VDI – Vertical Data Integration: First Test Run Using “Schechen” Data

After our initial – and admittedly somewhat bumpy – attempts with a regional pilot project to assess groundwater and soil moisture using geo-magnetic resonance (GMR), the next step was a consolidated evaluation of the data we had collected. Our goal: to combine these datasets with other sources of information – particularly electrical resistivity and borehole data (“groundtruthing”) – to enable more precise, depth-related interpretations. This approach we coin as Vertical Data Integration (VDI).

I first encountered this method during my PhD studies at the University of Hawai‘i at Mānoa, through my supervisor Dr. Roy H. Wilkens, who has continued to refine and expand his toolbox ever since (still going strong, by now well into his 70s!)

Originally developed to analyze acoustic profile data from the top-ten meters of ocean seabed, the method was later adapted to core samples from scientific ocean drilling expeditions – and can now be applied to our GMR signals and virtually any type of subsurface dataset.

The open-source tool set behind it has been steadily evolving since 1995. It's now extremely robust and well-suited for integration into our terrestrial workflows – efficient, intuitive, and above all: low-cost.

How does it work?

Whether you're working with electrical resistivity, seismic, or our GMR data – i.e. any near-surface or borehole-based geophysical measurements – our open-source tool allows you to visualize and analyze them in a depth-referenced way. At its core, the method enables the layered integration of geospatial data 🔗:

• Merging of electrical resistivity data, GMR measurements, core images, and other relevant data layers

• Implemented using a proven, open-source processing framework (continuously maintained and expanded since 1995+)

• Fully compatible with established GIS workflows like ArcGIS and QGIS

First Deployment: Schechen Pilot Project

This workflow was first deployed as part of our GMR-FLEX pilot trial in the town of Schechen. The objective: to quasi-correlate GMR data with resampled, pixel-based scaled core images – which, while still limited in resolution (smartphone photos!), served as a useful proof of concept.

Fig. 1: Vertical Data Integration (VDI) using GMR data (Geo-Magnetic Resonance), shown in depth-referenced comparison with image data from the drilled cores. The core images are first digitally cropped and aligned (top right), then normalized to a uniform pixel scale (top center). In the final step, the images are stitched together according to drilling depth to create a composite profile image (bottom left), allowing for direct comparison with the GMR data or integrated profile analysis with other data types – such as electrical resistivity or magnetics. The method is based on an open-source code that has been used in similar form for over 20 years in the field of scientific ocean drilling.

What’s next?

Since our data quality in late March was heavily affected by increased signal noise – likely caused by the nearby drilling rig – we’re planning a second GMR-FLEX pilot run for May to July 2025. Hence, our next targets are:

🔹 Goal 1: Improve GMR signal quality

🔹 Goal 2: Achieve full-depth measurements via borehole probe

This next trial will also allow us to detect temperature-driven changes in soil moisture, which is a key advantage for modeling water availability and distribution within the “sponge-like” subsurface. Additionally, GIS-based analyses of land use, water supply, and infrastructure (e.g., power lines, solar installations) will provide valuable context for interpretation.

Fig. 2: Our A(ction) Team in the Schechen Forest, located about 20 km north of Rosenheim (top left). After inspecting the core drilling rig (top right), we laid out and conducted the surface GMR measurement profiles around the drilling site in the forest. At this point, the drilled cores were still on site, covered with a plastic sheet (visible in the background of the top right photo), and could be documented using our smartphones. GMR signal interference caused by temporary operation of the drilling rig, along with limited image quality, resulted in modest data yield – but sufficient to enable an initial depth-referenced data and profile analysis using the VDI tool.

To be continued …

Carpe H2O | Panta Rhei | VDI | UH-Manoa Alumni Association