anaflow.tools.coarse_graining.K_CG
- K_CG(rad, cond_gmean, var, len_scale, anis, K_well='KH', prop=1.6)[source]
The coarse-graining conductivity.
This solution was presented in ‘’Zech 2013’’[R8].
This functions gives an effective conductivity for 3D pumpingtests in heterogenous aquifers, where the conductivity is following a log-normal distribution and a gaussian correlation function and taking vertical anisotropy into account.
- Parameters
rad (
numpy.ndarray
) – Array with all radii where the function should be evaluatedcond_gmean (
float
) – Geometric-mean conductivity.var (
float
) – Variance of the log-conductivity.len_scale (
float
) – Corralation-length of log-conductivity.anis (
float
) – Anisotropy-ratio of the vertical and horizontal corralation-lengths.K_well (string/float, optional) – Explicit conductivity value at the well. One can choose between the harmonic mean (
"KH"
), the arithmetic mean ("KA"
) or an arbitrary float value. Default:"KH"
prop (
float
, optional) – Proportionality factor used within the upscaling procedure. Default:1.6
- Returns
K_CG – Array containing the effective conductivity values.
- Return type
References
- R8
Zech, A. ‘’Impact of Aqifer Heterogeneity on Subsurface Flow and Salt Transport at Different Scales: from a method determine parameters of heterogeneous permeability at local scale to a large-scale model for the sedimentary basin of Thuringia.’’ PhD thesis, Friedrich-Schiller-Universität Jena, 2013
Examples
>>> K_CG([1,2,3], 0.001, 1, 10, 1, 2) array([0.00063008, 0.00069285, 0.00077595])