Multi-attribute machine learning analysis for weak BSR detection in the Pegasus Basin, Offshore New Zealand

Chenin, Julian; Bedle, Heather

doi:10.1007/s11001-020-09421-x

Cited by 11 publications

(12 citation statements)

References 48 publications

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“…Although masking of weak BSRs has been proposed for parallel strata within the Hikurangi Trough (Chenin & Bedle, 2020), our results do not show a relationship between the orientation of stratal reflections and BSR gaps as BSRs do cross the hinge point of multiple synclines, albeit up-dip from their troughs (Figure 3a). As highlighted in Figure 4a and in Figure 6, pane 2, pane 3, some modern BSRs do not track parallel to the approximately horizontal seafloor in the Glendhu Slope Basin (S6).…”

Section: Dynamic Synclinal Bsrscontrasting

confidence: 92%

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Sedimentary bottom simulating reflection muting—A new model of hydrate and fluid redistribution from the Pegasus Basin, New Zealand

2022

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Methane gas hydrate is a type of solid crystalline mineral structured as a clathrate that exists at low temperatures and high pressures. Typically composed of methane and water, hydrates inhabit stratal pore space and fractures in the subsurface (Bryan, 1974). Hydrates are encountered in marine continental margin environments worldwide and although estimates vary widely, a recent estimate of methane carbon stored within gas hydrates is thought to be 455 Gt (Wallmann et al., 2012). Mapping bottom simulating reflections (BSRs) in two-dimensional (2D) reflection seismic data is one method for deriving first-order approximations of global amounts of methane stored in hydrate in the marine environment (e.g. Kvenvolden, 1988;Milkov et al., 2003).Within seismic data, (BSRs) are common geophysical identifiers of the approximate base of the gas hydrate stability zone (BGHSZ), and as such are commonly used as indirect indicators of hydrate (e.g.

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Section: Dynamic Synclinal Bsrscontrasting

confidence: 92%

“…Here, stratal reflections are horizontally aligned and parallel, which introduces uncertainty concerning weak BSR identification (e.g. Chenin & Bedle, 2020) (Figures 3c and 5B′–B). Generally, we interpreted regions featuring gently dipping strata (ca.…”

Section: Resultsmentioning

confidence: 99%

Sedimentary bottom simulating reflection muting—A new model of hydrate and fluid redistribution from the Pegasus Basin, New Zealand

2022

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“…There are many continuing and promising attempts employed to advance our interpretations and improve the efficiency in exploring for this natural resource. Multi-attribute analysis involving principal component analysis and self-organizing maps of sets of seismic attributes improve the imaging of the BSR, which potentially aids to identifying the occurrence of gas hydrates [21]. Furthermore, instantaneous attributes, when grouped for self-organizing map clustering, better detect strong and weak BSRs, whereas AVA attributes seem to improve discontinuous BSR detection [21].…”

Section: Advanced Studies Of the Bsrs And Gas Hydrate Relationshipmentioning

confidence: 99%

“…Multi-attribute analysis involving principal component analysis and self-organizing maps of sets of seismic attributes improve the imaging of the BSR, which potentially aids to identifying the occurrence of gas hydrates [21]. Furthermore, instantaneous attributes, when grouped for self-organizing map clustering, better detect strong and weak BSRs, whereas AVA attributes seem to improve discontinuous BSR detection [21]. Additionally, Lee et al [22] conducted a multi-attribute analysis using the unsupervised K-means clustering algorithm, in addition to acoustic impedance and shear impedance inversion models, to estimate the extent and distribution of a gas hydrate reservoir.…”

Section: Advanced Studies Of the Bsrs And Gas Hydrate Relationshipmentioning

confidence: 99%

“…This study utilizes two seismic surveys, the PEG09 and APB13 surveys-both conducted within the Pegasus Basin, for a comparative analysis of the efficiency of the applied methods. The former has been used in many studies compared to the latter, which makes it an ideal survey candidate for exploring a new method [10,21,23,39,41]. The APB13 survey is used to validate the transferability of the geophysical attenuation method to ensure it provides consistent results across both surveys.…”

Section: Seismic Datamentioning

confidence: 99%

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Seismic Attribute Analyses and Attenuation Applications for Detecting Gas Hydrate Presence

et al. 2021

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Identifying gas hydrates in the oceanic subsurface using seismic reflection data supported by the presence of a bottom simulating reflector (BSR) is not an easy task, given the wide range of geophysical methods that have been applied to do so. Though the presence of the BSR is attributed to the attenuation response, as seismic waves transition from hydrate-filled sediment within the gas hydrate stability zone (GHSZ) to free gas-bearing sediment below, few studies have applied a direct attenuation measurement. To improve the detection of gas hydrates and associated features, including the BSR and free gas accumulation beneath the gas hydrates, we apply a recently developed method known as Sparse-Spike Decomposition (SSD) that directly measures attenuation from estimating the quality factor (Q) parameter. In addition to performing attribute analyses using frequency attributes and a spectral decomposition method to improve BSR imaging, using a comprehensive analysis of the three methods, we make several key observations. These include the following: (1) low-frequency shadow zones seem to correlate with large values of attenuation; (2) there is a strong relationship between the amplitude strength of the BSR and the increase of the attenuation response; (3) the resulting interpretation of migration pathways of the free gas using the direct attenuation measurement method; and (4) for the data analyzed, the gas hydrates themselves do not give rise to either impedance or attenuation anomalies that fully differentiate them from nearby non-hydrate zones. From this last observation, we find that, although the SSD method may not directly detect in situ gas hydrates, the same gas hydrates often form an effective seal trapping and deeper free gas accumulation, which can exhibit a large attenuation response, allowing us to infer the likely presence of the overlying hydrates themselves.

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Improved feature extraction in seismic data: multi-attribute study from principal component analysis

2021

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Multi-attribute machine learning analysis for weak BSR detection in the Pegasus Basin, Offshore New Zealand

Cited by 11 publications

References 48 publications

Sedimentary bottom simulating reflection muting—A new model of hydrate and fluid redistribution from the Pegasus Basin, New Zealand

Sedimentary bottom simulating reflection muting—A new model of hydrate and fluid redistribution from the Pegasus Basin, New Zealand

Seismic Attribute Analyses and Attenuation Applications for Detecting Gas Hydrate Presence

Improved feature extraction in seismic data: multi-attribute study from principal component analysis

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