Andrew Shatilo

Characterization of spatially varying surface waves in a land seismic survey

Summary We present several methods for analyzing surface waves in a highly sampled 3-C, 3D survey, and report the most important characteristics derived from those analyses. In particular, we demonstrate the spatial variability of surfacewave velocities and polarization properties. We also show that surface-wave velocities are correlated with other seismic and nonseismic properties of the near surface, such as shear-wave statics and surface texture derived from satellite imagery.

The case for separate sensor processing: Meeting the imaging challenge in a producing carbonate field in the Middle East

Carbonate platforms in the Middle East continue to represent an important source of hydrocarbon reserves. For more than 20 years, interpretation and attribute extraction from time-based 3D seismic imaging products have been base geoscience data in this production setting. With the continuing advances in seismic imaging, geophysicists have an obvious interest in applying the most current algorithms to their projects. However, many of these carbonate reservoirs have accompanying imaging challenges that cannot be addressed solely through the application of new imaging technology. Alternative processing strategies must be considered, either to replace more conventional approaches and/or to prepare the data so that they conform to the limitations of the imaging algorithm.

Constrained Polarization Filtering For Surface-wave Mitigation

We present a new method of surface-wave mitigation using polarization filtering. The method evolves from the polarization-analysis technique developed by Diallo et al., (2006) and introduces new constraints to effectively detect and mitigate surface waves without damaging the signal. Straightforward application of polarization filtering without these constraints results in ineffective filtering or damage to the signal, due to the complexity of surface-wave wavetrains. We illustrate the performance of the method with examples from multicomponent seismic data, and demonstrate the superiority of the filtering compared to the unconstrained approach.

Effect of Noise Suppression on Quality of 2C OBC Image

Two component ocean bottom cable (2C OBC) data are often affected by substantial noise. The noise is probably caused by shear wave energy registered on the vertical geophone. It exhibits random properties in common shot domain but coherent properties in common receiver domain. This phenomenon is observed in most OBC surveys worldwide, and the noise level can be very substantial. Typically, there is a substantial move out difference between the noise and the signal, i.e., reflected PP waves, allowing use of velocity filtering for noise suppression. Velocity of sound in water can be used as a quite universal parameter for normal moveout (NMO) correction before the velocity filtering. The NMO correction substantially simplifies design of the velocity filter. Efficiency of the proposed approach is illustrated using real 2C OBC data.

Resolution of Converted Waves In Attenuating Media

PS waves offer better resolution than PP waves at shallow targets before attenuation becomes significant, but when QP > QS , there is a “resolution crossover depth,” i.e., a depth below which PP waves offer better resolution than PS waves. An equation is given for calculating this crossover depth at near offsets, where the crossover depth is the same for both horizontal and vertical resolution. Seismic data from two 2D OBS lines supports the predicted resolution behavior. The scaled-to-depth PS images show better resolution than the PP images in the shallow section, and the resolution crossover depth can be determined.

Paradigm shift in 3D multicomponent seismic imaging in the Arabian Gulf

Ocean-bottom cable (OBC) technology has many applications in petroleum exploration and exploitation. It permits us to acquire data in areas with intensively developed production infrastructure that impede conventional marine-streamer acqui- sition. Permanently installed OBC systems provide data for monitoring production from reservoirs. In addition to their logistical advantages, OBC systems also allow us to acquire multicomponent data. Typically, 2-C OBC data are acquired by two types of detectors: hydrophones (fluid-pressure change detectors) and single- or multicomponent geophones (particle-velocity or acceleration detectors). The multicomponent character of OBC data permits us to discriminate between upcoming and downgoing waves and to attenuate water-column reverberations. At the same time, because of the differences between the physical measurement characteristics of hydrophones and geophones, their data character (including noise levels, multiple content, coupling effects) can be very different. Th...