KNN Interpolation
K-Nearest Neighbors interpolation for contour mapping in the oil and gas industry
About KNN Interpolation
Concept
KNN interpolation estimates unknown values by averaging the data points closest to the target location. It identifies the k nearest known samples in space and uses their values to predict the new point.
Dependence on Distance
The method relies on spatial proximity; points that are geographically closer have more influence on the interpolated value than distant ones.
Handling Discontinuities
KNN is effective in datasets with sharp boundaries or abrupt changes (such as fault zones or lithology transitions) because it doesn't assume smooth variation between points.
Oil & Gas Application
In reservoir and production mapping, KNN interpolation is used to generate contour maps of:
- Pressure distribution
- Porosity estimation
- Permeability mapping
- Saturation analysis
This helps engineers visualize subsurface variations and plan development strategies.
View Data Set TemplateKNN Interpolation Tool
Upload your data file (.xlsx, .csv)
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Tip: For small datasets (less than 50 points), use K=3-5. For larger datasets, use K=5-15. Higher values provide smoother results but may oversmooth local variations.
Enter Target Coordinates
Processing KNN interpolation...
Interpolation Results
Nearest Neighbors
| Well Name | X Coordinate | Y Coordinate | Z Value | Distance |
|---|