Geologically consistent velocities obtained by high definition tomography

Guillaume, P.; Lambaré, Gilles; Sioni, S.; Carotti, D.; Depré, Pascale; Culianez, Gregory; Montel, J.; Mitouard, Pierre; Depagne, Sylvere; Frehers, Sven; Vosberg, H.

doi:10.1190/1.3628054

Cited by 13 publications

(6 citation statements)

References 15 publications

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“…The use of the autocorrelation on short time windows increases the signal-to-noise ratio, making the frequency picking more accurate and the obtained result more precise. The effective Qvolume estimated from the frequency peaks is used as input to interval Q-tomography (Guillaume et al, 2011). The most interesting point here is that the workflow succeeds in automatically detecting the gas cloud anomaly responsible for the SOA without any a priori information of its position.…”

Section: Volumetric Q-tomographymentioning

confidence: 99%

Image Quality Enhancement Using Volumetric Q-tomography and Q-PSDM - Martin Linge Case Study

Gamar-Sadat¹,

Carotti²,

Gout³

et al. 2016

78th EAGE Conference and Exhibition 2016

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The compensation of absorption loss inside the imaging process using attenuation models estimated by Qtomography is now widely accepted and used in the industry. This technology becomes even more important in the case of a complex dataset. For the Martin Linge field, characterized by a strong presence of faults and gas clouds, the multi-azimuth broadband acquisition involving a variable-depth streamer has helped to improve the quality of the data. High-end processing and imaging so far provided an image with enhanced resolution compared to legacy data mainly with regard to faulting in the deeper area. Nevertheless, imaging remained poor in the deeper part of the section because of a seismic obscured area (SOA) caused by gas clouds. In this paper we now illustrate how we managed to enhance the resolution under this SOA zone using volumetric Q-tomography and Q-prestack depth migration (Q-PSDM). In other words, we show that multi-azimuth broadband acquisition combined with Q-tomography/Q-PSDM techniques can provide an improved final image in the case of a complex data with a SOA.

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Section: Volumetric Q-tomographymentioning

confidence: 99%

Image Quality Enhancement Using Volumetric Q-tomography and Q-PSDM - Martin Linge Case Study

Gamar-Sadat¹,

Carotti²,

Gout³

et al. 2016

78th EAGE Conference and Exhibition 2016

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show abstract

“…We apply the workflow on a complex Brunei offshore dataset to localize shallow gas pockets without any a priori information on their positions. This was made possible thanks to our high resolution tomography (Guillaume et al, 2011) using an accurate effective Q volume picked from pre-stack migrated gathers using 4 dimensions.…”

Section: Introductionmentioning

confidence: 99%

Automatic Gas Pockets Detection by High-resolution Volumetric Q-tomography Using Accurate Frequency Peak Estimation

Gamar-Sadat¹,

Guillaume²,

Pica³

et al. 2015

Proceedings

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Conventional imaging does not deal adequately with absorption, especially in the case of strong anomalies. Over recent years, many authors have proposed to compensate the absorption loss effects inside of the migration through the use of an attenuation model. Q tomography has been developed for estimating this attenuation model but is generally limited to estimating attenuation in predefined anomalies. In this paper, we explain how we developed a high-resolution volumetric Q tomography to attain an accurate volumetric estimation of the attenuation model. A key component of our workflow is the estimation of effective attenuation in the pre-stack data domain through accurate picking of the frequency peak. Finally we present a case study where our approach has been used to reveal shallow gas pockets and compensate for absorption in the migration.

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“…We apply the workflow on Brunei offshore dataset to localize shallow gas pockets without any a priori information on their positions. This was made possible thanks to an adaptation to Q tomography of non-linear slope tomography (Guillaume et al, 2011) using an accurate effective Q volume picked from pre-stack migrated gathers.…”

Section: Introductionmentioning

confidence: 99%

Success of high-resolution volumetric Q-tomography in the automatic detection of gas anomalies on offshore Brunei data

Gamar

Carotti

Guillaume

et al. 2015

SEG Technical Program Expanded Abstracts 2015

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Over recent years, many authors have proposed to compensate the absorption loss effects inside of the imaging process through the use of an attenuation model. This is necessary in the presence of strong attenuation anomalies. Q tomography has been developed for estimating this attenuation model but is generally limited to estimating attenuation in predefined anomaly areas. In this paper, we show how shallow gas pockets are revealed automatically by using a high-resolution volumetric Q tomography on the complex offshore Brunei dataset. A key component of our approach is the estimation of effective attenuation in pre-stack migrated domain through accurate picking of the frequency peak. Estimated Q-model is then used to compensate for absorption in the imaging process.

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Geologically consistent velocities obtained by high definition tomography

Cited by 13 publications

References 15 publications

Image Quality Enhancement Using Volumetric Q-tomography and Q-PSDM - Martin Linge Case Study

Image Quality Enhancement Using Volumetric Q-tomography and Q-PSDM - Martin Linge Case Study

Automatic Gas Pockets Detection by High-resolution Volumetric Q-tomography Using Accurate Frequency Peak Estimation

Success of high-resolution volumetric Q-tomography in the automatic detection of gas anomalies on offshore Brunei data

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