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Geophysical data acquisition is currently undergoing a quiet revolution driven by new advances in distributed sensing approaches based on fiber optics, inexpensive nodal systems, and ubiquitous sensors embedded in the Internet of Things. The commonality between these approaches is the capacity to economically conduct ultra-high-density measurements at scales above 1000 sensing locations, providing an unaliased view of seismic wavefields as well as other measurands including strain and temperature. Distributed Fiber Optic Sensing (DxS) and Distributed Acoustic Sensing (DAS) in particular are moving from specialized tools for vertical seismic profiling to broadly utilized approaches deployed in boreholes, on the surface, and now on the seafloor with application domains in seismology, hydrogeology, and oceanography, as well as applied geophysics. With this rapid growth in measurement density have come new challenges in data management and analysis requiring focused development of approaches for identifying patterns and extracting information from these massive datasets, potentially exploiting machine learning methodologies.
This workshop seeks to bring together researchers from industry, academia, and the public sector involved in exploiting these recent sensing advances with the broader geoscience community to explore both the underlying technologies as well as new domains for distributed sensor deployment. The format of the workshop is intended to foster lively discussion and interaction, and includes an evening poster session to facilitate longer debates.