The effects of seismic data conditioning on pre‐stack simultaneous impedance inversion

Singleton, Scott

doi:10.1190/1.3059200

Cited by 5 publications

(4 citation statements)

References 13 publications

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“…The input data (Fig. 3a) have low signal-to-noise ratio; hence, before AVO analysis, it was required to perform gather conditioning (Singleton 2009). The processes used in conditioning were bandpass filtering (8/16-80/110 Hz), supergather creation (in a 3 × 3 bin), random noise attenuation with the application of Parabolic Radon Transform (for surface wave, air wave and random noise removal) and trim statics.…”

Section: Pre-stack Attributesmentioning

confidence: 99%

Verification of bright spots in the presence of thin beds by AVO and spectral analysis in Miocene sediments of Carpathian Foredeep

2019

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Twin structural traps that lie within the Miocene strata of the Carpathian Foredeep that are localized above Cierpisz and Mrowla-Bratkowice highs exhibit identical bright-spot seismic anomalies, but only those associated with the Cierpisz high are profitable gas reservoirs. Bright spots can be a result of weak gas or water saturation, but also seismic interference known as tuning effect. For these reasons, it is crucial to differentiate between seismic anomalies. In this article, we present the possibilities of verification of seismic anomalies that occur within the siliciclastic Miocene sediments of the Carpathian Foredeep with the application of AVO analysis and spectral decomposition. AVO methodology enabled to limit the number of anomalies that are present in the post-stack seismic data. These anomalies, however, may also be a result of tuning which is common for the heterolithic sequences in the Miocene sediments of the Carpathian Foredeep. For classification of anomalies in the view of the above, spectral decomposition based on the Basis Pursuit algorithm was applied. Spectral decomposition enabled to divide AVO anomalies in those that are the result of gas saturation and the tuning effect. Gas-saturated zones are characterized by higher spectral amplitudes of the lower frequency range, whereas tuning effect yields higher spectral amplitudes for the higher frequency content. This relation is visible for the data set and enables qualitative differentiation for the set of seismic anomalies.

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Section: Pre-stack Attributesmentioning

confidence: 99%

Verification of bright spots in the presence of thin beds by AVO and spectral analysis in Miocene sediments of Carpathian Foredeep

2019

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“…Prior to AVO inversion, a seismic conditioning process was applied to the pre-stack data, following the approach of Singleton (2009). The key processes involved were coherent and random noise suppression, residual move-out analysis and spectral balancing between near and far traces.…”

Section: Avo Inversion and Interpretationmentioning

confidence: 99%

AVO Interpretation of a Gas Bearing Sand Reservoir Encased in Its Source Rock

Álvarez¹,

Marin²,

Bolívar³

et al. 2014

Proceedings

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In this paper we show a case study where a gas bearing sand reservoir encased with shale of great thickness and rich in organic matter, which are considered as source rock and potential reservoir (Barrero et. al, 2007), occasioned the presence of unconventional background trend in the AVO intercept (A) and gradient (B) crossplot. This condition, change the expected AVO response of the shales, altering the direction of the typical background trend, in which coincide the AVO response of the shales and brinesaturated sandstones. In consequence, to be able to identify AVO anomalies related to gas bearing sands in this geological context, a detailed log conditioning process and rock physics analysis were performed to have a robust set of well logs. Next, rock physics modeling, fluid substitution and thickness modeling was performed in order to understand the difference between the AVO anomalies related to gas bearing sands regarding to the 'non-conventional' trend produced by the organic shales. The results obtained along with AVO attribute volumes calculated from real seismic data, after a rigorous conditioning process in pre-stack domain, were used to identify potential AVO anomalies related to gas bearing sands.

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“…Because stacking is in itself a filter, it is obvious that noise that contaminates poststack data is equal or stronger on prestack seismic gathers. Undesired prestack seismic phenomena need to be diminished or removed prior to reservoir characterization (Singleton, 2008). Although there has been considerable work on residual velocity analysis and trim statics, most publications that address the reduction of crosscutting noise on seismic gathers have been limited to processing across offset, one gather at a time.…”

Section: Introductionmentioning

confidence: 99%

Noise suppression of time migrated gathers using prestack structure oriented filtering

Zhang

Lin

Marfurt

2015

SEG Technical Program Expanded Abstracts 2015

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Prestack seismic analysis provides information on rock properties, lithology, fluid content, and the orientation and intensity of anisotropy. However, such analysis demands high-quality seismic data. Unfortunately, noise is always present in seismic data even after careful processing. Noise in the prestack gathers may not only contaminate the seismic image, thereby lowering the quality of seismic interpretation, but it may also bias the seismic prestack inversion for rock properties, such as acoustic-and shear-impedance estimation. Common postmigration data conditioning includes running window median and Radon filters that are applied to the flattened common reflection point gathers. We have combined filters across the offset and azimuth with edge-preserving filters along the structure to construct a true "5D" filter that preserves amplitude, thereby preconditioning the data for subsequent quantitative analysis. We have evaluated our workflow by applying it to a prestack seismic volume acquired over the Fort Worth Basin, TX. The inverted results from the noise-suppressed prestack gathers are more laterally continuous and have higher correlation with well logs when compared with those inverted from conventional time-migrated gathers.

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The effects of seismic data conditioning on pre‐stack simultaneous impedance inversion

Cited by 5 publications

References 13 publications

Verification of bright spots in the presence of thin beds by AVO and spectral analysis in Miocene sediments of Carpathian Foredeep

Verification of bright spots in the presence of thin beds by AVO and spectral analysis in Miocene sediments of Carpathian Foredeep

AVO Interpretation of a Gas Bearing Sand Reservoir Encased in Its Source Rock

Noise suppression of time migrated gathers using prestack structure oriented filtering

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