This got me thinking about simulating the EQ. A few months ago I set out to learn a bit about the python computer language. In the process I found some remarkable open source codes. The one on point here is fatiando a terra written in 2012 by (then) PhD student Leonardo Uieda. Leo is a research department all on his own.
Anyway, one thing fatiando does is elastic seismic modeling and there is a demo script (seismic_wavefd_elastic_psv.py) in the cookbook. This generates a neat simulation of elastic waves in a crust/moho model and the (x,z) seismic reading from one seismometer. It is a movie, but here is the last frame.
|Fig 1. Default simulation result from fatiando script seismic_wavefd_elastic_psv.py|
You can see all the elements are here to simulate the Cushing EQ, we just need to change a few things. Specifically:
(1) Crust (granite) properties can be localized using a deep well in Osage County, OK that drilled almost 2 km of granite. The params are vp = 5970 m/s, vs = 3500 m/s and density 2650 kg/m^3.
(2) Crust thickness in N Oklahoma and Arkansas is about 45 km thick (reference, figure 7).
(3) The seismometer should at Fayetteville, 240 km from the EQ.
(4) Since all the action in Fayetteville is over by 85 seconds, limit the simulation to 100 sec.
With these edits and running the python script now gives the Cushing EQ as felt in Fayetteville AR case. Very cool. Thank you Leo.
|Fig 2. Simulation result for 7 Nov 2016 Cushing EQ as felt at Fayetteville AR.|