Near-surface imaging plays a crucial role in mine development, safety, efficiency, and environmental risk mitigation. Challenges in deep mining often stem from complex geological conditions and anthropogenic factors, such as undocumented historical mining activities. This study presents an integrated geophysical approach that combines multiple geophysical techniques to characterize the near-surface environment and delineate potential water conduits in a deep mining context.

Most surface-wave techniques focus on estimating the S-wave velocity (VS) model and consider the P-wave velocity (VP) model as prior information in the inversion step. Here, we show the application of three surface-wave methods to estimate both VS and VP models. We apply the methods to the data from a hard-rock site that were acquired through the irregular source–receiver recording technique. We compare the outcomes and performances of the methods in detail.

We studied bedrock fracturing at Åland Islands from bedrock outcrops, digital elevation models and geophysics using multiple scales of observation. Using the results we can compare properties of the fractures of different sizes to find similarities and differences; e.g. we found that glacial erosion has a probable effect on the study of larger bedrock structures. Furthermore, we collected data from 100 to 500 m long fractures, which have previously proved to be difficult to sample.

Near-surface characterisation is of great importance. Surface wave tomography (SWT) is a powerful tool to model the subsurface. In this work we compare straight-ray and curved-ray SWT at near-surface scale. We apply both approaches to four datasets and compare the results in terms of the quality of the final model and the computational cost. We show that in the case of high data coverage, straight-ray SWT can produce similar results to curved-ray SWT but with less computational cost.

In passive seismic measurement, all noise sources from the environment, such as traffic, vibrations caused by distant excavation, and explosive work from underground mines, are utilized. In the Kylylahti experiment, receivers recorded ambient noise sources for 30 d. These recordings were subjected to data analysis and processing using novel methodology developed in our study and used for imaging the subsurface geology of the Kylylahti mine area.