Browsing by Author "Bouchaoui, Lyes"

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Biomimétisme pour l’inversion et l’optimisation en géophysique
(Universite M'Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2025) Bouchaoui, Lyes; Ferahtia, Djalal(Directeur de thèse)
Le biomimétisme consiste à s'inspirer, ou imiter, la nature, que ce soit de colonies structurées (ex. abeilles, fourmis) ou individuelle (ex. gecko, Martin pêcheur), afin de répondre à des problèmes scientifiques et d’ingénierie de manière durable. Il peut se résumer en trois principes : complémentarité, coopération et adaptation. Parmi ces multiples applications, l’optimisation, est la plus intéressante en géophysique. Cette thèse explore l'application d'une technique bio-inspirée, l'algorithme d'optimisation par colonies de fourmis (ACO), pour résoudre des problèmes inverses en géophysique, en se concentrant sur l'inversion des données de sondages électriques verticaux (SEV). Les problèmes inverses en géophysique sont souvent mal posés, non linéaires et soumis à des incertitudes liées aux données bruitées. Inspiré du comportement des fourmis dans la recherche de nourriture, l'ACO offre un cadre robuste pour explorer de vastes espaces de solutions tout en évitant les minimas locaux. Cette étude évalue l'efficacité de l'ACO à travers des simulations sur des données synthétiques et son application à des données réelles provenant de la région de Hassi R'Mel en Algérie. Les résultats montrent que l'ACO surpasse les méthodes traditionnelles comme les algorithmes génétiques (AG) et le recuit simulé (RS) en termes de précision, de stabilité et de résistance au bruit. Les applications pratiques de cette approche incluent la caractérisation des aquifères et l'identification de structures géologiques favorables à l'exploitation des eaux souterraines. Les recherches futures incluent l'extension de l'ACO à d'autres méthodes géophysiques et l'amélioration de son efficacité computationnelle.
Vertical electrical sounding data inversion using continuous ant colony optimization algorithm : a case study from Hassi R'Mel, Algeria
(John Wiley and Sons Inc, 2022) Bouchaoui, Lyes; Ferahtia, Jalal; Farfour, Mohammed; Djarfour, Nouredine
Among the existing geophysical methods, the vertical electrical sounding remains a fast and economical way to detect groundwater resources. However, the interpretation of the vertical electrical sounding data often suffers from non-uniqueness due to the ill-posed nature of the inverse problem. In recent years, metaheuristic algorithms have been successfully used for solving ill-conditioned and ill-posed problems. This work presents a scheme that uses the continuous ant colony optimization (ACOR) technique to invert vertical electrical sounding data. The ACOR is a global search algorithm that explores and finds the globally optimal solution over a search space by mimicking the behaviour of biological ants. The development of this algorithm was due to the requirement to interpret a set of vertical electrical sounding collected at the region of Hassi R'Mel (Algerian Sahara). The area has a particular geological/geoelectrical structure, which renders the interpretation of vertical electrical sounding challenging as standard inversion approaches tend to fail to recover a reliable resistivity model. The ACOR algorithm was initially tested with synthetic data from models simulating the geological/hydrogeological structure of the studied area. The results verified the robustness and stability of the ACOR algorithm even in the presence of a high level of noise. Furthermore, the tests indicated that the ACOR algorithm performed better when compared to other inversion techniques for this particular geoelectrical structure. Five vertical electrical sounding profiles using a Schlumberger array collected in the region of Hassi R'Mel were inverted using the ACOR algorithm. The models confirmed the presence of the two central aquifer systems and showed the geometry of the aquifer with the most favourable conditions for water accumulations
Vertical electrical sounding data inversion using continuous ant colony optimization algorithm: A case study from Hassi R’Mel, Algeria
(2022) Bouchaoui, Lyes; Ferahtia, Jalal; Farfour, Mohammed; Djarfour, Nouredine
Among the existing geophysical methods, the vertical electrical sounding remains a fast and economical way to detect groundwater resources. However, the interpretation of the vertical electrical sounding data often suffers from non-uniqueness due to the ill-posed nature of the inverse problem. In recent years, metaheuristic algorithms have been successfully used for solving ill-conditioned and ill-posed problems. This work presents a scheme that uses the continuous ant colony optimization (ACOR) technique to invert vertical electrical sounding data. The ACOR is a global search algorithm that explores and finds the globally optimal solution over a search space by mimicking the behaviour of biological ants. The development of this algorithm was due to the requirement to interpret a set of vertical electrical sounding collected at the region of Hassi R’Mel (Algerian Sahara). The area has a particular eological/geoelectrical structure, which renders the interpretation of vertical electrical sounding challenging as standard inversion approaches tend to fail to recover a reliable resistivity model. The ACOR algorithm was initially tested with synthetic data from models simulating the geological/hydrogeological structure of the studied area. The results verified the robustness and stability of the ACOR algorithm even in the presence of a high level of noise. Furthermore, the tests indicated that the ACOR algorithm performed better when compared to other inversion techniques for this particular geoelectrical structure. Five vertical electrical sounding profiles using a Schlumberger array collected in the region of Hassi R’Mel were inverted using the ACOR algorithm. The models confirmed the presence of the two central aquifer systems and showed the geometry of the aquifer with the most favourable conditions for water accumulations.