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- Volume 21, Issue 5, 2003
First Break - Volume 21, Issue 5, 2003
Volume 21, Issue 5, 2003
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3D visualization continues to advance integrated interpretation environment
Authors H. Chambers and A.L. BrownHank Chambers, systems development director, integrated interpretation, and Alan Lee Brown, product manager, stratigraphic and petrophysical interpretation, Landmark Graphics Corporation, maintain that 3D visualisation is providing the catalyst to improved interpretation of E&P data through integrated workflows.
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Seeking the solution to cross-platform, cross-vendor data interoperability
By P. NeriPhilip Neri, integration solutions director, Paradigm looks at the issues in achieving multi-vendor data interoperability in oil and gas E&P operations and describes the integration framework which Paradigm has developed to resolve this longstanding problem
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Why momentum is building for better data management in exploration
More LessTim Dobush and Troy Wilson of Geosoft, a company specializing in geospatial solutions and software for managing large volumes of data in the earth sciences industry, provide an example from the mining exploration industry to illustrate the need for companies to better manage and integrate their date for productivity gains.
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WWF report advises caution on Norway’s offshore oil ambitions in the Barents Sea
The offshore oil and gas industry worldwide faces increasing pressure from environmentalists. A case in point is future development of prospective areas of the Barents Sea, where the World Wildlife Foundation is campaigning against oil and gas activity in sensitive areas. First Break reports on its objections. Wildlife in the Barents Sea, Europe’s so-called last unspoiled sea, is under threat from offshore oil and gas development. That’s the gist of a report just published by the World Wildlife Fund (WWF) Arctic Programme which points a finger of suspicion at the Norwegian government and oil industry. It states that the most environmentally vulnerable areas of the Barents Sea are in the exact same areas where new oil and gas development is set to take place. The report, The Barents Sea: a sea of opportunities and threats, maps the most biologically vulnerable areas of the Barents Sea against planned petroleum- related activities and shows an overlap between the two. The Barents Sea, which lies between Spitsbergen (Svalbard), Norway and Russia, is described as Europe’s last unspoiled marine environment, home to unique sea bird colonies, including one of the world’s largest puffin colonies, huge reefs, including the biggest cold water reef in the word, large populations of seals, whales and polar bears. It is one of the few ecosystems in Europe still relatively intact, according to WWF. WWF claims that the oil industry, including companies such as Statoil and Agip, has been lobbying the Norwegian Government to open the Barents Sea to oil and gas development and opposes plans for petroleum-free zones, arguing that oil companies can operate without harming the environment.
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VTI analysis on crosswell seismic data
More LessMany studies of anisotropy have been based on the detection and analysis of the signal from shear wave birefringence (or splitting) in two component or four component data. In general, this type of signal is weak and difficult to detect. The special layout in a crosswell seismic survey makes it possible to acquire the direct SH and SV wave using a 3C borehole receiver system. The possibility of anisotropy analysis using such a dataset was investigated with data acquired by the China National Petroleum Corporation in 1997. The stratified data we studied are in the cretaceous, and include the Yao-jia and Qing-shankou formations in this area. Drilling results indicate that the Yao-jia Formation is generally sand rich with delta sedimentary environments in the depth interval, 150-182 m. The Qing-shankou formation can be divided into (Q2+3) and Ql members and is composed of limestone and alternating layers of mudstone and shale, with deep lake subfacies and turbidity current environments in the depth interval 182-302 m. In the data acquisition procedure, we used two downhole sources, which were based on different working principles: (a) weight drop and (b) downhole vibrator. The data were recorded using a three-level array receiver system with 3C geo-phones. The data acquired with two different sources at the same observation interval showed good consistency. Velocity tomography, reflection imaging and Q-factor tomography was performed on 40 CSG (Common Source Gather) data of P wave. However, a single 3C CSG data set that included direct shear wave with a high ratio of S/N was used for analysis of anisotropy. By performing 3C reorientation on these data, the direct SH and SV wave were separated. Because of the high S/N in the CSG, we were able to pick the first breaks of SH and SV wave to perform interval velocity inversion. The inversion procedure was stable and convergent. We found that the difference between Vsh and Vsv was not a constant. This raised the possibility that it might be caused by anisotropy of the formation. We show that the Vsh and Vsv ratio calculated from direct shear recorded on 3C geophones is a reliable indicator for the analysis of anisotropy.
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The implications of anisotropy for seismic impedance inversion
Authors P. Rowbotham, D. Marion, R. Eden, P. Williamson, P. Lamy and P. SwabySeismic inversion is an established technique for deriving acoustic impedance (AI) from seismic data using well log information as a low frequency constraint. However, within anisotropic strata e.g. shale, velocity logs measured in deviated wells will typically exhibit higher velocities than would have been recorded in vertical boreholes (Furre and Brevik 1998; Hornby et al. 1999). If this effect is not corrected for before building a low frequency impedance model for seismic inversion, impedance results will be biased around deviated well trajectories. Since this is quite a subtle effect, the unwary interpreter might assign geological meaning to inversion artefacts. In this paper we demonstrate a simple but effective method for correcting deviated well AI logs for anisotropic effects. We know that others have performed similar but more sophisticated corrections (e.g. Vernik 2001; Vernik and Fisher 2001), but are not aware of this pitfall with deviated wells being widely acknowledged. Further, we consider the implications of the revealed anisotropy for single and simultaneous angle-stack (elastic impedance (EI)) inversions and propose workflows for compensating for anisotropy. Seismic impedance inversion has become an integral part of the reservoir characterisation workflow, since interpretation and quantification of reservoir rock properties is made using AI layer data rather than seismic amplitudes which relate to AI contrasts (van Riel, 2000). Recently seismic AVO data have also been inverted, bringing additional constraints on reservoir properties, since knowledge of the elastic rock properties can improve lithological and/or fluid reservoir characterisation over the use of AI alone. Two main families of inversion methods have developed, which we will classify as deterministic and stochastic. In general, deterministic methods search for a single global optimum, with an objective function being the mismatch between seismic and synthetic data. By their nature, the resulting AI volume will have a high frequency spectrum determined and limited by the seismic data, and a low frequency spectrum derived from the well data. By contrast, the high frequency limit of AIs generated by stochastic methods is raised beyond the seismic spectrum using the high frequency content of well logs coupled with geostatistics. These AI results are therefore non-unique, making them suitable for statistical uncertainty analysis on many high-resolution models. Both deterministically- and stochastically-generated AIs are subsequently converted to models of reservoir properties (porosity, Vshale etc) via upscaled petro-elastic relationships. Final results include 3D models of reservoir properties and associated uncertainties that reflect uncertainties on seismic inversion results and petro-elastic relationships. To date, there has been relatively little consideration of the impact of anisotropy on impedance inversion, despite the increasingly widespread acceptance that sedimentary rocks, and in particular shales, are often quite strongly anisotropic (e.g., Thomsen, 1986). This is presumably due to the fact that until now most inversion work has been focused on zero/near-offset cubes with (near-) vertical wells in relatively calm structural environments, where the impact of anisotropy can largely be factored out in the wavelet calibration step. However, as the community begins to consider AVO and the inversion of far-offset substacks (e.g., Vernik 2001), it will become increasingly important to estimate and account for anisotropy at various stages of the processing. In this paper we first consider the discrepancies between real AI logs from adjacent vertical and deviated wells. We then describe a correction to the deviated logs assuming an anisotropic model dependent on the proportion of shale, and show the effect of this correction on the inversion results. Finally, we consider the implications of anisotropy for EI and simultaneous AVO inversion. Even though we have used the geostatistical inversion method (Haas and Dubrule 1994; Dubrule et al. 1998), all impedance inversion techniques benefit from accounting for anisotropy revealed by deviated well logs.
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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)