The relevance of fracturing prediction is associated with growing attention to the search for hydrocarbon deposits in unconventional reservoirs. The diffraction component of the wave field provides key information for identifying both large and small-scale inhomogeneities of the geological environment which is very difficult due to the weak energy of the diffraction component. Its amplification and separation from the full wave field is a key task for searching for small-scale geological elements. The important parts for reliable identification of diffraction objects are: data and model quality, as well as the used algorithms for constructing diffraction images. The article discusses a conceptual approach for identifying diffracted waves against the background of strong reflections and a technique for obtaining a detailed seismic section. The processing flow for extracting the diffraction component and procedures for minimizing residual noise and interference on a seismic section is presented in the article. As a result of diffraction processing continuous high-amplitude signals were obtained in fault zones of the crystalline basement of the White Tiger field. To identify small-scale fracturing zones in diffracted wave sections an attribute analysis was applied. Additionally a comparison of the diffraction processing results with conventional PrSTM and PrSDM data was performed. FMI data from several production wells was used to analyze and to compare the spatial distribution of fault trending. Obtained results can be used both to refine the physical and geological model of hydrocarbon deposits to improve operational characteristics and to minimize risks of exploration drilling.
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