Exhaustive secondary data provide valuable insights into local patterns of spatial continuity. The covariance table(s) obtained from the Fast Fourier Transform (FFT) offers a high-performance computational alternative for mapping spatial continuity from exhaustive secondary data. Traditionally, a global covariance table is obtained from the entire grid of secondary data. This global covariance table is then used for estimation/simulation algorithms. The drawback of this approach is that it assumes that the spatial continuity of the variable to be modelled is constant over the area of interest. Many geological formations, such as folded strata, exhibit spatial continuity that changes from one location to another. Using a locally variable spatial continuity model improves the estimates for this type of geological formation. This paper proposes a methodology that considers local spatial continuity in Ordinary Kriging using covariance table(s). First, local covariance table(s) are constructed using FFT applied to sub-areas of the gridded secondary data. Second, local variogram models are fitted automatically based on the experimental points extracted from the local covariance table(s). Finally, Ordinary Kriging is performed using the local variogram models. As a result, each block of the model is estimated using its variogram model. The methodology is applied to a case study using public data. The results show increased precision and accuracy of the estimates due to the use of local variograms.