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Erschienen in: Earth Science Informatics 1/2021

05.01.2021 | Research Article

Event sequence interpretation of structural geological models: a knowledge-based approach

verfasst von: Xianglin Zhan, Cai Lu, Guangmin Hu

Erschienen in: Earth Science Informatics | Ausgabe 1/2021

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Abstract

Access to information about the occurrence of past geological events and their chronology is crucial to cognize the evolution of subsurface structures. We refer to such tasks as Event Sequence Interpretation (ESI). The sequence of events describes the process of structural evolution and is the basis for structural interpretation and structural geological modeling. ESI has not been highly automated due to the need of a large amount of expert knowledge. However, manual ESI can introduce cognitive biases and is also difficult in structurally complex regions, thus affecting the credibility of structural interpretations. Therefore, we propose a knowledge-based ESI approach for structural geological models in this paper. A hierarchical cognition model lays the foundation for the ESI apptoach. A knowledge representation meta-model is used to formally represent the knowledge of geological events. Each instance of the meta-model is called an Event Pattern, which describes the associations between the occurrence of geological events and the geometric configuration of structural elements (geological surfaces and geological bodies). The chronology of geological events comes from the spatial relations of the structural elements. Our method can quickly infer the spatial relations between structural elements from the structural interpretation data and derive the possible temporal relationships between events from these spatial relationships. By demonstrating event sequence-guided structural modeling, we show the positive impact of event sequences on structural geological modeling.

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Metadaten
Titel
Event sequence interpretation of structural geological models: a knowledge-based approach
verfasst von
Xianglin Zhan
Cai Lu
Guangmin Hu
Publikationsdatum
05.01.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
Earth Science Informatics / Ausgabe 1/2021
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI
https://doi.org/10.1007/s12145-020-00558-2

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