Technological evolution from conventional point sensors to distributed acoustic sensing (DAS): a comparative review

Seismic surveying has continuously evolved, transitioning from early mechanical seismoscopes to digital, multi-channel geophone arrays that defined the industry standard since 1970s. digital seismic reflection. Today, the field is undergoing a similar shift, with conventional inertial-based systems being challenged or complemented by Distributed Acoustic Sensing (DAS) systems. This paper examines the two primary seismic systems, such as geophones/accelerometers and DAS systems by focusing on their core principle and transduction systems. Methodologically, we employ a comparative performance framework based on key metrics including sensitivity, calibration, data volume, and spatiotemporal. Furthermore, a systematic review of experimental field trials from 2010 to 2025 is conducted across eight major seismic applications to ascertain practical differences. Results reveal that while traditional sensors excel in low-frequency sensitivity and discrete three-component recording, DAS offers superior spatiotemporal resolution and broadband frequency capabilities. Recent advancements in enhanced backscattering fibers (20 m gauge length) have demonstrated the potential to lower the noise floor of DAS systems to approximately 0. 15 p / Hz, significantly improving sensitivity to high-fidelity microseismic events. Field trial analysis shows heavy concentration of hybrid applications in borehole imaging, with emerging but limited use in environmental sensing, mineral exploration, and pipeline security. We also explore the potential of integrated sensing and quantum networks (ISAQN) to mitigate current signal-to-noise limitations. The study concludes that future of seismic acquisition depends on the continuous integration of these technologies via hybrid systems, leveraging the robust compartments of traditional sensors along the extensive coverage of DAS to overcome their respective uniaxial, low-frequency, and spatiotemporal limitations.