Methods of mathematical statistics application in assessing the density of actual and forecasting distribution density of residual oil reserves

The authors propose a method for mathematical statistics application for residual reserves in deposits predicting. They propose a method for making residual the current reserves distribution model based on geological and physical characteristics of the reservoir analysis. The article takes the first step to justify the use of statistical methods in the conditions of operational facilities of the Romashkino and Tuymazy oil fields. One of the urgent problems associated with the effective oil fields development is not only a reliable estimate of the distribution density of residual reserves, but their forecast for the subsequent development as well. There are many ways to estimate residual reserves nowadays. All of them are, to one degree or another, based on residual oil saturation ratio estimating, which in the conditions of insufficient accuracy of geophysical methods, as well as their rise in price (carbon-oxygen logging, for example) or their limited application, calls for other approaches in the residual oil reserves value assessing, based, for example, on the field data. Logging methods have their limitations. Their application requires other approaches in residual reserves amount assessing. Having analyzed multiple studies results, such as, for example, field data, implemented in the SPSS program regression analysis, which allows statistical data the processing the authors propose the mathematical statistics methods application in assessing the density of the actual and forecasting the residual oil reserves’ distribution density. The mathematical modeling results for oil from a porous medium displacement process are presented for Romashkino and Tuymazy oil deposits.