The relevance of the study. Currently, to solve the geological section prediction problems, including the prediction of sedimentation mass of oil and gas potential, based on the seismic observations data, the dynamic characteristics of reflected waves, directly related to their amplitude and energy, are widely used as diagnostic features. Until recently, the information on the phase-frequency characteristic properties was used little if at all. Meanwhile, the seismic response phase, in particular a complex pattern of change of their phase spectra, contains information on location of reflecting boundaries of the analyzed rock mass, the absorbing and dispersion properties of the bedded absorptive structure. Therefore, phase-frequency characteristics of reflected waves can serve as important diagnostic features for predicting sedimentation mass of oil and gas potential. The aim of the study is to develop algorithm for predicting and mapping the geological section types based on the phase-temporal analysis of the seismic records; to explore the reliability of the algorithm on the models of geological structures and test its application to processing and interpreting the data from the common depth point method at the Kontorovichsky oil field. The methods used in the study: the digital processing of spatiotemporal signals and field, methods of discrete Fourier transform, mathematical modeling and computer experiment. The results. The authors showed the possibility of extracting useful information from the phase-frequency characteristics of seismic signals for diagnostic features formation at geological section prediction. Based on the selected features, the method of phase-temporal seismic records analysis was developed and the algorithm for forecasting and mapping the geological section types was built. The developed algorithm was studied on the models of bedded absorptive structure, experimental processing and interpreting real data. The results obtained confirmed the prospects of applying phase-temporal analysis for predict the geological section types in inter-well space.