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Characterization of the Slope-destabilizing Effects of Gas-charged Sediment via Seismic Surveys

机译:含气沉积物的边坡稳定作用的地震勘测表征

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Finneidfjord, Norway has a history of submarine slope failure and hosts areas of buried, gas-chargedsediment. Using shipboard seismic survey data from Finneidfjord, we illustrate how novel seismic dataprocessing techniques can yield estimates of geotechnical properties of this gas-charged sediment: gassaturation (concentration) and excess pore pressure as well as their uncertainty. This data processinginvolves two steps: 1) estimate the amount of seismic attenuation that a gas-bearing layer creates, and 2)fit a wave attenuation model to the observed attenuation. We accomplish the first step using a waveletbasedspectral ratio approach, and find the seismic quality factor (inversely related to attenuation) fromthe change in amplitude spectra across the gas layer. The novelty of this paper really comes in the secondstep, where we create a Bayesian hierarchical model that combines a wave attenuation model with aspatial random (Gaussian) process model. The advantage of this combination is that our estimates of thegas properties not only must conform to the observations of attenuation (quality factor), but must alsosmoothly vary over space, as one would expect of any natural process. Ultimately, we end up withposterior distributions of gas properties at points throughout our gas-bearing layer, which give usestimates of parameter values and a sense of uncertainty about these estimates. We find good performanceand agreeable values for gas saturation, but the model shows weak sensitivity to pressure, leaving largeuncertainty in any excess pore pressure estimates. Implications for slope stability at Finneidfjord arediscussed.
机译:Finneidfjord,挪威拥有潜艇斜坡衰竭的历史,埋藏地区的埋地区域 沉淀。使用Finneidfjord的船舶地震测量数据,我们说明了新的地震数据 加工技术可以产生该气带沉积物的岩土性质的估计:气体 饱和度(浓度)和过量的孔隙压力以及它们的不确定性。此数据处理 涉及两个步骤:1)估计含气层产生的地震衰减量,2) 将波浪衰减模型适合观察到的衰减。我们使用一个小波划分的第一步完成第一步 光谱比方法,找到地震品质因素(与衰减相反) 气体层幅度谱的变化。本文的新颖性真的来自第二个 步骤,我们创建一个贝叶斯分层模型,将波浪衰减模型与a结合起来 空间随机(高斯)过程模型。这种组合的优势在于我们的估计 气体特性不仅必须符合衰减的观察(质量因数),而且还必须 随着空间平稳变化,因为人们会期望任何自然过程。最终,我们最终结束了 在整个含气层的煤气性能下的后分布,给我们 参数值的估计和这些估计的不确定性感。我们觉得很好 瓦斯饱和度的令人愉快的价值,但该模型显示对压力的敏感性较弱,留下大 任何过量的孔隙压力估算中的不确定性。 Finneidfjord对边坡稳定性的影响 讨论。

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