Probabilistic inversion of audio-frequency magnetotelluric data and application to cover thickness estimation for mineral exploration in Australia

Jiang, Wenping; Brodie, Ross; Duan, Jingming; Roach, Ian C.; Symington, Neil; Ray, Anandaroop; Goodwin, James

doi:10.1016/j.jappgeo.2022.104869

Cited by 9 publications

(12 citation statements)

References 32 publications

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“…In 2011, an inversion method was introduced based on a geostatistical approach (co-kriging) for three-dimensional inversions of total magnetic eld data by Shamsipour et al (2011). The method was adapted to include the depth weighting matrix approach to reduce the lack of resolution in depth (Jiang et al, 2023;Shamsipour et al, 2011). An e cient algorithm for 3D inversion of magnetic data over a porphyry-Cu deposit located in the Kerman Province of Iran was presented by Abedi et al (2015).…”

Section: Introductionmentioning

confidence: 99%

“…Nowadays, it is evident that geophysical studies are one of the main steps in mining and petroleum exploration and should be done before exploratory excavations (Kaufman & Keller, 1981;Loke & Barker, 1996;Pilkington, 1997;Pilkington & Keating, 2009;Telford et al, 1990). The high cost of excavation and its related heavy machinery and reduction of the exploration cost if using geophysical data are the reasons for this claim (Hinze, 1990;Hinze & Von Frese, 1990;Jiang et al, 2023;Talwani & Ewing, 1960;Talwani et al, 1959). Geophysical methods are different based on the physical properties and geological conditions of minerals.…”

Section: Introductionmentioning

confidence: 99%

“…The method was adapted to include the depth weighting matrix approach to reduce the lack of resolution in depth (Jiang et al, 2023;Shamsipour et al, 2011). An e cient algorithm for 3D inversion of magnetic data over a porphyry-Cu deposit located in the Kerman Province of Iran was presented by Abedi et al (2015).…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Depth, Physical Parameters, and Location using Nonlinear Inverse Modeling of Magnetic Data by Bhattacharya Method in a field of NW Iran

Hosseini

Khah²,

Kianoush

et al. 2023

Preprint

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Geophysical studies are utilized as one of the main steps in exploration that must be performed before exploratory drilling due to the high cost of excavation and its related heavy machinery and reduction of the exploration cost. One of the most critical geophysical issues in estimating the physical and geometric parameters is the store carrying out using the residual magnetic anomaly reduction. These parameters include depth, volume, shape factor, and type of storage. The present geophysical study aims to prepare and model magnetic data for proposed drilling sites in the Baba Ali Iron ore deposit in the Hamedan province of Iran. Inverse modeling is one of the most efficient interpretive methods of potential field data. In this study, the Bhattacharya method in MATLAB software is used to minimize the target function and potential field data to create the best fit for magnetic data. In this modeling, the graphs of the residual anomaly and model showed an excellent conformation two-dimensionally. Also, 3D modeling reconstructs the properties of the productive resources of anomalies correctly. After preparation of total magnetic maps, it was found out that the magnetic lens in four anomalies with surface depths of 20, 50, and 50 meters is estimated for this zone. Their specific gravity was 4.77 t / m3, and their initial storage capacity was 95,400 tones at most. Also, exploratory excavation is proposed to complete the preliminary explorations of the specified region by inverse modeling for the three points.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of Depth, Physical Parameters, and Location using Nonlinear Inverse Modeling of Magnetic Data by Bhattacharya Method in a field of NW Iran

Hosseini

Khah²,

Kianoush

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Nowadays, it is evident that geophysical studies are one of the main steps in mining and petroleum exploration and should be done before exploratory excavations (Kaufman & Keller, 1981;Pilkington, 1997;Pilkington & Keating, 2009;Telford et al, 1990). The high cost of excavation and its related heavy machinery and the reduction of the exploration cost if using geophysical data are the reasons for this claim (Hinze, 1990;Hinze & Von Frese, 1990;Jiang et al, 2023;Talwani & Ewing, 1960;Talwani et al, 1959). Geophysical methods differ based on the physical properties and geological conditions of minerals.…”

Section: Introductionmentioning

confidence: 99%

“…In 2011, an inversion method was introduced based on a geostatistical approach (co-kriging) for three-dimensional inversions of total magnetic field data by Shamsipour et al (2011). The method was adapted to include the depth weighting matrix approach to reduce the lack of resolution in depth (Jiang et al, 2023;Shamsipour et al, 2011). An efficient algorithm for 3D inversion of magnetic data over a porphyry-Cu deposit located in the Kerman Province of Iran was presented by Abedi et al (2015).…”

Section: Introductionmentioning

confidence: 99%

Geobody Estimation by Bhattacharyya Method Utilizing Nonlinear Inverse Modeling of Magnetic Data in Baba-Ali Iron Deposit, NW Iran

Kianoush

Khah²,

Hosseini

et al. 2023

Preprint

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Geophysical investigations are one of the leading efforts in any exploration project that must be performed ahead of time due to the high excavation expenditures, heavy machinery, and cost reduction. One of the essential geophysical concerns is the estimation of the physical and geometrical parameters of the reserve (geobody), which is done by exploiting the nonlinear inverse modeling of magnetic data. These parameters include depth, volume, shape factor, and type of storage. The present investigation aims to prepare and model magnetic data for proposed drilling sites in the Baba Ali Iron ore deposit in the Hamedan province of Iran. The areal and depth extent of the iron ore geobody was unknown. The Bhattacharyya method by MATLAB software coding was used to minimize the target function and potential field data and create the best fit for the magnetic data. The residual anomaly and model graphs exhibited an excellent two-dimensional conformation in this modeling. Also, 3D modeling correctly reconstructs the properties of the productive resources of anomalies. After preparing full magnetic maps, the magnetic lenses distinguished in four anomalies of surface depths, 20, 50, and deeper than 50 meters for this zone. This magnetite lens for the first zone was estimated based on filters applied on the entire magnetic map so that the lens's depth is trivial and almost zero. Their specific gravity is calculated as 4.77 t/m3, and their initial storage capacity is suggested to be about 95,400 tones at most. Finally, to complete the preliminary explorations of the specified area, exploratory drilling is suggested for three points by inverse modeling.

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Geobody estimation by Bhattacharyya method utilizing nonlinear inverse modeling of magnetic data in Baba-Ali iron deposit, NW Iran

Kianoush,

Keshavarz Faraj Khah,

Hosseini

et al. 2023

Heliyon

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Probabilistic inversion of audio-frequency magnetotelluric data and application to cover thickness estimation for mineral exploration in Australia

Cited by 9 publications

References 32 publications

Estimation of Depth, Physical Parameters, and Location using Nonlinear Inverse Modeling of Magnetic Data by Bhattacharya Method in a field of NW Iran

Estimation of Depth, Physical Parameters, and Location using Nonlinear Inverse Modeling of Magnetic Data by Bhattacharya Method in a field of NW Iran

Geobody Estimation by Bhattacharyya Method Utilizing Nonlinear Inverse Modeling of Magnetic Data in Baba-Ali Iron Deposit, NW Iran

Geobody estimation by Bhattacharyya method utilizing nonlinear inverse modeling of magnetic data in Baba-Ali iron deposit, NW Iran

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