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the original data. Processing models must
therefore be chosen carefully and interac-
tion between the processor and the inter-
preter encouraged.
The results of the image analysis imply
that there is a threshold at which seismic
image data are too indeterminate (i.e., not
enough contrast or continuity) to drive the
interpretation. Quantitative image analy-
sis could be used to determine the extent
of an interpretation that is data-supported
and areas that are more subjective. To
create interpretations for under-con-
strained problems, reference models, such
as fold or fault shape, can be employed.
These reference models can be based on
mechanical and geometric rules: e.g.,
angle of faulting, based on Andersonian
mechanics (Anderson, 1905, 1951), or
depth to detachment for faults
(Chamberlin, 1910), based on mass bal-
ance principles (Dahlstrom, 1969; Elliott,
1983). Indeed, Bond et al. (2012) show
that in areas of poor constraint, simple
geological reasoning and reconstruction
analysis can be used to reduce interpreta-
tion uncertainty. The method proposed in
this work opens the door for a workflow
for image quality assessment to indicate
those occasions when model-based inter-
pretation (e.g., fault geometry prediction
at depth) may be more robust than the
subjective fault interpretation of a geolo-
gist. Of course, these two approaches are
complementary: image analysis may aid
the interpreter in determining when geo-
metric modeling may be useful and when
interpretation uncertainty, and therefore
potential risk, is high.
Even in the advent of more complex
visualization through computing and
screen technology, including the use of
color and a greater pixel spectrum, inter-
pretation uncertainty is determined by the
quality of a seismic image. Understanding
the impact of image quality on seismic
interpretation using an 8-bit grayscale
image provides a basis from which to
investigate more complex aspects of visual
perception, including color and lumines-
cence. This work requires interdisciplin-
ary research with cognitive scientists, neu-
rologists, and others to fully understand
how best to represent seismic imagery to
maximize interpretation efforts.
A key finding of our experiments is
that there are significant variations in the
interpretation of fault geometries as depth
increases in the section. This reflects the
decay in image quality with depth. This
uncertainty may be important—for exam-
ple in picking the hanging-wall cut-offs of
stratal reflectors on normal faults to cor-
relate with those in the footwall that are
otherwise well-imaged. This, in turn,
influences determinations of fault
heave—information that is critical for
constructing maps that show fault link-
ages in sedimentary basins and for deter-
mining net extension of the upper crust.
These inherent uncertainties arising from
image quality are generally unreported in
larger-scale studies of fault patterns.
Therefore, the maps and net extension
calculations used in many tectonic studies
carry unknown errors.
ACKNOWLEDGMENTS
BP/GUPCO are acknowledged for providing
data from the Gulf of Suez. The authors acknowl-
edge the support of MVE and use of Move soft-
ware 2015.2 for this work. Ruediger Kilian is
acknowledged for his kind help with the ImageJ
code. Dr. Juan Alcalde is funded by NERC grant
NE/M007251/1, on interpretational uncertainty.
The work could not have been completed without
the support of individuals within the geoscience
community who took part in the interpretation
experiment.
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