Babel4

Heikkinen, Pekka; Korja, T.

doi:10.1002/9781119158332.ch38

Cited by 1 publication

(1 citation statement)

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“…In the past several decades, several research projects have successfully acquired deep seismic profiles, which have been used to build up regional and/or relatively large-scale crustal models (e.g., LITHOPROBE, Clowes et al, 1968;Clowes et al, 1999;Hope et al, 1999;COCORP;Cook et al, 1979;BIRPS;Brewer et al, 1983;ECORS;Roure et al, 1989;DEKORP;Meissner and Bortfeld, 1990;TAICRUST;Nakamura et al, 1998;CROP;Barchi et al, 1998;Pialli et al, 1998;Finetti et al, 2001;Pauselli et al, 2006;IBERSEIS;Simancas et al, 2003;TRANSALP;Castellarin et al, 2004;FIRE;Kukkonen et al, 2006;Korja et al, 2018;ALCUDIA;Ehsan et al, 2014;Ehsan et al, 2015). Data corresponding to these unique largescale crustal and lithospheric research programs are currently available through open seismic data repositories such as LITHOPROBE (Clowes, 2010), OPENFIRE (Heinonen et al, 2017, https://helda.helsinki.fi/handle/10138/225858), and SEISDARE (Deng and Stauffer, 2006). Higher-resolution seismic reflection data provided by the energy industry or national archives have also been used in local and/or regional geological studies of upper crust structures (e.g., Wu, 1986;William-Keach et al, 1989;Boncio et al, 2000;Clowes and Hyndman, 2002;Carvalho et al, 2008;Beidinger et al, 2011;Percival, et al, 2012;…”

Section: Open Access Edited Bymentioning

confidence: 99%

Evidencing subtle faults in deep seismic reflection profiles: Data pre-conditioning and seismic attribute analysis of the legacy CROP-04 profile

et al. 2023

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Legacy seismic reflection data constitute infrastructure of tremendous value for basic research. This is especially relevant in seismically hazardous areas, as such datasets can significantly contribute to the seismotectonic characterization of the region. The quality of the data and the resulting image can be effectively improved by using modern tools, such as pre-conditioning techniques and seismic attributes. The latter are extensively used by the hydrocarbon exploration industry, but are still only poorly applied to the study of active faults. Pre-conditioning filters are effective in removing random noise, which hampers the detection of subtle geologic structures (i.e., normal faults). In this study, a workflow including pre-conditioning and extraction of seismic attributes is used to improve the quality of the CROP-04 deep seismic reflection profile. CROP-04 was acquired in the 1980s across the Southern Apennines mountain range, one of the most hazardous seismically active regions in Italy. The results show the capacity of this method to extract, from low-resolution legacy data, subtle seismic fabrics that correspond to a dense network of fault sets. These seismic signatures and the enhanced discontinuities disrupting the reflections, which were invisible in the original data, correlate well with the main regional normal faults outcropping at the surface. Moreover, the data reveal higher structural complexity, due to many secondary synthetic and antithetic structures, knowledge of which is useful in modeling of the local and regional distribution of the deformation and potentially in guiding future field mapping of active faults. This proposed approach and workflow can be extended to seismotectonic studies of other high-hazard regions worldwide, where seismic reflection data are available.

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