Magnetic airborne survey – geophysical flight

camara, Erick; Guimarães, Suze Nei Pereira

doi:10.5194/gi-5-181-2016

Cited by 14 publications

(4 citation statements)

References 15 publications

(20 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…where C m = 10 −7 is a scale factor, the prime at each coordinate denotes the position of the differential volume element dv of magnetized material, and the components of M are referred with respect to the International Geomagnetic Reference Field (IGRF) [27]. M = χH = χ(H 0 + H a ) ≈ χH 0 , where χ is the magnetic susceptibility of a linear, isotropic and homogeneous material, H 0 is the auxiliary Earth's magnetic field (H 0 = B 0 /µ 0 , where µ 0 is vacuum's magnetic permeability), and H a is the auxiliary magnetic field generated by rocks, which is usually negligible for most magnetic rocks in Earth's crust.…”

Section: Potential Field Theorymentioning

confidence: 99%

“…Since the gradiometric tensor G is symmetric and traceless, its independent components allow determination of the locations of the mass center (G xz , G yz ), edges (G yy , G xx ) and corners (G xy ) of the anomaly; G zz provides the correct spatial position of the anomaly, above the geological mass center, as conventional gravity [16][17][18][19][20][21][22][23][24][25][26]. On the other side, magnetometry is sensitive to anomalies of parts-per-million, making of it a very sensitive tool of geophysical surveying [27].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

OpenMP Implementation of a Novel Potential-Field-Data Source-Growth-Based Inversion Approach for 3D Salt Imaging in Deepwater Gulf of Mexico

et al. 2020

View full text Add to dashboard Cite

Potential-field-data imaging of complex geological features in deepwater salt-tectonic regions in the Gulf of Mexico remains an open active research field. There is still a lack of resolution in seismic imaging methods below and in the surroundings of allochthonous salt bodies. In this work, we present a novel three-dimensional potential-field-data simultaneous inversion method for imaging of salt features. This new approach incorporates a growth algorithm for source estimation, which progressively recovers geological structures by exploring a constrained parameter space; restrictions are posed from a priori geological knowledge of the study area. The algorithm is tested with synthetic data corresponding to a real complex salt-tectonic geological setting commonly found in exploration areas of deepwater Gulf of Mexico. Due to the huge amount of data involved in three-dimensional inversion of potential field data, the use of parallel computing techniques becomes mandatory. In this sense, to alleviate computational burden, an easy to implement parallelization strategy for the inversion scheme through OpenMP directives is presented. The methodology was applied to invert and integrate gravity, magnetic and full tensor gradient data of the study area.

show abstract

Section: Potential Field Theorymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

OpenMP Implementation of a Novel Potential-Field-Data Source-Growth-Based Inversion Approach for 3D Salt Imaging in Deepwater Gulf of Mexico

et al. 2020

View full text Add to dashboard Cite

show abstract

“…This often results in a compromise between UAS interference and boom length: a longer boom reduces interference but increases flight instability. Additional mitigation methods such as compensation using coils or rings (Leliak, 1961), shielding using permalloy (Leliak, 1961;Telford et al, 1990), demagnetization using a degaussing coil (Camara and Guimarães, 2016;Versteeg et al, 2007), optimal source positioning strategies (Forrester et al, 2014;Huq et al, 2015), or component replacement have been used. An effective way to deal with high-frequency interference is to sample at higher rates than the interference and remove with pre-filtering (Pharr and Humphreys, 2010); this method has been previously suggested for UAS magnetic interference mitigation (Versteeg et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Magnetic interference mapping of four types of unmanned aircraft systems intended for aeromagnetic surveying

Tuck

Samson

Laliberté

et al. 2021

Geosci. Instrum. Method. Data Syst.

View full text Add to dashboard Cite

Abstract. Magnetic interference source identification is a critical preparation step for magnetometer-mounted unmanned aircraft systems (UAS) used for high-sensitivity geomagnetic surveying. A magnetic field scanner was built for mapping the low-frequency interference that is produced by a UAS. It was used to compare four types of electric-powered UAS capable of carrying an alkali-vapour magnetometer: (1) a single-motor fixed-wing, (2) a single-rotor helicopter, (3) a quad-rotor helicopter, and (4) a hexa-rotor helicopter. The scanner's error was estimated by calculating the root-mean-square deviation of the background total magnetic intensity over the mapping duration; averaged values ranged between 3.1 and 7.4 nT. Each mapping was performed above the UAS with the motor(s) engaged and with the UAS facing in two orthogonal directions; peak interference intensities ranged between 21.4 and 574.2 nT. For each system, the interference is a combination of both ferromagnetic and electrical current sources. Major sources of interference were identified such as servo(s) and the cables carrying direct current between the motor battery and the electronic speed controller. Magnetic intensity profiles were measured at various motor current draws for each UAS, and a change in intensity was observed for currents as low as 1 A.

show abstract

“…as compensation using coils or rings (Leliak, 1961), shielding using permalloy (Leliak, 1961;Telford et al, 1990), demagnetisation using a degaussing coil (Camara and Guimarães, 2016;Tuck et al, 2019;Versteeg et al, 2007), optimal source positioning strategies (Forrester et al, 2014;Huq et al, 2015) or component replacement (Versteeg et al, 2007) have been used.…”

Section: Introductionmentioning

confidence: 99%

Magnetic interference mapping of four types of unmanned aircraft systems intended for aeromagnetic surveying

Tuck¹,

Samson²,

Laliberté³

et al. 2020

Preprint

View full text Add to dashboard Cite

Abstract. Magnetic interference source identification is a critical preparation step for magnetometer-mounted unmanned aircraft systems (UAS) used for high-sensitivity geomagnetic surveying. A magnetic field scanner was built for mapping the interference that is produced by a UAS. It was used to compare four types of electric-powered UAS capable of carrying an alkali-vapour magnetometer: (1) a single-motor fixed-wing, (2) a single-rotor helicopter, (3) a quad-rotor helicopter, and (4) a hexa-rotor helicopter. The scanner’s error was estimated by calculating the root-mean-square deviation of the background total magnetic intensity over the mapping duration; averaged values ranged between 3.1–7.4 nT. Each mapping was performed above the UAS with the motor(s) engaged and with the UAS facing in two orthogonal directions; peak interference intensities ranged between 21.4–574.2 nT. For each system, the interference is a combination of both ferromagnetic and electrical current sources. Major sources of interference were identified such as servo(s) and the cables carrying direct current between the motor battery and the electronic speed controller. Magnetic intensity profiles were measured at various motor current draws for each UAS and a change in intensity was observed for currents as low as 1 A.

show abstract

Magnetic airborne survey – geophysical flight

Cited by 14 publications

References 15 publications

OpenMP Implementation of a Novel Potential-Field-Data Source-Growth-Based Inversion Approach for 3D Salt Imaging in Deepwater Gulf of Mexico

OpenMP Implementation of a Novel Potential-Field-Data Source-Growth-Based Inversion Approach for 3D Salt Imaging in Deepwater Gulf of Mexico

Magnetic interference mapping of four types of unmanned aircraft systems intended for aeromagnetic surveying

Magnetic interference mapping of four types of unmanned aircraft systems intended for aeromagnetic surveying

Contact Info

Product

Resources

About