Integration of surface-based tomographic models for zonation and multimodel guided extrapolation of sparsely known petrophysical parameters
Integration of surface-based tomographic models for zonation and multimodel guided extrapolation of sparsely known petrophysical parameters
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集成基于地表的层析成像模型，用于对稀疏已知的岩石物理参数进行分区和多模型引导外推
DOI：
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发表时间：
2013
期刊：
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通讯作者：
H. Paasche
中科院分区：
文献类型：
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作者：
B. Hachmöller;H. Paasche
摘要：我们通过修改最近开发的用于跨钻孔层析成像模型集成的统计方法来集成从地球表面获取的多个层析成像模型的信息。在此过程中，我们引入谱聚类分析作为模型集成过程的新核心，以捕获所有考虑的断层扫描模型中存在的空间异质性，并以模糊的方式描述这种异质性。由于谱聚类算法在本地分析模型结构，因此对于在地球表面进行的地球物理层析成像测量典型的系统和空间变化成像能力而言，它们被认为相对稳健。以合成含水层为例，模糊谱聚类算法可用于集成二维断层摄影折射地震和直流电阻率勘测提供的信息。然后，使用模糊隶属度域中的综合信息来导出综合的区域地球物理模型概述...
ABSTRACTWe integrate the information of multiple tomographic models acquired from the earth’s surface by modifying a statistical approach recently developed for the integration of cross-borehole tomographic models. In doing so, we introduce spectral cluster analysis as the new core of the model integration procedure to capture the spatial heterogeneity present in all considered tomographic models and describe this heterogeneity in a fuzzy sense. Because spectral cluster algorithms analyze model structure locally, they are considered relatively robust with regard to systematically and spatially varying imaging capabilities typical for geophysical tomographic surveys conducted on the earth’s surface. Using a synthetic aquifer example, a fuzzy spectral cluster algorithm can be used to integrate the information provided by 2D tomographic refraction seismic and DC resistivity surveys. The integrated information in the fuzzy membership domain is then used to derive an integrated zonal geophysical model outlinin...