Probabilistic Machine Learning for improved Decision-making with 3-D Geological Models

Florian Wellmann , Miguel de la Varga , Nilgün Güdük , Jan von Harten , Fabian Stamm , Zhouji Liang & s.Mohammad Moulaeifard
Geological models, as 3-D representations of subsurface structures, can be combined with gravity inversions to obtain geometric representations of geological objects with similar porperty distributions. These models are built on prior assumptions and imperfect information, and they often result from an integration of geological and geophysical data types with varying quality. These aspects result in uncertainties about the predicted subsurface structures and property distributions, which will affect the subsequent decision process. We discuss approaches to...
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