Recovery of Source Magnetization Direction from Magnetic Field Data

2020 ◽  
pp. 1-11
Author(s):  
Clive Foss
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Magnetization Direction ◽  
Magnetic Field Data

Interpretation of aeromagnetic data using eigenvector analysis of pseudogravity gradient tensor

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. L1-L10 ◽  
Author(s):  
Majid Beiki ◽  
Laust B. Pedersen ◽  
Hediyeh Nazi
Keyword(s):  
Magnetic Field ◽  
Least Squares ◽  
Field Data ◽  
Random Noise ◽  
Gravity Gradient ◽  
Aeromagnetic Data ◽  
Gradient Tensor ◽  
Magnetization Direction ◽  
Magnetic Field Data ◽  
Robust Least Squares

This study has shown that the same properties of the gravity gradient tensor are valid for the pseudogravity gradient tensor derived from magnetic field data, assuming that the magnetization direction is known. Eigenvectors of the pseudogravity gradient tensor are used to estimate depth to the center of mass of geologic bodies. The strike directions of 2D geological structures are estimated from the eigenvectors corresponding to the smallest eigenvalues. For a set of data points enclosed by a square window, a robust least-squares procedure is used to estimate the source point which has the smallest sum of squared distances to the lines passing through the measurement points and parallel to the eigenvectors corresponding to the maximum eigenvalues. The dimensionality of the pseudogravity field is defined from the dimensionality indicator I, derived from the tensor components. In the case of quasi-2D sources, a rectangular window is used in the robust least-squares procedure to reduce the uncertainty of estimations.Based on synthetic data sets, the method was tested on synthetic models and found to be robust to random noise in magnetic field data. The application of the method was also tested on a pseudogravity gradient tensor derived from total magnetic field data over the Särna area in west-central Sweden. Combined with Euler deconvolution, the method provides useful complementary information for interpretation of aeromagnetic data.

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.

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

Ogo 5 magnetic-field data near the Earth's bow shock: A correlation with theory

1972 ◽  
Vol 77 (4) ◽  
pp. 604-610 ◽  
Author(s):  
J. K. Guha ◽  
D. L. Judge ◽  
J. H. Marburger
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Bow Shock ◽  
Magnetic Field Data ◽  
Earth’S Bow Shock

Using an induction coil sensor to indirectly measure the B-field response in the bandwidth of the transient electromagnetic method

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1489-1494 ◽  
Author(s):  
Richard S. Smith ◽  
A. Peter Annan
Keyword(s):  
Magnetic Field ◽  
Field Data ◽  
Indirect Measurement ◽  
Rate Of Change ◽  
Induction Coil ◽  
Voltage Response ◽  
Magnetic Field Data ◽  
Transient Electromagnetic ◽  
Different Characteristics ◽  
The Magnetic Field

The traditional sensor used in transient electromagnetic (EM) systems is an induction coil. This sensor measures a voltage response proportional to the time rate of change of the magnetic field in the EM bandwidth. By simply integrating the digitized output voltage from the induction coil, it is possible to obtain an indirect measurement of the magnetic field in the same bandwidth. The simple integration methodology is validated by showing that there is good agreement between synthetic voltage data integrated to a magnetic field and synthetic magnetic‐field data calculated directly. Further experimental work compares induction‐coil magnetic‐field data collected along a profile with data measured using a SQUID magnetometer. These two electromagnetic profiles look similar, and a comparison of the decay curves at a critical point on the profile shows that the two types of measurements agree within the bounds of experimental error. Comparison of measured voltage and magnetic‐field data show that the two sets of profiles have quite different characteristics. The magnetic‐field data is better for identifying, discriminating, and interpreting good conductors, while suppressing the less conductive targets. An induction coil is therefore a suitable sensor for the indirect collection of EM magnetic‐field data.

scholarly journals The geomagnetic field at 1982 from DE-2 and other magnetic field data.

1988 ◽  
Vol 40 (9) ◽  
pp. 1103-1127 ◽  
Author(s):  
R. A. LANGEL ◽  
J. R. RIDGWAY ◽  
M. SUGIURA ◽  
K. MAEZAWA
Keyword(s):  
Magnetic Field ◽  
Geomagnetic Field ◽  
Field Data ◽  
Magnetic Field Data
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