Our aim was to identify some of the characteristics of low-frequency anomalies. Specifically, we have looked, in 3D broadband data from the North Sea, for any offset dependence in these anomalies and any frequency-related change in normal moveout (NMO) velocity that could influence stacking power over different frequencies. After high-resolution spectral decomposition, two types of low-frequency anomaly have been identified associated with hydrocarbon-bearing reservoirs: (1) at the reservoir top and (2) below the reservoir, with a time delay of approximately 100–200 ms. Both types of anomalies indicate offset dependence. On the near-offset stacks, they are relatively strong, but they tend to be absent on the far-offset stacks. In addition, horizon velocity analysis, which was performed along the horizons picked at the tops of reservoir and nonreservoir intervals, has revealed frequency-dependent NMO velocity. For nonreservoir events, we found no significant difference between the NMO velocities for the low-frequency and high-frequency filtered common-midpoint gathers. However, along the anomalously low-frequency events observed at the tops of, and below, oil-bearing reservoirs, lower velocity is observed for low-frequency and higher velocity for high-frequency filtered gathers. If these properties turn out to be universally typical, increased understanding and inclusion of them could lead to improved workflows and help increase the reliability of low-frequency analysis as a hydrocarbon indicator.
A Parametric Study on the Immunomodulatory Effects of Electroacupuncture in DNP-KLH Immunized Mice
