First, it is important to understand that Pinch Factor & Points in Pinch are options in krig_3d_geology that are only available to you if you select Estimate In Thickness Space, and even then, if you do select these options, you must be working with a data file type that supports these options.

So in order to use Estimate In Thickness Space the following special (additional) data requirements are imposed:

  • You must be using a .GEO file with at least 2 surfaces
  • You must use PINCH flags to designate that a layer is pinched-out for one or more borings for the bottoms of one or more layers.
    • PINCH flags are not case sensitive and can also be pinched or pinch-out
  • If you use any UNKNOWN flags to designate that the location of surface is not known or that a boring has terminated, you may not follow that flag with any numeric values in the same row.
    • UNKNOWN flags are not case sensitive and can also be missing, unk, na, short, terminated, or term

Provided that your data meets the above requirements, and the Estimate In Thickness Space toggle is on, when the surfaces are being created in krig_3d_geology, they are done in a special manner:

  • The top (uppermost) surface is created first in a normal manner
  • For all subsequent surfaces, the thickness of each layer is computed directly from the .GEO file, and the thickness of the layer is estimated, rather than the elevations of each surface.
  • For borings designated as PINCHED, if the Pinch Factor is greater than 1.0, the thickness used for the layer at that boring’s location becomes negative (rather than zero).
  • The magnitude of the negative thickness is governed by the Pinch Factor and the thickness trends of the “Points in Pinch” nearest borings.
    • Note: C Tech will not disclose the details of this algorithm
  • After all thicknesses for the layer are computed, values less than zero are set to zero.

Pinch Factor has the greatest effect on the pinching.  Sometimes a very high value (10, 20 or more) may be used to get the desired effect, but often just increasing it to 2.0 or 3.0 is sufficient.  The more sparse your data, the greater effect small values tend to have.