Intelligent geoinformation technologies for probabilistic and fuzzy calculations and optimization for GEOTEP and SMN in determining the optimal location, ranking of exploration wells, and mapping

Abstract

A geographic information system has been developed for planning, monitoring, and analyzing geological exploration activities. This system incorporates an intelligent core for data analysis, calculations, and optimization in the face of information uncertainty. The proposed methodologies and algorithms have been implemented in the Subsurface Resource Management System, which is designed to monitor geological exploration work and the use of subsurface resources. This paper discusses using fuzzy and probabilistic models — a hybrid approach — for assessing the resource base and calculating reserves. We have developed deterministic and fuzzy algorithms for geographic information system calculations to determine the optimal placement of exploration wells. To generate uncertainty maps for reserve estimation, we created an original fuzzy algorithm that surpasses the commonly used Monte Carlo method in terms of capability, accuracy, calculation time, and stability. This approach allows us to represent all imprecisely defined parameters as membership functions and utilize the proposed fuzzy operations to analyze real field data. The fuzzy operations for map generation include fuzzy overlay operations, which can be employed to create maps that illustrate the uncertainty of calculated parameters and reserves. We also provide a comparison with the "traffic light" map-building method.