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 Template

KNN Interpolation Tool

Upload your data file (.xlsx, .csv)

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Select Data Columns

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

Interpolated Z Value
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Target Location
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K Value Used
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Data Points
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Nearest Neighbors

Well Name X Coordinate Y Coordinate Z Value Distance

Contour Map Visualization