Interpretation of magnetic anomalies using some simple characteristic positions over tabular bodies

Subrahmanyam, M. B.; Rao, T. K. S. Prakasa

doi:10.1071/eg09005

Cited by 13 publications

(3 citation statements)

References 26 publications

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“…(2005) provided a detailed work on the historical development of geomagnetic anomaly interpretation techniques. Some of the data processing techniques for the anomaly interpretation use Fourier transform, Hilbert transform, nomograms, matching curve approach, distinctive points and distances (Bhattacharyya, 2012; Gay, 1965; Kara, 1997; McGrath & Hood, 1970; Nuamah & Dobroka, 2019; T. Rao et al., 1986; Subrahmanyam & Prakasa Rao, 2009). Moreover, inversion methodologies, local wave number approaches, directional derivative‐based methods, spectral analysis techniques, some special algorithms such as simplex algorithm and R‐parameter imaging were proposed for anomaly interpretation (Abdelrahman & Essa, 2005; Abdelrahman et al., 2012; Abo‐Ezz & Essa, 2016; Aziz et al., 2013; Cooper, 2015; Ekinci, 2016; Essa & Elhussein, 2019; Essa, Munschy, et al., 2022; Kelemework et al., 2021; Li & Oldenburg, 1996; Ma & Li, 2013; Mehanee et al., 2021; Melo & Barbosa, 2020; Pham et al., 2020; Salem et al., 2004; Tlas & Asfahani, 2011a, 2011b, 2015).…”

Section: Introductionmentioning

confidence: 99%

Inversion of Geomagnetic Anomalies Caused by Ore Masses Using Hunger Games Search Algorithm

Ai,

Ekinci,

Balkaya

et al. 2023

Earth and Space Science

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Geomagnetic anomaly interpretation through inversion procedures often yields useful results in determining the key details of ore masses. However, the problem is complicated due to the known ambiguous phenomena of the inversion process. Thus, details such as location, depth and shape can only be estimated using an efficient algorithm. To this end, we presented here a novel global optimization algorithm called Hunger Games Search (HGS) for the inversion of geomagnetic anomalies caused by ore masses. HGS is a well‐organized metaheuristic inspired by the hunger‐driven instincts and social behavioral decisions of animals. This is the first work in the literature to introduce this optimizer for the inversion of geophysical anomalies. We revealed the model parameter dependencies and the optimum control parameter values of the algorithm by performing some modal analyses and parameter tuning studies, respectively. The capability of HGS was demonstrated on synthetically produced geomagnetic responses and on three real anomalies obtained from some exploration fields in India and the USA. Uncertainty appraisal studies showed the solidity of the outputs of the algorithm. Moreover, some comparative studies with the fine‐tuned standard Particle Swarm Optimization, a commonly used tool for the inversion of geophysical anomalies, indicated that HGS algorithm provides better results in terms of convergence characteristics and solution stabilities in the presented inverse problem. We therefore recommend the use of this metaheuristic in model parameter estimation studies when dealing with this kind of geophysical potential field problems.

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Section: Introductionmentioning

confidence: 99%

Inversion of Geomagnetic Anomalies Caused by Ore Masses Using Hunger Games Search Algorithm

Ai,

Ekinci,

Balkaya

et al. 2023

Earth and Space Science

View full text Add to dashboard Cite

show abstract

“…Magnetic anomalies are inferred utilizing simple geometric models (point sources, dikes, spheres, horizontal and vertical cylinders, and prisms) to estimate model parameters. Several graphical and numerical approaches for analyzing magnetic data have been created using simple geometric models, for example, the matching curve, nomograms, and characteristic points methods are examples of these approaches 29 – 32 , Werner and Euler deconvolution 33 – 35 , moving average techniques 36 , least-squares approaches 36 , 37 , Fourier transforms 38 , 39 , alternative local wave number technique 40 , numerical gradient-based technique 17 , tilt-angle methods 41 , 42 , correlation techniques 43 , and spectral analysis techniques 44 . However, most of these methods have several defects such as individual subjectivity, use of only a few data points along with the measurement profile, hypersensitivity to noise, and influence of adjacent effect (which might degrade the accuracy of the results).…”

Section: Introductionmentioning

confidence: 99%

Magnetic data interpretation for 2D dikes by the metaheuristic bat algorithm: sustainable development cases

Essa

Diab

2022

Sci Rep

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Metaheuristic algorithms are increasingly being utilized as a global optimal method in the inversion and modeling of magnetic data. We proposed the Bat Algorithm Optimization (BAO) technique that is based on bat echolocation performance to find the global optimum solution. The best-estimated source parameters that correspond to the objective function minimum value are obtained after achieving the global optimum (best) solution. The suggested BAO technique does not require any prior knowledge; rather, it is a global search method that provides an effective tool for scanning the space of data to appraise sources parameters. The BAO technique is applied to magnetic data in the class of dipping and vertical dikes along 2D profiles to estimate the dimensional source parameters that include the depth to top, origin location, amplitude coefficient, index angle of magnetization, and width of the dipping dikes. The BAO technique has been used for single and multiple dikes structures. The accuracy and stability of the BAO technique are achieved on different synthetic examples of free and noisy data for single and multiple cases. Furthermore, the presented BAO technique was effectively utilized in three field examples from China and Egypt for iron ore deposits and metavolcanics basalt rock investigations. Overall, the BAO technique recovered inversion outcomes are in good agreement with borehole, geology, and published literature results.

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“…The strategies are based on: (i) graphical methods utilizing some distinctive features of the magnetic profile ( Koulomzine et al., 1970 ; Am, 1972 ; Subrahmanyam and Prakasa Rao, 2009 ); (ii) spectral analysis techniques ( Prakasa Rao et al., 1986 ); and (iii) numerical techniques such as the Werner Deconvolution method ( Hartman et al., 1971 ; Ku & Sharp; McGrath and Hood, 1973 ; Silva, 1989 ; Dondurur and Pamukcu, 2003 ). Large potential field data necessitate automatic interpretation techniques like Euler's algorithm and Werner deconvolution ( Thompson, 1982 ; Werner, 1953 ).…”

Section: Introductionmentioning

confidence: 99%

Application of K-means algorithm to Werner deconvolution solutions for depth and image estimations

Eshimiakhe

Lawal

2022

Heliyon

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Interpretation of magnetic anomalies using some simple characteristic positions over tabular bodies

Cited by 13 publications

References 26 publications

Inversion of Geomagnetic Anomalies Caused by Ore Masses Using Hunger Games Search Algorithm

Inversion of Geomagnetic Anomalies Caused by Ore Masses Using Hunger Games Search Algorithm

Magnetic data interpretation for 2D dikes by the metaheuristic bat algorithm: sustainable development cases

Application of K-means algorithm to Werner deconvolution solutions for depth and image estimations

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