relation: https://khub.utp.edu.my/scholars/13092/
title: Inspiration for seismic diffraction modelling, separation, and velocity in depth imaging
creator: Bashir, Y.
creator: Muztaza, N.M.
creator: Alashloo, S.Y.M.
creator: Ali, S.H.
creator: Ghosh, D.P.
description: Fractured imaging is an important target for oil and gas exploration, as these images are heterogeneous and have contain low-impedance contrast, which indicate the complexity in a geological structure. These small-scale discontinuities, such as fractures and faults, present themselves in seismic data in the form of diffracted waves. Generally, seismic data contain both reflected and diffracted events because of the physical phenomena in the subsurface and due to the recording system. Seismic diffractions are produced once the acoustic impedance contrast appears, including faults, fractures, channels, rough edges of structures, and karst sections. In this study, a double square root (DSR) equation is used for modeling of the diffraction hyperbola with different velocities and depths of point diffraction to elaborate the diffraction hyperbolic pattern. Further, we study the diffraction separation methods and the effects of the velocity analysis methods (semblance vs. hybrid travel time) for velocity model building for imaging. As a proof of concept, we apply our research work on a steep dipping fault model, which demonstrates the possibility of separating seismic diffractions using dip frequency filtering (DFF) in the frequency-wavenumber (F-K) domain. The imaging is performed using two different velocity models, namely the semblance and hybrid travel time (HTT) analysis methods. The HTT method provides the optimum results for imaging of complex structures and imaging below shadow zones. © 2020 by the authors.
publisher: MDPI AG
date: 2020
type: Article
type: PeerReviewed
identifier:   Bashir, Y. and Muztaza, N.M. and Alashloo, S.Y.M. and Ali, S.H. and Ghosh, D.P.  (2020) Inspiration for seismic diffraction modelling, separation, and velocity in depth imaging.  Applied Sciences (Switzerland), 10 (12).   ISSN 20763417     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85087349193&doi=10.3390%2fapp10124391&partnerID=40&md5=708cc84855a2e3b24af64b66c1bf7fd1
relation: 10.3390/app10124391
identifier: 10.3390/app10124391