A multi-attribute seismic ML uncertainty assessment for geoscientists
Multi-attribute seismic machine learning gives us remarkable new ways to interrogate seismic data. The outputs can be stunning. Facies boundaries appear in minutes. Waveform patterns nobody noticed suddenly organize into what looks like coherent geology.
But here is what we've learned at AASPI these methods find patterns in whatever you give them. Feed them acquisition footprint and they will cluster your footprint beautifully. Give them unnormalized attributes and the result reflects data scaling, not geology. Skip the despiking step and one bad trace pulls a cluster center to the wrong place. Run a SOM on a full volume when you care about a 50ms window and the method spends most of its effort distinguishing water column from basement.
None of these are software problems. They are workflow problems. And they are extremely common - in student projects, in industry practice, and in published research - regardless of what software produced the result. A good interpretation is one you can explain and defend. The tool that generated it is secondary.
"The algorithm found exactly what you gave it. The question is whether what you gave it was geology."
- the whole point of this questionnaire!!!This tool was developed at AASPI (Attribute Assisted Seismic Processing and Interpretation) at the University of Oklahoma — a research group whose philosophy has always been to understand what the data is telling us, not just to produce a result. This questionnaire is that philosophy in checklist form. It is designed to work with any multi-attribute seismic ML software or workflow. The questions apply whether you wrote the code yourself, used a commercial platform, or anything in between.
At the end you get two uncertainty matrices - one for your data and attribute quality, one for your method rigor and geologic validation - plus specific, actionable recommendations for every gap the questionnaire finds.
Methods covered:
Version 1.0 - 2025. Covers unsupervised volumetric classification and dimension reduction. Works with any multi-attribute seismic ML software or workflow. Supervised methods coming in a future version. Your answers are never stored or transmitted.