Artificial Intelligence Approaches in Achimov Formation Hierarchical Clustering Research Project

Currently, due to the depletion of terrigenous oilfields there is an increasing tendency in non-conventional hydrocarbon resources like Achimov formations, which characterized by high heterogeneity and low permeability and porosity. Furthermore, AF was transit interval on the most of oil fields, resulting in poor knowledge at core data and well logs. This fact makes it difficult to estimate AF geological properties and predict potential for drilling zones. While researching such a complex object engineers often try to fill in the data from analogous fields that sometimes increases error caused by incorrect analog choice. AF have huge potential in terms of regeneration of the oil and gas resources base, however for its effective development and analysis there is a need in correct systematization and intelligence analysis of available information about this object. This challenge can be solved by creating an expert system, which will allow to process huge amount of scattered information, analyze it with respect to its scale and suggest some kind of information such as perspective in terms of development and analogous zones and fields, technological solutions and their results, based on previous experience