Abstract
This paper describes a unified automated pipeline for first break picking and acquisition geometry control with deep learning models. It consists of three global stages, which require minimal human intervention and can be fine-tuned for new surveys to further increase the quality of the result. Evaluation of this pipeline on the ongoing projects showed that it significantly sped up both tasks, while the quality of the result was on par with the traditional procedures, performed mostly manually.
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