About

John Hole is a Professor of Geophysics at the Department of Geosciences, Virginia Tech. He earned his Ph.D. from the University of British Columbia in 1993. His research focuses on exploration seismology of the continental crust, contributing to the understanding of geophysical properties and processes within Earth's crust. He is involved in research activities related to geophysics, with a particular emphasis on seismic exploration and crustal studies. His contact information includes his office at 1040 Derring Hall, Virginia Tech, and his research group maintains a homepage with further details about his work.

Research topics

• Geology
• Artificial Intelligence
• Computer Science
• Mining engineering
• Geotechnical engineering
• Seismology
• Waste management
• Petroleum engineering
• Engineering

Selected publications

• Radar imaging of fracture geometry and aperture to characterize rock-fall hazards in mining

  Geophysics · 2025-01-11 · 1 citations

  articleSenior author

  ABSTRACT Ground-penetrating radar (GPR) is used in an underground salt mine to detect and characterize mining-induced fractures concealed in the mine roof. GPR images reflections from <1 to approximately 50 m into the salt. Fracture locations and apertures identified by radar are validated with fractures logged in drillholes and exposed fractures. Open fractures with apertures <1 mm are imaged due to the strong dielectric contrast between salt and air. Depth migration from topography accurately positions the fractures within the mine roof. Radar images all previously known fractures and adds previously unknown information. Radar works between rock bolts. Radar attenuation is quantified using reflections at 77 logged fracture intersections in drillholes. This enables the prediction of the fracture aperture. Strong variations in aperture are observed along the fractures. The imaged roof fractures are interpreted to be caused by extensional stress induced by the mined cavity. The ability of GPR to image and quantify fractures in the mine roof can improve mine safety mitigation.

  PublisherDOI

• Distributed acoustic sensing (DAS) for longwall coal mines

  International Journal of Rock Mechanics and Mining Sciences · 2025-03-27 · 5 citations

  article
  PublisherDOI

• Distributed Acoustic Sensing (DAS) for Longwall Coal Mines

  2024-12-19

  preprintOpen access

  Seismic monitoring of underground longwall mines can provide valuable information for managing coal burst risks and understanding the ground response to extraction. However, the underground longwall mine environment poses major challenges for traditional in-mine microseismic sensors including the restricted use of electronics due to potentially explosive atmospheres, the need to frequently and quickly relocate sensors as rapid mining progresses, and source parameter errors associated with complex time-dependent velocity structure. Distributed acoustic sensing (DAS), a technology that uses rapid laser pulses to measure strain along fiber-optic cables, shows potential to alleviate these shortcomings and improve seismic monitoring in coal mines when used in conjunction with traditional monitoring systems. Moreover, because DAS can acquire measurements that are not possible to record with traditional seismic sensors, it also enables entirely new monitoring approaches. This work demonstrates several DAS deployment strategies such as deploying fiber on the mine floor, in boreholes drilled from the surface and from mine level, on the longwall mining equipment, and wrapped around secondary support cans. Although there are several data processing and deployment improvements needed before DAS-based monitoring can become routine in underground longwall mines, the findings presented here can aid decision makers in assessing the potential of DAS to meet their needs and help guide future deployment designs.

  PublisherOA PDFDOI

• An Autoencoder-Based Deep Learning Model for Enhancing Noise Characterization and Microseismic Event Detection in Underground Longwall Coal Mines Using Distributed Acoustic Sensing Monitoring

  50th U.S. Rock Mechanics/Geomechanics Symposium · 2024 · 5 citations

  • Computer Science
  • Artificial Intelligence
  • Mining engineering

  ABSTRACT: The longwall mining method is designed to optimize coal extraction through controlled roof caving, which inevitably induces seismicity. This research employs a distributed acoustic sensing (DAS) system incorporating a fire-safe fiber-optic cable strategically installed underground within an operational longwall coal mine. Despite lower sensitivity than traditional seismometers, DAS sensing technology benefits from dense sensor spacing and close proximity to the active face, where many microseismic events occur. To automatically detect seismic events within the voluminous DAS data records, we employ convolutional autoencoder deep learning models that can be used for anomaly (potential seismic event) detection in power spectral density (PSD) images of DAS recordings. The kernel density estimation (KDE) technique is used to calculate the probability density function (PDF) for the density scores of the latent space (representation of compressed data). We then use this calculated parameter as a threshold to distinguish between the PSD associated with background noise and with potential seismic events. The DAS monitoring system in conjunction with the developed deep learning model could enhance longwall coal mining safety and efficiency by offering valuable data from its densely deployed multichannel sensors near mining operations. 1. INTRODUCTION Longwall mining is an efficient underground mining method for extracting a variety of stratified resources including coal, potash, and soda ash and represents a considerable advancement over conventional methods (Peng, 2019). A modern longwall primarily consists of hydraulic shields that support the roof and floor, a cutting device (e.g., a shearer or plow) that travels along the face extracting slices of coal, and an armored conveyor belt, which transports the resource to a larger mine haulage system. Normally longwall mining is safe and efficient, but a variety of ground control-related hazards are possible, especially in deep mines. One of the most significant of these hazards is a class of dynamic failures associated with induced seismicity and damage to mine workings, generally referred to as coal bursts or mine bumps. Much like tectonic earthquakes, mining-induced seismicity is difficult to predict and can have devastating consequences. For example, over the past several decades, coal bursts have killed hundreds of miners (Zhang et al., 2017).

  PublisherDOI

• Radar imaging of fractures and voids behind the walls of an underground mine

  Geophysics · 2021 · 6 citations

  • Geology
  • Geotechnical engineering

  Two- and three-dimensional rock-penetrating-radar data were acquired on the wall of a pillar in an underground limestone mine. The objective was to test the ability of radar to image fractures and karst voids and to characterize their geometry, aperture, and fluid content, with the goal of mitigating mining hazards. Strong radar reflections in the field data correlate with fractures and a cave exposed on the pillar walls. Large pillar wall topography was included in the steep-dip Kirchhoff migration algorithm because standard elevation corrections are inaccurate. The depth-migrated 250 MHz radar images illuminate fractures, karst voids, and the far wall of the pillar up to approximately 25 m depth into the rock, with a spatial resolution of <0.5 m. Higher frequency radar improved the image resolution and aided in the interpretation, but at the cost of shallower depth of penetration and extra acquisition effort. Due to the strong contrast in physical properties between the rock and the fracture fluid, fractures with apertures as thin as a 50th of a radar wavelength were imaged. Water-filled fractures with mm-scale aperture and air-filled fractures with cm-scale apertures produce strong reflections at 250 MHz. A strong variation in the reflection amplitude along each fracture is interpreted to represent the variable fracture aperture and the nonplanar fracture structure. Fracture apertures were quantitatively measured, but distinguishing water from air-filled fractures was not possible due to the complex radar wavelet and fracture geometry. Two conjugate fracture sets were imaged. One of these fracture sets dominates the rock mass stability and water inrush challenges throughout the mine. All of the detected voids and a large cave are at the intersection of two fractures, indicating preferential water flow and dissolution along conjugate fracture intersections. Detecting, locating, and characterizing fractures and voids prior to excavation can enable miners to mitigate potential collapse and flood hazards before they occur.

  PublisherDOI

• RADAR IMAGING OF FRACTURES AND VOIDS BEHIND THE WALLS OF AN UNDERGROUND MINE

  Abstracts with programs - Geological Society of America · 2020-01-01

  article
  PublisherDOI

• EVOLUTION OF THE NORTHERN US CORDILLERA: RESULTS FROM THE IDOR EARTHSCOPE PROJECT

  Abstracts with programs - Geological Society of America · 2020

  1st authorCorresponding
  • Geology
  PublisherDOI

• Ground-Penetrating Radar for Karst Detection in Underground Stone Mines

  Mining Metallurgy & Exploration · 2019-12-01 · 19 citations

  articleSenior author
  PublisherDOI

• Aftershock Sequence of the 2011 Virginia Earthquake Derived from the Dense AIDA Array and Backprojection

  Bulletin of the Seismological Society of America · 2019-01-02 · 8 citations

  articleOpen accessCorresponding

  After the 23 August 2011 Mineral, Virginia, earthquake, a temporary dense array (Aftershock Imaging with Dense Arrays (AIDA)) consisting of ~200 stations was deployed at 200-400 m spacing near the epicenter for 12 days. Backprojection of the data was used to automatically detect and locate aftershocks. The co-deployment of a traditional aftershock network of 36 stations at ~2-10 km spacing enables a quantitative comparison. The AIDA backprojection aftershock catalog is complete to magnitude -1.0 and includes events as small as M-1.8. For comparison, the traditional network was complete to M-0.3 for the same time period. The AIDA backprojection catalog observes the same major patterns of seismicity in the epicentral region, but additional details are illuminated. The primary zone of seismicity is not a single fault but is a tabular zone of multiple small faults, this zone has a subtle concave shape along strike and with depth, and a broader zone of new events is observed at shallow depth. In addition, a new separate, shallow cluster was detected and located to the east of the main aftershock zone. The addition of smaller events to the catalog did not change the b-value or the temporal decay constant, but illuminated spatial and temporal patterns. Both the b-value and temporal decay constant are different for 12 days than for 4 months and are different at < 3km depth than at greater depth. Very low b-value, especially at greater depth, is consistent with observed very high stress drops. Conclusively, the results indicate the benefits of dense arrays and auto-detection by backprojection for aftershock studies. And finally, the reduced detection threshold and higher spatial resolution enabled the study of earthquake mechanisms and strain transfer at an unprecedented small scale.

  PublisherOA PDFDOI

• Three‐Dimensional Basin and Fault Structure From a Detailed Seismic Velocity Model of Coachella Valley, Southern California

  Journal of Geophysical Research Solid Earth · 2019-04-12 · 33 citations

  articleOpen access

  Abstract The Coachella Valley in the northern Salton Trough is known to produce destructive earthquakes, making it a high seismic hazard area. Knowledge of the seismic velocity structure and geometry of the sedimentary basins and fault zones is required to improve earthquake hazard estimates in this region. We simultaneously inverted first P wave travel times from the Southern California Seismic Network (39,998 local earthquakes) and explosions (251 land/sea shots) from the 2011 Salton Seismic Imaging Project to obtain a 3‐D seismic velocity model. Earthquakes with focal depths ≤10 km were selected to focus on the upper crustal structure. Strong lateral velocity contrasts in the top ~3 km correlate well with the surface geology, including the low‐velocity (&lt;5 km/s) sedimentary basin and the high‐velocity crystalline basement rocks outside the valley. Sediment thickness is ~4 km in the southeastern valley near the Salton Sea and decreases to &lt;2 km at the northwestern end of the valley. Eastward thickening of sediments toward the San Andreas fault within the valley defines Coachella Valley basin asymmetry. In the Peninsular Ranges, zones of relatively high seismic velocities (~6.4 km/s) between 2‐ and 4‐km depth may be related to Late Cretaceous mylonite rocks or older inherited basement structures. Other high‐velocity domains exist in the model down to 9‐km depth and help define crustal heterogeneity. We identify a potential fault zone in Lost Horse Valley unassociated with mapped faults in Southern California from the combined interpretation of surface geology, seismicity, and lateral velocity changes in the model.

  PublisherOA PDFDOI

Recent grants

• Collaborative Research: Seismic Imaging of New Transitional Crust in the Salton Trough Oblique Rift

  NSF · $932k · 2008–2015

• Collaborative Research: Batholiths: Generation and Evolution of Crust in Continental Magmatic Arcs

  NSF · $511k · 2003–2011

Frequent coauthors

• G. S. Fuis

  United States Geological Survey

  39 shared

• Joann M. Stock

  33 shared

• K. K. Davenport

  Earth System Science Interdisciplinary Center

  29 shared

• M. J. Rymer

  United States Geological Survey

  21 shared

• M. R. Goldman

  United States Geological Survey

  19 shared

• R. D. Catchings

  18 shared

• L.K. Han

  16 shared

• S. L. Klemperer

  Stanford University

  16 shared

Labs

• Department of GeosciencesPI

Education

• Ph.D., Geophysics

  University of British Columbia

  1993

• B.Sc. Honours, Geology; Physics

  Carleton University

  1986