adaptive_indicator_krig

adaptive_indicator_krig is an alternative geologic modeling concept that uses geostatistics to assign each cell’s lithologic material as defined in a pregeology (.pgf) file, to cells in a 3D volumetric grid.

There are two methods of lithology assignment:

• Nearest Neighbor is a quick method that merely finds the nearest lithology sample interval among all of your data and assigns that material. It is very fast, but generally should not be used for your final work.
• Kriging provides the rigorous probabilistic approach to geologic indicator kriging. The probability for each material is computed for each cell center of your grid.  The material with the highest probability is assigned to the cell.  All of the individual material probabilities are provided as additional cell data components.  This will allow you to identify regions where the material assignment is somewhat ambiguous.  Needless to say, this approach is much slower (especially with many materials), but often yields superior results and interesting insights.  

adaptive_indicator_krig is an extension of the technology in lithologic modeling for several reasons:

1. Material assignments are done on a nodal versus cell basis providing additional inherent resolution

2. Gridding is handled by outside modules. This allows for assigning material data based on a PGF file after kriging analyte (e.g. chemistry) or other parameter data with 3d estimation.

3. Though it does not provide material boundaries that are as smooth as gridding and horizons, it does provide much smoother interfaces than lithologic modeling's Lego-like material structures.

There are two fundamental differences between lithologic modeling and adaptive_indicator_krig

1. Geology / Grid input:
   1. lithologic modeling expects input from modules like gridding and horizons (which is a set of surfaces) and it builds you grid for you just as 3d estimation does.
   2. adaptive_indicator_krig is more like the "Kriging to an external grid" option in 3d estimation.  You need to create the 3D grid (which doesn't need to have any data) that it will use.  It will take that grid as a starting point for material assignments and later smoothing.
2. Lithologic Material Assignment
   1. lithologic modeling assigns whole cells to cell sets and sets CELL data which is Material_ID.
   2. adaptive_indicator_krig takes the external grid and further refines it by splitting whole cells along all boundaries between two or more materials to create smoother interfaces.

Module Input Ports

• Input Field [Field] Accepts a data from 3d estimation, horizons to 3d or other modules that have already created a grid containing volumetric cells. If the input field has data such as concentrations, it will be included in the output.
• Filename [String / minor] Allows the sharing of file names between similar modules.
• Refine Distance [Number] Accepts the distance used to discretize the lithologic intervals into points used in kriging.

Module Output Ports

• Geologic legend Information [Geology legend] Supplies the geologic material information for the legend module.
• Output Field [Field] Contains nodal data and a refined grid representing geologic materials..
• Filename [String / minor] Outputs a string containing the file name and path. This can be connected to other modules to share files.
• Refine Distance [Number] Outputs the distance used to discretize the lithologic intervals into points used in kriging or displayed in post_samples as spheres.

Properties and Parameters

The Properties window is arranged in the following groups of parameters:

• Grid Settings: control the grid type, position and resolution
• Krig Settings: control the estimation methods
  • NOTE: Nearest Neighbor assigns the lithologic material cell data based on the nearest lithologic material (in anisotropic space) to your PGF borings.  This is done based on the cell center (coordinates) and an enhanced refinement scheme for the PGF borings.  In general Nearest Neighbor should not be used for final results

Advanced Variography Options:

It is far beyond the scope of our Help to attempt an advanced Geostatistics course. The terminology and variogram plotting style that we use is industry standard and we do so because we will not provide detailed technical support nor complete documentation on these features, which would effectively require a geostatistics textbook, in our help.

However, we have offered an online course on how to take advantage of the complex, directional anisotropic variography capabilities in adaptive_indicator_krig(which applies equally well to lithologic modeling and 3d estimation), and that course is available as a recorded video class. This class is focused on the mechanics of how to employ and refine the variogram anisotropy with respect to your data and the physics of your project such as contaminated sediments in a river bottom. The variogram is displayed as an ellipsoid which can be distorted to represent the Primary and Secondary anisotropies and rotated to represent the Heading, Dip and Roll. Overall scale and translation are also provided as additional visual aids to compare the variogram to the data, though these do not affect the actual variogram.

We are not hiding this capability from you as the Anisotropic Variography Study folder of Earth Volumetric Studio Projects contains a number of sample applications which demonstrate exactly what is described above. However, we assure you that understanding how to apply this to your own projects will be quite daunting and really does require a number of prerequisites:

• A thorough explanation of these complex applications
• A reasonable background in Python and how to use Python in Studio
• An understanding of all of the variogram parameters and their impact on the estimation process on both theoretical datasets as well as real-world datasets.

This 3 hour course addresses this issues in detail.