AUTHOR=Deng Tengfei TITLE=Poroelastic effects on seismic monitoring in partially saturated loosely deposited sands JOURNAL=Frontiers in Earth Science VOLUME=Volume 13 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2025.1561168 DOI=10.3389/feart.2025.1561168 ISSN=2296-6463 ABSTRACT=IntroductionA better understanding of the relationship between water saturation and seismic characteristics of loosely deposited sand is crucial for assessing the liquefaction potential of open-pit mine dumps. The classic elastic models, based on Gassmann’s theory, are commonly used to constrain water saturation from seismic data. However, while effective at low frequencies, these models fail to capture macroscopic wave-induced fluid flow and poroelastic effects at higher frequencies, which may hinder the application of laboratory results to field conditions. In contrast, Biot’s poroelastic theory enables seismic wave propagation modeling across a broad frequency range.MethodsTo evaluate poroelastic effects in seismic monitoring, we compare elastic and poroelastic models in terms of wave velocities, Poisson’s ratio, P-wave travel time, and surface wave dispersion across different frequencies. Our study incorporates numerical simulations and experimental data to assess the extent of discrepancies between these models.ResultsOur findings show that the poroelastic model predicts seismic wave velocities with up to a 6% difference compared to the elastic model. While minimal differences are observed in field-scale surveys, the discrepancies become more significant in pilot plant experiments and ultrasonic measurements as frequency increases. These results highlight the influence of poroelastic effects, which are not captured adequately by elastic models at higher frequencies.DiscussionThe observed frequency-dependent discrepancies suggest that elastic models may be insufficient for high-frequency seismic applications. This underscores the need for improved methodologies that integrate poroelastic effects to enhance the scalability of laboratory findings to field conditions.