A Promptable Foundation Model for Unified and Zero-Shot Subsurface Understanding

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a summary:Understanding the Earth under the surface of the earth is very important to transmit energy, mitigate natural risks, and planetary science. However, under the surface analysis remains fragmented, with separate models of structural interpretation, class analysis, geological body retail, and property modeling-tightly associated with specific data distributions and task compositions. We offer GeoGical Model 3D (GEM), a uniform generic structure that reformulates all these tasks as an air -conditioned inference along the underlying structural frameworks derived from sub -surface photography. This formula moves beyond models for the task by enabling the joint inference mechanism, as GEM publishes the claims provided by man as well as records, masks or structural drawings-relying on a conclusive production of geological coherent outputs. Through this mechanism, GEM achieves a zero circular through tasks with fast, heterogeneous types, without re -training on new tasks or data sources. This ability arises from a two -stage training process that combines learning of representation subject to overseeing wide -range field seismic data with aggressive polishing using mixed claims and signs through the various surface tasks. GEM explains the extensive application via investigative studies and tasks, including the analysis of the Mars radar layer, the structural interpretation in the areas of spread, the complete seismic class interpretation, the geographical body retail, and the modeling of the property. By bridging expert knowledge with obstetric thinking in a structurally perceived manner, GEM lay the basis for the transmission of AI-AI-Anrasition, which is developed and human on the developmental geophysical lines from the segmented pipelines to the vertically integrated thinking system. Project page: URL https