Expanded Processing Techniques for EMI Systems
Dr. Mark Prouty | Geometrics
The goal of this project was to expand existing investigations and processing routines for advanced electromagnetic induction (EMI) arrays. Previous demonstrations conducted with advanced systems both at seeded sites (e.g., Aberdeen Proving Ground, MD and Yuma Proving Ground, AZ) and live sites such as Camp Sibert, AL, Camp San Luis Obispo (SLO), CA and Camp Butner, NC have shown that unanswered questions remain relating to antenna array configuration, physics-based target modeling, and classification.
The project objective was not to develop new sensors, sensor hardware, or programs for target modeling. Rather, it was to seize an opportunity to review and update earlier research in retrospect in order to search for a better and/or simpler antenna configuration, and to maximize the benefit derived from these systems through expanded data processing and better anomaly classification. The study was enabled and justified by the fact that real data and ground truth were available from the ESTCP classification studies at SLO and Camp Butner.
The research was focused on five tasks:
- Improved Target Detection – The objective of this task was to exploit the capability of an instrument such as the MetalMapper, which samples the vector field at multiple locations inside the transmitter loop, to generate simple physics-based estimates of position and size of targets within the field of view of the transmitter. Applied to dynamic data either in real-time during acquisition or during post-acquisition processing, this type of processing can serve as a primary target picking screen that sorts targets into at least two and perhaps three categories: 1) high-confidence clutter; 2) targets selected for cued identification; and perhaps 3) high-confidence targets of interest (i.e., dig). The advantage here is to reduce the number of anomalies that must be revisited for static data collection. These algorithms have been implemented as part of the acquisition software, allowing the operator to see a higher-level processed answer in real-time, to assist in re-locating static targets, or to stop and acquire static data.
- Target Parameter Extraction with Multiple-Point Static or Dynamic Data Sets – The MetalMapper and other advanced EMI systems were developed with cued target characterization in mind. In principle, a data set acquired at a single spatial measurement point is sufficient for the target analysis. In this project, the objective was to determine the extent to which the quality of parameter extraction is enhanced by sampling the secondary EMI response at several spatial points in the proximity of the target. In addition, the researchers analyzed the ability to discriminate targets using the dynamic data. The researchers found that some of the benefits obtained from more sample points over a larger aperture will be offset by two mechanisms. First, the platform is in motion, producing noise and position uncertainty. Second, the dynamic data acquired with the MetalMapper used only the vertical axis transmitter.
- Optimal Array Configuration(s) – The goal was to define one or more antenna arrays that meet the need for cost-effective sensor arrays for static (i.e., cued) measurements for characterization and identification. This could result in smaller systems that are easier to deploy and less expensive, yet may provide nearly equivalent performance for discrimination.
- Multiple Source Detection – The objective was to identify those target picks associated with complex secondary magnetic fields that arise either from the presence of multiple targets in close proximity, targets that are asymmetrical, or that may be too large dimensionally to be approximated with a point dipole. A multi-target inversion algorithm was developed and tested. Downward continuation and reduction-to-pole algorithms have also been developed to aid interpretation and to provide useful starting models for the multi-target inversion.
- Oasis montaj Integration – This task was not part of the original work scope, but was added to integrate new routines into existing Oasis montaj workflows.
Results by task include:
- Improved Target Detection – This task implemented a simple physics-based indicator in the MetalMapper acquisition program and in Oasis montaj (MMTargets). The model used by the indicator is a spherical target, as well as an inversion routine. These routines will help users find the location of targets during acquisition and processing. This will likely reduce the number of statically acquired targets that are off-center.
- Target Parameter Extraction with Multiple-Point Static or Dynamic Data Sets – The capability of MMTargets to invert multiple-point static datasets for single and multiple targets has been demonstrated. Both modeled data and actual survey data were used in the single target demonstration, while only modeled data were used in the multi-target demonstration. Essentially, MMTargets has the functionality to invert any MetalMapper dataset acquired by any means for single or multiple targets to provide characteristic information to a classifier.
- Optimal Array Configuration(s) – The optimal array task addressed the issue of survey instrument cost and complexity versus benefit to characterization and classification efforts. Several transmitter-receiver permutations were investigated.
- Multiple Source Detection – The objective here was to identify those target picks associated with complex secondary magnetic fields that arise either from the presence of multiple targets in close proximity, targets that are asymmetrical, or targets that may be too large dimensionally to be approximated with a point dipole. A multi-target inversion algorithm has been developed and tested. Downward continuation and reduction-to-pole algorithms have also been developed to aid interpretation and to provide useful starting models for the multi-target inversion.
- Oasis montaj Integration – This task was not part of the original work scope, but was added to integrate new routines into existing Oasis montaj workflows. TEM2CSV and TEM2SU were created to help import the time-domain electromagnetic (TEM) files recorded by the MetalMapper system into Oasis montaj. Oasis montaj GXs have been written to streamline the import of MetalMapper data, perform constrained inversions using several basic shapes, generate inversion summary plots for each target, and import inversion results into Oasis montaj for use in classification routines.
This project expanded the software support for current state-of-the-practice MetalMapper surveys. The detection and inversion phases were enhanced. These routines were demonstrated with modeled data and with a few cases from actual surveys. More testing is needed to demonstrate that these routines should be part of standard workflows.