Application of the bootstrap method on a large input data set - case study western part of the Sava Depression

The bootstrap method is a nonparametric statistical that provides through resampling the input data set to obtain new normally distributed. Due various factors, deep geological are difficult many set, and in most cases, they not Therefore, it necessary introduce tool will enable obtaining with which analyses can be done. was applied field "A", reservoir "L" located western part of Sava Depression. It variable porosity on 25 data. minimum number resampling's required for large sample normal distribution 1000. Interval estimation obtained by 0.1875 0.2144 95% confidence level.