Home | People | Lisa Maria Ringel, MEng

Lisa Maria Ringel, MEng

MEng Lisa Maria Ringel

+49 345 / 55 – 26076

Room 4.23
von-Seckendorff-Platz 3
06120 Halle (Saale)

Lisa Maria Ringel, MEng

+49 345 / 55 – 26076

Room 4.23
von-Seckendorff-Platz 3
06120 Halle (Saale)

About Me

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.

Research Interests

■  Numerical Methods
■  Inversion
■  Bayesian statistics
■  Hydraulic and Tracer Tomography

CV

2019 – today | 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

Publications

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., and 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.

Bayer, P., Afshari Moein, M. J., Somogyvári, M., Ringel, L. M., & Jalali, M. (2020). Stress-based tomography: potential, open-questions and future developments. Paper presented at the EGU General Assembly, 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.

Logo applied geoology
Daniela Rothe
Daniela Rothe

Secretary

Tel.: +49 345 / 55 – 26151
Fax: +49 345 / 55 – 27068

Room H3 1.30
von-Seckendorff-Platz 3
06120 Halle (Saale)