Matched Field Processing accounting for complex Earth structure: method and review

Matched Field Processing (MFP) is a technique to locate the source of a recorded wavefield. It is the generalization of plane-wave beamforming, allowing for curved wavefronts. In the standard approach to MFP, simple analytical Green's functions are used as synthetic wavefields that the recorded wavefields are matched against. We introduce an advancement of MFP by utilizing Green's functions computed numerically for Earth structure as synthetic wavefields. This allows in principle to incorporate the full complexity of elastic wave propagation without further manual considerations, and through that provide more precise estimates of the recorded...  more

Matched Field Processing (MFP) is a technique to locate the source of a recorded wavefield. It is the generalization of plane-wave beamforming, allowing for curved wavefronts. In the standard approach to MFP, simple analytical Green's functions are used as synthetic wavefields that the recorded wavefields are matched against. We introduce an advancement of MFP by utilizing Green's functions computed numerically for Earth structure as synthetic wavefields. This allows in principle to incorporate the full complexity of elastic wave propagation without further manual considerations, and through that provide more precise estimates of the recorded wavefield's origin. We call this approach numerical MFP (nMFP). To demonstrate the applicability and potential of nMFP, we present two real data examples, one for an earthquake in Southern California, and one for secondary microseism activity in the Northeastern Atlantic and Mediterranean Sea. In addition, we explore and clarify connections between localisation approaches for the ambient seismic field, real world limitations, and identify key areas for future developments. To increase the adoption of MFP in the seismological community, tutorial code is provided.