analytical realization
The analytical realization module is one of three similar modules (the other two are lithologic realization and stratigraphic_realization), which allows you to very quickly generate statistical realizations of your 2D and 3D kriged models based upon C Tech’s Proprietary Extended Gaussian Geostatistical Simulation (GGS) technology, which we refer to as Fast Geostatistical Realizations^®^ or FGR^®^. Our extensions to GGS allow you to:
- Create realizations very rapidly
- Exercise greater control over the frequency and magnitude of noise typical in GGS.
- Control deviation magnitudes from the nominal kriged prediction based on a Min Max Confidence Equivalent.
- Deviations are the absolute value of the changes to the analytical prediction (in user units)
- Apply Simple or Advanced Anisotropy control over 2D or 3D wavelengths
C Tech’s FGR^®^ creates more plausible cases (realizations) which allow the Nominal concentrations to deviate from the peak of the bell curve (equal probability of being an under-prediction as an over-prediction) by the same user defined Confidence. However, FGR allows the deviations to be both positive (max) and negative (min), and to fluctuate in a more realistic randomized manner.
Module Input Ports
- Realization [Special Field] Accepts outputs from 3d estimation and krig_2d to allow for EGGS models to be created
Module Output Ports
- Output Field [Field] Outputs the subsetting level
- Deviations Field [Field] Outputs the deviations from the nominal kriged model
Important Parameters
There are several parameters which affect the realizations. A brief description of each follows:
- Randomness Generator Type
- There are four types, each of which create a different 2D/3D random distribution
- Anisotropy Mode
- Two options here are Simple or Advanced. These are equivalent to the variogram settings in 3d estimation or krig_2d
- Seed
- The “Seed” is used in the random number generator, and makes it reproducible.
- Unique seeds create unique realizations
- Wavelength
- The 2D or 3D random distribution is governed by a mean wavelength that determines the apparent frequency of deviations from the nominal kriged result.
- Wavelength is in your project coordinates (e.g. meters or feet)
- Longer wavelengths create smoother realizations
- Shorter wavelengths create more “noisy” variations in the realizations
- Very short wavelengths will give results more similar to GGS (aka Sequential Gaussian Simulations)
- Min Max Confidence Equivalent
- This parameter determines the magnitude of the deviations.
- Values close to 50% result in outputs that deviate very little from the nominal kriged result.
- (we do not allow values below 51% for algorithm stability reasons)
- Values at or approaching 99.99% will result in the greatest (4 sigma) variations (more similar to GGS)