[S-TT41] Seismic monitoring and processing system

[STT41-04] Cosmic-ray muography framework for density estimation in porous medium

*Ahmed Khaled Eleslambouly¹, Mohammed Ali¹, Jun Matsushima², Basiri Hamid², Fateh Bouchaala¹, Masashi Kodama³, Toshiyuki Yokota³ (1.Department of Earth Sciences, Khalifa University of Science and Technology , 2.Department of Environment Systems, Graduate School of Frontier Sciences, The University of Tokyo , 3.National Institute of Advanced Industrial Science and Technology (AIST) )

Keywords:Muography, Density Estimation, Geophysical Monitoring, Muon Attenuation

Muography, a passive geophysical imaging technique, has gained increasing attention for its capability to probe geological structures by detecting cosmic-ray muons flux. Muons, high-energy subatomic particles generated by galactic cosmic rays, provide a naturally occurring and cost-effective source for geophysical investigations. Their significant penetrating power enables the detection of density variations in geological structures and man-made objects. As muons pass through materials, interactions such as ionization and scattering cause attenuation of the muon flux, which can be directly correlated to the density of the material. This study presents a comprehensive methodological framework for density estimation using muography, focusing on material density and saturation degree variations. Our approach integrates experimental measurements with plastic scintillator detectors and numerical simulations using the PHITS Monte Carlo code to analyze muon attenuation through different materials. This study applies this principle to acrylic and sand objects of varying densities, utilizing both laboratory experiments and simulations to derive empirical relationships between density length and muon flux. Our experimental setup involved placing acrylic and sand samples of known density and varying thicknesses between Four plastic scintillator detectors. Measurements were conducted over extended periods to capture statistically significant flux variations. To enhance data reliability, we applied a series of filters and corrections to filter to isolate muon signals from background noise and environmental variations. The results demonstrate the effectiveness of muography in detecting density variations across materials with distinct saturation levels. Acrylic samples of varying thickness exhibited attenuation patterns consistent with theoretical predictions. The measured densities showed reduced relative errors after applying filtering and environmental corrections, highlighting the importance of these preprocessing steps. Simulation results, though generally consistent with experimental data, revealed discrepancies at smaller thicknesses attributed to model simplifications and boundary conditions. In the case of sand samples with varying degrees of water saturation, muon flux attenuation correlated strongly with increasing density due to water content. Our findings confirmed the method's sensitivity to even minor changes in saturation, with errors remaining within acceptable limits for practical geophysical applications. The empirical relationships obtained were used to construct a density estimation model that can be generalized for similar geological settings. The presented methodological framework underscores the potential of muography as a reliable, non-invasive tool for subsurface density estimation. The technique's passive nature and minimal operational costs make it particularly suitable for long-term monitoring of reservoirs and density changes associated with varying fluid properties due to production or injection. Additionally, integrating laboratory experiments with simulations provides a robust validation of the proposed model, contributing to improved accuracy in density estimation. This research advances the application of muography in geophysical studies by offering a systematic approach to density estimation supported by empirical evidence from both experimental and simulated datasets.