The article describes the algorithm for seismic imaging data processing that enables detecting and evaluating geological anomalies based on the system of specific criteria. Employing the algorithm we can complete the process of profile record, amplitude and velocity spectra computation, filtering and imaging of T-X curves. Subsequently computation and statistical processing of kinematic and dynamic parameters are made in the selected velocity windows. The main procedures for the algorithm include tomographic recovery of wavefield parameters in the plane of extraction panel, detection and interpretation of anomalous zones based on the prediction criteria to determine type of the discontinuity. There is a good reason that tomography in the plane of extraction panel shall be made in velocity windows of the dedicated wavetrains step by step for the main informative parameters. Analysis of the velocity distribution for the amplitude module maximum provides high accuracy when it comes to detect anomalous zones. This parameter is marked by relative independence on chance factors. Analysis of typical wavetrain frequency shift is determining factor indicative not only of the discontinuity but also of its type. Recording of wavetrain amplitude distribution is characterized by high accuracy in terms of anomalous zone detection. However, recording is complicated by dependence on a host of chance factors. The other parameters have much lesser quality and can be used as auxiliary. The algorithm is implemented into software capable to computerize most time-consuming operations. Use of this algorithm is illustrated as a case study for the results of data analysis and interpretation for seismic exploration at 37К10-В longwall panel section in Kuzembaev Mine (Kazakhstan).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.