This work proposes a sampling inspection framework for point measurement non-destructive testing of pipelines to improve its time and cost efficiencies. Remaining pipe wall thickness data from limited dense inspection are modelled with spatial statistics approaches. The spatial dependence in the available data and some subjective requirements provide a reference for selecting a most efficient sampling inspection scheme. With the learned model and the selected sampling scheme, the effort of inspecting the residual part of the same pipeline or cohort will be significantly reduced from dense inspection to sampling inspection, and the full information can be reconstructed from samples while maintaining a reasonable accuracy. The recovered thickness map can be used as an equivalent measure to the dense inspection for subsequent structural analysis for failure risk estimation or remaining life assessment.