limitations

• The dataset is very small at 12.6 KB, suggesting limited scope or summary-level results.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for training machine learning models.

Provenance

Source

figshare

Collection Method

Likely contains results from an AI-driven fault prediction framework applied to processed seismic data.

Freshness

Last updated 2026-05-11 05:24:41; freshness should be verified.

Geography

Santos Basin