The Application of Decision Tree Method to the Identification of Formation Types in Tight Gas Reservoirs

Abstract

Numerous test data accumulates in the process of gas reservoir exploration and development, so it is necessary to apply the data mining technology to this process. Influenced by the geologic factors such as structure, deposition and diagenesis, tight sandstone gas reservoir formation types are so diversified that traditional cross-plot analysis technique hardly identify the formation types. In this paper, the formation types of tight sandstone gas reservoir in Daniudi area are successfully identified using the decision tree algorithm of data mining based on hierarchical decomposition theory, facilitating the development of the gas reservoir.