Matched Field Processing (MFP) is a technique to locate the source of a recorded wave field. It is the generalization of beamforming, allowing for curved wavefronts. In the standard approach to MFP, simple analytical Green's functions are used as synthetic wave fields that the recorded wave fields are matched against. We introduce an advancement of MFP by utilizing Green's functions computed numerically for real Earth structure as synthetic wave fields. This allows in principle to incorporate the full complexity of elastic wave propagation, and through that provide more precise estimates of the recorded wave field's origin.

This repository acts as the development platform for this approach.

A manuscript describing the method in detail is available as a pre-print at EarthArXiv doi.org/10.31223/X5492H and submitted to Geophysical Journal International for peer review. A separate repository contains the information (what data was used, settings files, figure scripts) to reproduce the results we present in our manuscript: seismology-hamburg/schippkus_hadziioannou_2022.

• Install requirements
• Download or clone the repository
• Configure settings.yml in ./code/
• python logic.py in ./code/

• python 3.8+
• obspy to read seismic data
• cartopy to plot maps
• tqdm to get progressbars
• pyyaml to parse the settings.yml
• instaseis to read the Green's function database
• local green's function database readable by instaseis, e.g., downloaded from syngine
• global_land_mask for fast checks whether cells are on land