Review of geophysical data acquisition methods for underground feature detection and future trends
Year: 2025
Type: article
Abstract: Accelerated human activities and the growing demand for natural resources have facilitated the need for a comprehensive understanding of subsurface environments. This paper comprehensively reviews non-destructive geophysical data acquisition methods for underground feature detection (UFD), focusing on wave-based methods (e.g., seismic and acoustic waves), electromagnetic field-based methods (e.g., electrical resistivity tomography (ERT) and transient electromagnetic method (TEM)), and density contrast-based methods (gravimetry and muography). The principles, historical development, current research trends and field applications of each method are discussed, with their respective advantages and limitations analysed. Wave-based methods, such as ground-penetrating radar and seismic reflection, offer high-resolution imaging for near-surface cavities but are constrained by signal attenuation and geological heterogeneity. Electromagnetic methods provide deeper penetration but are affected by external interference and conductivity variations. Density contrast-based methods provide stable and non-invasive detection of deeply buried cavities, although conventional gravimeters face challenges related to resolution and sensitivity. Quantum gravimeter, the most recent advancement, leverages atomic interferometry for unparalleled precision, yet its widespread adoption remains constrained by issues of portability, environmental stability, and cost. Future advancements will focus on enhancing detection accuracy, improving real-world applicability, and integrating artificial intelligence to automate data processing and refine multi-method data fusion.
Authors: Chuanyang Peng, Chao Wang, Zili Li
Institution: University College Cork
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,820
Award: G5020180812
OpenAlex ID: W4410196351
