Automated anomaly picking from broadband electromagnetic data in an unexploded ordnance (UXO) survey

Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 1870-1876 ◽  
Author(s):  
Hoaping Huang ◽  
I. J. Won
Keyword(s):  
Magnetic Field ◽  
Magnetic Susceptibility ◽  
Field Data ◽  
Real Data ◽  
False Alarms ◽  
Rough Terrain ◽  
Unexploded Ordnance ◽  
Electromagnetic Data ◽  
Apparent Conductivity ◽  
Using Data

We present automated anomaly‐picking methods for detecting unexploded ordnance (UXO) from broadband electromagnetic (EM) data. Using data consisting of in‐phase and quadrature responses at multiple (typically 10) frequencies, a detector function attempts to detect all metal objects but to suppress false alarms caused by geology, variations in sensor height, and sensor motions in the earth's magnetic field. Promising detector functions considered here are (1) the sum of all quadrature responses, Qsum, (2) the sum of all differences among the in‐phase or quadrature components, Ispread or Qspread, (3) the sum of the Ispread and Qspreads, Tspread, (4) the weighted total apparent conductivity (TAC) from all frequencies, and (5) the apparent magnetic susceptibility (AMS) derived from the lowest frequency of a survey. These detector functions favor metallic objects and are relatively insensitive to geologic variations and motion‐induced noise, which are common with a handheld or cart‐mounted sensor in rough terrain. We discuss the properties of these detector functions, apply them to field data from two sites, and compare the results with limited ground truths. Based on the theoretic study and test on the real data, the total apparent conductivity is the best detector function for picking and classifying anomalies, which shows more distinct anomalies and quieter background than other detector functions.

Electromagnetic detection of buried metallic objects using quad–quad conductivity

Geophysics ◽  
2004 ◽  
Vol 69 (6) ◽  
pp. 1387-1393 ◽  
Author(s):  
Haoping Huang ◽  
I. J. Won
Keyword(s):  
Magnetic Susceptibility ◽  
Rough Terrain ◽  
Unexploded Ordnance ◽  
Magnetic Polarization ◽  
Phase Component ◽  
Apparent Conductivity ◽  
Electromagnetic Detection ◽  
Phase Data ◽  
Magnetic Soil

Apparent conductivity computed from in‐phase and quadrature components has been used successfully to detect buried metallic objects such as unexploded ordnance (UXO). The conductivity computation uses magnetic susceptibility calculated from the lowest‐frequency in‐phase data obtained at a specific sensor height. Over magnetic soils, however, the in‐phase component may fluctuate with varying sensor heights. Uncertainties in sensor height, common with handheld or cart‐mounted sensors in rough terrain, can produce errors in the computed magnetic susceptibility, which, in turn, causes errors in apparent conductivity. To overcome these limitations, we have developed an algorithm to compute the quad–quad apparent conductivity from the quadrature components at two frequencies. Our results show that the quad–quad technique has several advantages for detecting metal targets in magnetic terrains: it is (1) insensitive to the magnetic polarization currents; (2) it is immune to sensor motion over magnetic soil; and (3) it is biased to metal objects and can detect small and/or deep metal targets. The first two properties suppress the noise caused by magnetic terrain and sensor motion and thus yield a quiet background. The last property emphasizes metal objects as sought anomalies over geologic variations.

An Augmented Iteratively Re-weighted and Refined Least Squares Method for lp Minimization Problem in Inverse Modeling of Potential Field Magnetic Data

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Maysam Abedi
Keyword(s):  
Magnetic Field ◽  
Magnetic Susceptibility ◽  
Least Squares ◽  
Minimization Problem ◽  
Potential Field ◽  
Field Data ◽  
Least Squares Method ◽  
Porphyry Copper ◽  
Magnetic Data ◽  
Magnetic Field Data

The presented work examines application of an Augmented Iteratively Re-weighted and Refined Least Squares method (AIRRLS) to construct a 3D magnetic susceptibility property from potential field magnetic anomalies. This algorithm replaces an lp minimization problem by a sequence of weighted linear systems in which the retrieved magnetic susceptibility model is successively converged to an optimum solution, while the regularization parameter is the stopping iteration numbers. To avoid the natural tendency of causative magnetic sources to concentrate at shallow depth, a prior depth weighting function is incorporated in the original formulation of the objective function. The speed of lp minimization problem is increased by inserting a pre-conditioner conjugate gradient method (PCCG) to solve the central system of equation in cases of large scale magnetic field data. It is assumed that there is no remanent magnetization since this study focuses on inversion of a geological structure with low magnetic susceptibility property. The method is applied on a multi-source noise-corrupted synthetic magnetic field data to demonstrate its suitability for 3D inversion, and then is applied to a real data pertaining to a geologically plausible porphyry copper unit.  The real case study located in  Semnan province of  Iran  consists  of  an arc-shaped  porphyry  andesite  covered  by  sedimentary  units  which  may  have  potential  of  mineral  occurrences, especially  porphyry copper. It is demonstrated that such structure extends down at depth, and consequently exploratory drilling is highly recommended for acquiring more pieces of information about its potential for ore-bearing mineralization.

Coordination Of The Geosynchronous And Auroral Substorms

1996 ◽  
Author(s):  
Charles F. Kennel
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Conjugate Point ◽  
Magnetic Field Data ◽  
Correlation Studies ◽  
Close Relationship ◽  
Initial Onset ◽  
Fine Structures ◽  
Spatio Temporal ◽  
Using Data

Studies using data from the ATS-5 geosynchronous spacecraft revealed a clear relationship between midnight region injection events near the spacecraft and auroral displays near the ATS magnetic conjugate point (Hones et al., 1971a; Mende et al., 1972; Eather et al., 1976; Mende and Shelley, 1976). A comparison of ATS-5 particle and magnetic field data with all-sky photographs taken at the conjugate point, Great Whale River, indicated that an injection at geostationary orbit generally corresponded to the brightening of the onset arc when the spacecraft was in the midnight sector (Akasofu et al., 1974). Results such as this whetted the collective appetite. How closely can the initial onset and injection be related to one another in time, do the onset and injection start on the same field field line, does the westward propagation of dipolarization correspond to the westward surge, can one relate the fine structures of the auroral expansion and the dipolarization? As time passed, increasingly precise answers have been given to these and similar questions, and auroral and geosynchronous substorm phenomenology has become more tightly integrated. In this chapter, we sample some of the evidence that supports this statement. The GEOS 2 spacecraft was stationed with its magnetic conjugate point near Kiruna, Sweden, so that the conjugate aurora could be studied with the extensive network of ground-based observatories in Scandinavia (Knott, 1975; Knott et al., 1979). In the first part of this chapter, we review some of the correlation studies carried out in the GEOS 2 project. In one particular series of four substorms, it was found that the dipolarization occurred at the same time as the aurora brightened and expanded poleward over the ground conjugate region (Section 14.2). In another case, a dispersionless injection at GEOS 2 corresponded to an intensification of the auroral X-ray band in Scandinavia (Section 14.2). Westward surges at the auroral conjugate point were associated with dipolarization at the spacecraft on a statistical basis (Section 14.3). Finally, the close relationship between both the auroral and geostationary substorm phenomena was extended to small spatio-temporal scales.

scholarly journals A Bike Built for Magnetic Mapping

Eos ◽  
2017 ◽  
Author(s):  
Uri Schattner
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Low Cost ◽  
Magnetic Sensor ◽  
Rough Terrain ◽  
Magnetic Field Data ◽  
Ground Magnetic

Mounting a magnetic sensor on a bicycle offers an efficient, low-cost method of collecting ground magnetic field data over rough terrain where conventional vehicles dare not venture.

Polar Magnetic Field Reversals of the Sun in Maunder Minimum

2000 ◽  
Vol 179 ◽  
pp. 193-196
Author(s):  
V. I. Makarov ◽  
A. G. Tlatov
Keyword(s):  
Magnetic Field ◽  
Maunder Minimum ◽  
The Sun ◽  
Annual Rings ◽  
Field Reversal ◽  
Polar Magnetic Field ◽  
Pine Trees ◽  
Using Data ◽  
Magnetic Field Reversal

AbstractA possible scenario of polar magnetic field reversal of the Sun during the Maunder Minimum (1645–1715) is discussed using data of magnetic field reversals of the Sun for 1880–1991 and the14Ccontent variations in the bi-annual rings of the pine-trees in 1600–1730 yrs.

scholarly journals Photovoltaic Prediction Software: Evaluation with Real Data from Northern Spain

2021 ◽  
Vol 11 (11) ◽  
pp. 5025
Author(s):  
David González-Peña ◽  
Ignacio García-Ruiz ◽  
Montserrat Díez-Mediavilla ◽  
Mª. Isabel Dieste-Velasco ◽  
Cristina Alonso-Tristán
Keyword(s):  
Energy Production ◽  
Field Data ◽  
Real Data ◽  
Software Tools ◽  
Horizontal Axis ◽  
Real Field ◽  
Tracking Systems ◽  
Northern Spain ◽  
Commercial Software ◽  
Solar Tracking

Prediction of energy production is crucial for the design and installation of PV plants. In this study, five free and commercial software tools to predict photovoltaic energy production are evaluated: RETScreen, Solar Advisor Model (SAM), PVGIS, PVSyst, and PV*SOL. The evaluation involves a comparison of monthly and annually predicted data on energy supplied to the national grid with real field data collected from three real PV plants. All the systems, located in Castile and Leon (Spain), have three different tilting systems: fixed mounting, horizontal-axis tracking, and dual-axis tracking. The last 12 years of operating data, from 2008 to 2020, are used in the evaluation. Although the commercial software tools were easier to use and their installations could be described in detail, their results were not appreciably superior. In annual global terms, the results hid poor estimations throughout the year, where overestimations were compensated by underestimated results. This fact was reflected in the monthly results: the software yielded overestimates during the colder months, while the models showed better estimates during the warmer months. In most studies, the deviation was below 10% when the annual results were analyzed. The accuracy of the software was also reduced when the complexity of the dual-axis solar tracking systems replaced the fixed installation.

WANG–LANDAU SIMULATION ON THERMODYNAMIC AND MAGNETIC PROPERTIES OF HONEYCOMB LATTICE

2011 ◽  
Vol 25 (26) ◽  
pp. 3435-3442
Author(s):  
XIAOYAN YAO
Keyword(s):  
Magnetic Field ◽  
Monte Carlo Simulation ◽  
Magnetic Properties ◽  
Free Energy ◽  
Magnetic Susceptibility ◽  
Magnetic Property ◽  
Ground State ◽  
Antiferromagnetic Order ◽  
Honeycomb Lattice ◽  
Antiferromagnetic Ising Model

Wang–Landau algorithm of Monte Carlo simulation is performed to understand the thermodynamic and magnetic properties of antiferromagnetic Ising model on honeycomb lattice. The internal energy, specific heat, free energy and entropy are calculated to present the thermodynamic behavior. For magnetic property, the magnetization and magnetic susceptibility are discussed at different temperature upon different magnetic field. The antiferromagnetic order is confirmed to be the ground state of the system, and it can be destroyed by a large magnetic field.

Discrete linear transformations of potential field data

Geophysics ◽  
1989 ◽  
Vol 54 (4) ◽  
pp. 497-507 ◽  
Author(s):  
Jorge W. D. Leão ◽  
João B. C. Silva
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Amazon Basin ◽  
Real Data ◽  
Damping Factor ◽  
Linear Transformations ◽  
Potential Field Data ◽  
Data Window ◽  
Green’S Matrix ◽  
Equivalent Layer

We present a new approach to perform any linear transformation of gridded potential field data using the equivalent‐layer principle. It is particularly efficient for processing areas with a large amount of data. An N × N data window is inverted using an M × M equivalent layer, with M greater than N so that the equivalent sources extend beyond the data window. Only the transformed field at the center of the data window is computed by premultiplying the equivalent source matrix by the row of the Green’s matrix (associated with the desired transformation) corresponding to the center of the data window. Since the inversion and the multiplication by the Green’s matrix are independent of the data, they are performed beforehand and just once for given values of N, M, and the depth of the equivalent layer. As a result, a grid operator for the desired transformation is obtained which is applied to the data by a procedure similar to discrete convolution. The application of this procedure in reducing synthetic anomalies to the pole and computing magnetization intensity maps shows that grid operators with N = 7 and M = 15 are sufficient to process large areas containing several interfering sources. The use of a damping factor allows the computation of meaningful maps even for unstable transformations in the presence of noise. Also, an equivalent layer larger than the data window takes into account part of the interfering sources so that a smaller damping factor is employed as compared with other damped inversion methods. Transformations of real data from Xingú River Basin and Amazon Basin, Brazil, demonstrate the contribution of this procedure for improvement of a preliminary geologic interpretation with minimum a priori information.

scholarly journals A reexamination of “interstellar ion waves” previously identified in Pioneer 10 magnetic field data

1998 ◽  
Vol 25 (19) ◽  
pp. 3721-3724 ◽  
Author(s):  
Neil Murphy ◽  
Edward J. Smith ◽  
Joyce Wolf ◽  
Devrie S. Intriligator
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Magnetic Field Data ◽  
Ion Waves ◽  
Pioneer 10
Sign in / Sign up

Export Citation Format

Share Document