Bayesian seismic tomography based on velocity-space Stein variational gradient descent for physics-informed neural network

In this study, we propose a Bayesian seismic tomography inference method using physics-informed neural networks (PINN). PINN represents a recent advance in deep learning, offering the possibility to enhance physics-based simulations and inverse analyses. PINN-based deterministic seismic tomography uses two separate neural networks (NNs) to predict seismic velocity and travel time. Naive Bayesian NN (BNN) approaches are unable to handle the high-dimensional spaces spanned by the weight parameters of these two NNs. Hence, we reformulate the problem to perform the Bayesian estimation exclusively on the NN predicting seismic velocity, while the NN predicting travel time is used only for deterministic travel time calculations, with the help of the adjoint method. Furthermore, we perform BNN by introducing a function-space Stein variational gradient descent (SVGD), which performs particle-based variational inference in the space of the function predicted by the NN (i.e., seismic velocity), instead of in the traditional weight space. The result is a velocity-space SVGD for the PINN-based seismic tomography model (vSVGD-PINN-ST) that decreases the complexity of the problem thus enabling a more accurate and physically consistent Bayesian estimation, as confirmed by synthetic tests in one- and two-dimensional tomographic problem settings. The method allows PINN to be applied to Bayesian seismic tomography practically for the first time. Not only that, it can be a powerful tool not only for geophysical but also for general PINN-based Bayesian estimation problems associated with compatible NNs formulations and similar, or reduced, complexity

Deep Investigations of Outer-Rise Tsunami Characteristics Using Well-Mapped Normal Faults Along the Japan Trench

To assess the risk of tsunamis from outer-rise earthquakes, we carried out tsunami simulations using 33 simple rectangular fault models with 60° dip angles based on marine seismic observations and surveys of the Japan Trench. The largest tsunami resulting from these models, produced by a Mw 8.7 normal-faulting event on a fault 332 km long, had a maximum height of 27.0 m. We tested variations of the predictions due to the uncertainties in the assumed parameters. Because the actual dip angles of the Japan Trench outer-rise faults range from 45° to 75°, we calculated tsunamis from earthquakes on fault models with 45°, 60°, and 75° dip angles. We also tested a compound fault model with 75° dip in the upper half and 45° dip in the lower half. Rake angles were varied by ±15°. We also tested models consisting of small subfaults with dimensions of about 60 km, models using other earthquake scaling laws, models with heterogeneous slips, and models incorporating dispersive tsunami effects. Predicted tsunami heights changed by 10–15% for heterogeneous slips, up to 10% for varying dip angles, about 5–10% from considering tsunami dispersion, about 2% from varying rake angles, and about 1% from using the model with small subfaults. The use of different earthquake scaling laws changed predicted tsunami heights by about 50% on average for the 33 fault models. We emphasize that the earthquake scaling law used in tsunami predictions for outer-rise earthquakes should be chosen with great care

Spatial variations of incoming sediments at the northeastern Japan arc and their implications for megathrust earthquakes

The nature of incoming sediments is a key controlling factor for the occurrence of megathrust earthquakes in subduction zones. In the 2011 Mw 9 Tohoku earthquake (offshore Japan), smectite-rich clay minerals transported by the subducting oceanic plate played a critical role in the development of giant interplate coseismic slip near the trench. Recently, we conducted intensive controlled-source seismic surveys at the northwestern part of the Pacific plate to investigate the nature of the incoming oceanic plate. Our seismic reflection data reveal that the thickness of the sediment layer between the seafloor and the acoustic basement is a few hundred meters in most areas, but there are a few areas where the sediments appear to be extremely thin. Our wide-angle seismic data suggest that the acoustic basement in these thin-sediment areas is not the top of the oceanic crust, but instead a magmatic intrusion within the sediments associated with recent volcanic activity. This means that the lower part of the sediments, including the smectite-rich pelagic red-brown clay layer, has been heavily disturbed and thermally metamorphosed in these places. The giant coseismic slip of the 2011 Tohoku earthquake stopped in the vicinity of a thin-sediment area that is just beginning to subduct. Based on these observations, we propose that post-spreading volcanic activity on the oceanic plate prior to subduction is a factor that can shape the size and distribution of interplate earthquakes after subduction through its disturbance and thermal metamorphism of the local sediment layer

モホ反射面のつくりかた

日本地質学会第125年学術大会（つくば特別大会 / 2018年12月1～2日 産業技術総合研究所

R/V Kairei Cruise Report KR19-07

調査海域: 北海道南東沖 / Area: Kuril Trench ; 期間: 2019年8月26日～2019年9月15日 / Operation Period: August 26, 2019～September 15, 2019http://www.godac.jamstec.go.jp/darwin/cruise/kairei/kr19-07/

R/V Kaimei Cruise Report KM18-06

調査海域: 日本海溝 / Area: Japan Trench ; 期間: 2018年6月26日～2018年7月19日 / Operation Period: June 26, 2018～July 19, 2018http://www.godac.jamstec.go.jp/darwin/cruise/kaimei/km18-06/

Cruise Report of KR07-10

調査海域: 南海トラフ / Area: Nankai Trough ; 期間: 2007年7月26日～2007年8月16日 / Operation Period: July 26, 2007～August 16, 2007http://www.godac.jamstec.go.jp/darwin/cruise/kairei/kr07-10/