anaflow.tools.coarse_graining.TPL_CG

TPL_CG(rad, cond_gmean, len_scale, hurst, var=None, c=1.0, anis=1, dim=2.0, K_well='KH', prop=1.6)[source]

The gaussian truncated power-law coarse-graining conductivity.

Parameters:

  • rad (numpy.ndarray) – Array with all radii where the function should be evaluated

  • cond_gmean (float) – Geometric-mean conductivity

  • len_scale (float) – upper bound of the corralation-length of conductivity-distribution

  • hurst (float) – Hurst coefficient of the TPL model. Should be in (0, 1).

  • var (float or None, optional) – Variance of log-conductivity If given, c will be calculated accordingly. Default: None

  • c (float, optional) – Intensity of variation in the TPL model. Is overwritten if var is given. Default: 1.0

  • anis (float, optional) – Anisotropy-ratio of the vertical and horizontal corralation-lengths. This is only applied in 3 dimensions. Default: 1.0

  • dim (float, optional) – Dimension of space. Default: 2.0

  • K_well (str or 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:

TPL_CG – Array containing the effective conductivity values.

Return type:

numpy.ndarray