EGU25-4107, updated on 14 Mar 2025
https://doi.org/10.5194/egusphere-egu25-4107
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Poster | Monday, 28 Apr, 14:00–15:45 (CEST), Display time Monday, 28 Apr, 08:30–18:00
 
vPoster spot A, vPA.17
Sequential Gaussian Mixtures for Transient Hydraulic Tomography Inversion in Fractured Aquifers
Prem Chand Muraharirao and Phanindra Kbvn
Prem Chand Muraharirao and Phanindra Kbvn
  • Indian Institute of Technology Hyderabad, Civil Engineering, India (ce22resch11007@iith.ac.in)

Fractured aquifer parameters are expected to have complex non-Gaussian spatial distributions. Gaussian Mixture Models, known for their effectiveness in representing non-Gaussian distributions, present a promising alternative for capturing the complex heterogeneity of fractured geologic settings however their usage in the fractured geologic settings is unexplored. In this study we extended the application of Gaussian mixtures to transient hydraulic tomography on laboratory-based fractured geologic settings using sequential Gaussian Mixture Model (GMM). We further examined the impact of the number of Gaussian components, sampling strategies and the amount of pumping data on the performance of the sequential GMM. Results demonstrate that GMM with an optimal number of Gaussian components effectively identifies high and low conductivity regions, fracture connectivity, and reasonably predicts drawdowns (R² = 0.61) pumping from validation ports. Stratified sampling of GMM parameters (R2 = 0.74, average RMSEmedian= 9.89 mm) outperforms other sampling strategies like random (R2 = 0.61, average RMSEmedian= 20.64 mm ), uniform (R2 = 0.64, average RMSEmedian= 11.70 mm) and quasi-random sampling (R2 = 0.67, average RMSEmedian= 11.40 mm) techniques in mapping the fracture connectivity and parameter distribution. Stratified sampling with reduced and information-based pumping data maintains commensurable accuracy (R2 = 0.75, average RMSEmedian= 11.34 mm). Overall, our findings suggest that the sequential GMM combined with stratified sampling technique effectively captures the spatial variability of aquifer parameters in fractured media.

How to cite: Muraharirao, P. C. and Kbvn, P.: Sequential Gaussian Mixtures for Transient Hydraulic Tomography Inversion in Fractured Aquifers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4107, https://doi.org/10.5194/egusphere-egu25-4107, 2025.