The objects of the doctoral research are two hydrocarbon fields with Upper Miocene sandstone reservoirs, located in the western part of the Sava Depression. Namely, those are the "A" field with "L" reservoir and the "B" field with "K" reservoir. Both currently produce hydrocarbons using a secondary method (water injection). This is very mature explored and developed area, what allows significant improvements and upgrades of geological models in order to increase hydrocarbon recovery. This applies especially for methods of statistical and geomathematical analysis of numerous reservoir variables such as porosity and permeability (primary variables) and injected water volumes (secondary variable). Furthermore, the most existing reservoirs maps (structural, porosity, etc.) should be made in much more detail, using advancing mapping algorithms. Mathematical algorithms such as variograms and Kriging had been the main tools in analysing spatial dependence and possible anisotropy of the selected variables. The Kriging method has a long history of application in the field of Croatian part of the Pannonian Basin System (CPBS). The statistical method Jack-knifing was a tool who extend the number of values of statistical parameters and thus to improve the analysis in which the number of data deficient, i.e. approximately less than 50 measurements per selected regionalized variable (porosity: reservoir “L” 25 data, reservoir “K” 19 data). For a small input data set (<20), for variables injected volume of water (reservoir “L” 10 data; reservoir “K” 3 data) and permeability (reservoir “L” 10 data; reservoir “K” 18 data) following interpolation methods are applied: Inverse Distance, Nearest and Natural Neighbourhood. The size of the small input set for different types of variables, i.e., measured points, was defined by 20 or more „solid“ data, and about 15 has been sufficient to apply the Inverse Distance and Nearest Neighbourhood methods. For a small input data set, the recommended mapping method is the Inverse Distance method. When interpreting mapping results after applying Ordinary Kriging (before or after Jack-knifing method) or interpolation method for a small sample of the final evaluation of the resulting maps is necessary to fulfill the following: visually (maps with no expressed local value („bull-eyes“ or „butterflies“), are appropriate) and numerically (using the cross-validation value). According to the results of the cross-validation values, the Inverse Distance method in the cases of mapping permeability and injected volume of water for reservoirs “K” and “L” is most acceptable. The methodology for calculating geological probability was applied in calculating the persistence of the remaining economic quantities of hydrocarbons in the western part of the Sava Depression. A modification of the methodology for the calculation of geologic probability was applied to the reservoirs that are in the secondary hydrocarbon production phase. The variables that are included in the geological probability calculation are: trap, reservoir, source rocks, migration and hydrocarbons preservation. The calculated value of exploratory geological probability for the western part of the Sava Depression is 0.4218, while the value of the modified geological probability for reservoirs in the secondary hydrocarbons production phase is 0.5625. The calculation of the risk neutral value of monetary units has been applied to: exploration of additional hydrocarbons in existing structures and production hydrocarbons from water flooding reservoirs. The calculated value of 2.32·106 risk-neutral USD (500 000 m3 of geological reserves of hydrocarbons) for the exploration geological probability value is the investment maximum in the western Sava Depression exploration area for the company's 50 million USD hydrocarbon exploration budget. For the value of the modified geological probability, the amount of the risk-neutral USD for the “L” reservoir is 1.21·106, and for the “K” reservoir 1.17·106, which is also the investment maximum for the company’s 35 million USD hydrocarbon production budget.