Guanyu Yuan
+49 345 / 55 – 26076
lisa.ringel@geo.uni-halle.de
Room 4.23
von-Seckendorff-Platz 3
06120 Halle (Saale)
+49 345 / 55 – 26076
lisa.ringel@geo.uni-halle.de
Room 4.23
von-Seckendorff-Platz 3
06120 Halle (Saale)
My research focuses on the stochastic characterization of discrete fracture networks (DFNs). I use data from tomographic experiments to infer the properties of DFNs. For this purpose, I work on the implementation of fast forward models by suitable numerical methods and I compare different inversion approaches by their efficiency and performance.
2019 – today | Research Assistant
Martin Luther University Halle-Wittenberg, Applied Geology
2019 – 2023 | PhD student
Martin Luther University Halle-Wittenberg, Applied Geology
2018 – 2019 | Research Assistant
Ingolstadt University of Applied Sciences, Institute of New Energy Systems (InES)
2018 | Master‘s thesis
German Aerospace Center, Institute of Aeroelasticity
Title: Preliminary design of a wind tunnel experiment for transient shock boundary layer interaction
2017 – 2018 | M. Eng. Technical Development in Mechanical Engineering
Ingolstadt University of Applied Sciences
2015 – 2018 | Scholarship holder
Max Weber-Program
2013 – 2017 | B. Eng. Renewable Energy Technologies
Ingolstadt University of Applied Sciences
Ringel, L. M., Illman, W. A., & Bayer, P. (2024). Recent developments, challenges, and future research directions in tomographic characterization of fractured aquifers. Journal of Hydrology, 631, 130709.
Römhild, L., Ringel, M. L., Liu, Q., Hu, L., Ptak, T. & Bayer, P. (2024). Hybrid Discrete Fracture Network Inversion of Hydraulic Tomography Data From a Fractured-Porous Field Site. Water Resources Research, 60, e2023WR036035.
Jiang, Z., Ringel, L. M., Bayer, P. & Xu, T. (2023). Fracture Network Characterization in Reservoirs by Joint Inversion of Microseismicity and Thermal Breakthrough Data: Method Development and Verification. Water Resources Research, 59(9), e2022WR034339.
Ringel, L. M., Jalali, M. & Bayer, P. (2022). Characterization of the highly fractured zone at the Grimsel Test Site based on hydraulic tomography. Hydrol. Earth Syst. Sci., 26, 6443–6455.
Ringel, L. M., Jalali, M. & Bayer, P., (2022). Inversion of
Hydraulic Tomography Data from the Grimsel Test Site with a Discrete Fracture Network Model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2220, https://doi.org/10.5194/egusphere-egu22-2220.
Ringel, L. M., Jalali, M. & Bayer, P. (2022). Estimation of hydraulic and geometrical characteristics of fractured geothermal reservoirs using in-situ tomographic methods, European Geothermal Congress 2022, Berlin, Germany, 17–21 October 2022.
Ringel, L. M., Jalali, M. & Bayer, P. (2021). Stochastic Inversion of Three-Dimensional Discrete Fracture Network Structure With Hydraulic Tomography. Water Resources Research. 57(12), e2021WR030401.
Ringel, L. M., Jalali, M. & Bayer, P. (2020). Inversion of three-dimensional discrete fracture networks using hydraulic tomography. Paper presented at the AGU Fall Meeting, virtual.
Ringel, L. M., Somogyvari, M., Jalali, M. & Bayer, P. (2020). Characterization of discrete fracture networks by invasive tomographic methods. Paper presented at Computational Methods in Water Resources, virtual.
Ringel, L. M., Somogyvari, M., Jalali, M., & Bayer, P. (2020). A fast and robust approach for simulating the pressure diffusion in three-dimensional discrete fracture networks applied to inversion problems. Paper presented at the EGU General Assembly, virtual.
Ringel, L. M., Somogyvári, M., Jalali, M., & Bayer, P. (2019). Comparison of Hydraulic and Tracer Tomography for Discrete Fracture Network Inversion. Geosciences, 9(6), 274.
Ringel, L. M., Somogyvári, M., Jalali, M., & Bayer, P. (2019). Inversion of discrete fracture networks by hydraulic and tracer tomography. Paper presented at the EGU General Assembly, Vienna.
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