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Walter Gerbino, Chiara Micelli; Classification of seismic images depends on perceptual skill more than geological expertise. Journal of Vision 2010;10(7):1193. doi: 10.1167/10.7.1193.
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© ARVO (1962-2015); The Authors (2016-present)
Expert interpreters inspect seismic images to identify relevant features and diagnose the possible presence of interesting subsoil structures. Typically, a 2D seismic image is a set of adjoining seismic traces referring to variations of acoustic impedance that, taken together, compose a non mimetic representation of the subsoil. Seismic interpreters must rely on both domain-specific knowledge in the field of structural geology and general-purpose visual abilities involved in texture segregation and feature matching. We studied three groups of observers with different degrees of expertise with seismic images (researchers of the National Institute of Oceanography and Experimental Geophysics; geology students; psychology students) and compared their performance in a task in which they should classify a target fragment as belonging or not belonging to a large seismic image. As expected, more experienced observers performed better than less experienced observers; furthermore, observers of all groups classified meaningful targets (those with clear geologically relevant features) more efficiently than non-meaningful targets (those with uncertain features). Against our expectations, however, the superiority of meaningful over non-meaningful targets did not increase at increasing expertise; rather, it appeared to depend on the level of individual perceptual skill, which was broadly distributed over the three groups. We argue that performance in the classification of seismic image fragments - which is a possible component of a seismic interpreter's work – reflects general-purpose visual abilities more than geological expertise.
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