High‐resolution clinoform characterization by 2‐D model‐driven seismic Bayesian inversion

Tetyukhina, Daria; Vliet, Lucas J. van; Lüthi, Stefan M.; Wapenaar, Kees

doi:10.1190/1.2792852

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Channels are generally visually close to or below seismic resolution (Caldwell et al, 1997;Tetyukhina et al, 2010), so thin to their surrounding geometry that their subtleties are nearly invisible in traditional seismic data. Thus, delineating thin reservoir sands from conventional seismic data has always been a challenge.…”

Section: Introductionmentioning

confidence: 99%

Imaging Subsurface Channels within the Tertiary Niger Delta Basin using Spectral Decomposition Methods

Adizua,

Lenyie

2023

Journal of Earth Sciences and Geotechnical Engineering

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Channels are hydrocarbon prospective areas which are often below the resolution of seismic data. This study was therefore conducted with the aim of using spectral decomposition methods for imaging of buried channels and associated structures in a 3D Post-Stack Depth Migrated (PSDM) volume acquired from a field in the Niger Delta Basin. Two commonly used spectral decomposition methods were used to enhance the resolution of seismic data for interpretation. The methods utilized included Fast Fourier Transform (FFT) and Continuous Wavelet Transform (CWT). Petrel and Opendtect were the interpretational software tools utilized for the study. The seismic data was conditioned using structural smoothing, and a zone of interest was selected around -1000 to -3000ms. Three dominant frequencies were selected from the sub-volume generated around the zone of interest. The frequencies were 10Hz, 25Hz and 32Hz respectively. These frequencies were extracted from the seismic data using FFT and CWT decomposition methods. The results were colored using Red, Green and Blue (Red for 10Hz, Green for 25Hz and Blue for 32Hz). These frequencies were then blended together in a process called RGB blending. The resultant output was a mix of only these three dominant frequencies. Analysis of these results revealed the presence of several channels, crevasse splay deposits, flood-plains and faults on two time-slices obtained at -2020ms and -1800ms. The channels were meandering channels of low sinuosity, some of which were fault controlled. The crevasse splay deposits were significantly large and increased in number at the shallow time-slice. Some of the crevasse splay deposits were found bifurcating fault lines and being deposited on floodplains, indicating that they were younger than the faults. Channel flow direction was from East to West, while channel migration was from South to North of the study area. The increase in the number of channels from the base to the top of the seismic data suggested a multistory stacked channel system. It was established that channels and crevasse splays were best enhanced using the FFT decomposition method while major and minor faults were best enhanced using CWT method. Hence, this study has proven that the spectral decomposition method is very effective in imaging subsurface buried channels, thus delineating prospects and can be used for reservoir characterization. Keywords: Spectral decomposition, Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT), Channels, Crevasse splays, Faults, Reservoir Characterization.

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Section: Introductionmentioning

confidence: 99%

Imaging Subsurface Channels within the Tertiary Niger Delta Basin using Spectral Decomposition Methods

Adizua,

Lenyie

2023

Journal of Earth Sciences and Geotechnical Engineering

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High‐resolution reservoir characterization by 2‐D model‐driven seismic Bayesian inversion: An example from a Tertiary deltaic clinoform system in the North Sea

Tetyukhina

Lüthi

Vliet

et al. 2008

SEG Technical Program Expanded Abstracts 2008

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In order to retrieve a high-resolution reservoir model from seismic and well data, an approach was developed based on an a priori layered model from well data, specifically the acoustic impedances derived from the sonic and density logs. The procedure consists of using a forward model of the well data as a priori information that is then iteratively matched with the seismic data using a Bayesian inversion process. The inversion is then extended to 2D, whereby the extrapolation is guided by a simple geometric envelope described with a small number of parameters. It is tested on a seismic data set containing a deltaic clinoform in the North Sea, whereby the clinoform geometry is parameterized by a sigmoid and used as prior information. In the subsequent optimization the clinoform geometry is further refined with a limited number of local knots to improve the match with the seismic data. This lowparameterization inversion approach thus uses geological shapes and well constraints to obtain a subsurface model than can have a substantially higher resolution than the seismic wavelength.

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High resolution thin reservoir prediction in Andian area, Biyang Depression

Zhang

Yin

2010

SEG Technical Program Expanded Abstracts 2010

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High‐resolution clinoform characterization by 2‐D model‐driven seismic Bayesian inversion

Cited by 3 publications

References 12 publications

Imaging Subsurface Channels within the Tertiary Niger Delta Basin using Spectral Decomposition Methods

Imaging Subsurface Channels within the Tertiary Niger Delta Basin using Spectral Decomposition Methods

High‐resolution reservoir characterization by 2‐D model‐driven seismic Bayesian inversion: An example from a Tertiary deltaic clinoform system in the North Sea

High resolution thin reservoir prediction in Andian area, Biyang Depression

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