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

Gamar-Sadat, F.; Guillaume, P.; Pica, A.; Pignot, G.; Poggi, Pasquale; Henry-Baudot, A.; Prescott, A.; Gacha, A.; Carotti, D.; Prieux, V.

doi:10.3997/2214-4609.201413251

Cited by 4 publications

(4 citation statements)

References 9 publications

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“…ere is no presence of absorption (Q) anomalies in the data, so a constant background Q quality factor of 150 using the spectral ratio method was derived and used for QPSDM. It is worth mentioning that another technology for absorption inversion called "volumetric Q tomography" (Gamar-Sadat et al, 2015) was tested on a small swath. e test result showed that there is no signi cant spatial variation in the Q model for this data, and both models were able to produce similar QPSDM images.…”

Section: Q-compensated Prestack Depth Migrationmentioning

confidence: 99%

Revealing new hydrocarbon potential through Q-compensated prestack depth imaging at Wenchang Field, South China Sea

Li¹,

Li²,

Xu³

et al. 2019

The Leading Edge

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Wenchang Field in the South China Sea contains a well-developed fault system, resulting in complex subsurface geology. Imaging the complex fault system plays an important role in hydrocarbon exploration in this area since the fault system forms a link between the source rocks and reservoirs. However, it is difficult to obtain a high-quality depth image of the fault system due to the effects of complex velocity and seismic absorption. Inaccurate depth velocities lead to fault shadows and structure distortions at the target zone. Absorption effects further deteriorate seismic imaging as they cause amplitude attenuation, phase distortion, and resolution reduction. We demonstrate how a combination of high-resolution depth velocity modeling and Q imaging work together to resolve these challenges. This workflow provides a step change in image quality of the complex fault system and targeted source rocks at Wenchang Field, significantly enhancing structure interpretation and reservoir delineation. A couple of commercial discoveries have been made, and several other potential hydrocarbon reservoirs have been identified based on the reprocessed data, which reveal new hydrocarbon potential in this region.

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Section: Q-compensated Prestack Depth Migrationmentioning

confidence: 99%

Revealing new hydrocarbon potential through Q-compensated prestack depth imaging at Wenchang Field, South China Sea

Li¹,

Li²,

Xu³

et al. 2019

The Leading Edge

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“…Estimation of the Q model for this survey was done using the frequency peak shift (FPS) method and volumetric Q tomography (Gamar-Sadat et al, 2015). e proposed ow is able to estimate a background Q model while localizing small anomalies, especially ones related to gas.…”

Section: Q Tomography and Q Psdmmentioning

confidence: 99%

Imaging challenges and processing solutions in the Brazilian Equatorial Margin: A case study in the Barreirinhas Basin

et al. 2018

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e Barreirinhas Basin is located in northeast Brazil and is part of the Brazilian Equatorial Margin, a new exploration frontier with complex geology. is basin is characterized by a rugose water bottom, a fast carbonate platform, shallow gas pockets, and a complex channel network. All of these elements represent a signi cant challenge for velocity model building and imaging of the depositional system. From preprocessing to nal imaging, high-end technologies were required to meet the processing objectives. e 3D designature and 3D deghosting were crucial to remove bubble energy and ghosts related to canyon di ractions. e velocity model building exploited o set-dependent dip information in the nonlinear slope tomography-i.e., dip-constrained tomography (DCT)-to deal with small-scale lateral velocity variations. e full-waveform inversion, up to 20 Hz, was able to e ciently capture small velocity anomalies and resolve highspatial-resolution variations that DCT could not totally solve. Even with a detailed velocity model, some dim zones and amplitude variations were still observable in the depth-migrated image. Gas pockets, responsible for the absorption and phase distortion of the seismic signal (commonly denoted by the quality factor of attenuation, Q), were detected and delineated using volumetric Q tomography. e resultant interval Q model was consistent with the geology, and its use was bene cial in a Q-compensating Kirchho prestack depth migration.

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“…Our approach consists of calculating a prestack dense effective Q-volume in four dimensions (time, inline, crossline, offset), using the shift of the frequency peak (Gamar et al, 2015). The picking of the frequency peak is done on amplitude spectra computed around the maximum of the autocorrelation of the data.…”

Section: Volumetric Q-tomographymentioning

confidence: 99%

“…For this challenging processing project, we applied a workflow that uses volumetric Q-tomography for converting volumetric, effective Q-measurements made on prestack data into a 3D interval Qmodel. To compute the effective Q-volume in the prestack domain, we use a method based on the frequency peak shift (Gamar et al, 2015). The absorption effects can be accurately compensated within the imaging process (Xie et al, 2009) thanks to an interval Q-model computed by tomography (Xin et al, 2008, Cavalca et al, 2011, Gamar et al, 2015.…”

Section: Introductionmentioning

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

Cited by 4 publications

References 9 publications

Revealing new hydrocarbon potential through Q-compensated prestack depth imaging at Wenchang Field, South China Sea

Revealing new hydrocarbon potential through Q-compensated prestack depth imaging at Wenchang Field, South China Sea

Imaging challenges and processing solutions in the Brazilian Equatorial Margin: A case study in the Barreirinhas Basin

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

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