Interactive data processing and analysis tool to compute the Curie point depth from aeromagnetic data using the method of Bouligand et al. (2009)
The user interface is really a work in progress for now. More to come soon.
pycpd is programmed in python 3 and was tested on a mac running python 3.8 installed via macports.
The following python modules are needed to run the software
- numpy and scipy
- pandas
- PyQt5
- cartopy (https://scitools.org.uk/cartopy/docs/latest/)
- netCDF4 (https://github.com/Unidata/netcdf4-python)
- pyproj (https://github.com/jswhit/pyproj)
- pyfftw (https://pypi.python.org/pypi/pyFFTW)
- spectrum (http://www.thomas-cokelaer.info/software/spectrum/html/contents.html)
- GDAL (https://gdal.org)
Run the following command in the source directory in order to use the maximum entropy method to estimate the spectra (c code wrapped with cython)
python setup.py build_ext --inplace
Examples can be found in the data directory.
- Aeromagnetic data should be gridded on a cartesian grid with spatial units in meters
- Recognized formats are:
- netCDF (COARDS compliant)
- USGS sgd grid
- Formats recognized by GDAL (not fully tested)
- In order to display the map, the user is asked to enter coordinate projection information. This is done by giving a proj4 string (http://proj4.org), e.g. for coordinates projected in the Lambert conic conformal for Eastern Canada, the string is
proj=lcc lat_1=49 lat_2=77 lat_0=63 lon_0=-92 x_0=0 y_0=0 ellps=GRS80 towgs84=0,0,0,0,0,0,0 units=m no_defs
- Alternatively, coordinate projection information can be retrieved by the GDAL driver if they are contained in the data file.
Borehole data should be in a csv file with the same header as given in the Global Heat Flow Database of the International Heat Flow Commission (http://www.heatflow.und.edu/index2.html). An example file can be found at http://www.heatflow.und.edu/Global2010.csv. The first lines of this file are:
Data Number,Codes,Site Name,Latitude,Longitude,Elevation,minD,maxD,No. Temps,Gradient,No. Cond.,Conductivity,No.Heat Prod.,Heat Prod.,Heat Flow,No. sites,Year of Pub.,Reference,Comments,,
1,,SMU-KG2,44.4637,-111.7322,1987,28,66,,81,2,1.88,,,,,1983,Brott_etal1983,Williams_etal1995,,
2,,SMU-SP3,44.3278,-112.2128,1795,10,99,,55,5,2.06,,,,,1983,Brott_etal1983,Brott_etal1983,,
3,,SMU-SP2,44.3678,-112.1432,1859,25,70,,46,5,1.67,,,,,1983,Brott_etal1983,Brott_etal1983,,
The script mk_db.py can be used to extract the heat flow data for the area corresponding to your aeromagnetic data grid, and store it in a python shelf that pycpd understands.
@Article{bouligand09,
Title = {Mapping {C}urie temperature depth in the western {U}nited {S}tates with a fractal model for crustal magnetization},
Author = {Bouligand, Claire and Glen, Jonathan M. G. and Blakely, Richard J.},
Journal = {Journal of Geophysical Research: Solid Earth},
Year = {2009},
Month = nov,
Number = {B11},
Pages = {B11104--},
Volume = {114},
DOI = {10.1029/2009JB006494},
ISSN = {0148-0227},
Keywords = {aeromagnetic compilation, Curie temperature isotherm, western United States, Great Basin, 1517 Geomagnetism and Paleomagnetism: Magnetic anomalies: modeling and interpretation, 3255 Mathematical Geophysics: Spectral analysis, 4440 Nonlinear Geophysics: Fractals and multifractals, 5418 Planetary Sciences: Solid Surface Planets: Heat flow, 0903 Exploration Geophysics: Computational methods: potential fields, geothermie},
Owner = {giroux},
Publisher = {AGU},
Timestamp = {2012.05.02},
URL = {http://dx.doi.org/10.1029/2009JB006494}
}