Field data inversion (“Koenigsee”)¶

This minimalistic example shows how the Refraction Manager can be used to invert a field data set. Here, we consider the Koenigsee data set, which represents classical refraction seismics data set with slightly heterogeneous overburden and some high-velocity bedrock. The data file can be found in the pyGIMLi example data repository.

We import pyGIMLi and the refraction manager.

import pygimli as pg
from pygimli.physics import Refraction


The helper function pg.getExampleFile downloads the data set and saves it into a temporary location.

filename = pg.getExampleFile("traveltime/koenigsee.sgt")


We initialize an instance of the refraction manager with the filename.

ra = Refraction(filename)
print(ra)


Out:

Data: Sensors: 63 data: 714
Refraction object
Data: Sensors: 63 data: 714
None


Let’s have a look at the data in the form of traveltime curves and apparent velocity images.

ra.showData()  # show first arrivals as curves (done later with response)
ra.showVA()  # show data as apparent velocity image


Out:

(<matplotlib.axes._subplots.AxesSubplot object at 0x7f8803d559b0>, <matplotlib.colorbar.Colorbar object at 0x7f8818c04fd0>)


Finally, we call the invert method and plot the result.The mesh is created based on the sensor positions on-the-fly. Yes, it is really as simple as that.

ra.invert(zWeight=0.2)
ra.showResult()


Out:

(<matplotlib.axes._subplots.AxesSubplot object at 0x7f8803c96208>, <matplotlib.colorbar.Colorbar object at 0x7f880805beb8>)


You can play around with the gradient starting model (vtop and vbottom arguments) and the regularization strength lam. You can also customize the mesh by calling ra.createMesh() with options of your choice prior to the inversion call.

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Created using Bootstrap, Sphinx and pyGIMLi 1.0.12+20.g65e71e67 on Mar 10, 2020.