Application of high-resolution small group interval processing technology and attribute analysis for hydrate identification

Natural gas hydrate resources are playing more and more important role in energy exploration, and the type characteristics and accumulation patterns of shallow layer natural gas hydrate have attracted more and more attention. Shallow layer gas hydrates generally occur in the near-seabed strata, and require higher resolution in the exploration process. Conventional multi-channel seismic are difficult to meet this requirement due to their low dominant frequency. With the advantages of high resolution and flexible operation mode, the marine high-resolution small group interval seismic exploration technology has been widely used in shallow gas hydrate exploration. Due to the influence of acquisition equipment conditions, the actual high-resolution small group interval data often has the characteristics of low signal-to-noise ratio. Therefore, fine processing and attribute analysis were carried out according to the characteristics of high-resolution small group interval seismic data. First, the key technical methods such as multi-domain noise suppression method based on the f−x (f: frequency; x: the offset) domain and curvelet domain, adaptive ghost suppression based on frequency domain, and cable floating correction based on combination of gather coherence and ghost reflection traveltime were used to obtain seismic profiles with clearer wave group characteristics. The processed profile has the characteristics of high signal-to-noise ratio, good continuity, and clear stratigraphic configuration, which can better reveal the seismic reflection characteristics such as BSR characteristics, blank zone, and gas channel, and lay a foundation for identifying the geological information to locate the shallow gas hydrate occurrence area. Secondly, the seismic attributes such as instantaneous amplitude attribute, instantaneous frequency attribute, and hydrocarbon detection were further analyzed for the finely processed data for the identification of the distribution type and accumulation law of shallow gas hydrate.