Advances in interbed multiples prediction and attenuation: Case study from onshore Kuwait
Adel El-Emam* and Khaled Shams Al-Deen, Kuwait Oil Company; Alexander Zarkhidze and Andy Walz,
WesternGeco
Introduction
Multiples contamination both surface and interbed related
is a problem in almost all Middle East basins. The high
acoustic impedance of carbonates and anhydrites layered
with clastics is the major generator of these interbed
multiples. These types of multiples are known to hinder the
interpretation, fracture characterization, and inversion
studies; they significantly complicate both the structural
and stratigraphic interpretation within the zone of interest at
the Cretaceous level as well as at the frontier Jurassic and
Permian sections (El-Emam et al., 2001). Previous work
has demonstrated marginal success in attenuating the main
interbed multiples using the 1D multiple modeling
technique post-migration thorough the analysis and
identification of the major multiple generators using well
data (El-Emam et al., 2005).
This paper presents a case study describing the application
of several data-driven multiple attenuation techniques using
more advanced true-azimuth algorithms prior to prestack
migration. The algorithms applied in this study are general
surface multiple prediction (GSMP), extended interbed
multiple prediction (XIMP) and deterministic interbed
demultiple (DID). Multiple modeling and subtraction were
performed on a high-resolution full-azimuth dataset
acquired in northwest Raudhatain oil field, onshore Kuwait.
Study Area
A full-azimuth 3D survey with square-patch geometry was
acquired over 115 km2 in northwest Raudhatain oil field,
(Figure 1), using a point-receiver acquisition system. The
point-receiver interval was 6.25 m, staggered in four sublines to output 25-m group intervals after digital group
forming (DGF).
The full-azimuth, square-patch geometry with shot-line and
receiver-line intervals of 200 m and station intervals of 25
m yielding a nominal fold over 900 was considered the
most suitable design for this study, (Figure 2).
Figure 2: Source-Receiver location map (to the right) and
geometry template (to the left).
Surface-related multiple analysis and prediction
Prior to any multiple removal attempts, careful
preconditioning is required to ensure the best possible
signal-to-noise ratio. Several passes of ambient and
coherent noise attenuation and intra-array perturbation
corrections before digital group forming were performed to
enable generating reliable multiple models.
In order to effectively handle the multiples present in the
data, the sequence started by addressing the surface-related
multiples. 3D GSMP was used to predict and adaptively
subtract the surface multiples. The advantage of this
technique is that, almost no preconditioning is required in
terms of interpolation, regularization, and extrapolation;
these are carried out on-the-fly and all calculations were
done from the smoothed surface, consequently this
technique has minimal assumptions and successfully
overcomes the challenges of sparse, missing, or irregularly
spaced traces (Moore et al., 2008).
This algorithm predicts the multiples at true azimuth,
ensuring that the multiples model accurately matches the
multiples in the input data. Figure 3 shows an example of a
prestack time migration stack section before and after the
process.
Figure 1: NW Raudhatain oil field survey location map.
© 2011 SEG
SEG San Antonio 2011 Annual Meeting
3546
Interbed multiples prediction and attenuation
Although the results do not show a significant difference on
the stack data, it is an important step in the multiple
attenuation workflow because all the subsequent interbed
multiple attenuation algorithms assume that the data are
free of surface multiples. Figure 4 is an example of gathers
and Figure 5 gives semblance plots that demonstrate that
the surface-related multiples are mainly represented by a
slow trend and are well attenuated by this technique.
amplitude, and phase errors that must be adaptively
matched to the input reference data before subtraction. The
various interbed multiple models predicted using XIMP
and DID were simultaneously and adaptively matched to
the input seismic data using least-squares filters and
subtracted. This approach provided the ability to match
each model in a window, and the results were determined
by taking into account the quality of each multiple model.
Interbed multiple analysis and prediction
Conclusions
The XIMP algorithm is similar to the 3D GSMP and has
most of its advantages. It is a true-azimuth 3D algorithm
based on the method described by Jakubowicz (1998). The
technique has the same requirements as conventional
interbed multiple prediction (IMP) methods; it still requires
identification of the multiple generators, but the iterative
top-down methodology required in the past was replaced by
simultaneous prediction for all identified generators. The
adaptive subtraction workflow was modified to account for
the simultaneous prediction. Several horizons were
identified as multiple generators: namely Dammam, Rus,
Hartha, Mutriba, Mishrif, Ahmadi, Mauddud, Zubair,
Minagish, and Gotnia, these horizons were interpreted on
the pre-migrated stack data for the entire volume. Each
horizon was then used to predict its relevant multiples.
Figure 6 shows two examples of the predicted multiple
models generated by the Rus and Mutriba formations.
Multiple contaminations in Kuwait seismic data impact the
structural and stratigraphic mapping accuracy and reservoir
characterization reliability within known reservoir
formations. Previous studies concluded that those multiples
cannot be easily attenuated using conventional methods; it
was also concluded that these multiples respond well to the
data-driven techniques such as IMP.
Due to the relatively low signal-to-noise ratio of the
shallow data, and to address specifically the Dammam-toRus multiple generating interval, the DID technique was
employed. Originally designed to handle shallow watercolumn related multiples, it was later adopted to attenuate
interbed multiples (Moore et al., 2006). This algorithm is
designed to be applied in cases where the period of the
multiple is already known. This technique employs a
model-driven, non-linear multiple prediction approach and
accurately derives both first- and higher-order multiple
amplitudes.
The subtraction of various combinations of these multiple
models was tested using different QC tools such as
semblance plots and well ties to determine the most
appropriate results. Ultimately, the models from only
seven generators (Dammam, Rus, Hartha, Mutriba, Mishrif,
Ahmadi, and Mauddud) were identified as the major
contributors to the multiple contaminations and used for
final subtraction.
Adaptive subtraction
For various reasons such as imperfect geometry, inadequate
sampling of wavefield, the assumptions of the algorithms,
low signal-to-noise ratio, complexity of the geology, and
others, the multiple models will always have some timing,
This case study demonstrates the use of the latest industry
multiple attenuation techniques that utilize 3D true-azimuth
data-driven algorithms with no need for regularization or
interpolation and produce superior results. In addition, all
multiple attenuation algorithms are applied prestack and
pre-migration; consequently, the subsequent velocity model
building, subsurface imaging, and prestack inversion are
deemed to be more robust in the absence of the multiples.
The results have been verified through various QC tools
including well ties (Figure 7) and seismic inversion; it is
clearly shown that those multiples have not only been
successfully attenuated in the reservoir level, but also in the
overburden.
The impact of effective multiple attenuation helps in
improving the seismic image of the deep Jurassic targets
below the salt and anhydrites of the Gotnia, which leads to
better fault imaging and fracture interpretation by means of
fracture cluster tracking and azimuthal analysis of different
attributes, ultimately obtaining a better understanding of the
hydrocarbon reservoir.
Acknowledgements
The authors thank Kuwait Oil Company and the Kuwait
Ministry of Oil for their kind permission to publish this
paper. Thanks also to Zhiming (James) Wu, Sonika, Bill
Dragoset, Fred Hugand, Bruce Hootman, and Paul Ras for
their input and support as well as to the WesternGeco
Kuwait data processing center for preprocessing the data.
Special thanks extend to Mr. Wael Zahran; Senior
Geophysicist in KOC for reviewing and commenting on the
abstract.
© 2011 SEG
SEG San Antonio 2011 Annual Meeting
3547
Interbed multiples prediction and attenuation
Figure 3: Prestack time migration stack before (left) and after (middle) GSMP, and after internal demultiple (right).
High velocity interbed
multiple
Slow velocity surface
multiple
Figure 4: Gather (from left to right): before GSMP, after GSMP, after interbed demultiple, and all multiples model.
Figure 5: Semblances; before GSMP (left), after GSMP (middle), and after interbed demultiple (right).
© 2011 SEG
SEG San Antonio 2011 Annual Meeting
3548
Interbed multiples prediction and attenuation
Figure 6: Raw interbed multiple models: Rus (left) and Mutriba (right).
Figure 7: Well tie before (left) and after (right) interbed multiple attenuation.
© 2011 SEG
SEG San Antonio 2011 Annual Meeting
3549
EDITED REFERENCES
Note: This reference list is a copy-edited version of the reference list submitted by the author. Reference lists for the 2011
SEG Technical Program Expanded Abstracts have been copy edited so that references provided with the online metadata for
each paper will achieve a high degree of linking to cited sources that appear on the Web.
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© 2011 SEG
SEG San Antonio 2011 Annual Meeting
3550