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 Unveiling Fault Orientation Evolution

ActiveFaultOrientation 

Over the past three decades forward thermo-mechanical numerical modeling has transformed the way geoscientists look at the long-term evolution of the lithosphere. More than just generating aesthetically pleasing pictures, outputs from numerical models contain a rich source of quantitative information that can be used to infer the evolution of rocks in ancient and actively deforming regions. For example, pressure-temperature-time evolution of rock materials have long been extracted from 2D and 3D forward thermo-mechanical numerical models as these three scalar variables are direct outputs from the codes. Such data have been used successfully by petrologists and modelers to decipher the fate of metamorphic rocks in orogens providing valuable insights into the formation mobile belts. However, problem arises when one tries to extract structural patterns - which are not a scalar field computed in the codes - from 3D models. Structural data is the next step to adding value to any numerical experiment. How can we then compare, for example, the active surface deformation distribution in a 3D model with faults orientation in nature? It can be done manually by measuring active fault orientations at the surface of a model, but this is time consuming and might introduce bias in delineating individual faults. Some automatized attempts have relied on stress data, but as 3D strain dominates in 3D models, we cannot safely apply an Andersonian model to infer fault orientation ... continued


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Contributed by Guillaume Duclaux, Université Côte d'Azur

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