Theoretical Developments in Electromagnetic Induction Geophysics with Selected Applications in the Near Surface

Near-surface applied electromagnetic geophysics is experiencing an explosive period of growth with many innovative techniques and applications presently emergent and others certain to be forthcoming. An attempt is made here to bring together and describe some of the most notable advances. This is a difficult task since papers describing electromagnetic induction methods are widely dispersed throughout the scientific literature. The traditional topics discussed herein include modeling, inversion, heterogeneity, anisotropy, target recognition, logging, and airborne electromagnetics (EM). Several new or emerging techniques are introduced including landmine detection, biogeophysics, interferometry, shallow-water electromagnetics, radiomagnetotellurics, and airborne unexploded ordnance (UXO) discrimination. Representative case histories that illustrate the range of exciting new geoscience that has been enabled by the developing techniques are presented from important application areas such as hydrogeology, contamination, UXO and landmines, soils and agriculture, archeology, and hazards and climat

Remote Sensing of World War II Era Unexploded Bombs Using Object-Based Image Analysis and Multi-Temporal Datasets: A Case Study of the Fort Myers Bombing and Gunnery Range

During World War II, United States Army and Navy pilots trained on several hundred bombing ranges encompassing more than 12 million acres of land, leaving behind crater-scarred landscapes across the country. Post-war estimates suggest that 10-15% of aerial bombs used failed to detonate as intended, so these areas today are contaminated by a large number of dangerous unexploded bombs (UXB) which remain under the surface. Until recently, detecting UXB has been a tedious and expensive process done in three stages: (1) identifying and mapping general areas of concentrated bomb craters using historical air photos and records; (2) intensely searching these areas at a larger scale for much smaller UXB entry holes; and (3) confirming the presence of individual UXB using magnetometry or ground-penetrating radar. This research aims to streamline the workflow for stage 1 and 2 using semi-automated object-based image analysis (OBIA) methods with multi-source high spatial-resolution imagery. Using the Fort Myers Bombing and Gunnery Range in Florida as a study area, this thesis determines what OBIA software and Imagery is best at locating UXB in this environment. I assess the use of LiDAR-derived DEMs, historical air photos and high-resolution color digital orthophotos in Feature Analyst and Imagine Objective, and discuss optimal inputs and configurations for UXB searches in karst wetlands. This methodology might be applied by the detection and clearance industry in former war zones, and aid in restoring former training ranges to safe land uses in the U.S

Enhancing magnetic signals in unexploded ordnances (UXO) detection based on edge-preserved stable downward continuation method

Abstract This paper describes an efficient edge-preserved regularization algorithm for downward continuation of magnetic data in detecting unexploded ordnance (UXO). The magnetic anomalies arising from multi-source UXO can overlap at a height over the ground surface while causative sources may not be readily separated due to low level of signal-to-noise ratio of the observed data. To effectively work the magnetic method in the cleanup stage of contaminated area with UXO, the magnetic anomalies of UXO sources should be enhanced in order to separate the locations of different sources. The stable downward continuation of magnetic data can increase the signal-to-noise ratio, which subsequently causes the separation of UXO sources by enhancing the signals. In this study the researchers formulated the downward continuation as a linear ill-posed deconvolution problem. To obtain a reasonable downward continued field, the proposed filter is stabilized in a Fourier domain to regularize the downward solution using the edge-preserved (or total-variation) algorithm. The L-curve method was used to choose the optimum value of the regularization parameter, which is a trade-off between the misfit and the solution norms in the cost function of optimization problem. A synthetic magnetic field was constructed from isolated multi-source UXO anomalies, the results of which show that the data can be stably downward continued to the ground surface. Likewise, a field data set was provided to demonstrate the capability of the applied method in UXO detection. The results of the synthetic and real case study revealed that the observed magnetic anomalies at a specific height of survey over the ground surface have low amplitude, indeed, the causative UXO sources may not be readily distinguished in detection process, especially anomalies from small UXOs. It was shown that the continued data can enhance the locations of UXOs while small ones are not distinguishable in the primary data

The Journal of ERW and Mine Action Issue 17.1 (2013)

Clearance Operations | Gender and Age Issues | Notes from the Field | Research and Developmen

Classifying GPR images using convolutional neural networks

This thesis focused on classifying GPR cylinders\u27 B-scans according to their depth, size, material, and the dielectric constant of the underlying medium using four different architectures of convolutional neural networks. Two CNNs were newly proposed for this study, while the other two were used by other authors. These CNNs were trained using a couple of adjusted training options including initial learning rate, learn rate drop factor, and learn rate drop period; which had a positive impact on a part of the used models, while the option maximum number of epochs worked good with all of the used models. Results show that the first newly proposed CNN showed a superior performance due to the use of a deep network with a large amount of small filters. Using this model, it was found that the best results were carried out when GPR B-scans were classified according to the cylinders\u27 materials

The Emergence and Future of Near-Surface Geophysics

Over the past 30 years, geophysical methods have assumed a much more prominent and integral role in many investigations where subsurface features have environmental and engineering importance. In fact, the field once referred to as environmental and engineering geophysics has broadened to include other applications (e.g., archeology, forensics), and is now commonly referred to more generally as near-surface geophysics. It is difficult to precisely define near-surface geophysics, and the definition will likely depend on whom you ask. However, we define it as the use of geophysical methods to investigate the zone between the surface and hundreds of meters into the Earth\u27s crust. Applications include, but are not limited to, potable water management, engineered infrastructure and construction, site clearance, gas storage, natural-hazard mitigation, mining, forensics, and archaeology. Although the same physical principles are relevant for any target depth, the high degree of near-surface heterogeneity, rapid change in physical properties, and proximity to the free surface often dictates that dominant processes and therefore key assumptions differ between the near-surface and deeper investigations. While near-surface geophysics shares many technical and cultural attributes of oil and gas exploration, the majority of near-surface geophysicists practice under different economic drivers and conditions