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- Volume 24, Issue 9, 2006
First Break - Volume 24, Issue 9, 2006
Volume 24, Issue 9, 2006
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It’s far from over for UK oil and gas exploration and production
A more optimistic note compared with previous years is sounded in the UK Offshore Operators Association (UKOOA) 2006 economic report entitled Energy Now and for the Future.It states among other things that the target of producing 3 million barrels of oil equivalent per day in 2010 is now likely to be met. In this extract, we include the report’s Foreword and the section on the Outlook for the UKCS in 2006.
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Application of reverse time migration to complex imaging problems
Authors P.A. Farmer, I.F. Jones, H. Zhou, R.I. Bloor and M.C. GoodwinPaul A. Farmer, Ian F. Jones, Hongbo Zhou, Robert I. Bloor, and Mike C. Goodwin explain the revival of interest in reverse time migration with some examples from the North Sea of model building and migrating with the full acoustic two-way wave equation. Standard shot-based one-way wavefield extrapolation (WE) preSDM techniques image the subsurface by downward continuing the source and receiver wave-fields for each shot. The imaging condition is invoked by cross correlating these two wave-fields at each depth level, and then summing the contributions from all shots in the aperture to form the image. One of the assumptions made in using this technique is that the wave-fields travel along the direction of extrapolation only in one direction: downwards for the source wave-field, and upwards for the receiver or scattered wave-field. In practice, each of these wave-fields will generally travel both up and down when the velocity model is complex, when turning (diving) ray-paths are involved, or when multiples are being generated. In addition, approximations in the extrapolation techniques usually limit the dips present in the final image to less than seventy degrees. Steeper dips, and turning rays are usually imaged using Kirchhoff techniques, but these fail to deliver acceptable images once we have a multi-pathing problem. One technique which can address all these issues is migration using the two-way wave equation. Here, we have used an anisotropic reverse time migration (RTM) algorithm to achieve this. RTM properly propagates the wave-field through velocity structures of arbitrary complexity, correctly imaging dips greater than 90 degrees. It even has the potential to image with internal multiples when the boundaries responsible for the multiple are present in the model. Although hitherto considered economically impracticable, recent enhancements to computing capacity, both in terms of CPU speeds and highly efficient hardware infrastructure, have made RTM commercially viable. Following an historical review of the approximations used in migration, we will show anisotropic RTM examples from the North Sea, outlining the potential benefit of model building and migrating with the full acoustic two-way wave equation.
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Wave equation multiple modelling: acquisition independent 3D SRME
Authors T. Weisser, A.L. Pica, P. Herrmann and R. TaylorTerje Weisser, Antonio Pica, Philippe Herrmann, and Roger Taylor of CGG discuss the case for an alternative approach to 3D surface-related multiple elimination which does not require dense acquisition and has a number of applications including the processing of legacy data for 4D seismic monitoring. Marine seismic data acquired over structured or rugose seafloors contain complex multiple wave-fields, and in deep water this multiple energy may contaminate our target zone, either directly by overlaying it or indirectly as the migration process smears the energy up across shallower events. Recent advances in de-multiple processing technology have seen the industry move to full 3D surface related multiple elimination (3D SRME) to better deal with these complex multiple wavefields. But this has come at some cost as 3D SRME techniques generally perform better with high-density acquisition and require heavy interpolation pre-processing. We present a test of CGG’s alternative approach to 3D SRME to determine whether high density acquisition is a necessity for effective 3D SRME, or an unnecessary expense.
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A comparison of NMO curves for application in VTI media
By J. StarrJoel Starr, PGS Marine Geophysical, evaluates the increasing range of NMO options avail able for today’s seismic data processors. NMO, or normal moveout, is the time shift needed to correct for the effect of offset and velocity in a CMP gather. NMO equations approximate the time shift which would be computed by tracing a ray through a horizontally layered Earth. A few years ago the 2nd order NMO equation, or hyperbolic NMO, was considered adequate in most cases. Today there are many options in the industry to apply higher order NMO which reduces the error in the approximation to the ray traced solution for longer offsets. There are two characteristics which are important when considering the application of a given NMO curve: 1) accuracy; how well the NMO curve approximates the ray traced solution, and 2) stability; how well the curve can tolerate small errors in the estimated velocity field (one would not want small errors in the estimated velocity field to cause large errors in the move-out time calculated). If the data being processed is isotropic in nature, then the NMO equation will be dependent on velocity, v and offset x.
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Emerging technology for quantifying minimal anisotropy
Authors C. Barrientos, E. Wielemaker, T.J. Plona, J.B.U. Haldorsen, P. Saldungaray and L. Arroyo FrancoUntil recently, reliable measurement of anisotropy magnitude and orientation was possible only when the velocity anisotropy was greater than 5%. Carlos Barrientos, Erik Wielemaker, Thomas Plona, Jakob Haldorsen, and Pablo Saldungaray (Schlumberger) and Jose Luis Arroyo Franco (Pemex) show how quantification of anisotropy of less than 5% is possible by means of improved transmitters and additional receivers (both axial and azimuthal). Quantification of anisotropy as small as 1% is now not only possible but can be achieved through the use of either sonic or seismic methods. Such information is crucial in determining stress direction for well placement and for application of oriented perforating techniques. The ability to detect minimum anisotropy also aids in identification of in-field drilling opportunities in mature fields and to maximize fracture treatments. The Pemex Cuitlahuac field in the Tertiary Burgos Basin in the northeastern corner of Mexico was selected to demonstrate the mechanisms of anisotropy detection because of its formations in which the targets are tight and laminated gas sands deposited in a flu-vio-deltaic environment. Evidence of weak acoustic anisotropy using data acquired with a new modular sonic tool as well as borehole seismic data generated by shear vibrators is presented. Also, two different mechanisms of anisotropy, differing in magnitude and direction, are described.
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New approach to common reflection surface and depth imaging: Tembungo Field, Sabah, Malaysia
By A.R. GhazaliThe Tembungo Field area is located about 100 km offshore Sabah, in eastern Malaysia (Figure 1). Geologically, it is a folded anticlinal structure with intense flower-type faulting. The exploration target is a deep turbidite complex in Miocene basin slope fan system. The velocity field in the overburden is severely complicated by the presence of near-surface reef carbonates, gas wipeout and complex faulting. These complications result in strong energy scattering, low signal to noise (S/N) ratio and strong multiple energy that lead to a significant deterioration of the seismic image over the field and across the whole general area. Processing, including the use of prestack depth migration (PreSDM) with a view to extracting adequate signal under these circumstances, has been fraught with difficulties. The commercial importance of the Tembungo Field was a major incentive for seeking ways of resolving the above imaging issues. A new approach that we devised and adopted proved to be immensely successful. The approach consisted of processing the data with Common Reflection Surface (CRS) technology followed by post-stack depth migration (PostSDM) in which the provelocity model was obtained through a pre-stack depth migration (PreSDM) process. The term ‘provelocity’ will be used in the present work specifically to denote the parameter derived from seismic processing as ‘velocity’ because this is a modelling parameter that can be quite different from the true propagation velocity in the ground (Al-Chalabi, 1994). Unlike conventional PreSDM, which aims at enhancing the image of the subsurface, the process in the present case was exclusively employed to produce an optimum PostSDM provelocity model. This is perhaps the most significant ‘innovation’ in the present work. It is driven by the fact that CRS is more amenable to post-stack than to pre-stack processes. Figure 2 shows the overall workflow of the approach. CRS has already established itself as an effective technique for enhancing S/N ratio. The CRS technique was introduced by Müller (1998) as a data driven zero-offset simulation method. Hubral (1999) then refined the technique and followed the strategy of a macro model independent imaging principle. The technique uses larger stacking surfaces rather than relying on a single CMP stack location as in conventional stacking processes. This improves the emergence angle and wavefront curvatures approximation, utilizing seismic wavefield and travel time information. The parameter derivations are based on second order travel time estimations which utilize multi-dimensional global maximum of the coherency function.
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Quantitative characterization of seismic thin beds: a methodological contribution using conventional amplitude and seismic inversion
Authors M. Fervari and F. LuoniIn the last decades, the interest in thin hydrocarbon reservoirs has grown progressively justifying the great effort spent on developing techniques for quantitative interpretation of thin beds seismic response (Widess, 1973; Kallweit and Wood, 1982). Neidell and Poggiagliolmi (1977) and Meckel and Nath (1977) identified seismic amplitude and apparent thickness as the key elements to describe complex waveforms in thin layers environments. They suggested using this information to predict net thickness wherever well data are available for calibration. This approach was further developed introducing a stratigraphic modelling procedure to systematically investigate the relationship between layers geometry-lithology and seismic response (Schramm, Dedman, and Lindsey, 1977). In the mid eighties, interactive interpretation using workstations allowed the quantitative analysis techniques to be extended to 3D seismic data. Brown et al. (1986) in their classic publication proposed using statistical tuning curves (derived by interactive cross plotting) and deterministic curves (by wavelet extraction) to remove the geometric effects of thin beds from seismic amplitudes. The detuned amplitudes were then input to map the net gas sand thickness. In the recent past, Neff (1990 and 1993) has implemented a workflow for reservoir characterization based on seismic and petrophysical modelling (incremental pay thickness modelling). This approach enable the mapping of gross pay, net pay, net porosity, and hydrocarbons in place for clastic and carbonatic reservoirs. Conceptually, this procedure is absolutely necessary whenever layer thickness makes the amplitude interpretation less intuitive and the definition of a reservoir quality indicator more difficult. In this article we have extended the analytical approach for thin beds evaluation to the three AVO classes (Rutherford and Williams, 1989). Since we were mainly interested in the methodological aspects of seismic thin beds characterization, we have chosen to follow an approach based on both forward and inverse wedge modelling, that combines rock physics and tuning analysis for a petrophysical interpretation of the tuning curves. For each AVO class we defined a reference model starting from deepwater real data. Then we investigated (1) which reservoir quality indicator (net to gross, porosity, net thickness, and porosity thickness) could be predicted from seismic amplitude and apparent thickness and be quantified after tuning charts calibration and (2) how reliable are two common practices of seismic lithology, namely reservoir quantification (i.e. prediction of specific petrophysical parameters from seismic derived elastic attributes) and classification (i.e. facies discrimination based on the inverted elastic attributes). Finally, we illustrate two examples of thin beds reservoirs quantification both in the development and appraisal phases.
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Volumes & issues
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Volume 42 (2024)
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Volume 41 (2023)
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Volume 40 (2022)
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Volume 39 (2021)
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Volume 38 (2020)
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Volume 37 (2019)
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Volume 36 (2018)
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Volume 35 (2017)
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Volume 34 (2016)
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Volume 33 (2015)
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Volume 32 (2014)
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Volume 31 (2013)
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Volume 30 (2012)
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Volume 29 (2011)
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Volume 28 (2010)
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Volume 27 (2009)
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Volume 26 (2008)
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Volume 25 (2007)
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Volume 24 (2006)
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Volume 23 (2005)
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Volume 22 (2004)
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Volume 21 (2003)
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Volume 20 (2002)
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Volume 19 (2001)
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Volume 18 (2000)
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Volume 17 (1999)
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Volume 16 (1998)
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Volume 15 (1997)
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Volume 14 (1996)
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Volume 13 (1995)
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Volume 12 (1994)
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Volume 11 (1993)
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Volume 10 (1992)
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Volume 9 (1991)
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Volume 8 (1990)
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Volume 7 (1989)
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Volume 6 (1988)
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Volume 5 (1987)
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Volume 4 (1986)
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Volume 3 (1985)
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Volume 2 (1984)
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Volume 1 (1983)