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RESEARCH ARTICLE

Analysis of crooked-line 2D seismic reflection data recorded in areas with complex surface and subsurface conditions

Ionelia Panea 1 3 Delia Bugheanu 2
+ Author Affiliations
- Author Affiliations

1 Faculty of Geology and Geophysics, University of Bucharest, 6 Traian Vuia Street, Bucharest 020956, Romania.

2 Faculty of Environment, University of Leeds, Leeds, LS2 9JT, UK.

3 Corresponding author. Email: ipanea2@yahoo.com

Exploration Geophysics 48(4) 493-503 https://doi.org/10.1071/EG15107
Submitted: 15 October 2015  Accepted: 4 August 2016   Published: 1 September 2016

Abstract

We analysed a crooked-line two-dimensional (2D) seismic reflection dataset recorded in the northern part of the Eastern Pannonian Basin using a different processing flow than the one typically used in hydrocarbon exploration studies, with the purpose of obtaining high-resolution images for the depth interval of interest. The data acquisition was done using irregular spacing between receivers and sources due to the rough topography and complicated geological structure. As an effect of data acquisition, the midpoints were spread over an area with a width of ~900 m on the central part of the seismic profile. A significant number of field records contained noisy first arrivals on the offset interval used in the computation of static corrections. We defined two types of geometry: one for a 2D crooked-line and another for a pseudo-3D survey; then, we used the same processes and parameters during processing. For the noisy field records, we used refraction interferometry (RI) by cross-correlation and convolution to enhance the first arrivals and to better control picking of the first-arrival traveltimes. We show that the continuity of the supervirtual first arrivals depends on the number of records, with noisy and clear first arrivals used as input to RI. Comparing the pre- and post-stack data, represented by filtered common-depth-point (CDP) gathers and time sections, respectively, we notice that the use of pseudo-three-dimensional (3D) geometry helps us to improve the signal-to-noise ratio (SNR) of pre- and post-stack data, and to image the main geological marker reflections in the investigated area.

Key words: head waves, processing, seismic reflection, statics.


References

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