Preliminary tunnel surveys are essential for identifying geological hazards such as aquifers, faults, and karstic zones. While first-arrival tomography is effective for imaging shallow anomalies, traditional seismic sources face significant limitations in forested mountainous regions due to mobility, cost, and environmental impact. To address this, we deployed a seismic source delivered by an unmanned aerial vehicle (UAV) for a highway tunnel survey in Lijiang, China. The UAV system, paired with nodal geophones, enabled rapid, low-impact, and high-resolution data acquisition in rugged terrain. To enhance the weak far-offset refractions affected by near-surface attenuation, we applied supervirtual refraction interferometry (SVI), which significantly improved the signal-to-noise ratio and expanded the usable first-arrival dataset. The combined use of UAV excitation and SVI processing produced a high-precision P-wave velocity model through traveltime tomography, aligned well with borehole data. This model revealed the spatial distribution of weathered zones and bedrock interfaces, and allowed us to infer potential fracture zones. The results offer critical guidance for tunnel alignment and hazard mitigation in complex geological settings.

This study presents stratigraphic and structure findings from the southeastern Bannu Basin, a structurally complex segment of the Sub-Himalayan foreland in Pakistan. Two dimensional seismic reflection data were integrated with well-log data from the Chonai-01 and Marwat-01 wells to reconstruct the subsurface basin architecture and to evaluate its hydrocarbon potential. In general, the deformation in the region is strongly controlled by the Neoproterozoic Salt Range Formation, with salt tectonics generating anticlines, deep salt detachment, and fault systems that form favorable structural traps. Seismic interpretation reveals both normal and reverse faulting, and multiple unconformities, indicating episodic tectonic activity linked to Himalayan orogeny. Well correlation of individual formations highlights lateral stratigraphic variations, including thick Siwalik Group deposits and key reservoir units such as the Datta and Lumshiwal formations. These findings demonstrate that mild salt-related deformation and stratigraphic discontinuities play a central role in hydrocarbon migration and entrapment. The structural and stratigraphic similarity of the Bannu Basin to the Potwar Plateau underscores its significant exploration potential within the Himalayan foreland system, while the integrated seismic–well workflow provides a robust framework for future exploration.

Unmanned aerial vehicles (UAVs) have gradually become an important technical platform for geophysical exploration because of their high mobility, low cost, adaptability to complex environments, and increasing capacity for autonomous operation. Conventional geophysical survey methods often face difficulties in equipment deployment, operational risk, and insufficient spatial resolution in mountain canyons, polar regions, volcanic areas, mining districts, and disaster-affected zones, whereas UAV platforms provide a new technical pathway for efficient, high-resolution, and low-disturbance geophysical observation. This review summarizes recent progress in UAV-based geophysical exploration, focusing on UAV platforms and intelligent control, UAV magnetic surveys, UAV gravimetry, UAV radiometric surveys, UAV electromagnetic surveys, UAV-based ground-penetrating radar, UAV seismic exploration, and UAV remote sensing for geological hazard monitoring. Although UAV geophysical exploration has made substantial progress, it still faces challenges related to payload capacity, sensor miniaturization, high-precision positioning, data quality control in complex environments, and multi-physics data fusion and interpretation.

Unmanned aerial vehicles (UAVs) extend geophysical measurements into terrain where ground access is difficult and crewed surveys are costly or operationally constrained. Their practical value, however, differs substantially among sensing methods and platform configurations. This narrative review compares UAV magnetometry, gravimetry, radiometric surveying, electromagnetic surveying, ground-penetrating radar (UAV-GPR), seismic surveying, and geological remote sensing. UAV magnetometry and geological surface mapping have the strongest evidence of established practice for defined tasks. Radiometric surveying, UAV-GPR, and several electromagnetic configurations have demonstrated field capability, but their performance depends on counting statistics, coupling, source geometry, and site conditions. UAV gravimetry has actual flight demonstrations, although large-aircraft results do not establish equivalent capability on compact platforms; UAV-assisted seismic systems remain application-specific. Across methods, useful performance depends on the complete measurement chain, particularly sensor clearance, motion and interference correction, timing, calibration, and independent validation. We identify requirements for multi-sensor interpretation and distinguish the roles and limitations of artificial intelligence in acquisition, processing, inversion, and quality control. Progress toward wider adoption should be assessed through reproducible survey performance and uncertainty, rather than payload integration alone.