Broadband Seismic for Sub-basalt Exploration

Spjuth, C.; Sabel, P.; Foss, S. K.; Dromgoole, Peter W.; Friedrich, Clemens; Herredsvela, J.; Day, Arthur L.; Dhelie, P.E.; Hegna, Stian; Hy, T.; Koch, K.

doi:10.3997/2214-4609.20148151

Cited by 3 publications

(2 citation statements)

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“…As we know, the width of the main lobe of the wavelet depends on the relative high-frequency energy and broadening the low-frequency bandwidth can effectively reduce the amplitude of wavelet side lobes (Kroode et al 2013;Liu et al 2013). Considering the influence of low frequencies on seismic imaging and velocity analysis in contrast to high frequencies, less absorption, less scattering and better penetration of low frequencies illustrate their importance in the field of deep imaging technology (Pedersen and Becken 2005;Spjuth et al 2012;Cao and Chen 2014;Zhang et al 2015). Geophysicists still prioritize low-frequency regularizations in waveform, impedance, elastic and AVO inversion (Zong et al 2012;Kroode et al 2013;Li et al 2016a) to improve the stability of the inversion process and the rate of convergence to a precise earth model.…”

Section: Introductionmentioning

confidence: 99%

Bayesian seismic multi-scale inversion in complex Laplace mixed domains

Yin

Zong

2017

Pet. Sci.

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Seismic inversion performed in the time or frequency domain cannot always recover the long-wavelength background of subsurface parameters due to the lack of low-frequency seismic records. Since the low-frequency response becomes much richer in the Laplace mixed domains, one novel Bayesian impedance inversion approach in the complex Laplace mixed domains is established in this study to solve the model dependency problem. The derivation of a Laplace mixed-domain formula of the Robinson convolution is the first step in our work. With this formula, the Laplace seismic spectrum, the wavelet spectrum and time-domain reflectivity are joined together. Next, to improve inversion stability, the object inversion function accompanied by the initial constraint of the linear increment model is launched under a Bayesian framework. The likelihood function and prior probability distribution can be combined together by Bayesian formula to calculate the posterior probability distribution of subsurface parameters. By achieving the optimal solution corresponding to maximum posterior probability distribution, the low-frequency background of subsurface parameters can be obtained successfully. Then, with the regularization constraint of estimated low frequency in the Laplace mixed domains, multi-scale Bayesian inversion in the pure frequency domain is exploited to obtain the absolute model parameters. The effectiveness, anti-noise capability and lateral continuity of Laplace mixed-domain inversion are illustrated by synthetic tests. Furthermore, one field case in the east of China is discussed carefully with different input frequency components and different inversion algorithms. This provides adequate proof to illustrate the reliability improvement in low-frequency estimation and resolution enhancement of subsurface parameters, in comparison with conventional Bayesian inversion in the frequency domain.

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Section: Introductionmentioning

confidence: 99%

Bayesian seismic multi-scale inversion in complex Laplace mixed domains

Yin

Zong

2017

Pet. Sci.

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“…Similarly, Woodburn et al (2011) stress the importance of low frequencies for subbasalt imaging and discuss the application of a low-frequency boosting filter at the start of the processing. Also, the use of broadband seismic acquisition techniques, able to extend the data bandwidth on high and low frequencies, has recently been suggested (Spjuth et al, 2012) as has the use of processing solutions to achieve the same objective (e.g. Zhou et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

High-resolution coherency functionals for velocity analysis: An application for subbasalt seismic exploration

et al. 2013

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We tested the properties of three different coherency functionals for the velocity analysis of seismic data relative to subbasalt exploration. We evaluated the performance of the standard semblance algorithm and two high-resolution coherency functionals based on the use of analytic signals and of the covariance estimation along hyperbolic traveltime trajectories. Approximate knowledge of the wavelet was exploited to design appropriate filters that matched the primary reflections, thereby further improving the ability of the functionals to highlight the events of interest. The tests were carried out on two synthetic seismograms computed on models reproducing the geologic setting of basaltic intrusions and on common midpoint gathers from a 3D survey. Synthetic and field data had a very low signal-to-noise ratio, strong multiple contamination, and weak primary subbasalt signals. The results revealed that high-resolution coherency functionals were more suitable than semblance algorithms to detect primary signals and to distinguish them from multiples and other interfering events. This early discrimination between primaries and multiples could help to target specific signal enhancement and demultiple operations.

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Recent seismic technologies for sub-basalt imaging

Nibe¹,

Aoki²,

Takanashi

2014

J. Petroleum Tech.

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Although sub-basalt exploration has been achieved great attention, the progress is very limited due to the dif culty of imaging beneath the basalt. Most of seismic energy are usually scattered and attenuated by thick basalts. Also Basalts usually generate a lot of multiples. As a result, quality of seismic data are usually not enough for interpretation. But recently, seismic techniques are advanced rapidly and some of those new techniques are expected to be effective in sub-basalt imaging. In this article, we review issues relating to sub-basalt imaging and some of the new recently advanced techniques, especially de-ghosting techniques in data acquisition are reviewed because low-frequency is a key factor in sub-basalt imaging.

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Broadband Seismic for Sub-basalt Exploration

Cited by 3 publications

References 0 publications

Bayesian seismic multi-scale inversion in complex Laplace mixed domains

Bayesian seismic multi-scale inversion in complex Laplace mixed domains

High-resolution coherency functionals for velocity analysis: An application for subbasalt seismic exploration

Recent seismic technologies for sub-basalt imaging

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