Seismic characterization of a Mississippi Lime resource play in Osage County, Oklahoma, USA

Dowdell, Benjamin L.; Kwiatkowski, J. Tim; Marfurt, Kurt J.

doi:10.1190/int-2013-0026.1

Cited by 11 publications

(3 citation statements)

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“…This migration-SOF-demigration process is iterated three times, providing acceptable convergence of the least-squares misfit function (see Guo et al [2012] for such analysis). We observed that in Figure 10a, a low-amplitude strip exists in Dowdell et al, 2013) showing (a) a vertical line through the prestack timemigrated data and (b) a horizon slice along the top Ellenburger through coherence volume. The coherence image is particularly noisy.…”

Section: Applicationmentioning

confidence: 96%

“…The merged 15-fold surveys cover an area of 207 km 2 (80 mi 2 ). Initially, the data were processed with a conventional workflow that worked very well on an Osage Co., OK, 60-fold Mississippi Lime survey acquired in 2012 (Dowdell et al, 2013). The resulting images were strongly contaminated by the acquisition footprint (Figure 7), much of it due to highly aliased broadband groundroll.…”

Section: Applicationmentioning

confidence: 99%

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Data conditioning of legacy seismic using migration-driven 5D interpolation

2016

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Legacy seismic surveys cover much of the midcontinent USA and Texas, with almost all 3D surveys acquired in the 1990s considered today to be low fold. Fortunately, recent advances in 5D interpolation have not only enhanced the quality of structural and stratigraphic images, but they have also improved the data sufficiently to allow more quantitative interpretation, such as impedance inversion. Although normal-moveout-corrected, common-midpoint-based 5D interpolation does an excellent job of amplitude balancing and the suppression of acquisition footprint, it appears to misinterpolate undercorrected diffractions, thus smearing fault and stratigraphic edges. We described a least-squares migration-driven 5D interpolation workflow, in which data were interpolated by demigrating the current subsurface image to the missing offsets and azimuths. Such demigration accurately interpolates fault edges and other diffractors, thereby preserving lateral discontinuities, while suppressing footprint and balancing the amplitudes. We have applied this workflow to a highly aliased low-fold survey acquired in the early 1990s now of use in mapping the newly reinvigorated Mississippi Lime play. This workflow improves reflector continuity, preserves faults delineated by coherence, balances the amplitude, and provides improved well ties.

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Section: Applicationmentioning

confidence: 96%

Section: Applicationmentioning

confidence: 99%

Data conditioning of legacy seismic using migration-driven 5D interpolation

2016

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“…The objective is to map tripolite (high-porosity, diagenetically altered chert) that forms reservoir sweet spots as well as natural fractures that can provide conduits through the otherwise tight (usually underlying) fractured chert (Dowdell et al, 2013). In this survey from Kansas, there is also a spiculitic (from sponges) component to the chert (the Cowley Formation).…”

Section: Interpretation / February 2015 Sb7mentioning

confidence: 99%

Pitfalls and limitations in seismic attribute interpretation of tectonic features

2015

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Seismic attributes are routinely used to accelerate and quantify the interpretation of tectonic features in 3D seismic data. Coherence (or variance) cubes delineate the edges of megablocks and faulted strata, curvature delineates folds and flexures, while spectral components delineate lateral changes in thickness and lithology. Seismic attributes are at their best in extracting subtle and easy to overlook features on high-quality seismic data. However, seismic attributes can also exacerbate otherwise subtle effects such as acquisition footprint and velocity pull-up/push-down, as well as small processing and velocity errors in seismic imaging. As a result, the chance that an interpreter will suffer a pitfall is inversely proportional to his or her experience. Interpreters with a history of making conventional maps from vertical seismic sections will have previously encountered problems associated with acquisition, processing, and imaging. Because they know that attributes are a direct measure of the seismic amplitude data, they are not surprised that such attributes "accurately" represent these familiar errors. Less experienced interpreters may encounter these errors for the first time. Regardless of their level of experience, all interpreters are faced with increasingly larger seismic data volumes in which seismic attributes become valuable tools that aid in mapping and communicating geologic features of interest to their colleagues. In terms of attributes, structural pitfalls fall into two general categories: false structures due to seismic noise and processing errors including velocity pull-up/push-down due to lateral variations in the overburden and errors made in attribute computation by not accounting for structural dip. We evaluate these errors using 3D data volumes and find areas where present-day attributes do not provide the images we want. IntroductionSimple-to-make errors, or pitfalls, confront every seismic interpreter. The more common interpretation pitfalls range from miscorrelating seismic reflections across faults to applying an overly simple geologic model or hypothesis (e.g., that all channels should be filled with sand), to processing pitfalls whereby truly chaotic geology is "filtered" to look more continuous. While seismic attributes provide a means of recognizing potential pitfalls, they also provide a means of making new pitfalls. Although seismic attributes such as coherence and curvature have been in use for 10-20 years, not all interpreters include them in their workflows, either because they are already adept at efficient map making or because they do not have access to the software. Importantly, seismic attributes are more heavily favored by younger, less experienced interpreters in situations in which attributes increase their productivity and allow them to extract and quantify subtle features that would otherwise take years of interpretation

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