Toward Global Regional Seismic Moment Tensor Inversion with Three-Dimensional Earth Models for Nuclear Explosion Monitoring with Sparse Networks: Demonstration of Reciprocity for Strain Greens Tensor Database Simulation with Salvus

Technical Report · Fri Oct 06 00:00:00 EDT 2023

DOI:https://doi.org/10.2172/2007591· OSTI ID:2007591

Rodgers, Arthur ^[1]; Krischer, Lion ^[2]; Afanasiev, Michael ^[2]; Boehm, Christian ^[3]; Doody, Claire ^[4]

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1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Eidgenoessische Technische Hochschule (ETH), Zurich (Switzerland)
2. Mondiac Ltd., Zurich (Switzerland)
3. Eidgenoessische Technische Hochschule (ETH), Zurich (Switzerland); Mondiac Ltd., Zurich (Switzerland)
4. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Seismic source characterization is an essential function of global nuclear explosion monitoring (NEM). While large events (roughly with moment magnitude, M_w, greater than 5.0) can often be easily detected, located and identified with high signal-to-noise ratios at teleseismic distances (> 20°), trends in NEM research require confident source characterization at much lower magnitudes (say down to 3.0) and exploitation of sparse observations (from only a few stations) at regional distance (< 20°). Regional distance waveform inversion to characterize sources is now widely used and effective (e.g. Ford et al., 2009; Alvizuri and Tape, 2018; Alvizuri et al., 2018; Chiang et al., 2018; Ford et al., 2022). These methods obtain the magnitude, depth and seismic moment tensor, which represents the forces that excited the observed seismic waves (slip on an earthquake fault, explosion, collapse or a combination of various forces). Common to many problems in seismology, the isolation of the source 2 properties requires removal of path propagation effects that waves experience while traveling through the three-dimensional (3D) Earth (the structure exists due to different rock types, material properties, temperature and tectonic processes).

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC52-07NA27344
• OSTI ID: 2007591
• Report Number(s): LLNL-TR-855543; 1084544
• Country of Publication: United States
• Language: English

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