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STATISTICAL PROCESSING OF GEOLOGICAL DATA FOR THE ROIL16 GROUNDWATER BODY

Teodora Vasile

Abstract

This paper has as main objective the statistical processing of geological information from hydrogeological wells on the ROIL16 ? Plain Vlasia groundwater body. The first step was the collection of detailed information and data, such as geological and hydrogeological characteristics, the features of the superficial deposits and soils, an inventory of associated surface systems, an estimation of the flow directions. The geological information was taken from the water wells of National Network Monitoring of Romania. The data that was used reffered to lithology, top and base filter, depth to static water level etc. Based on this information, there were created geological sections with different orientations using the AutoCAD 2019 program. The statistical processing of the geological date was made using the numerous Surfer 10 analysis tools. In order to evaluate the distribution of geological deposits (sand and gravel, clay and loessoid deposits) there were created, calculated and analyzed: post, contour and base maps, omni-directional variograms, model variograms calculated for different directions in the data set, surface variograms, anisotropy parameters (large and small radius, theta-anisotropy angle), variogram grid. The variogram characterizes the spatial continuity of the geological date. The variogram analysis consists of the experimental variogram calculated from the geological date and the variogram model fitted to the data. The variogram model was chosen from a set of mathematical functions describing spatial relations. The Point Kriging method was used to interpolate geological data. To account for geometric anisotropy (variable spatial continuity in different directions), separate experimental and model variograms were calculated for 8 directions. In conclusion, the statistical analysis indicates the spatial distribution of the probability of occurrence of lithological deposits: sand and gravel, clay and loessoid deposits.

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DOI resolver: doi.org/10.5593/sgem2019/1.2/s02.063

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