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- Volume 54, Issue 6, 2006
Geophysical Prospecting - Volume 54, Issue 6, 2006
Volume 54, Issue 6, 2006
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Comparing state‐of the art near‐surface models of a seismic test line from Saudi Arabia
Authors Ralph Bridle, Nikolai Barsoukov, Mohammad Al‐Homaili, Robert Ley and Ameerah Al‐MustafaABSTRACTWe present a seismic Test Line, provided by Saudi Aramco for various research teams, to highlight a few major challenges in land data processing due to near‐surface anomalies. We discuss state‐of‐the‐art methods used to compensate for shallow distortions, including single‐layer, multilayer, plus/minus, refraction and tomostatics methods. They are a starting point for the new technologies presented in other papers, all dealing with the same challenging data described here.
The difficulties on the Test Line are mostly due to the assumption of vertical raypaths, inherent in classical applications of near‐surface correction statics. Even the most detailed velocity/depth model presents difficulties, due to the compleX‐raypath. There is a need for methods which are based on more complex models andtheories.
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CRS‐stack‐based seismic imaging considering top‐surface topography
Authors Z. Heilmann, J. Mann and I. KoglinABSTRACTIn this case study we consider the seismic processing of a challenging land data set from the Arabian Peninsula. It suffers from rough top‐surface topography, a strongly varying weathering layer, and complex near‐surface geology. We aim at establishing a new seismic imaging workflow, well‐suited to these specific problems of land data processing. This workflow is based on the common‐reflection‐surface stack for topography, a generalized high‐density velocity analysis and stacking process. It is applied in a non‐interactive manner and provides an entire set of physically interpretable stacking parameters that include and complement the conventional stacking velocity.
The implementation introduced combines two different approaches to topography handling to minimize the computational effort: after initial values of the stacking parameters are determined for a smoothly curved floating datum using conventional elevation statics, the final stack and also the related residual static correction are applied to the original prestack data, considering the true source and receiver elevations without the assumption of nearly vertical rays. Finally, we extrapolate all results to a chosen planar reference level using the stacking parameters. This redatuming procedure removes the influence of the rough measurement surface and provides standardized input for interpretation, tomographic velocity model determination, and post‐stack depth migration. The methodology of the residual static correction employed and the details of its application to this data example are discussed in a separate paper in this issue.
In view of the complex near‐surface conditions, the imaging workflow that is conducted, i.e. stack – residual static correction – redatuming – tomographic inversion – prestack and post‐stack depth migration, leads to a significant improvement in resolution, signal‐to‐noise ratio and reflector continuity.
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CRS‐stack‐based residual static correction
Authors I. Koglin, J. Mann and Z. HeilmannABSTRACTIn the case of onshore data sets, the acquired reflection events can be strongly impaired due to rough top‐surface topography and inhomogeneities in the uppermost low‐velocity layer, the so‐called weathering layer. Without accounting for these influences, the poor data quality will make data processing very difficult.
Usually, the correction for the top‐surface topography is not perfect. The residuals from this correction and the influence of the weathering layers lead to small distortions along the reflection events. We integrated a residual static correction method into our data‐driven common‐reflection‐surface‐stack‐based imaging workflow to further eliminate such distortions. The moveout‐corrected traces and the stacked pilot trace are cross‐correlated to determine a final estimate of the surface‐consistent residual statics in an iterative manner.
As the handling of top‐surface topography within the common‐reflection‐surface stack is discussed in a separate paper in this special issue, the corresponding residual static correction will be explained in more detail. For this purpose, the results obtained with a data set from the Arabian Peninsula will be presented.
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CRS strategies for solving severe static and imaging issues in seismic data from Saudi Arabia
Authors G. Gierse, J. Pruessmann and R. ComanABSTRACTStatic shifts from near‐surface inhomogeneities very often represent the key problem in the processing of seismic data from arid regions. In this case study, the deep bottom fill of a wadi strongly degrades the image quality of a 2D seismic data set. The resulting static and dynamic problems are solved by both conventional and common‐reflection‐surface (CRS) processing. A straightforward approach derives conventional refraction statics from picked first breaks and then goes through several iterations of manual velocity picking and residual statics calculation. The surface‐induced static and dynamic inhomogeneities, however, are not completely solved by these conventional methods.
In CRS processing, the local adaptation of the CRS stacking parameters results in very detailed dynamic corrections. They resolve the local inhomogeneities that were not detected by manual picking of stacking velocities and largely compensate for the surface‐induced deterioration in the stack. The subsequent CRS residual statics calculations benefit greatly from the large CRS stacking fold which increases the numbers of estimates for single static shifts. This improves the surface‐consistent averaging of static shifts and the convergence of the static solution which removes the remaining static shifts in the 2D seismic data. The large CRS stacking fold also increases the signal‐to‐noise ratio in the final CRS stack.
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Tomographic joint inversion of first arrivals in a real case fromSaudi Arabia
Authors Gualtiero Böhm, Flavio Accaino, Giuliana Rossi and Umberta TinivellaABSTRACTA joint inversion of both first and refracted arrivals is applied on a seismic line, acquired onshore, in order to obtain a well‐resolved velocity field for the computation of static corrections. The use of different arrivals in the inversion involves exploiting the information derived from the different raypaths associated with each wave type, thus enhancing the reliability of the inversion. The data was gathered by Saudi Aramco in an area of the Arabian Peninsula characterized by strong lateral variations, both in topography and shallow velocity, and where therefore a well‐defined near‐surface velocity field is important. In addition to velocity, the depth distribution of the quality factor Q is computed from the tomographic inversion of the seismic‐signal frequency shift. Thus, the Q‐factor field is used to perform an inverse Q‐data filtering and improve the resolution of the final stacked section.
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Application of the topographic datuming operator to a data setfrom the Eastern Arabian Peninsula
Authors Claudio Bagaini and Tariq AlkhalifahABSTRACTWe apply a redatuming methodology, designed to handle rugged topography and the presence of high‐velocity layers near the acquisition surface, to a 2D land seismic data set acquired in Saudi Arabia. This methodology is based on a recently developed prestack operator, which we call the topographic datuming operator (TDO). The TDO, unlike static corrections, allows for the movement of reflections laterally with respect to their true locations, corresponding to the new datum level. Thus, it mitigates mispositioning of events and velocity bias introduced by the assumption of surface consistency and the time‐invariant time shifts brought about by static corrections. Using the shallow velocities estimated from refracted events, the TDO provides a superior continuity of reflections and better focusing than that obtained from conventional static corrections in most parts of the processed 2D line. The computational cost of applying the TDO is only slightly higher than static corrections. The marginal additional computational cost and the possibility of estimating, after TDO redatuming, stacking velocities that are not affected by a spurious positive bias, as in the case of static corrections, are further advantages of the proposed methodology. The likelihood of strong heterogeneities in the most complex part of the line limits the applicability of any approach based upon geometrical optics; however, the TDO produces results that are slightly better than those obtained from static corrections because of its ability to partially collapse diffractions generated in the near surface.
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An integrated method for resolving the seismic complex near‐surface problem
Authors M.N. Al‐Ali and D.J. VerschuurABSTRACTWe describe an integrated method for solving the complex near‐surface problem in land seismic imaging. This solution is based on an imaging approach and is obtained without deriving a complex near‐surface velocity model. We start by obtaining from the data the kinematics of the one‐way focusing operators (i.e. time‐reversed Green's functions) that describe propagation between the acquisition surface and a chosen datum reflector using the common‐focus‐point technology. The conventional statics solutions obtained from prior information about the near surface are integrated in the initial estimates of the focusing operators. The focusing operators are updated iteratively until the imaging principle of equal traveltime is fulfilled for each subsurface gridpoint of the datum reflector. Therefore, the seismic data is left intact without any application of time shifts, which makes this method an uncommitted statics solution. The focusing operators can be used directly for wave‐equation redatuming to the respective reflector or for prestack imaging if determined for multiple reflecting boundaries. The underlying velocity model is determined by tomographic inversion of the focusing operators while also integrating any hard prior information (e.g. well information). This velocity model can be used to perform prestack depth imaging or to calculate the depth of the new datum level. We demonstrate this approach on 2D seismic data acquired in Saudi Arabia in an area characterized by rugged topography and complex near‐surface geology.
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Ground viscosity and stiffness measurements for near surface seismic velocity
Authors Robert Ley, Willem Adolfs, Ralph Bridle, Mohammad Al‐Homaili, Aldo Vesnaver and Paul RasABSTRACTIn land surveys, the weathering layer can often distort the seismic signal due to it passing through rapid velocity and density changes, dispersion, scattering and inelastic absorption. In a simple spring‐dashpot model for the earth response, an equivalent medium groups these complex phenomena into two parameters only; these are called ground viscosity and ground stiffness. The most recent controllers for vibrators can estimate both parameters. To validate these measurements, Saudi Aramco conducted an experiment measuring ground viscosity and stiffness from two different vibrator control systems over an area of varying terrain conditions, including unconsolidated sand and limestone outcrop. The two systems measured different values, but detected similar trends that correlated well with weathering conditions and surface geology, e.g. lower viscosity values on the outcrop than on the sand.
The ratio of ground viscosity to ground stiffness can approximate the shallow S‐wave velocity, which we converted into P‐wave velocity through calibration with sparse uphole data. Static corrections incorporating this velocity information somewhat improved the focusing of seismic time sections. This new approach does not require additional acquisition efforts, and can model shallow complex formations in arid areas where classical static methods often fail.
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Geostatistical integration of near‐surface geophysical data
More LessABSTRACTAccurate statics calculation and near‐surface related noise removal require a detailed knowledge of the near‐surface velocity field. Conventional seismic surveys currently are not designed to provide this information, and 3D high‐resolution reflection/refraction acquisition is not feasible for large survey areas. Satellite images and vibrator plate attributes are dense low‐cost data, which can be used in spatially extrapolating velocities from sparse uphole data by geostatistics. We tested this approach in two different areas of Saudi Arabia and found that the optimal recipe depends on the local geology.
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The impact of field‐survey characteristics on surface‐relatedmultiple attenuation
Authors B. Dragoset, I. Moore and C. KostovABSTRACTField‐survey characteristics can have an important impact on the quality of multiples predicted by surface‐related multiple elimination (SRME) algorithms. This paperexamines the effects of three particular characteristics: in‐line spatial sampling, source stability, and cable feathering. Inadequate spatial sampling causes aliasing artefacts. These can be reduced by f–k filtering at the expense of limiting the bandwidth in the predicted multiples. Source‐signature variations create artefacts in predicted multiples due to spatial discontinuities. Variations from a well‐behaved airgun array produced artefacts having an rms amplitude about 26 dB below the rms amplitude of multiples predicted with no variations. Cable feathering has a large impact on the timingerrors in multiples predicted by 2D SRME when it is applied in areas having cross dip. All these problems can be reduced by a combination of better survey design, use of advanced data‐acquisition technologies, and additional data‐processing steps.
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OBC signal fidelity
Authors Michael W. Norris, Marvin L. Johnson and Mat WalshABSTRACTA suite of three tests was performed to characterize the signal fidelity of OBC 4C acquisition systems. The test methodology was to evaluate individual sensor stations by acquiring source lines that were parallel to the in‐line and cross‐line horizontal sensors and source lines that were at 45° to the in‐line and cross‐line sensors. This technique provides constant azimuth gathers with a uniform offset range and removes issues associated with source array directivity.
Characterization of the test data identified the frequency content of the geophone signals and the correlation between the vertical and cross‐line geophones as the most sensitive indicators of signal infidelity. In the former case, stations with questionable signal fidelity exhibited a very reverberatory signal. This signal was most evident on the cross‐line sensor. In the latter case, when normalized cross‐correlation coefficients are computed in a moving window, the cross‐line sensor and the vertical sensor are highly correlated, beginning several hundred milliseconds after the first arrivals.
These characteristics can be exploited to allow stations with questionable signal fidelity to be programmatically identified. One means of identifying questionable stations is to compute the histogram of the instantaneous frequency. The frequency distributions from questionable stations are unambiguously distinguishable from stations that exhibit better signal fidelity. It was noted that signal fidelity appeared as a range, between acceptable and poor. To characterize the signal fidelity of an acquisition system adequately, the number of test samples must be statistically significant.
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Sea surface shape derivation above the seismic streamer
Authors Robert Laws and Ed KraghABSTRACTThe rough sea surface causes perturbations in the seismic data that can be significant for time‐lapse studies. The perturbations arise because the reflection response of the non‐flat sea perturbs the seismic wavelet. In order to remove these perturbations from the received seismic data, special deconvolution methods can be used, but these methods require, as input, the time varying wave elevation above each hydrophone in the streamer. In addition, the vertical displacement of the streamer itself must also be known at the position of each hydrophone and at all times. This information is not available in conventional seismic acquisition. However, it can be obtained from the hydrophone measurements provided that the hydrophones are recorded individually (not grouped), that the recording bandwidth is extended down to 0.05 Hz and that data are recorded without gaps between the shot records.
The sea surface elevation, and also the wave‐induced vertical displacement of the streamer, can be determined from the time‐varying pressure that the sea waves cause in the hydrophone measurements. When this was done experimentally, using a single sensor seismic streamer without a conventional low cut filter, the wave induced pressure variations were easily detected. The inversion of these experimental data gives results for the sea surface elevation that are consistent with the weather and sea state at the time of acquisition. A high tension approximation allows a simplified solution of the equations that does not demand a knowledge of the streamer tension. However, best results at the tail end of the streamer are obtained using the general equation.
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Volumes & issues
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Volume 72 (2023 - 2024)
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Volume 71 (2022 - 2023)
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Volume 70 (2021 - 2022)
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Volume 69 (2021)
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Volume 68 (2020)
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Volume 67 (2019)
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Volume 66 (2018)
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Volume 65 (2017)
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Volume 64 (2015 - 2016)
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Volume 63 (2015)
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Volume 62 (2014)
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Volume 61 (2013)
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Volume 60 (2012)
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Volume 59 (2011)
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Volume 58 (2010)
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Volume 57 (2009)
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Volume 56 (2008)
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Volume 55 (2007)
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Volume 54 (2006)
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Volume 53 (2005)
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Volume 52 (2004)
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Volume 51 (2003)
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Volume 50 (2002)
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Volume 49 (2001)
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Volume 48 (2000)
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Volume 47 (1999)
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Volume 46 (1998)
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Volume 45 (1997)
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Volume 44 (1996)
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Volume 43 (1995)
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Volume 42 (1994)
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Volume 41 (1993)
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Volume 40 (1992)
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Volume 39 (1991)
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Volume 38 (1990)
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Volume 37 (1989)
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Volume 36 (1988)
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Volume 35 (1987)
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Volume 34 (1986)
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Volume 33 (1985)
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Volume 32 (1984)
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Volume 31 (1983)
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Volume 30 (1982)
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Volume 29 (1981)
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Volume 28 (1980)
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Volume 27 (1979)
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Volume 26 (1978)
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Volume 25 (1977)
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Volume 24 (1976)
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Volume 23 (1975)
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Volume 22 (1974)
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Volume 21 (1973)
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Volume 20 (1972)
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Volume 19 (1971)
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Volume 18 (1970)
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Volume 17 (1969)
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Volume 16 (1968)
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Volume 15 (1967)
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Volume 14 (1966)
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Volume 13 (1965)
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Volume 12 (1964)
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Volume 11 (1963)
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Volume 10 (1962)
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Volume 9 (1961)
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Volume 8 (1960)
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Volume 7 (1959)
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Volume 6 (1958)
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Volume 5 (1957)
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Volume 4 (1956)
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Volume 3 (1955)
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Volume 2 (1954)
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Volume 1 (1953)