Structural models: optimizing risk analysis by understanding conceptual uncertainty
Abstract Geoscience may be regarded as an uncertain science, as it is often based on the interpretation of equivocal data. Analysis of multiple interpretations of a single dataset has shown that conceptual uncertainty can result in a wide range of interpretational outcomes. Many geological models based on a wide variety of concepts were developed by different geoscientists for the same dataset. In this paper we suggest methods to improve the effectiveness of interpretation workflows based on understanding of how geoscientists apply concepts to equivocal datasets, the processes they use, the effects of their previous experience, and their use of broader contextual information. We argue that understanding the influence of conceptual uncertainty on interpretation of equivocal data and modification of current workflow practices can improve risk management.
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