Broadly speaking, my research interests can be classified into two subcategories: (1) Earthquake source and (2) the Structure. Both of these go hand-in-hand, where understanding of one is impossible without the knowledge of the other.
3D numerical simulations
3D velocity model of southern Alaska (modified from Eberhart-Phillips et. al. 2006) with velocity model of Cook Inlet basin (Shellenbaum et. al. 2010) embedded in it.
References:
Silwal, V., C. Tape, and E. Casarotti, Wavefield Simulation of earthquakes in southern Alaska for tomographic inversion, AGU Fall Meeting 11-15 Dec. 2017, New Orleans
Seismic wavefield simulations within a three-dimensional seismic velocity model for Alaska (in prep)
Silwal, V., 2018, Earthquake source mechanisms and three-dimensional wavefield simulations in Alaska, PhD Thesis
Moment tensor inversions
Earthquakes in general occur on a
fault by shear dislocation, which can be modeled as a double
couple moment tensor. A double couple moment tensor is a 3 × 3
symmetric matrix whose eigenvalues are (λ, 0, −λ). We are
concerned with estimating the magnitude and orientation
(strike, dip, rake) of the moment tensor. Alternative terms
for double couple moment tensors are ‘fault-plane solution’ or
‘focal mechanism.’ Our approach to moment tensor estimation
can also be applied to ‘full’ moment tensors, which contain an
additional two parameters (Alvizuri & Tape (2016)).We perform moment tensor inversion using the ‘cut-and-paste’ (CAP) method of Zhu & Helmberger (1996). The best moment tensor is obtained by minimizing the difference between the data with the synthetics. The synthetics are computed for all possible moment tensors using a 1D reference structural model. Different bandpass filters are applied to the body waves and surface waves when comparing the data with the synthetics.
(left)
Waveform fits between data (black) and synthetics (red)
for an event in Anchorage (2009-04-07). The 'x' marked on
the beachball are the theoretical piercing points of the
emerging ray path to the stations.
(right)
Best depth estimate [centroid depth]. The inverted red
triangle is the best depth estimated by Alaska Earthquake
Center (AEC) using P-arrival times [hypocenter depth].
References:
Silwal, V. and C. Tape, 2016, Seismic moment tensors and estimated uncertainties in southern Alaska, Journal of Geophysical Research: Solid Earth, 121, 2772–2797, doi:10.1002/2015JB012588
Silwal, V., C. Tape, and A. Lomax, 2018, Crustal earthquakes in the Cook Inlet and Susitna region of southern Alaska, Tectonophysics, doi:10.1016/j.tecto.2018.08.013
Alvizuri, C., V. Silwal, L. Krischer, and C. Tape, 2018, Estimation of full moment tensors, including uncertainties, for nuclear explorsions, volcanic events, and earthquakes. Journal of Geophysical Research: Solid Earth, doi: 10.1029/2017jb015325
References:
Silwal, V. and C. Tape, 2016, Seismic moment tensors and estimated uncertainties in southern Alaska, Journal of Geophysical Research: Solid Earth, 121, 2772–2797, doi:10.1002/2015JB012588
Silwal, V., C. Tape, and A. Lomax, 2018, Crustal earthquakes in the Cook Inlet and Susitna region of southern Alaska, Tectonophysics, doi:10.1016/j.tecto.2018.08.013
Alvizuri, C., V. Silwal, L. Krischer, and C. Tape, 2018, Estimation of full moment tensors, including uncertainties, for nuclear explorsions, volcanic events, and earthquakes. Journal of Geophysical Research: Solid Earth, doi: 10.1029/2017jb015325
Event detection using attentive deep learning
We have used an attention-based deep
learning model for automatically detecting events, picking
seismic phases and estimating magnitude. In this study, we
also developed automated selection criteria to filter out
the less reliable detection based on the probability of
detection and picked phases; this saved lots of
computational time when working with sizeable seismic data
sets. Our deep learning based model was applied from January
2013 to October 2013, and we were able locate approximately
4.5 times more earthquakes than those in the ISC catalogue
within a very short time. Magnitude estimation clearly shows
that the attention deep learning model is quite efficient in
detecting low magnitude and recurring events that were not
previously detected by manual picking or other automated
algorithms. Our model enhanced the region’s seismicity and
could map several earthquakes along the neotectonic likely
active faults of western Pamir, which further supports the
western extrusion of Pamir rocks due to the collision of the
Pamir Plateau in the Tajik Depression.
References:
Satyam Pratap Singh, Vipul Silwal*, 2023, Enhanced crustal and intermediate seismicity in the Hindu Kush-Pamir region revealed by attentive deep learning model, Artificial Intelligence in Geosciences, Volume 4, Pages 150-163.
References:
Satyam Pratap Singh, Vipul Silwal*, 2023, Enhanced crustal and intermediate seismicity in the Hindu Kush-Pamir region revealed by attentive deep learning model, Artificial Intelligence in Geosciences, Volume 4, Pages 150-163.
Moment tensor catalog of Alaska and India
For performing a earthquake based tomographic inversion it is important to have reliable source mechanisms. We prepare a moment tensor catalog of >250 events (2007-2017) that are distributed in Alaska.
Undergraduate researchers Qingping Yu and Joshua Purba also contributed to this.
References:
Vipul Silwal, 2018, Seismic moment tensors for six events in Minto Flats fault zone, 2012-2016
Vipul Silwal, 2018, Seismic moment tensor catalog for crustal events in southern Alaska
Vipul Silwal, 2015, Seismic moment tensor catalog for southern Alaska
Vipul Silwal, 2015, Seismic moment tensor catalog for Minto Flats fault zone (2000-2014)
Active fault mapping
Distribution of similar mechanism faulting for earthquakes in a seismic zone can be used as a strong evidence for the presence of a fault(s). This is specially useful when faults are sub-surface or overlain by a layer of sediment as in a basin environment and there is no surface feature.
These studies are generally supplemented with earthquake relocation, gravity and magnetic measurements, and revisit historical catalogs to get a better perspective on tectonics at regional scale.
(right) Consistent thrust faulting mechanism for small-to-intermediate magnitude earthquakes around Cook Inlet and Susitna basin, Alaska.
References:
Tape, C., V. Silwal, C. Ji, L. Keyson, M. E. West, and N. Ruppert, 2015, Transtensional Tectonics of the Minto Flats Fault Zone and Nenana Basin, Central Alaska, Bulletin of the Seismological Society of America, Vol. 105, No. 4, pp. 2081–2100, August 2015, doi: 10.1785/0120150055
Silwal, V., C. Tape, and A. Lomax, Crustal earthquakes in the Cook Inlet and Susitna region of southern Alaska (submitted to Tectonophysics).