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.
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.
(<matplotlib.axes._subplots.AxesSubplot object at 0x7f40fcbb9e80>, <matplotlib.colorbar.Colorbar object at 0x7f40f5a62c50>)
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.
(<matplotlib.axes._subplots.AxesSubplot object at 0x7f40fc139470>, <matplotlib.colorbar.Colorbar object at 0x7f40fcbe3ac8>)
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.