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Seismic reflection imaging of an ultrashallow interface from a P‐wave data set with a poor signal‐to‐noise ratio
Author(s) -
Balia Roberto,
Gavaudo Enrico
Publication year - 2003
Publication title -
near surface geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.639
H-Index - 39
eISSN - 1873-0604
pISSN - 1569-4445
DOI - 10.3997/1873-0604.2003009
Subject(s) - reflection (computer programming) , data processing , noise (video) , geology , reflector (photography) , signal processing , interface (matter) , set (abstract data type) , signal (programming language) , data acquisition , economic geology , data set , computer science , seismology , optics , metamorphic petrology , artificial intelligence , database , physics , telecommunications , light source , radar , bubble , maximum bubble pressure method , parallel computing , image (mathematics) , tectonics , programming language , operating system
It is well known that pitfalls are commonly encountered in the acquisition and processing of shallow reflection data. Although they can often lead to misinterpretations, the obsession with these difficulties can generate an excessively pessimistic attitude and ultimately lead to rejecting data that contain genuine reflections. The authors revisited a data set acquired during an ultrashallow P‐wave reflection experiment conducted in December 1996 on a subsurface model characterized by one main, complex interface. The model had been purpose‐built to control acquisition and processing decisions, and to contribute to clarifying at least some of the critical aspects inherent in the ultrashallow seismic reflection method. For the experiment, the acquisition geometry was purposely designed regardless of the known characteristics of the model, considering only a target depth of less than ten metres. The data, which had been acquired with CMP techniques, were generally characterized by a poor signal‐to‐noise ratio and had been considered completely useless. Initially, inexperience in acquiring and, above all, processing ultrashallow reflection data, in conjunction with mise‐valuations, had led to disappointing failures. Velocity analysis on reflection data had proved very difficult and standard processing sequences were inadequate. However, in this case a good result was obtained by modelling the near‐surface velocity using direct‐wave traveltimes analysis and by adopting a simple but segregated processing sequence, which proved necessary due to significant velocity gradients and large relative variations of the reflector depth. Time‐to‐depth conversion afforded a more than acceptable result.