Abstract
Land seismic acquisition is moving toward “light and dense” geometries, with point receiver systems believed to be an ultimate configuration of choice. Cableless land nodal systems enable more flexible spatial sampling at the price of eliminating even small arrays. For large surveys in a desert environment, such spacing remains insufficient to address the complex near surface, while recordings with single sensors exhibit a significant reduction in data quality. At the same time, exploration problems increasingly demand smaller uncertainty in all seismic products. While 1 m geophone sampling could have addressed these problems, it remains out of economic reach as point sensor cost plateaus. We examine an emerging alternative technology of distributed acoustic sensing (DAS) that revolutionized borehole geophysics but is still mostly unknown in the seismic world. Fully broadband DAS sensors promise massive channel count and uncompromised inline sampling down to 0.25 m. Their distributed nature offers the unique capability to conduct a continuous recording with multiscale grids of “shallow,” “deep,” and “full-waveform inversion” receivers, all implemented with a single set of fixed cables and only one round of shooting. These distinct features allow us to simultaneously pursue near-surface characterization, imaging of deeper targets, and velocity model evaluation. Specifically, in a desert environment, distributed sensors may offer superior data quality compared to point sensors, whereas DAS capability of “seismic zoom” in the near surface becomes instrumental for near-surface characterization. Finally, simultaneous acquisition of surface seismic and vertical arrays that can be achieved easily with DAS can effectively address the exploration of subtler targets such as low-relief structures. We support these findings with a field case study from a desert environment and synthetic examples. With many distinct advantages, surface seismic with DAS emerges as a compelling alternative to modern point-sensor acquisitions.
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