Computing a theoretical dispersion curve
This tutorial details all the steps needed to compute a dispersion with gpdc. Another more interactive way to compute dispersion curves is Gplivemodel.
Contents
Creating a model file
Crete a text file (e.g. "test.model"):
# My first model: two layers over a half-space # First line: number of layers 3 # One line per layer: # Thickness(m), Vp (m/s), Vs (m/s) and density (kg/m3) 7.5 500 200 1700 25 1350 210 1900 # Last line is the half-space, its thickness is ignored but the first column is still mandatory 0 2000 1000 2500
All lines beginning with '#' are considered as comments and they are ignored. Several models can be chained in one single file, but no comment line is allowed between layers. Column separators can be either TAB or SPACE. The number of consecutive separators does not matter.
Computing the dispersion curves
To get the dispersion curve of Rayleigh fundamental mode:
gpdc Test.model
You get as output:
# My first model: two layers over a half-space # First line: number of layers # One line per layer: # Thickness(m), Vp (m/s), Vs (m/s) and density (kg/m3) # Last line is the half-space, its thickness is ignored but the first column is still mandatory # 1 Rayleigh dispersion mode(s) # CPU Time = 1 ms # Mode 0 0.2 0.00107875907546066 0.209523150557933 0.00107907141898638 [...] 19.0909691332367 0.00525624231593241 20 0.00526288933387501
To compute Rayleigh higher modes (4 in this case) as well as the fundamental mode:
gpdc Test.model -R 5
To compute Love higher modes (4 in this case) as well as the fundamental mode:
gpdc Test.model -R 0 -L 5
To compute Love modes, you must set explicitly the number of Rayleigh to 0, it is one by default.
Saving the dispersion curves
gpdc Test.model -R 2 > Test_Rayeigh_2modes.disp
Plotting the dispersion curves
We use figue to plot couples of values (X, Y), additionally we provide a make-up file to get the correct type and labeling of axes. Before running the next command you can download Dc.mkup.
gpdc Test.model -R 2 | figue -c -m Dc.mkup
Going further
Help about command line options
To get help about all options:
gpdc -h all
Programming interface
The computation of dispersion is implemented in libQGpCoreWave.so (or equivalent for Windows and Mac). You can access it through various languages: C++, C or Fortran. Complete examples are provided for C and Fortran in the source distribution archive. Download gpdc to have the simplest archive.
A C++ example
#include <QGpCoreWave.h> [...] // 3-layer model initialization LayeredModel model(3); model.h()[0]=7.5; model.h()[1]=25.0; model.slowP()[0]=1.0/500.0; model.slowP()[1]=1.0/1350.0; model.slowP()[2]=1.0/2000.0; model.slowS()[0]=1.0/200.0; model.slowS()[1]=1.0/210.0; model.slowS()[2]=1.0/1000.0; model.rho()[0]=1800; model.rho()[1]=1900; model.rho()[2]=2500; // Initialize frequency sampling, in angular frequency (omega)!! QVector<double> x; x.resize(50); x[0]=...; [...] x[49]=...; // Or use Curve to generate linear or log series Curve<Point1D> c; c.line( minFreq, 0.0, maxFreq, 0.0 ); c.resample( nSamples, minFreq, maxFreq, Log | Function ); c.multiply( 2*M_PI ); // convert to angular frequency QVector<double> x = c.xVector(); // Dispersion computation, fundamental mode only Rayleigh rayleigh( &model ); //Love love( &model ); Dispersion dispersion( 1, &x); dispersion.calculate( modelRayleigh, 0 ); // 0 is to avoid ellipticity computation // Access computed values Curve<Point2D> * dc = dispersion.curve(0); // See Curve header for more information // Or directly, fundamental mode, ith sample value. dispersion.mode(0)[i]
To compile:
g++ [...] -lQGpCoreTools -lQGpCoreWave
Fortran interface
call dispersion_curve_init(verbose) call dispersion_curve_rayleigh(nLayers, h, vp, vs, rho, nSamples, omega, nModes, slowness, group); call dispersion_curve_love(nLayers, h, vp, vs, rho, nSamples, omega, nModes, slowness, group);
| Argument | Type | Description |
|---|---|---|
| verbose | Integer 4 bytes | 0 minimal ouput, 1 verbose output |
| nLayers | Integer 4 bytes | Number of layers |
| h | Vector of floats 8 bytes (nLayers elements) | Thicknesses of layers (m) |
| vp | Vector of floats 8 bytes (nLayers elements) | Vp in each layer (m/s) |
| vs | Vector of floats 8 bytes (nLayers elements) | Vs in each layer (m/s) |
| rho | Vector of floats 8 bytes (nLayers elements) | Density in each layer (kg/m3) |
| nSamples | Integer 4 bytes | Number of frequency samples |
| omega | Vector of floats 8 bytes (nSamples elements) | Angular frequencies (rad/s) |
| nModes, | Integer 4 bytes | Number of modes including fundamental |
| slowness | Vector of floats 8 bytes (nSamples*nModes, elements) | Output of slowness values |
| group | Integer | 0 for phase, 1 for group |
To compile:
gfortran [...] -lQGpCoreTools -lQGpCoreWave
Theoretical considerations
The equations and methods implemented in libQGpCoreWave.so are fully described from a theoretical point of view in Marc Wathelet's PhD thesis (chapter 3).
