Magnetic interpretation utilizing a new inverse algorithm for assessing the parameters of buried inclined dike‑like geological structure

• Autorzy: Essa Khalid S. , Elhussein Mahmoud

Identyfikatory

DOI

10.1007/s11600-019-00255-9

• Języki publikacji: EN

Abstrakty

EN

A new algorithm has been established to interpret magnetic anomaly data due to inclined dike-like structure. This algorithm uses first horizontal derivative anomalies attained from magnetic anomaly data utilizing filters of sequential window lengths. The final estimated parameters are the half-width, the depth, angle of magnetization and amplitude factor of an inclined dike-like geological structure. A minimum variance criterion is used for selecting the most suitable variables. This algorithm has been realized to theoretical data without and with random noise. The effects of interference due to near structures have additionally been studied. The method was then applied to two field examples from Turkey and Peru, which demonstrate its effectiveness and accurateness. Thus, it is a respectable correspondence among the model parameters retrieved from this approach, drilling information, and the outcomes published in the literature. For example, in Turkey, we applied the technique to gauge the source variables and also the results were precise to w = 64.74 m and h = 87.65 m (2% and 3% errors, respectively) based on information from Aydin and Gelişli (Jeofizik 10:41–49, 1996).

Słowa kluczowe

EN

magnetic anomaly; depth; half-width; inclined dike

PL

anomalia magnetyczna; głębokość

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2019
• Tom: Vol. 67, no. 2
• Strony: 533--544
• Opis fizyczny: Bibliogr. 30 poz.

Twórcy

autor

Essa Khalid S.

• Geophysics Department, Faculty of Science, Cairo University, Giza P.O. 12613, Egypt

autor

Elhussein Mahmoud

• Geophysics Department, Faculty of Science, Cairo University, Giza P.O. 12613, Egypt

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).