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# GravMag: Use an equivalent layer to upward continue gravity dataΒΆ

Download source code: gravmag_eqlayer_upcontinue.py

"""
GravMag: Use an equivalent layer to upward continue gravity data
"""
from fatiando.gravmag import prism, sphere
from fatiando.gravmag.eqlayer import EQLGravity
from fatiando.inversion import Damping
from fatiando import gridder, utils, mesher
from fatiando.vis import mpl

# Make synthetic data
props = {'density': 1000}
model = [mesher.Prism(-500, 500, -1000, 1000, 500, 4000, props)]
shape = (25, 25)
x, y, z = gridder.regular([-5000, 5000, -5000, 5000], shape, z=0)
gz = utils.contaminate(prism.gz(x, y, z, model), 0.1, seed=0)
# Setup the layer
layer = mesher.PointGrid([-6000, 6000, -6000, 6000], 1000, (50, 50))
# Estimate the density
# Need to apply enough damping so that won't try to fit the error as well
solver = EQLGravity(x, y, z, gz, layer) + 1e-22*Damping(layer.size)
solver.fit()
residuals = solver[0].residuals()
print("Residuals:")
print("mean:", residuals.mean())
print("stddev:", residuals.std())

# Now I can forward model the layer at a greater height and check against the
# true solution of the prism
gz_true = prism.gz(x, y, z - 500, model)
gz_up = sphere.gz(x, y, z - 500, layer)

mpl.figure(figsize=(14, 4))
mpl.subplot(1, 3, 1)
mpl.axis('scaled')
mpl.title('Layer (kg.m^-3)')
mpl.pcolor(layer.y, layer.x, layer.props['density'], layer.shape)
mpl.colorbar()
mpl.m2km()
mpl.subplot(1, 3, 2)
mpl.axis('scaled')
mpl.title('Fit (mGal)')
levels = mpl.contour(y, x, gz, shape, 15, color='r')
mpl.contour(y, x, solver[0].predicted(), shape, levels, color='k')
mpl.m2km()
mpl.subplot(1, 3, 3)
mpl.title('Residuals (mGal)')
mpl.hist(residuals, bins=10)

mpl.figure()
mpl.axis('scaled')
mpl.title('True (red) | Layer (black)')
levels = mpl.contour(y, x, gz_true, shape, 12, color='r')
mpl.contour(y, x, gz_up, shape, levels, color='k')
mpl.m2km()
mpl.show()