ORIGINAL_ARTICLE
A simulation study of RX-mode waves generation in the equatorial plasmasphere
The generation mechanism of RX-mode waves in the equatorial plasmasphere has not been well understood. The Akebono passing through the storm time geomagnetic equator shows the possibility of the local enhancement of RX-mode waves in association with intense Z-mode waves in the equatorial region. We use the initial parameters inferred from observational data from around the plasma-wave generation region obtained by the Akebono satellite. A comparison of linear growth-rate calculations and simulation results is presented. The results of the simulation show two strong peaks related to the Z-mode and RX-mode waves, while the separation of these wave frequencies is equal to one cyclotron frequency. It is shown that electromagnetic Z- and RX-mode waves could be coupled by a nonlinear interaction.
https://www.ijgeophysics.ir/article_33610_2068becf8f94f418ac4e282884d0bb4c.pdf
2015-12-22
1
10
RX- mode
Simulation
cyclotron frequency
growth rate
Mohammad Javad
Kalaee
1
Institute of Geophysics, University of Tehran, Tehran
LEAD_AUTHOR
Yuto
Katoh
2
Department of Geophysics, Graduate School of Science, Tohoku University, Sendai, Japan
AUTHOR
Buneman, O., 1959, Dissipation of currents in ionized media, Phys. Rev., 115, 503-51.
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Eliasson, B., and Shukla, P. K., 2003, Simulation study of radiation generation by upper-hybrid waves in space plasmas, J. Phys. Lett., A312, 91-96.
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Kalaee, M. J., Ono, T., Katoh, Y., Iizima, M. and Nishimura, Y., 2009, Simulation of mode conversion from UHR-mode wave to LO-mode wave in an inhomogeneous plasma with different wave normal angles, Earth Planets and Space, 61, 1243-1254.
6
Kalaee, M. J., Katoh, Y., Kumamoto, A., Ono, T., and Nishimura Y, 2010, Simulation of mode conversion from upper-hybrid waves to LO-mode waves in the vicinity of the Plasmapause, Annales Geophysicae, 28, 1289-1297.
7
Kalaee, M. J., Katoh, Y., and Ono, T., 2013, A simulation study of the plasma wave enhancements in the earth’s equatorial plasmasphere, Earth, Moon and Planets, 110, 131-141.
8
Katoh, Y., Ono, T., and Iizima, M., 2005, Numerical simulation of resonant scattering of energetic electrons in the outer radiation belt, Earth Planets and Space, 57, 117-124.
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Li, W., Thorne, R. M., Bortnik, J., Nishimura, Y., Angelopoulos, V., Chen, L., McFadden, J. P., and Bonnell, J. W., 2010, Global distributions of superathermal electrons observed on the THEMIS and potential mechanisms for access into the plasmasphere, J. Geophys.Res.,115, 1-14.
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Nishimura, Y., Ono, T., Iizima, M., Shinbori, A., and Kumamoto, A., 2007, Generation mechanism of Z-mode waves in the equatrial plasmasphere, Earth planets space, 59, 1027-1034.
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Oya, H., 1991, Studies on Plasma and Plasma waves in the Plasmasphere and Auroral Particle Acceleration Region, by PWS on board the EXOS-D (Akebono) Satellite, J. Geomag. Geoelectr., 43, 369-393.
14
ORIGINAL_ARTICLE
Geological noise removal in geophysical magnetic survey to detect unexploded ordnance based on image filtering
This paper describes the application of three straightforward image-based filtering methods to remove the geological noise effect which masks unexploded ordnances (UXOs) magnetic signals in geophysical surveys. Three image filters comprising of mean, median and Wiener are used to enhance the location of probable UXOs when they are embedded in a dominant background geological noise. The study area consists of three buried UXOs while a geological dyke structure covers the magnetic anomaly of the desired objects. To provide a better representation of the actual locations of UXOs in the observed magnetic anomaly over this area, all image-based filters could appropriately separate the geological dyke effect from the UXOs. These image filters can be good candidates to remove the geological noise effect in UXO detection when encountering a mixed response of multi-source magnetic anomaly in contaminated territories with UXOs. An analytic signal map of the separated magnetic anomaly of UXOs was provided to enhance locations of the UXOs in the studied field. Also, a combination of the analytic signal and the Euler deconvolution methods were used to estimate the depth of three buried UXO targets in the study area indicating a high sensitivity of the estimated parameter to the noise level.
https://www.ijgeophysics.ir/article_33611_f70468fc6db6983925a2dba5b5983149.pdf
2015-12-22
11
23
Image filtering
geological noise removing
UXO detection
magnetic anomaly
Maysam
Abedi
1
Department of Mining Engineering, College of Engineering, University of Tehran
LEAD_AUTHOR
Kiomars
Mosazadeh
2
Malek Ashtar University of Technology, Tehran
AUTHOR
Hamid
Dehghani
3
Malek Ashtar University of Technology, Tehran
AUTHOR
Ahmad
MadanchiZare
4
Malek Ashtar University of Technology, Tehran
AUTHOR
Abedi, M., Mosazadeh, K., Dehghani, H., and MadanchiZare, A., 2014, Enhancing magnetic signals in unexploded ordnances (UXO) detection based on edge-preserved stable downward continuation method: Journal of Mining & Environment, 5, 13-24.
1
Beard, L.P., Doll, W.E., Holladay, J.S., Gamey, T.J., Lee, J.L.C., and Bell, D.T., 2004, Field tests of an experimental helicopter time-domain electromagnetic system for unexploded ordnance detection: Geophysics, 69, 664-673.
2
Bell, T., Barrow, B., Miller, J., and Keiswetter, D., 2001, Time and Frequency Domain Electromagnetic Induction Signatures of Unexploded Ordnance: Subsurface Sensing Technology and Applications, 2, 153-175.
3
Benavides, A., and Everett, M.E., 2007, Non-linear inversion of controlled source multi-receiver electromagnetic induction data for unexploded ordnance using a continuation method: J. Appl. Geophys., 61, 243-253.
4
Billings, S.D., and Youmans, C., 2007, Experiences with unexploded ordnance discrimination using magnetometry at a live-site in Montana: J. Appl. Geophys., 61, 194-205.
5
Billings, S.D., and Wright, D., 2010, Interpretation of high-resolution low-altitude helicopter magnetometer surveys over sites contaminated with unexploded ordnance: J. Appl. Geophys., 72, 225-231.
6
Blakely, R.J., 1995, Potential theory in gravity and magnetic applications: Cambridge University Press.
7
Bruschini, C., Gros, B., Guerne, F., Piéce, P.Y., and Carmona, O., 1998, Ground penetrating radar and imaging metal detector for antipersonnel mine detection: J. Appl. Geophys., 40, 59-71.
8
Butler, D.K., 2000, Assessment of Microgravity for UXO Detection and Discrimination: U.S. Army Engineer Research and Development Center, 1-37.
9
Butler, D.K., 2001, Potential fields methods for location of unexploded ordnance: The Leading Edge, 20, 890 – 895.
10
Butler, D.K., Wolfe, P.J., and Hansen, R.O., 2001, Analytical modeling of magnetic and gravity signatures of unexploded ordnance: Journal of Environmental and Engineering Geophysics, 6, 33 – 46.
11
Butler, D.K., 2003, Implications of magnetic backgrounds for unexploded ordnance detection: J. Appl. Geophys., 54, 111-125.
12
Butler, D.K., Simms, J.E., Furey, J.S., and Bennett, H.H., 2012, Review of Magnetic Modeling for UXO and Applications to Small Items and Close Distances: Journal of Environmental and Engineering Geophysics, 17, 53-73.
13
Davis, K., Li, Y., and Nabighian, M.N., 2010, Automatic detection of UXO magnetic anomalies using extended Euler deconvolution: Geophysics, 75, G13-G20.
14
Davis, K., Li, Y., and Nabighian, M.N., 2011, Effects of low-pass filtering on the calculated structure index from magnetic data: Geophysics, 76, L23-L28.
15
Debeglia, N., and Corpel, J., 1997, Automatic 3-D interpretation of potential field data using analytic signal derivatives: Geophysics, 62, 87-96.
16
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17
Huang, H., and Won, I.J., 2000, Conductivity and Susceptibility Mapping Using Broadband Electromagnetic Sensors: Journal of Environmental and Engineering Geophysics, 5, 31-41.
18
Huang, H., and Won, I.J., 2003a, Detecting metal objects in magnetic environments using a broadband electromagnetic method: Geophysics, 68, 1877-1887.
19
Huang, H., and Won, I.J., 2003b, Automatic anomaly picking from broadband electromagnetic data in an unexploded ordnance (UXO) survey: Geophysics, 68, 1870-1876.
20
Huang, H., and Won, I.J., 2003c, Characterization of UXO-Like Targets Using Broadband Electromagnetic Induction Sensors: IEEE Trans. Geosci. Remote Sensing, 41, 652-663.
21
Huang, H., and Won, I.J., 2004, Electromagnetic detection of buried metallic objects using quad-quad conductivity: Geophysics, 69, 1387-1393.
22
Huang, H., SanFilipo, B., Oren, A., and Won, I.J., 2007, Coaxial coil towed EMI sensor array for UXO detection and characterization: J. Appl. Geophys., 61, 217-226.
23
Khireddine, A., Benmahammed, K., and Puech, W., 2007, Digital image restoration by Wiener filter in 2D case: Advances in Engineering Software, 38, 513-516.
24
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25
Krahenbuhl, R., Li, Y., Nabighian, M., Davis, K., and Billings, S., 2011, Advanced UXO Detection and Discrimination Using Magnetic Data Based on Extended Euler Deconvolution and Shape Identification through Multipole Moments: SERDP Project MR-1638, p. 117.
26
Li, Y., Krahenbuhl, R., Meglich, T., Oldenburg, D., Pasion, L., Billings, S., van Dam, R., and Harrison, B., 2010, Improving UXO Detection and Discrimination in Magnetic Environments: SERDP Project MM-1414, p. 278.
27
Li, Y., Devriese, S.G.R., Krahenbuhl, R., and Davis, K., 2013, Enhancement of Magnetic Data by Stable Downward Continuation for UXO Application: IEEE Trans. Geosci. Remote Sensing, 51, 3605-3614.
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31
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32
Pasion, L.R., 2007, Inversion of time domain electromagnetic data for the detection of unexploded ordnance: PhD Thesis, The University of British Columbia.
33
Pasion, L.R., Billings, S.D., Oldenburg, D.W., and Walker, S.E., 2007, Application of a library based method to time domain electromagnetic data for the identification of unexploded ordnance: J. Appl. Geophys., 61, 279-291.
34
Pawlowski, J., 1994, Ordnance Investigation Using an Electromagnetic Method, Lake Erie, Port Clinton, Ohio: report for USAE Waterways Experiment Station, by Geophysics Ltd., Mississauga, Ontario.
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36
Pederson, A., and Stalcup, B., 1997, Phase III advanced technology demonstrations at Jefferson proving ground: Proceedings of the UXO Forum’ 97: pp. 281 – 289.
37
Press, W.H., 2008, Computational Statistics with Application to Bioinformatics: Unit 19, Wiener Filtering (and some Wavelets), The University of Texas at Austin.
38
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39
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40
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41
Sanchez, V., Li, Y., Nabighian, M.N., and Wright, D.L., 2008, Numerical Modeling of Higher Order Magnetic Moments in UXO Discrimination: IEEE Trans. Geosci. Remote Sensing, 46, 2568-2583.
42
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44
ORIGINAL_ARTICLE
Classification of hydrometeors using microwave brightness temperature data from AMSU-B over Iran
The Advanced Microwave Sounding Unit-B (AMSU-B) installed on the NOAA-15, 16, and 17 satellites, is the new generation of a series of microwave imagers/sounders that can sense atmospheric moisture and other hydrometeors through clouds. This paper demonstrates the potential of multi-frequency AMSU-B data for classifying different types of hydrometeors. Ten types of these hydrometers have been collected using meteorological data (synoptic reports, radiosonde data and infrared and water vapor images) over Iran. Co-located AMSU-B data were used to perform a quantitative classification of the hydrometers. Three main classes including heavy precipitating, moderate precipitating, and non-precipitating hydrometeors were found based on the multi-frequency brightness temperature signatures. The distinguishing criteria for this type of analysis are: (a) brightness temperature (BT) at 89 GHz frequency, (b) slopes of the BT between 89 and 150 GHz, and (c) crossover of BT curves between 89 and 183 GHz frequencies.
https://www.ijgeophysics.ir/article_33612_6677998fec34a5f6fa1056a928aa5c67.pdf
2015-12-22
24
39
Classification
AMSU-B
Hydrometeors
Brightness temperature
Abolhasan
Gheiby
1
University of Hormozgan, Bandar Abbas, Iran
LEAD_AUTHOR
Majid
Azadi
2
Atmospheric and Meteorological Research Centre, Tehran, Iran
AUTHOR
S. Q. Kidder, M. D. Goldberg, R. M. Zehr, M.Demana, T. F. Purdom, C. S. Velden, N. Grody, S. J. Kusselson, Satellite analysis of tropical cyclones using the advanced microwave sounding unit (AMSU), Bult. Amer. Meteor. Soc., 81(2000) 1241-1259.
1
G. Liu, J. A. Curry, Large-scale cloud features during January 1993 in the North Atlantic Ocean as determined from SSM/I and SSM/T2, J. Geophys. Res., 101(1996) 7019-7032.
2
G. Liu, J. A. Curry, Precipitation characteristics in Greenland-Iceland-Norwegian Seas determined by using satellite microwave data, J. Geophys. Res., 102(1997) 13987-13997.
3
J. L. Schools., J. A. Weinman, G. D. Alexander, R. E. Stewart, L. J. Angus, C. L. Lee, Microwave properties of frozen precipitation around a North Atlantic Cyclone, J. Appl. Meteor., 38(1999) 29-43.
4
M. Katsumata, H. Uyeda, K. Iwanami, G. Liu, The response of 36 and 89GHz microwave channels to convective snow clouds over Ocean: observation and modeling, J. Appl. Meteor., 39(2000) 2322-2335.
5
R. Bennartz and G. W. Petty, The sensitivity of microwave remote sensing observations of precipitation to ice particle size distribution, J. Appl. Meteor., 40(2001) 345-364.
6
J. R. Wang, J. Zhan, P. Racette, Storm-associated microwave radiometric signatures in the frequency range of 90-220 GHz, J. Atmos. Oceanic Technology, 14(1997) 13-31.
7
R. W. Saunders, T. J. Hewison, S. J. Stringer, N. C. Atkinson, The radiometric characterization of AMSU-B, IEEE. Trans. On Microwave Theory and Techniques, 43(1995) 760-771.
8
NOAA K L M User’s Guide, available Online at: http://www.2.ncdc.noaa.gov/docs/klm/
9
R. Ferraro, F. Weng, N. C. Grody, L. Zhao, Precipitation characteristics over and from the NOAA-15 AMSU sensor, Geophys. Res. Letter, 27(2000) 2669-2672.
10
N. C. Grody, J. Zhao, R. Ferraro, F. Weng, and R. Boers, Determination of perceptible water and cloud liquid water over Ocean from NOAA 15 advanced microwave sounding unit, J. Geophys. Res., 106(2001) 2943-2953.
11
D. H. Staelin, F. W. Chen, Precipitation observation near 54 and 183 GHz using the NOAA-15 satellite, IEEE Trans. on geosciences and remote sensing, 38(2000) 2322-2332.
12
METEOSAT images available online at: http://www.sat.dundee.ac.uk
13
Large Array-data Stewardship System (CLASS), available online at http://www.class.noaa.gov
14
B. M. Muller, E. F. Henry, X. Xiang, 1994: Simulations of the effects of water vapor, Cloud liquid water, and ice on AMSU moistures channel brightness temperatures. J. Appl. Meteorol., 33(1994) 1133-1154.
15
ORIGINAL_ARTICLE
A simple form of MT impedance tensor analysis to simplify its decomposition to remove the effects of near surface small-scale 3-D conductivity structures
Magnetotelluric (MT) is a natural electromagnetic (EM) technique which is used for geothermal, petroleum, geotechnical, groundwater and mineral exploration. MT is also routinely used for mapping of deep subsurface structures. In this method, the measured regional complex impedance tensor (Z) is substantially distorted by any topographical feature or small-scale near-surface, three-dimensional (3-D) electrical inhomogeneity. The effects of this local galvanic distortion should be separated and removed from the regional response to improve the accuracy and reliability of the data interpretation. In this paper, it is attempted to introduce an effective form of tensor analysis to facilitate the process of GB (Groom-Bailey) tensor decomposition on MT data. This approach was used to recover the regional response of conductivity structures beneath 12 MT sounding sites of a sedimentary basin in South Australia. The results of this study clearly indicate that the regional structures beneath these sites are two-dimensional (2-D) and their strike are mainly in NS (±100) direction which are geologically supported. The obtained results also show that the distortion parameters of the surficial bodies are fairly constant for the whole frequency band or its two or, at most, three subsets. In addition, the low misfit values between the measured impedances and those produced by a hypothetical 3D/2D model confirm that the regional structures beneath all these 12 MT sites are 2-D and some local surficial 3-D features are superimposed on them.
https://www.ijgeophysics.ir/article_33613_65e3164c35d29ca3c02de72284b755e9.pdf
2015-12-22
40
56
Impedance tensor
near-surface inhomogeneity
regional structure
tensor analysis
tensor decomposition
galvanic distortion
Ali
Moradzadeh
1
School of Mining, College of Engineering, University of Tehran, Tehran, Iran
LEAD_AUTHOR
Bahr, K., 1988, Interpretation of the magnetotelluric impedance tensor: regional induction and local telluric distortion: J. Geophys., 62, 119-127.
1
Bahr, K., 1991, Geological noise in magnetotelluric data: a classification of distortion types: Phys. Earth Planet. Inter., 66, 24-38.
2
Berdichevsky, M. N., and Dmitriev, V. I., 1976, Basic principles of interpretation magnetotelluric sounding curves: Geoelectric and Geothermal Studies, 165-221, Budapest.
3
Berdichevsky, M. N. and Zhdanov, M. S., 1984, Advanced Theory of Deep Geomagnetic Sounding: Elsevier, 408.
4
Bibby, H. M. Caldwell, T. G. and Brown, C., 2005, Determinable and non-determinable parameters of galvanic distortion in magnetotellurics: Geophys. J. Int., 163, 915–930.
5
Booker, J. R., 2014, The magnetotelluric phase tensor: A critical review: Survey in Geophysics, 35, 7–40.
6
Cai, J. T., Chen, X. B. and Zhao, G. Z., 2010, Refined techniques for data processing and two-dimensional inversion in magnetotelluric I: Tensor decomposition and dimensionality analysis: Chinese J. Geophys., 53(6), 1060-1071.
7
Caldwell, T. G., Bibby, H. M. and Caldwell, C., 2004, The magnetotelluric phase tensor: Geophys. J. Int.,158, 457–469.
8
Cerv, V., Pek, G., and Menvielle, M., 2010, Bayesian approach to magnetotelluric tensor decomposition: Annals of Geophysics, 53(2), 21-32.
9
Chakridi, R., Chouteau, M., and Mareschal, M., 1992, A simple technique for analysing and partly removing galvanic distortion from the magnetotelluric impedance tensor: application to Abitibi and Kapuskasing data (Canada): Geophys. J. Int., 108, 917-929.
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11
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12
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13
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14
Eggers, D. E., 1982, An eigenstate formulation of the magnetotelluric impedance tensor: Geophysics, 47, 1204 - 1214.
15
Groom, R. W., and Bailey, R. C., 1989, Decomposition of magnetotelluric impedance tensors in the presence of local three-dimensional Galvanic distortion: J. Geophys. Res., 94, 1913-1925.
16
Groom, R. W., and Bailey, R. C., 1991, Analytic investigations of the effects of near-surface three-dimensional Galvanic scatterers on MT tensor decompositions: Geophysics, 56, 496-518.
17
Groom, R. W., and Bahr, K., 1992, Corrections for near surface effects: decomposition of the magnetotelluric impedance tensor and scaling corrections for regional resistivities: A tutorial. Survey in Geophysics, 13, 341-379.
18
Groom, R. W., Kurtz, R. D., Jones, A. G., and Boerner, D. E., 1993, A quantitative methodology to extract regional magnetotelluric impedances and to determine the dimension of the conductivity structure: Geophys. J. Int., 115, 1095-1118.
19
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20
Li, Y., Yu, P., Zhang, L., Wang, J., and Wu, J., 2010, An Improved Approach on Distortion Decomposition of Magnetotelluric Impedance Tensor: 2010 SEG Annual Meeting, 17-22 October, Denver, Colorado, SEG-2010-0824.
21
Lilley, F. E. M., 1995, Strike direction: obtained from basic models for 3D magnetotelluric data: Three-dimensional Electromagnetics (Eds. M Oristaglio and B. Spies), 359-370. Ridgefield, Conn. USA.
22
Lilley, F. E. M., 1998, Magnetotelluric tensor decomposition: Part I. Theory for a basic procedure: Geophysics, 63(6), 1885–1897.
23
Lilley, F. E. M., 2012, Magnetotelluric tensor decomposition: insights from linear algebra and Mohr diagrams: In: New achievements in geoscience (Ed: Hwee-Sam Lim) doi: 10.5772/2066.href=’’http://www.intechopen.com/books/new-achievements-in- geoscience”.
24
Lilley, F. E. M., and Weaver, J. T., 2010, Phases greater than 90° in MT data: analysis using dimensionality tools: J. Appl. Geophys., 70, 9-16.
25
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26
Jiracek, G. R., Reddig, R. P., and Kojima, R. K., 1989, Application of the Rayleigh-FFT technique to magnetotelluric modelling and correction: Phys. Earth Planet. Inter., 53, 365-375.
27
Jones, A. G., and Dumas, I., 1993, Electromagnetic images of a volcanic zone: Phys. Earth Planet. Inter., 81, 289-314.
28
Jones, A. G., and Groom, R. W., 1993, Strike-angle determination from the magnetotelluric impedance tensor in the presence of noise and local distortion: rotate at your peril: Geophys. J. Int., 113, 524-534.
29
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34
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35
Moradzadeh, A., 1998, Electrical Imaging of the Adelaide Geosyncline using Magnetotellurics (MT): Ph.D. Thesis, Flinders Univ. of South Australia.
36
Moradzadeh, A., and White, A., 2005, An assessment of the geoelectric dimensionality of subsurface structures using magnetotelluric data: J. Sci. & Tech., Shahrood University of Technology, 6, 59-65.
37
Moradzadeh, A., 2003, Static shift appraisal and its correction in magnetotelluric (MT) surveys: The 21st Symposium on Geosciences, 197-201, Tehran, Iran.
38
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39
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Swift, C. M., Jr., 1967, A Magnetotelluric Investigation of an Electrical Conductivity Anomaly in the Southwestern of United States: Ph.D. Thesis, Mass. Inst. Tech.
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Yee, E., and Paulson, K. V., 1987, The Canonical decomposition and its relationship to other forms of magnetotelluric impedance tensor analysis: Geophysics, 61, 173-189.
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Zhdanov, M. S., 1987, Application of space analysis of electromagnetic fields to investigation of the geoelectrical structure of the earth: Phys. App. Geophys., 125, 483-497.
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Zhang, P., Roberts, R.G., and Pedersen, L. B., 1987, Magnetotelluric strike rules: Geophysics, 52, 267-278.
47
ORIGINAL_ARTICLE
Application of surface-derived attributes in determining boundaries of potential-field sources
This paper describes an edge detection method based on surface-derived attributes. The surface-derived attributes are widely used in the interpretation ofseismic datain two main categories: (1) derivative attributes including the dip angle and the azimuth; (2) derivative attributes including curvature attributes. In general, the magnitude of the normal curvature of a surface (curvature attributes) can be expressed in terms of derivatives of that surface which are called the first and second fundamental forms of the surface. For a quadratic surface which fits data, it is shown that the dip-angle equation in the interpretation of the seismic data is similar to the horizontal gradient magnitude (HGM) equation in the interpretation of potential field data. Among the infinite number of curvature attributes, a few of them which are suitable for edge detection are shown. The coefficients of a quadratic surface are calculated using the least square method. At a particular point, the attributes are obtained using these coefficients. Zero contours of most positive curvature and the determinant of the curvature matrix delineate the location of the edges of anomalies. Theshape indexattributequantitatively reflects the local shape of the surface over sources in terms of cap, dome, ridge, saddle, rut, trough and cup.Here, the maximum curvature is introduced as a new technique to detect the horizontal location of anomalies. First, the introduced attributes were applied to the noise-free synthetic data. Then, the data with the noise added were used to check the stability of the method. In the presence of high-level noise, this method was successful in determining boundaries of the anomalies.Zero contoursof the most positive curvature, the determinant of curvature matrix and the maximum curvature properly illustratethe linear features within the mapped surface. The results of using surface-derived attributes were compared with tilt angle and HGM filters. This comparison showed that zero contours of the most positive and maximum curvature attributes are approximately matched with zero contours of the tilt angle and maximum values of HGM. Finally, this method was used for real data from Mobrun massive sulfide ore of Canada.MATLAB softwarewas used for programming and calculating the required parameters of this method.
https://www.ijgeophysics.ir/article_33614_7e47b6607eaf57618a0c495ffc5c5840.pdf
2015-12-22
57
71
Surface-derived attributes
potential field data
most positive curvature
Maximum Curvature
Shape Index
zero contours
Mohammad
Barazesh
1
Institute of Geophysics, University of Tehran, Iran
AUTHOR
Seyed-Hani
Motavalli-Anbaran
2
Institute of Geophysics, University of Tehran, Iran
LEAD_AUTHOR
Hojjat
Ghorbanian
3
Institute of Geophysics, University of Tehran, Iran
AUTHOR
Barraud, J., April 2013, "Improving identification of valid depth estimates from gravity gradient data using Curvature and Geometry analysis," First break, Volum 31.
1
Bergbauer, S. 2002, The use of curvature for the analyses of folding and fracturing with application to the emigrant gap anticline, Wyoming: Phd. thesis, Stanford university.
2
Cevallos, C., kovac, p., lowe, s. j., 2013, “Application of Curvatures to airborn gravity gradient data in oil exploration,”Geophysics,VOL.78,NO.4.
3
Cooper, G. R. J., and D. R. Cowan, 2003, The application of fractional calculus to potential field data: Exploration Geophysics, 34, 51 –56.
4
Grant, F. S., and West, G. F., 1965, Interpretation theory in applied geophysics, McGraw-Hill. , 70, 39-43.
5
Grauch, V. J. S., and L. Cordell, 1987, Limitations of determining density or magnetic boundaries from the horizontal gradient of gravity or pseudo gravity data: Geophysics, 52, 118 –121.
6
Hansen, R. O., and E. deRidder, 2006, Linear feature analysis for aeromagnetic data: Geophysics, 71, no. 6, L61 –L67.
7
Marfurt, K. J., 2007, Seismic Attributes for Prospect Indentification and Reservoir Characterization: Society of Exploration Geophysics.
8
Miller, H. G., and V. Singh, 1994, Potential field tilt — A new concept for location of potential field sources: Journal of Applied Geophysics, 32, 213 –217.
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Nabighian, M. N., 1972, The analytic signal of two-dimensional bodies with polygonal cross-section — Its properties and use for automated anomaly interpretation: Geophysics, 37, 507–517.
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Oruç, B., I. Sertçelik, Ö. Kafadar, and H. H. Selim, 2013, Structural interpretation of the Erzurum Basin, eastern Turkey, using curvature gravity gradient tensor and gravity inversion of basement relief: Journal of Applied Geophysics, 88, 105 –113.
11
Plouff, D., 1976, Gravity and magnetic fields of polygonal prisms and applications to magnetic terrain corrections: Geophysics, 41, 727–741.
12
Phillips, J. D., R. O. Hansen, and R. J. Blakely, 2007, The use of curvature in potential-field interpretation: Exploration Geophysics, 38, 111 –119.
13
Roberts, A., 2001, Curvature attributes and their application to 3D interpreted horizons: First Break, 19, 85–100.
14
Roy, L., Agarwal, B. N. P., and Shaw, R. K., 2000, A new concept in Euler deconvolution of isolated gravity anomalies: Geophysical Prospecting, v. 48, no. 3, p. 559-575.
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Santos, D. F., J. B. C. Silva, V. C. F. Barbosa, and L. F. S. Braga, 2012, Deeppass — An aeromagnetic data filter to enhance deep features in marginal basins: Geophysics, 77, no. 3, J15 –J22.
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Verduzco, B., J. D. Fairhead, C. M. Green, and C. MacKenzie, 2004, New insights to magnetic derivatives for structural mapping: The Leading Edge, 23, 116 –119.
17
Wijns, C., C. Perez, and P. Kowalczyk, 2005, Theta map: Edge detection in magnetic data: Geophysics, 70, no. 4, L39 –L43.
18
ORIGINAL_ARTICLE
The preventive role of Snell’s law in mode conversion from Z- to whistler-mode waves in an inhomogeneous magnetoplasma with a low density
Electromagnetic waves with different modes, such as Z-, whistler-, LO- and RX- modes are found in different regions of the Earth magnetosphere and the magnetosphere of other planets. Since whistler-mode waves influence the behavior of the magnetosphere, and they are used as experimental tools to investigate the upper atmosphere, they are important. On the other hand, the mode conversion process can be considered as one of the processes of generating electromagnetic waves that can occur under certain conditions. Usually, propagation waves in an inhomogeneous plasma are a necessary, but not a sufficient condition for a mode conversion process. Snell’s law has an important role in the mode conversion process. Although, this law lets a mode conversion occur from Z- to LO-mode waves, in a case from Z- mode to whistler mode waves, it plays a preventive role.The aim of this paper is to demonstrate the preventiverole of Snell’s law in a mode conversion from Z- to Whistler-mode waves in an inhomogeneous magnetoplasma with a low density. We used the dispersion relation in the magnetoplasma with a low density and for an oblique wave normal angle. By applying the Snell’s law, we showed that with the propagation of the Z-mode waves in an inhomogeneous plasma, there is not any matching point between Z- and Whistler mode waves, and for any wave normal angle always an evanescentlayer exists between the two modes.In this case, Snell’s law prevents the mode conversion from occurring. It also prevents the transfer of energy from one to another mode waves.
https://www.ijgeophysics.ir/article_33615_5c3f36c7caa82fd869b39a0632079a78.pdf
2015-12-22
72
80
whistler
Snell’s law
inhomogeneous plasma
mode conversion
magnetosphere
Mohammad Javad
Kalaee
1
Institute of Geophysics, University of Tehran, Tehran, Iran
LEAD_AUTHOR
Inan, U. S. and Bell, T. F., 1977, The plasmapause as a VLF waveguide, J. Geophys. Res. 82, 2819.
1
Inan, U. S., Bell, T. F., Bortnik, J., and Albert, J. M., 2003, Controlled precipitation of radiation belt electrons, J. Geophys. Res., 108(A5), 1186, doi:10.1029/2002JA009580.
2
James, H.G., 1979, Wave propagation experiments at medium frequencies between two ionospheric satellites 3. Z mode pulses, J. Geophys. Res. 84, 499–506.
3
James, H.G., 1991, Guided Z mode propagation observed in the OEDIPUS A tethered rocket experiment, J. Geophys. Res. 96, 17865–17878.
4
Jones, D., 1976, Source of terrestrial non-thermal radiation, Nature, 260, 686–689.
5
Jones, D., 1980, Latitudinal beaming of plantary radio emissions, Nature, 288, 225–229.
6
Jones, D., 1977, Mode-coupling of Z-mode waves as a source of terrestrial kilometric and Jovian decametric radiations, Astron. Astrophys., 55, 245-252.
7
Jones, D., 1988, Planetary radio emissions from low magnetic latitudes observations and theories, in Planetary Radio EmissionsII, edited by Rucker, H. O., S. J .Bauer, and B. M. Pedersen, 255–293, Austrian Acad.Sci., Vienna, Austria.
8
Kalaee, M. J., Ono, T., Katoh, Y., Iizima, M. and Nishimura, Y., 2009, Simulation of mode conversion from UHR-mode wave to LO-mode wave in an inhomogeneous plasma with different wave normal angles, Earth Planets and Space, 61, 1243-1254.
9
Kalaee, M. J., Katoh, Y., Kumamoto, A., Ono, T., and Nishimura Y, 2010, Simulation of mode conversion from upper-hybrid waves to LO-mode waves in the vicinity of the Plasmapause, Annales Geophysicae, 28, 1289-1297.
10
Kalaee, M. J, Katoh, Y., Ono, T., 2014a, Effects of the angle between the density gradient and the external magnetic field on the linear mode conversion and resultant beaming angle of LO-mode radio emissions, Earth, Moon and Planets, DOI: 10.1007/s11038-014-9448-4.
11
Kalaee, M. J., and Katoh, Y., 2014b, A simulation study on the mode conversion process from slow Z-mode to LO mode by tunneling effect and variations of beaming angles, Advances in Space Research, DOI 10.1016/j.sar. 2014.08.025.
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Oya, H., 1971, Conversion of electrostatic plasma waves into electromagnetic waves: numerical calculation of the dispersion relation for all wavelengths, Radio Sci., 12, 1131–1141.
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14
Storey, L. R. O., 1953, An investigation of whistling atmospherics, Philos. Trans. R. Soc. London, Ser. A. 246, 113.
15
ORIGINAL_ARTICLE
Rupture characteristics of the 2012 earthquake doublet in Ahar-Varzagan region using the Empirical Green Function method
On August 11, 2012,within several minutes, two shallow destructive earthquakes with moment magnitudes of 6.5 and 6.4 occurred in Varzagan, Azerbaijan-e-Sharghi Province, in the northwest of Iran In this study, the Empirical Green Function (EGF) method was used for strong ground motion simulationto estimate the source parameters and rupture characteristics of the earthquakes. To simulate the first earthquake, two aftershocks with magnitudes of 5.6 and 5.2 were used as the EGFs. In the second event, an aftershock with a magnitude of 5 was used as the small event. The size of the main fault caused by the first event was about 18 km in length and 10 km in width. Also, the size of the asperity in the second earthquake was about 16 km in the strike direction and 11 km in the dip direction. The durations of the ruptures in the first and second events were more than 9 and 10s, respectively. The estimated fault plane solution showed strike-slip faulting for the first earthquake and a reverse mechanism with a strike-slip component for the second one. Strike, dip and rake of a causative fault of the first and second earthquakes were determined as 270, 81 and 175 degrees and 230, 57 and 134 degrees, respectively. In addition, the stress drop in the first and second events was calculated to be about 22 and 34 bar, respectively.
https://www.ijgeophysics.ir/article_33616_aa09d8c86030d53377ebbdaf7b2fa6ab.pdf
2015-12-22
81
92
Rupture characteristics
Strong ground motion
Ahar-Varzagan earthquake doublet
Empirical Green Function
Hesaneh
Mohammadi
1
Islamic Azad University, Tehran North Branch, Iran
AUTHOR
Mohammadreza
Gheitanchi
2
Earth Physics Department, Institute of Geophysics, University of Tehran, Iran
LEAD_AUTHOR
Astiz, L., and Kanamori, H., 1984, An earthquake doublet in Ometepec, Guerrero, Mexico: Phys. Earth PlanetInterior, 34, 24–45.
1
Cheng, F., and Huang, H., 2011, Strong ground motion simulation of the October 22, 1999 Chiay earthquake using hybrid Green function method: 4th IASPEI international symposium, University of California, Santa Barbara.
2
Courboulex, F., Virieux, J., Deschamps, A., Gilbert, D., And Zoll, A., 1996, Source investigation of a small event using empirical Green functions and simulated annealing: Geophys. J. Int., 125, 768–780.
3
Eshelby, J. D., 1957, The determination of the elastic field of an ellipsoidal inclusion, and related problems: Proc. Roy. Soc., A241, 376–396.
4
Hartzel, S. H., 1978, Earthquake aftershocks as Green functions: Geophys. Res. Lett., 5, 1–4.
5
Hutchings, L. and Viegas, G., 2012, Application of Empirical Green Functions in earthquake source, wave propagation and strong ground motion studies: Lawrence Berkeley National Laboratory, USA, 3, 80–130.
6
Irikura, K., 1991, The physical basis of the empirical Green function method and the prediction of strong ground motion for large earthquake: Proc. International workshop of seismology and earthq. Eng., 89–95.
7
Kagan, Y. Y., and Jackson, D. D., 1991, Long-term earthquake clustering: Geophys. J. Int., 104,117–133.
8
Lay, T., and Kanamori, H., 1980, Earthquake doublets in the Solomon Islands: Phys. Earth Planet. Interior., 21, 283–304.
9
Lin, C. H., Yeh, Y. H., Ando, M., Cheng, T. M, and Pu, H. C, 2008, Earthquake doublet sequences: Evidence of static triggering in the strong convergent zones of Taiwan: Terrestrial Atmospheric and Oceanic Sciences, 19, 589–594.
10
Miyake, H., Iwata, T, and Irikura, K., 2000, Source characterization of inland crustal earthquakes for nearsource ground motions: Proceedings of the 6th international conference on seismic zonation.
11
Mueller, C., 1985, Source pulse enhancement by deconvolution of an empirical Green function: Geophys. Res. Lett., 12, 33–36.
12
Raghu, S. T. G., 2008, Modeling and synthesis of strong ground motion: Department of Civil Engineering, Indian Institute of Technology, Madras, India.
13
Wells, D. and Coppersmith, K., 1994, New empirical relationships among magnitude, rupture length, rupture width, rupture area and surface displacement: Bulletin of the Seismological Society of America, 8, 974–1002.
14
ORIGINAL_ARTICLE
The detection of 11th of March 2011 Tohoku's TEC seismo-ionospheric anomalies using the Singular Value Thresholding (SVT) method
The Total Electron Content (TEC) measured by the Global Positioning System (GPS) is useful for registering the pre-earthquake ionospheric anomalies appearing before a large earthquake. In this paper the TEC value was predicted using the singular value thresholding (SVT) method. Also, the anomaly is detected utilizing this predicted value and the definition of the threshold value, leading to the use of the anomaly as a precursor. The SVT is used in the matrix completion problem, namely the accurate recovery of a matrix from a nearly minimal set of entries. In this study, the SVT has been applied to the ionospheric TEC of the global ionosphere maps(GIM) data on a powerful earthquake in Tohoku on the 11th of March in 2011. In this method, the two-hour TEC observations of this region are converted into a matrix for several consecutive days before and after the occurrence of an earthquake. In this matrix the rows and the columns represent the days and the sequential hours, respectively. The prediction of the non-linear time series is formulated as a method for solving the low-rank recovery problem. Results indicate that under suitable conditions the TEC values can be estimated properly in the aforementioned days and hours by solving a simple optimization problem. In order to show the efficiency of this method in predicting the time series, the results obtained from this research were compared with those from other researches.
https://www.ijgeophysics.ir/article_33617_eed4d5b327de68b41473e768b674b6f1.pdf
2015-12-22
93
103
Singular Value Thresholding
Anomaly Detection
TEC
Earthquake
Ionosphere
Mohammad Ali
Sharifi
1
School of Surveying and Geospatial Engineering, College of Engineering,University of Tehran, Iran and Research Institute of Geoinformation Technology (RIGT), College of Engineering, University of Tehran, Iran
LEAD_AUTHOR
Saeed
Farzaneh
2
School of Surveying and Geospatial Engineering, College of Engineering,University of Tehran, Iran
AUTHOR
Farideh
Sabzehee
3
School of Surveying and Geospatial Engineering, College of Engineering,University of Tehran, Iran
AUTHOR
Akhoondzadeh, M., 2012. Anomalous TEC variations associated with the powerful Tohoku earthquake of 11 March 2011, Nat. Hazards Earth Syst. Sci., 12, 1453–1462, doi:10.5194/nhess-12-1453-2012.
1
Akhoondzadeh, M., 2013. Support vector machines for TEC seismo-ionospheric anomalies detection, Ann. Geophys.,31, 173–186, doi:10.5194/angeo-31-173-2013.
2
Akhoondzadeh, M., 2011. Comparative study of the earthquake precursors obtained from satellite data. PhD thesis, University of Tehran, Surveying and Geomatics Engineering Department, Remote Sensing Division.
3
Cai, J. F., Candes, E. J., Shen, Z., 2010. A singular value thresholding algorithm for matrix completion, SIAM Journal on Optimization, 20 (4), 1956-1982.
4
Candes, E. J., Recht, B., 2009. Exact matrix completion via convex optimization, Foundations of Computational Mathematics, 9(6), 717-772.
5
Candes, E. J., Tao, T., 2009. The power of convex relaxation: Near-optimal matrix completion. IEEE Transduction on Information Theory,56(5):2053–2080.
6
Candes, E. J., Plan, Y., 2009. Matrix completion with noise. Proceedings of the IEEE 98(6), 925-936.
7
Devi, M., Barbara, A.K., Depueva, A., Depuev, V., 2008. Preliminary results of TEC measurements in Guwahati, India, Adv. Space Res., 42, 753-756.
8
Hayakawa, M., Molchanov, O. A., 2002. Seismo- Electromagnetics: Lithosphere-Atmosphere-Ionosphere Coupling, Terra Scientific Publishing Co. Tokyo, pp. 1–477.
9
Liu, J. Y., Chuo, Y. J., Shan, S. J., Tsai, Y. B., Chen, Y. I., Pulinets, S. A., Yu, S. B., 2004. Pre-earthquake ionospheric anomalies registered by continuous GPS TEC measurements, Ann. Geophys., 22, 1585–1593, doi:10.5194/angeo-22-1585-2004.
10
Mayaud, P. N., 1980. Derivation, Meaning and use of geomagnetic indices,Geophy, 22, American Geo. Union, Washington, D.C.
11
Namgaladze, A. A., Klimenko, M. V., Klimenko, V. V., Zakharenkova, I. E., 2009. Physical mechanism and mathematical modelling of earthquake ionospheric precursors registered in Total Electron Content, Geomagnetism and Aeronomy, 49, 252–262.
12
Pulinets, S. A., Boyarchuk, K. A., 2004. Ionospheric Precursors of Earthquakes, Springer, Berlin, pp. 207-246.
13
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14
ORIGINAL_ARTICLE
Detecting buried channels using linear least square RGB color stacking method based on deconvolutive short time Fourier transform
Buried channels are one of the stratigraphic hydrocarbon traps. They are often filled with a variety of porous and permeable sediments so they are important in the exploration of oil and gas reservoirs. In reflection seismic data, high-frequency components are sensitive to the channel thickness, whereas, low-frequency components are sensitive to the channel infill materials. Therefore, decomposition of seismic data to its spectral components provides useful information about both thickness and infill materials of buried channels.A 4D spectral data is produced by applying spectral decomposition to a 3D seismic data cube which is decomposed into several single frequency 3D cubes. Since different frequencies carry different types of information, each single frequency cube cannot show all subsurface information simultaneously. Therefore, we used color stacking method and constructed RGB plots, which represent more information than single frequency volumes. In this paper, we applied three methods of Deconvolutive Short Time Fourier Transform (DSTFT), S Transform (ST) and Short Time Fourier Transform (STFT) to a land seismic data from an oil field in the south-west of Iran. We used the resulting spectral volumes to create RGB color stacking plots for tracing buried channels. According to the results, the RGB plots based on the DSTFT method revealed more details than the ST and STFT methods.
https://www.ijgeophysics.ir/article_33618_12466edc396adff86333eb9a347119d0.pdf
2015-12-22
104
112
Buried channels
spectral decomposition
deconvolutive short time Fourier transform
color stacking method
Mehdi
Sadeghi
1
Institute of Geophysics, University of Tehran, Tehran, Iran
AUTHOR
Amin
Roshandel Kahoo
2
School of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran
LEAD_AUTHOR
Hamid Reza
Siahkoohi
3
Institute of Geophysics, University of Tehran, Tehran, Iran
AUTHOR
Azita
Nikoo
4
School of Mining, Petroleum and Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran
AUTHOR
Auger, F., Flandrin, P., Goncalves, P., and Lemoine, O., 1996, Time-frequency toolbox for use with MATLAB, CNRS, France.
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3
Fahmy, W. A., G. Matteucci, D. Butters, J. Zhang, and J. Castagna, 2005, Successful application of spectral decomposition technology toward drilling of a key offshore development well: 75th Annual International Meeting, SEG, Expanded Abstracts, 262–264.
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Guo, H., K. J. Marfurt and J. Liu, 2009, Principal component spectral analysis: Geophysics, 74, 35 – 43.
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H, Sattari., A, Gholami., H. R. Siahkoohi., 2013, Sparsity based short-time Fourier transform and applications in thin bed characterization: Iranian Journal of geophysics, 7-3, 36-48.
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Nikoo, A., Roshandel kahoo, A., Nejati kalatah, A., and Hassanpor, H., 2012, Buried channel detection using reduced interference distribution: International Geophysical Conference and Oil & Gas Exhibition, Istanbul, Turkey, 17-19 September 2012.
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Sadeghi, M., Roshandel Kahoo, A., Siahkoohi, H. R., and Heidarian, A. R., 2013, Demonstrating buried channels using principal component analysis: Earth and Space Physics, Institute of geophysics, Tehran University, 40, 45-56.
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