Regional evaluation of hydrocarbon potential in the south Ustyurt region based on integrated geological and geophysical data

Abstract

A methodology for regional hydrocarbon prospectivity assessment in the South Ustyurt Region (SUR) has been developed through the integration of drilling, seismic exploration, gravimetry, magnetometry, geothermal studies, and airborne gamma-ray spectrometry data. The hydrocarbon potential of the SUR was evaluated using advanced software tools, including IP Seismic, ArcGIS, and others. The research methodology based on machine learning techniques, specifically Self-Organizing Map (SOM) clustering, to identify correlations between geophysical anomalies, regional and local structures, and predicted hydrocarbon accumulations. Structural mapping analysis confirmed the block heterogeneity of the sedimentary cover. Airborne gamma-ray spectrometry identified 15 anomalous zones characterized by reduced concentrations of thorium, potassium, and uranium, suggesting potential hydrocarbon presence. Most of these anomalies are concentrated in the Shakhpakhty Steppe. The correlation between airborne gamma-ray spectrometry and seismic data further confirmed the association of radioactive anomalies with fault tectonics. In the Shakhpakhty Step and Assakeaudan Depression, the Kazgurly, Utezhan, Kozhantay, Western Kozhantay, Otynshy, and Southern Tabyn areas show high probabilities of hydrocarbon accumulation. Exploratory drilling and additional 3D seismic surveys are recommended for these locations. Furthermore, the research findings require further validation through the integration of remote sensing and well data within a unified 3D model. The integration of modern digital technologies and artificial intelligence to improve forecasting accuracy and exploration efficiency is recommended for similar studies in Kazakhstan and other regions with comparable geological conditions.