Geoscience Objects
variogram
See also: variogram (fitted model counterpart).
Overview
The experimental-variogram object is used to capture spatial variability of univariate data across an area of interest. Spatial variability is described by direction and summarized per each lag in a direction.
The experimental variogram is calculated a part of a standard variography workflow and is precursor to variogram modeling. An experimental variogram is a key input to fitting a variogram model.
Required Data
To construct an experimental variogram object the following information is required.
-
data_variance(number): The variance of the source data -
directions(object): Table describing geometry and type of each direction for which lags exist.data(binary blob): Table with columns: offset, count, direction_type, azimuth, dip, azimuth_tolerance, dip_tolerance, bandwidth, bandheight.offset(integer): Index in the lags table at which the information associated with this direction beginscount(integer): Number of entries in lag tabl associated with this direction (number of lags).direction_type(string: ["directional", "omnidirectional" or "downhole"]): type of direciton describedazimuth(float): Clockwise rotation about the z-axisdip(float): Incline of the direction, negative points downazimuth_tolerance(float): Tolerance considered on either side of the azimuth direction, contributing to the conical definition of the searchdip_tolerance(float): Tolcerance considered on either side of the dip, contributing to the conical definition of the searchbandwidth(float): Width of the search to be considered once the conical search has reached its extextsbandheight(float): Height of the search to be considered once the conical search has reached its extexts
length(integer): Number of directionswidth(const): Must be 9data_type(const): Must be "uint64/uint64/string/float64/float64/float64/float64/float64/float64"
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lags(object): Table describing individual lagsdata(binary blob): Table with columns: start, end, centroid, value, num_pairs.start(float): start distance of the lagend(float): end distance of the lagcentroid(float): average distance (centroid) of all pairs represented in lagvalue(float) : calculated value representing spatial correlation, semi-variance or other described by thevariogram_typefield.num_pairs(integer): number of pairs considered in thevaluecalculation.
length(integer): Total number of lag binswidth(const): Must be 5data_type(const): Must be "uint64/uint64/float64/float64/float64/float64/uint64"directions(object): Contains:
Example Tables
Two small examples below demonstrate the defined format of the directions and lags tables described above.
Directions Table
| offset | count | direction_type | azimuth | dip | azimuth_tolerance | dip_tolerance | bandwidth | bandheight |
|---|---|---|---|---|---|---|---|---|
| 0 | 20 | directional | 0 | 0 | 22.5 | 22.5 | 50 | 50 |
| 20 | 20 | directional | 90 | 0 | 22.5 | 22.5 | 50 | 50 |
| 40 | 20 | directional | 0 | -90 | 10.0 | 10.0 | 20 | 20 |