Interpolation and Gridding
Definition
The process of estimating values between measured points to create a continuous surface or image from discrete survey transects. Common algorithms include kriging, minimum curvature, and triangulation. The grid resolution must be appropriate to the data spacing or interpolation will invent detail.
- Purpose
- Estimate values between measured survey points
- Common algorithms
- Kriging, minimum curvature, triangulation
- Risk
- Over-fine grid invents detail not in the data
- Key constraint
- Grid resolution should match survey line spacing
Common questions
Why does grid resolution matter so much?+
A grid finer than the actual line or point spacing manufactures apparent features between real readings, and those artefacts can be misread as genuine buried anomalies during interpretation.
Why is kriging often preferred for irregular survey data?+
Kriging weights nearby points using a modelled spatial covariance rather than distance alone, giving a statistically grounded estimate instead of a purely geometric one.
Related terms
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- De-Striping
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- Migration (GPR)
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- Zero-Time Correction
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