The NEPOS Project: Near-Surface Seismic Exploration of Planetary Bodies with Adaptive Networks

Ground motion observations on planetary objects are a prerequisite for a detailed understanding of their interior structure and evolution. The imaging of the near surface structure - in particular on the Moon - has strong practical implications. First, the race is on to detect ice-bearing rocks near the surface from which water could be extracted and used as a resource for crewed missions. Second, due to the substantial bombardment of the lunar surface with meteorites and the lack of an atmosphere, observatories or habitats may have to be built underground. It has been proposed that cavities from ancient lava flows below the lunar surface could be used to place infrastructure. Current mission plans for geophysical exploration focus on static seismic sensors/arrays that would be restricted to the area they can explore. With the NEPOS project we want to go beyond these restrictions and develop concepts for mobile seismic arrays that work in an autonomous way using robotic technology. The scientific challenges include the understanding of wavefield effects of icy rocks and caves in a strongly scattering environment, the provision of optimal source-receiver configurations to detect them, as well as an integrated data-processing workflow from observation to subsurface image including the quantification of uncertainties. In order to solve these challenges, we first developed a Digital Twin for wave propagation in the strongly heterogeneous lunar crust to generate synthetic seismic data using the spectral element code SALVUS. We compared the synthetic seismograms to data from the Apollo 17 Lunar Seismic Profiling Experiment (LPSE) and find that their main characteristics coincide. We further generated synthetic seismograms for a variety of network configurations and subsurface heterogeneities, which will be used to test appropriate imaging methods for the lunar subsurface structure. Due to the presence of strongly scattering media ambient noise tomography seems to be a promising method, as was already shown in previous studies. We apply seismic interferometry to LPSE data, as well as to our synthetic seismograms, to reconstruct Greens functions, which give us information on the subsurface properties.