The Research Group focuses on determining the physical properties of consolidated and unconsolidated rocks, i.e. physical rock parameters such as electrical and hydraulic conductivity, porosity, density, magnetic susceptibility, etc., across various spatial scales – from core samples in the laboratory and in-situ borehole measurements to large-scale field surveys.
Quantifying the material properties of geological architectural elements is essential for addressing applied questions related to the sustainable use of the subsurface. Numerical modelling and simulations are employed to predict the development of subsurface systems in response to management strategies and external boundary conditions. Current examples of societal relevance include assessing the impact of sea-level rise and storm surges on groundwater resources, risk assessment in areas prone to sinkholes, and the sustainable utilisation of geothermal energy.
LIAG’s rock physics laboratories and borehole logging equipment are unique in Germany, both in terms of the range of measurable physical rock parameters and the associated scientific expertise. Often, it is only the combined interpretation of different physical parameters that enables an improved representation of the subsurface – and thus its potential use, for instance in energy or fluid storage.
These methods are used to determine the physical parameters of subsurface structures in boreholes. Measurements include acoustic, magnetic, electrical, electromagnetic, nuclear, mechanical, and imaging techniques down to depths of up to six kilometers.
Hydraulic, electrical, structural, and thermal properties of consolidated and unconsolidated rock material are analyzed at LIAG across scales from the pore to the core. Techniques include (gas) permeametry, spectral induced polarization, nitrogen adsorption, nuclear magnetic resonance spectroscopy, and capillary pressure measurements. The samples are examined for permeability, pore geometry (e.g., via micro-CT), and porosity. These measurements are critical for characterizing reservoirs, energy storage formations, and aquifers, and serve as input for numerical and mathematical models. The combination and comparison of different physical parameters also help evaluate and optimize the use of various measurement methods for specific applications.
Magnetic properties of rocks are measured under magnetically shielded conditions and at high temperatures. These serve as proxies for reconstructing geological and climatic changes over long timescales. Rock magnetism helps address questions related to soil properties, pollution, and diagenesis. Magnetostratigraphy enables reconstruction of geomagnetic polarity reversals to determine the age and geological history of rocks. LIAG’s Grubenhagen facility houses one of Germany’s most sensitive cryogenic magnetometers, and the only one capable of measuring full drill cores. Such measurements provide valuable chronological data on rock formations.
This area investigates the mechanical and hydraulic behavior of rocks. At LIAG, experiments are conducted under variable stress, temperature, and fluid pressure conditions using a true triaxial testing system equipped with deformation, acoustic emission, and ultrasonic measurement capabilities. By determining parameters such as elastic modulus, permeability, and induced microseismicity, the behavior of rocks under reservoir conditions (pressure and temperature) can be evaluated for applications such as deep geothermal energy, energy storage, and nuclear waste disposal.
Cyclostratigraphy is applied for pattern recognition in sedimentary rocks and to complement luminescence dating and paleomagnetism in determining rock ages. Multivariate statistical methods are also used for characterizing rock properties, particularly based on borehole data.
The inherent heterogeneity and measurement uncertainties in subsurface material properties mean that subsurface models are typically underdetermined. This parameter uncertainty also affects the reliability of forecasts, making its quantification and communication essential. Tools from geostatistics and stochastic modeling are used to address these challenges.

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