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Ali Gholami - One of the best experts on this subject based on the ideXlab platform.
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sparse time Frequency Decomposition and some applications
IEEE Transactions on Geoscience and Remote Sensing, 2013Co-Authors: Ali GholamiAbstract:In this paper, time-Frequency (TF) Decomposition (TFD) is studied in the framework of sparse regularization theory. The short-time Fourier transform is first formulated as a convex constrained optimization where a mixed l1-l2 norm of the coefficients is minimized subject to a data fidelity constraint. Such formulation leads to a novel invertible Decomposition with adjustable TF resolution. Then, a fast and efficient algorithm based on the alternating split Bregman technique is proposed to carry out the optimization with computational complexity [N2 log(N)]. Window length is a key parameter in windowed Fourier transform which affects the TF resolution; a novel method is also presented to determine the optimum window length for a given signal resulting to maximum compactness of energy in the TF domain. Numerical experiments show that the proposed sparsity-based TFD generates high-resolution TF maps for a wide range of signals having simple to complicated patterns in the TF domain. The performance of the proposed algorithm is also shown on real oil industry examples, such as ground roll noise attenuation and direct hydrocarbon detection from seismic data.
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Fast Sparse Time-Frequency Decomposition
72nd EAGE Conference and Exhibition incorporating SPE EUROPEC 2010, 2010Co-Authors: Ali Gholami, N. Amini, Hamidreza Siahkoohi, A. EdalatAbstract:Time-Frequency analysis plays an important role in seismic data processing and interpretation. A fast algorithm is presented for sparse time-Frequency Decomposition. A sparsity constraint is used to render the Decomposition process unique while producing high resolution energy distribution maps which can be used as a reliable attribute for delineating reservoirs.
P. Szafian - One of the best experts on this subject based on the ideXlab platform.
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Integrated reservoir characterization using high definition Frequency Decomposition, multi-attribute analysis and forward modelling. Chandon discovery, Australia
First Break, 2019Co-Authors: A. Mantilla, P. Szafian, Rebecca E. Bell, C. HanAbstract:Frequency Decomposition and forward modelling represent advanced seismic techniques that can be applied to assist hydrocarbon exploration. The Chandon (4TCF) and Yellowglen (net-pay column 137m) gas discoveries in the Exmouth Plateau, North Carnarvon Basin (NCB), Australia (Figure 1) offer an excellent opportunity to test and demonstrate the applicability of these techniques in the search for hydrocarbons, because of the high-quality seismic data available, the textbook-example of gas flat-spot response, the fluvial-dominated reservoir and the existing proven hydrocarbon accumulation (Geoscience Australia, 2014). This study presents a workflow for reservoir characterization based on the integration of seismic interpretation, seismic attribute analysis, core analysis, petrophysical interpretation, rock physics modelling, and synthetic seismic modelling to ultimately mitigate uncertainty. Firstly, the complex tectonostratigraphic history of the petroleum system is resolved using attribute analysis, attribute colour blends, and Frequency Decomposition. This analysis reveals an extensive set of reservoir features, emphasizing the structural evolution and stratigraphic architecture. Frequency Decomposition represents a powerful tool for looking at band restricted Frequency volumes of the seismic data, to reveal hidden geological features. The discrete Frequency volumes are combined in a Red-Green-Blue (RGB) blend that shows the contribution of and interaction between different Frequency bands, highlighting geological features. However, up until now Frequency Decomposition images have been used rather qualitatively. This study offers a different approach: it uses forward seismic modelling to compare the high definition Frequency Decomposition (HDFD, see Eckersley et al., 2018) responses of the original data set and the synthetic models (e.g. Han, 2018), in order to validate the model geometries and their rock and fluid property distribution. A 3D seismic cube (Chandon 3D Survey, 875 km2), was used for seismic interpretation which was supplemented by information obtained from four wells (Figure 1). Especially useful logs were the Vertical Seismic Profile and Sonic Scanner logs for rock property estimates and subsequent mechanical layering. Core analysis was available for Yellowglen, Chandon-2&3 wells. Well completion reports, including advanced studies such as special core analysis interpretations, rock physics, formation evaluation, and core photography observations were synthesised as part of the framework for this study. Checkshots were available for three of the four wells to enable accurate well-ties. Published papers on the system assisted in establishing the geological framework for this project.
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Integrated Reservoir Characterisation Using High Definition Frequency Decomposition, Multiattribute Analysis and Forward Modelling. Chandon Discovery, Australia
81st EAGE Conference and Exhibition 2019, 2019Co-Authors: A. Mantilla, P. Szafian, Rebecca E. BellAbstract:Reservoir characterisation using advanced seismic techniques can mitigate risk and enhance hydrocarbon exploration. This study presents an integrated reservoir characterisation of the Triassic Mungaroo Formation in the Yellowglen-Chandon gas discoveries based on formation evaluation, structural analysis, and stratigraphic expression using wireline log interpretation, core description, a synthesis of regional studies, application of structural and stratigraphic seismic multi-attribute analysis, and development of high-definition Frequency Decomposition. An initial stage of data conditioning covered noise cancellation and spectral enhancement. The stratigraphic analysis from Frequency Decomposition and attribute combination revealed the position and geometries of fluvial channels, the main reservoir architectural element. Iso-proportional slicing confirmed the presence of these geo-bodies throughout the vertical extent of the reservoir and supported the reconstruction of the tectonostratigraphic history. Characterisation involved the identification of hydrocarbon accumulations. Rock-physics and seismic forward modelling tested the veracity of these identified accumulations and corroborated their existence. Forward modelling is indeed effective in predicting the Frequency response of new prospect geobodies in undrilled areas, by establishing reasonable assumptions of elastic properties and gas saturation values. The end product was the identification of issues and strengths regarding the petroleum system elements and the comparison between Chevron volumetrics and the ones derived by this study.
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quantitative interpretation of Frequency Decomposition blends using forward modelling thebe discovery nw australia
80th EAGE Conference and Exhibition 2018, 2018Co-Authors: K Kraus, P. Szafian, R BellAbstract:Summary Geological expression techniques including Frequency Decomposition are very powerful tools in understanding and risking reservoirs. A cognitive approach in visualising responses of different band-limited Frequency volumes is through red-green-blue (RGB) colour blending. The non-unique colour responses are subject to a variety of complex interference patterns that are related to a number of geological factors: bed thickness, lithology, porosity, fluid content. This study presents a joint seismic forward modelling and Frequency Decomposition workflow on the Thebe gas discovery, offshore NW Australia to isolate and quantify the effects of hydrocarbon saturation on colour blends. Observations from real life blends are compared to equivalent synthetic models created through comprehensive rock physics modelling at two well locations; Thebe-1 and Thebe-2. Primary gas-bearing sand units within the Triassic Mungaroo Formation have been identified and are associated with a unique combination of high intensity Frequency responses surrounded by a low Frequency zone related to a pronounced gas-water contact. Sensitivity analysis through forward modelling has confirmed that fluid effects play a significant role in the Frequency responses, and yield unique interference patterns in gas saturated sands. Frequency responses were used to establish spatial distribution of these gas-bearing sands to identify locations of ‘sweet-spots’ and de-risk development plans.
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Calibration of Frequency Decomposition Colour Blends Using Forward Modelling - Examples from the Scarborough Gas Field
79th EAGE Conference and Exhibition 2017, 2017Co-Authors: Chris Han, P. SzafianAbstract:This study investigates using a combination of seismic forward modelling with Frequency Decomposition (FD) and colour blending analysis with the aim of better understanding what the major controlling factors on the Frequency response are and how this impacts the spectral interference colour patterns observed in FD colour blends. Examples are provided using data from the Scarborough giant gas accumulation, offshore Northwest Australia. Forward modelling of reflectivity is common practice in the oil and gas industry, generally used to provide information on amplitude and phase changes which may occur in response to changes in a model. By incorporating Frequency Decomposition and red-green-blue (RGB) colour blending into the workflow there may be potential to detect subtle changes within the data, since the interplay between three band-restricted Frequency volumes produces a colour blend which is extremely sensitive to Frequency change and can often highlight features or trends not seen in full Frequency or bandpass volumes. Increasing understanding of FD colour blends may aid in supporting or disproving interpretations made using other lines of evidence, as well as potentially allowing additional geological insights to be made, such as identification of facies, fluids, thicknesses and other changes in reservoir characteristics based on Frequency response.
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Frequency Decomposition of Broadband Seismic Data: Challenges and Solutions
EAGE Workshop on Broadband Marine Seismic Data, 2015Co-Authors: P. Szafian, J. Lowell, A. Eckersley, T. KristensenAbstract:An improved, matching pursuit based high definition Frequency Decomposition method has been introduced to meet the challanges of broad bandwidth seismic data. It is largely sensitive to the finely separated thin events, yet it also has an enhanced Frequency resolution and lateral consistency.
Chris Han - One of the best experts on this subject based on the ideXlab platform.
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Understanding Frequency Decomposition colour blends using forward modelling — examples from the Scarborough gas field
First Break, 2018Co-Authors: Chris HanAbstract:Frequency Decomposition (FD) colour blending of 3D seismic data has become a mainstream technique used by oil and gas industry G&G specialists for imaging subsurface geology. The workflow involves creating Frequency band-restricted components of the seismic data and blending these together into a single volume, typically using a three-dimensional, red-green-blue (RGB) colour scheme. The blends often produce high-resolution, detailed images capable of detecting very subtle features owing to the interference between three Frequency band components which tune at different frequencies. A major advantage is being able to assess distribution and extrapolation of results away from well locations since the results are volumetric and not restricted to a well location. The workflow has typically been applied in a qualitative manner to identify depositional features, structures and geomorphologies visually based on colour changes in the blends. However, the link between the colours and rock physics is poorly understood.
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Calibration of Frequency Decomposition Colour Blends Using Forward Modelling - Examples from the Scarborough Gas Field
79th EAGE Conference and Exhibition 2017, 2017Co-Authors: Chris Han, P. SzafianAbstract:This study investigates using a combination of seismic forward modelling with Frequency Decomposition (FD) and colour blending analysis with the aim of better understanding what the major controlling factors on the Frequency response are and how this impacts the spectral interference colour patterns observed in FD colour blends. Examples are provided using data from the Scarborough giant gas accumulation, offshore Northwest Australia. Forward modelling of reflectivity is common practice in the oil and gas industry, generally used to provide information on amplitude and phase changes which may occur in response to changes in a model. By incorporating Frequency Decomposition and red-green-blue (RGB) colour blending into the workflow there may be potential to detect subtle changes within the data, since the interplay between three band-restricted Frequency volumes produces a colour blend which is extremely sensitive to Frequency change and can often highlight features or trends not seen in full Frequency or bandpass volumes. Increasing understanding of FD colour blends may aid in supporting or disproving interpretations made using other lines of evidence, as well as potentially allowing additional geological insights to be made, such as identification of facies, fluids, thicknesses and other changes in reservoir characteristics based on Frequency response.
Martalouise Ackers - One of the best experts on this subject based on the ideXlab platform.
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Understanding seismic thin-bed responses using Frequency Decomposition and RGB blending
First Break, 2012Co-Authors: N J Mcardle, Martalouise AckersAbstract:RGB colour blending is a powerful technique of co-visualization of different band-limited magnitude volumes created by Frequency Decomposition. The aims of this study were to investigate the impact of changes in geometry and acoustic impedance on what we observe in a blend of Frequency magnitude volumes, and to examine how sensitive different methods of Frequency Decomposition are to these variations. We present a comparison of Frequency Decomposition methods applied to the Hermod Member submarine fan system, a well understood fan system from the Northern North Sea, and to simple synthetic models. Observations made from RGB imaging are compared to equivalent results from synthetic models created using well measurements and systematic variations in reservoir parameters. We show that thickness variations between events are the dominant factor controlling RGB colour response and that subtle lithological changes, presented as differences in acoustic impedance, are a second order effect. Furthermore, when the source Frequency and Decomposition bands of a synthetic wedge model are matched to a real dataset, we can relate colour values directly to thicknesses. In doing so we extend the classical tuning wedge for use as a calibration tool for Frequency Decomposition colour blends.
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Frequency Decomposition methods applied to synthetic models of the hermod submarine fan system in the north sea
74th EAGE Conference and Exhibition incorporating EUROPEC 2012, 2012Co-Authors: N J Mcardle, Martalouise Ackers, B K BrynAbstract:Frequency Decomposition methods have been applied to a seismic dataset which images the late Palaeocene Hermod Fm. submarine fan system which occurs within the Viking Graben in the Northern North Sea. Conventional bandpass Decomposition methods are compared to HD Frequency Decomposition – a technique based on matching pursuit of wavelets and the sensitivities of each method are discussed. Red-Green-Blue colour blending is shown to image in great detail channels, levees and splays. In order to understand the controlling factors determining the colour, contrast and amplitude shown in the RGB blends produced using each Decomposition method, synthetic models of a Hermod splay has been produced. Within these models thickness and acoustic impedance are varied to investigate which has a larger effect. Frequency Decomposition and blending of the synthetic models closely resembles blends created from the original data and it is likely that thickness changes, within the Hermod fan, which varies from above the tuning thickness in the channel core, to below tuning in the distal splays is mainly responsible for colour, amplitude and constrast changes within the blends.
Sergey Fomel - One of the best experts on this subject based on the ideXlab platform.
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time variant wavelet extraction with a local attribute based time Frequency Decomposition for seismic inversion
Interpretation, 2017Co-Authors: Rui Zhang, Sergey FomelAbstract:AbstractSeismic impedance inversion has been widely used to estimate subsurface properties. Conventional inversion assumes that seismic data are the convolution result of seismic wavelet and reflectivity, implying that seismic data are stationary when a constant wavelet is considered. However, seismic data are nonstationary because of noise contamination and attenuation during wave propagation, which means that the Frequency spectrum of the seismic signal changes from shallow to deep formations. We have developed a time-variant wavelet extraction method by using a local-attribute-based spectral Decomposition technique. Time-variant wavelets are generated according to the local Frequency spectrum, which can be used to construct a time-variant wavelet kernel matrix. By using this time-variant kernel matrix, we can obtain a better correlation between synthetic and extracted seismograms than by using constant wavelet on a field data example. Using this example, we have also compared the time-variant and const...
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seismic data analysis using local time Frequency Decomposition
Geophysical Prospecting, 2013Co-Authors: Yang Liu, Sergey FomelAbstract:Many natural phenomena, including geologic events and geophysical data, are fundamentally nonstationary - exhibiting statistical variation that changes in space and time. Time-Frequency characterization is useful for analysing such data, seismic traces in particular. We present a novel time-Frequency Decomposition, which aims at depicting the nonstationary character of seismic data. The proposed Decomposition uses a Fourier basis to match the target signal using regularized least-squares inversion. The Decomposition is invertible, which makes it suitable for analysing nonstationary data. The proposed method can provide more flexible time-Frequency representation than the classical S transform. Results of applying the method to both synthetic and field data examples demonstrate that the local time-Frequency Decomposition can characterize nonstationary variation of seismic data and be used in practical applications, such as seismic ground-roll noise attenuation and multicomponent data registration.
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Seismic data analysis using local time‐Frequency Decomposition
Geophysical Prospecting, 2012Co-Authors: Yang Liu, Sergey FomelAbstract:Many natural phenomena, including geologic events and geophysical data, are fundamentally nonstationary - exhibiting statistical variation that changes in space and time. Time-Frequency characterization is useful for analysing such data, seismic traces in particular. We present a novel time-Frequency Decomposition, which aims at depicting the nonstationary character of seismic data. The proposed Decomposition uses a Fourier basis to match the target signal using regularized least-squares inversion. The Decomposition is invertible, which makes it suitable for analysing nonstationary data. The proposed method can provide more flexible time-Frequency representation than the classical S transform. Results of applying the method to both synthetic and field data examples demonstrate that the local time-Frequency Decomposition can characterize nonstationary variation of seismic data and be used in practical applications, such as seismic ground-roll noise attenuation and multicomponent data registration.