Seismic the sequence stratigraphic interpretation of a fluvial

Seismic attributes are routinely used by
geophysicist to assist seismic stratigraphic analyses. Barnes (2000) employed
instantaneous seismic attributes to quantify seismic stratigraphic facies
parameters. Randen et al., (1998) introduced a new technique that detects
intersections of bedding configurations in seismic reflection profiles using seismic attributes. These intersections are
believed to record stratal terminations such as onlaps, downlaps, erosional truncations, and toplaps. Gutiérrez (2001)
improved the sequence stratigraphic interpretation of a fluvial system by using
seismic inversion of 3D seismic data. Barrash and Reboulet (2004) used porosity
data to investigate stratigraphic units. Contreras and Latimer (2010) used
acoustic impedance as an additional attribute for sequence stratigraphy. Van
Hoek et al. (2010) used geometric seismic attributes in seismic stratigraphic
analysis. Khalifa and Alta’ee (2011) obtained the stacking of parasequences
based on variations in porosity. Miller et al.

(2013) proposed that sequence-bounding unconformities are
linked with abrupt changing surfaces of acoustic impedance.

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In past decades, several methods have been proposed for
picking horizons automatically. Maroni et al. (2001) introduced an
automatic horizon-picking algorithm to map sediment layers on subbottom
profiles. Their method is based on multi-resolution analysis through the wavelet
transform which decomposes a signal into different scale components. Faraklioti
and Petrou (2004) presented an automatic picking algorithm based on a surface detection technique. They used voxel connectivity method which
relates voxels to their neighbors. They first identified small horizon
fragments using connected component analysis. They then combined the fragments
according to their orientation similarity to form horizons across the whole
seismic survey. Yu et al. (2011) introduced a method for horizon picking
using a pattern recognition algorithm, which can effectively pick a coherent horizon
in 3D seismic data. Their method uses an orientation vector field (OVF of Yu et
al., 2011) to select a pick within a trace to preserve the lateral continuity
among seismic traces. They used the minimum-spanning tree algorithm (MST of
Boruvka, 1926; Nesetril et al., 2001) to select the optimized traces. The
method can reduce the interpretation time and improve the quality for automatic
horizon picking. Wu and Hale (2015) used user-predefined
seeds to semi-automatically pick the horizons.
Their method is limited to the accuracy
of the structure tensor computation.

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