Crustal-scale prestack depth imaging of the 1994 and 1999 LARSE surveys
Michael Thornton and Hua-wei Zhou
Journal name: Geophysical Prospecting
Issue: Vol 56, No 4, July 2008 pp. 577 - 585
Special topic: Passive and controlled-source crustal imaging
Info: Article, PDF ( 809.47Kb )
While seismic imaging for crustal and mantle structures has traditionally relied on surface wave and refraction data, the use of reflection data for crustal-scale targets has been largely limited to the common midpoint (CMP) stack techniques. The rapid increase in the number of seismograph array deployments in recent years in crustal and mantle seismology has reached a level such that a re-examination of the imaging techniques is becoming necessary. In this paper we show the advantage of prestack depth imaging for crustal reflection studies, based on data from two reflection surveys of the Los Angeles Regional Seismic Experiment (LARSE) to map faults and crustal-scale structures. Our analysis indicates that the quality of the previous images of these surveys is limited by the CMP stack technique. For comparison, we present here depth images of the same LARSE data using wave equation prestack depth imaging and a tomographic velocity model based on first arrivals of the LARSE surveys and local earthquakes. Our new images are considerably improved over previous images in terms of resolution and reflector continuity. The new images show reflectors throughout the crust and suggest truncations in the Moho associated with the San Andreas Fault. A series of bright reflector segments, which are associated with the San Gabriel and San Andreas faults have been identified and might represent reflections from the fault zones. Our results suggest that the presence of high noise level, strong lateral velocity heterogeneity and wide angle geometry argue for, rather than against, the use of prestack depth imaging over the simple CMP stack techniques. As demonstrated in this study, it is now viable to conduct prestack depth imaging of crustal reflection data using a velocity model based on earthquake first arrivals thanks to the dense acquisition deployment.