Spectral Induced Polarization Survey with Distributed Array System for Mineral Exploration: Case Study in Saudi Arabia

Alfouzan, Fouzan; Alotaibi, Abdulrahman; Cox, Leif H.; Zhdanov, Michael S.

doi:10.3390/min10090769

Cited by 14 publications

(9 citation statements)

References 28 publications

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“…This method is better than other geophysical methods due to its accuracy in depicting the distribution of polarized regions caused by the presence of metallic mineral deposits [7,8]. Apart from prospecting for metal minerals, the IP method is also commonly used for geotechnical studies to determine the clay content in the subsurface or the physical properties of the subsurface layer [8][9][10][11][12]. In the IP method, it is known the induced polarization in the time domain hereinafter called Time Domain Induced Polarization (TDIP).…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of Laboratory Physical Modeling in Acquiring the Response of Time Domain Induced Polarization (TDIP)

Yatini

Santoso

Laesanpura

et al. 2022

J. Penelit. Fis. Apl.

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Induced Polarization (IP) is one of the Geophysical methods that utilize the polarization properties of the rocks for metallic mineral exploration. The problems are how to distinguish the metallic minerals deposit based on the chargeability. The physical modeling of IP is used to study the behavior of TDIP response. The study of a simple mathematical model is carried out to obtain the theoretical curves which are presented as the subsurface parameter. These curves are used as a reference to assess the result of physical modeling. The laboratory physical modeling uses a tank model with a size of (200x100x70) cm3, with a block as a target and water as a host medium. The results show laboratory physical modeling which has been made is quietly good. The approximate position and geometry of the target can be identified. The resistivity inversion modeling is sensitive to recognizing the geometry and position, while the chargeability inversion is on the distribution of metallic minerals. The quantitative correlation between chargeability and iron-ore content is obtained by Dipole-dipole and Wenner configuration. Both are connected exponentially, with a different exponential constant for different block targets.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of Laboratory Physical Modeling in Acquiring the Response of Time Domain Induced Polarization (TDIP)

Yatini

Santoso

Laesanpura

et al. 2022

J. Penelit. Fis. Apl.

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“…Airborne time-domain electromagnetics (ATEM) was originally developed for mineral prospection [1][2][3][4] and is now a very consolidated methodology. Its first application probably dates back to 1948 [5], but since then, many different helicopter and fixed-wing acquisition systems have become commercially available.…”

Section: Introductionmentioning

confidence: 99%

1D Stochastic Inversion of Airborne Time-Domain Electromagnetic Data with Realistic Prior and Accounting for the Forward Modeling Error

2021

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Airborne electromagnetic surveys may consist of hundreds of thousands of soundings. In most cases, this makes 3D inversions unfeasible even when the subsurface is characterized by a high level of heterogeneity. Instead, approaches based on 1D forwards are routinely used because of their computational efficiency. However, it is relatively easy to fit 3D responses with 1D forward modelling and retrieve apparently well-resolved conductivity models. However, those detailed features may simply be caused by fitting the modelling error connected to the approximate forward. In addition, it is, in practice, difficult to identify this kind of artifacts as the modeling error is correlated. The present study demonstrates how to assess the modelling error introduced by the 1D approximation and how to include this additional piece of information into a probabilistic inversion. Not surprisingly, it turns out that this simple modification provides not only much better reconstructions of the targets but, maybe, more importantly, guarantees a correct estimation of the corresponding reliability.

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“…Airborne time-domain electromagnetic (ATEM) data have been collected for decades for mineral prospection [1][2][3][4]. Probably, the Stanmac-McPhar ATEM system-tested during the summer of 1948 in Canada-can be considered the first application of this methodology [5].…”

Section: Introductionmentioning

confidence: 99%

(Quasi-)Real-Time Inversion of Airborne Time-Domain Electromagnetic Data via Artificial Neural Network

et al. 2020

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The possibility to have results very quickly after, or even during, the collection of electromagnetic data would be important, not only for quality check purposes, but also for adjusting the location of the proposed flight lines during an airborne time-domain acquisition. This kind of readiness could have a large impact in terms of optimization of the Value of Information of the measurements to be acquired. In addition, the importance of having fast tools for retrieving resistivity models from airborne time-domain data is demonstrated by the fact that Conductivity-Depth Imaging methodologies are still the standard in mineral exploration. In fact, they are extremely computationally efficient, and, at the same time, they preserve a very high lateral resolution. For these reasons, they are often preferred to inversion strategies even if the latter approaches are generally more accurate in terms of proper reconstruction of the depth of the targets and of reliable retrieval of true resistivity values of the subsurface. In this research, we discuss a novel approach, based on neural network techniques, capable of retrieving resistivity models with a quality comparable with the inversion strategy, but in a fraction of the time. We demonstrate the advantages of the proposed novel approach on synthetic and field datasets.

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Spectral Induced Polarization Survey with Distributed Array System for Mineral Exploration: Case Study in Saudi Arabia

Cited by 14 publications

References 28 publications

Effectiveness of Laboratory Physical Modeling in Acquiring the Response of Time Domain Induced Polarization (TDIP)

Effectiveness of Laboratory Physical Modeling in Acquiring the Response of Time Domain Induced Polarization (TDIP)

1D Stochastic Inversion of Airborne Time-Domain Electromagnetic Data with Realistic Prior and Accounting for the Forward Modeling Error

(Quasi-)Real-Time Inversion of Airborne Time-Domain Electromagnetic Data via Artificial Neural Network

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