Horizontal loop electromagnetic data inversion through novel metaheuristics and its applications to ore deposit explorations

Abstract The success of horizontal loop electromagnetic method in determining ore body model parameters is intricately tied to the inversion process. However, geophysical inverse problems often grapple with ill‐posed and non‐unique mathematical difficulties. To handle this situation, we presented two new metaheuristics: the Barnacles Mating Optimizer and the Hunger Games Search algorithm. This pioneering approach is the first in the literature to employ both optimizers simultaneously to invert electromagnetic anomalies. To test the core functionality of these inversion tools, we simplified the horizontal loop electromagnetic problem by using a single frequency. Before carrying out the data inversions, a synthetic anomaly caused by a simple multi‐source model was used to perform some modal analyses. These analyses revealed the composite modality character of the inversion process and highlighted the necessity of an algorithm that effectively balances global exploration (thoroughly searching the model space while avoiding local minima) and local exploitation, which focuses on approximating the global optimum closely. In addition, the findings indicated the importance of conducting post‐inversion analyses to evaluate potential uncertainties in the estimations. Initial experiments with nine challenging benchmark functions revealed that Hunger Games Search outperforms in tackling optimization problems. The performances of both algorithms were then examined using synthetic horizontal loop electromagnetic anomalies and two field data sets from Australia. To achieve a balanced comparison, we fine‐tuned the control parameters of both algorithms, optimizing their performance under comparable conditions. These assessments provided valuable insights into the effectiveness of each algorithm when properly configured. Uncertainty appraisal analyses mostly confirmed the consistency and mathematical consistency of the obtained solutions. In the real data inversion cases, the outputs of Hunger Games Search showed strong agreement with the drilling data. This study illustrates the stronger performance of the Hunger Games Search algorithm relative to Barnacles Mating Optimizer in the presented scenarios and demonstrates its effectiveness in estimating source parameters using horizontal loop electromagnetic anomalies.

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Publication Details

Journal
Geophysical Prospecting
Published
2025-04-17
DOI
https://doi.org/10.1111/1365-2478.70027
Citations
1
Primary Topic
Geophysical and Geoelectrical Methods
Type
article
Field-Weighted Citation Impact
1.87
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article

Horizontal loop electromagnetic data inversion through novel metaheuristics and its applications to ore deposit explorations

Zhuofan Liu, Hanbing Ai, Yunus Levent Ekinci, Ahmad Alvandi et al.
1 citations
Geophysical Prospecting
Geophysical and Geoelectrical Methods
1.87
article

Horizontal loop electromagnetic data inversion through novel metaheuristics and its applications to ore deposit explorations

Zhuofan Liu, Hanbing Ai, Yunus Levent Ekinci, Ahmad Alvandi, Çağlayan Balkaya, Arka Roy, Arkoprovo Biswas, Kejia Su, Yue Shen
article en
1 citations

Abstract

Abstract The success of horizontal loop electromagnetic method in determining ore body model parameters is intricately tied to the inversion process. However, geophysical inverse problems often grapple with ill‐posed and non‐unique mathematical difficulties. To handle this situation, we presented two new metaheuristics: the Barnacles Mating Optimizer and the Hunger Games Search algorithm. This pioneering approach is the first in the literature to employ both optimizers simultaneously to invert electromagnetic anomalies. To test the core functionality of these inversion tools, we simplified the horizontal loop electromagnetic problem by using a single frequency. Before carrying out the data inversions, a synthetic anomaly caused by a simple multi‐source model was used to perform some modal analyses. These analyses revealed the composite modality character of the inversion process and highlighted the necessity of an algorithm that effectively balances global exploration (thoroughly searching the model space while avoiding local minima) and local exploitation, which focuses on approximating the global optimum closely. In addition, the findings indicated the importance of conducting post‐inversion analyses to evaluate potential uncertainties in the estimations. Initial experiments with nine challenging benchmark functions revealed that Hunger Games Search outperforms in tackling optimization problems. The performances of both algorithms were then examined using synthetic horizontal loop electromagnetic anomalies and two field data sets from Australia. To achieve a balanced comparison, we fine‐tuned the control parameters of both algorithms, optimizing their performance under comparable conditions. These assessments provided valuable insights into the effectiveness of each algorithm when properly configured. Uncertainty appraisal analyses mostly confirmed the consistency and mathematical consistency of the obtained solutions. In the real data inversion cases, the outputs of Hunger Games Search showed strong agreement with the drilling data. This study illustrates the stronger performance of the Hunger Games Search algorithm relative to Barnacles Mating Optimizer in the presented scenarios and demonstrates its effectiveness in estimating source parameters using horizontal loop electromagnetic anomalies.

Geophysical ProspectingVol. 73(5)
King Fahd University of Petroleum and Minerals (SA), Muş Alparslan University (TR), Süleyman Demirel Üniversitesi (TR), University of Tehran (IR), China University of Geosciences (CN), Bitlis Eren University (TR), National Centre for Earth Science Studies (IN), Banaras Hindu University (IN)
Openalex Percentile: Top 19%
Geophysical and Geoelectrical Methods
1.87
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