Bulk and clay mineral composition indicate origin of terra rossa soils in Western Herzegovina

The correct selection of the value of p is a complex and iterative procedure that requires experience in the interpretation of the obtained interpolated maps. Inverse Distance Weighting is a method applied to the porosities of the K and L hydrocarbon reservoirs discovered in the Neogene (Lower Pontian) subsurface sandstones in northern Croatia (Pannonian Basin System). They represent small and large data samples. Also, a standard statistical analysis of the data was made, followed by a qualitative–quantitative analysis of the maps, based on the selection of different values for the power distance exponent (p-value) for the K and L reservoir maps. According to the qualitative analysis, for a small data set, the p-value could be set at 1 or 2, giving the optimal result, while for a large data set, a p value of 3 or 4 could be applied. For quantitative analysis, in the case of a small data set, p = 2 is recommended, resulting in a root mean square error value of 0.03458, a mean absolute error of 0.02013 and a median absolute deviation of 0.00546. In contrast, a p-value of 3 or 4 is selected as appropriate for a large data set, with root mean square errors of 0.02435 and 0.02437, mean square errors of 0.01582 and 0.01509 and median absolute deviations 0.00896 and 0.00444. Eventually for a small data set, it is recommended to use a p-value of 2, and for a large data set, a p-value of 3 or 4.

Interpolation is a procedure that depends on the spatial and/or statistical properties of the analysed variable(s). It is a particularly challenging task for small datasets, such as in those with less than 20 points of data. This problem is common in subsurface geological mapping, i.e., in cases where the data is taken solely from wells. Successful solutions of such mapping problems depend on interpolation methods designed primarily for small datasets and the datasets themselves. Here, we compare two methods, Inverse Distance Weighting and the Modified Shepard’s Method, and apply them to three variables (porosity, permeability, and thickness) measured in the Neogene sandstone hydrocarbon reservoirs (northern Croatia). The results show that cross-validation itself will not provide appropriate map selection, but, in combination with geometrical features, it can help experts eliminate the solutions with low-probable structures/shapes. The Golden Software licensed program Surfer 15 was used for the interpolations in this study.

Morphometric analysis of Holocene pebbles from Sava River gravel in NW Croatia revealed shape distributions as observed along a 30 km long watercourse. Limestones, dolomites, and sandstones were identified as the major (>4%) and effusive magmatics in this alluvial aquifer system in Zagreb, with cherts and tuffs as minor pebble lithologies (up to 4%). Their distributions mainly indicate distant Alpine provenance for carbonate pebbles (limestone and dolomite) and local input for sandstones and minor lithotypes, laterally from the Samoborska Gora and Medvednica mountain. Carbonates are predominantly disc- and sphere-shaped, implying distant sources. Scattered distributions of pebble shapes (sphere, disc, blade, and rod) for sandstones and minor lithotypes possibly indicate multiple sources, some of them probably local. The tentatively interpreted “original sedimentary environments” for the main pebble lithotypes (calculated from their flatness ratios) possibly indicate that they are predominantly lake beach pebbles, followed by moraine and riverbed pebbles. However, these results should be strongly questioned.