Petrophysical Joint Inversion Applied to Alpine Permafrost Field Sites to Image Subsurface Ice, Water, Air, and Rock Contents

• Published in: Frontiers in Earth Science
• Main Authors: Coline Mollaret, Florian M. Wagner, Christin Hilbich, Cristian Scapozza, Christian Hauck
• Format: Article in Journal/Newspaper
• Language: English
• Published: Frontiers Media S.A. 2020
• Subjects: joint inversion; ground ice content; mountain permafrost; geophysics; electrical resistivity; refraction seismic; Science; Q; Ice; permafrost
• Online Access: https://doi.org/10.3389/feart.2020.00085; https://doaj.org/article/99b3ca2f0f1a4029879bc4c924693bab

Quantification of ground ice is crucial for understanding permafrost systems and modeling their ongoing degradation. The volumetric ice content is however rarely estimated in permafrost studies, as it is particularly difficult to retrieve. Standard borehole temperature monitoring is unable to provide any ice content estimation, whereas non-invasive geophysical techniques, such as refraction seismic and electrical resistivity measurements can yield information to assess the subsurface ice distribution. Electrical and seismic data are hereby complementary sensitive to the phase change. A petrophysical joint inversion was recently developed to determine volumetric water, air, ice and rock contents from electrical and seismic data using a petrophysical model, but was so far only tested on synthetic data and one proof-of-concept field example. In order to evaluate its applicability on different types of permafrost materials and landforms (bedrock, rock glacier, talus slope), we apply this petrophysical joint inversion scheme to five profiles located in the northwestern Alps. The electrical mixing rule (Archie's second law) was hereby identified as a source of model uncertainty, as it applies only when the electrolytic conduction is the dominating process. We therefore investigate and compare four petrophysical models linking the electrical resistivity with the ground constituents: Archie's law, Archie's law with an additional surface conduction factor, a model considering only surface conduction, and the geometric mean model. In most cases, the three first resistivity relations yield largely comparable results, whose reliability is discussed. The geometric mean model better resolve high ice content, as it is less influenced by the ice-rock ambiguity. We perform a systematic analysis of the regularization parameters and then evaluate our results with validation data including thaw depths and ice contents derived from borehole measurements. Geophysical surveys have generally a lower resolution than borehole data, but ...