Mathematical model for calculation of data sources in building membership function in problems of estimating reliable hydrocarbon reserves

In solving the problems of assessing the reliable hydrocarbon deposits the initial data are considered in the form of fuzzy relationships, which is possible by constructing a stray field that is a fuzzy modeling method based on the data compression algorithm. This algorithm allows reducing the quantity dimension and taking away the random information from the initial data, which is a possible cause of an erroneous estimate. The data compression algorithm has two stages. The first stage is based on a clustering algorithm that helps locate the data sources. The second stage is based on the Hooke-Jeeves method of calculating the source weight. Experiments were carried out to study the influence of the number of sources on the result of building the stray field. A set of petrophysical parameters (porosity by GWL, pore sizes in cores) measured at one time was used as initial data, which characterized the capacitive properties of the rock. Each experiment is supplied with the maps of sources, stray fields and relative errors. It has been inferred that with a decreasing the source number the stray fields saved their structure, though there increased the relative error of a stray field and of the map of initial data density.