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首页> 外文期刊>Geophysics: Journal of the Society of Exploration Geophysicists >Probabilistic falsification of prior geologic uncertainty with seismic amplitude data: Application to a turbidite reservoir case
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Probabilistic falsification of prior geologic uncertainty with seismic amplitude data: Application to a turbidite reservoir case

机译:利用地震振幅数据对先前地质不确定性进行概率伪造:在浊积岩储层中的应用

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摘要

Geophysical subsurface modeling is often highly uncertain due to limited data resolution. At the same time, a wealth of geologic information, often from databases and outcrop studies, is available to state prior uncertainty on key geologic modeling parameters. In most inversion procedures, these uncertainties are ignored and only a limited number of geologic scenarios are considered. We have developed a workflow, inspired by a Popper-Bayes philosophy that aims at probabilistically updating prior geologic parameters uncertainty with data without the need for inversion or iterative data conditioning. Our approach consists of stating a wide prior model of uncertainty (in rock physics and facies), and generating a set of facies models and their corresponding geophysical responses (here the seismic response) by forward simulation. Then, a global measure of similarity is defined between any two generated seismic responses and the field data. The proposed measure, based on the wavelet transform decomposition, analyzes differences in patterns found in the seismic data and aims at comparing seismic images as a whole, avoiding any local trace-by-trace comparison. Based on this global measure of similarity, our procedure identifies the geologic interpretations that are unlikely given the observed seismic data. The proposed approach was applied and validated using seismic data from a synthetic example and an offshore reservoir in west Africa. The uncertainty included geologic parameters, such as infill channel size, proportion, and sinuosity, and geophysical parameters, such as the rock physics model and the wavelet in the forward seismic model. The synthetic example allowed for the validation of the methodology using rejection sampling. For the offshore reservoir, updated probabilities were obtained for each uncertain parameter, and some of the prior geologic interpretations were found to be inconsistent with the available seismic amplitude data cube (e.g., narrow channel width).
机译:由于有限的数据分辨率,地球物理地下建模通常高度不确定。同时,大量的地质信息(通常来自数据库和露头研究)可用于陈述关键地质建模参数的先验不确定性。在大多数反演程序中,这些不确定性都会被忽略,仅考虑有限数量的地质情况。我们开发了一个工作流程,该工作流程的灵感来自Popper-Bayes哲学,该哲学的目的是用数据概率地更新先前的地质参数不确定性,而无需进行反演或迭代数据条件处理。我们的方法包括陈述一个广泛的先验不确定性模型(在岩石物理学和相中),并通过正演模拟生成一组相模型及其对应的地球物理响应(此处为地震响应)。然后,在任意两个生成的地震响应与现场数据之间定义相似度的全局度量。所提出的措施基于小波变换分解,分析了地震数据中发现的模式差异,旨在整体比较地震图像,从而避免了任何局部逐迹线比较。基于这种全球相似性度量,我们的程序确定了在观察到的地震数据下不太可能发生的地质解释。拟议的方法已应用并使用了来自合成实例的地震数据和西非的一个海上储层进行了验证。不确定性包括地质参数,例如填充通道的大小,比例和波度,以及地球物理参数,例如岩石物理模型和正向地震模型中的小波。综合示例允许使用拒绝采样对方法进行验证。对于近海油藏,获得了每个不确定参数的更新概率,并且发现一些先前的地质解释与可用的地震振幅数据立方体(例如,狭窄的河道宽度)不一致。

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