Assessment on maximum magnitude of natural and triggered earthquake when water is impounded in the mining pit: A case study in Nui Nho quarry, Vietnam based on gravity and magnetic data

2020 ◽  
Vol 20 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Xuan-Nam Bui ◽  
Trong Dinh Cao ◽  
Long Quoc Nguyen ◽  
Bach Xuan Mai ◽  
Le Hung Trinh ◽  
...  
Keyword(s):  
Magnetic Data ◽  
Maximum Magnitude ◽  
Gravity And Magnetic ◽  
Triggered Earthquake ◽  
Gravity And Magnetic Data

Basin Definition Using Gravity and Magnetic Data: Case Study from El Qaa Plain, Sinai, Egypt

2012 ◽  
Author(s):  
Mohamed Ahmed ◽  
William Sauck ◽  
Mohamed Sultan ◽  
Farouk Soliman ◽  
Mohamed Rashed
Keyword(s):  
Magnetic Data ◽  
Gravity And Magnetic ◽  
Gravity And Magnetic Data

Automatic 3-D interpretation of potential field data using analytic signal derivatives

Geophysics ◽  
1997 ◽  
Vol 62 (1) ◽  
pp. 87-96 ◽  
Author(s):  
Nicole Debeglia ◽  
Jacques Corpel
Keyword(s):  
Signal Amplitude ◽  
Vertical Gradient ◽  
Analytic Signal ◽  
Magnetic Data ◽  
Practical Implementation ◽  
Potential Field Data ◽  
Gravity And Magnetic ◽  
Second Derivatives ◽  
Gravity And Magnetic Data ◽  
Derivatives Of

A new method has been developed for the automatic and general interpretation of gravity and magnetic data. This technique, based on the analysis of 3-D analytic signal derivatives, involves as few assumptions as possible on the magnetization or density properties and on the geometry of the structures. It is therefore particularly well suited to preliminary interpretation and model initialization. Processing the derivatives of the analytic signal amplitude, instead of the original analytic signal amplitude, gives a more efficient separation of anomalies caused by close structures. Moreover, gravity and magnetic data can be taken into account by the same procedure merely through using the gravity vertical gradient. The main advantage of derivatives, however, is that any source geometry can be considered as the sum of only two types of model: contact and thin‐dike models. In a first step, depths are estimated using a double interpretation of the analytic signal amplitude function for these two basic models. Second, the most suitable solution is defined at each estimation location through analysis of the vertical and horizontal gradients. Practical implementation of the method involves accurate frequency‐domain algorithms for computing derivatives with an automatic control of noise effects by appropriate filtering and upward continuation operations. Tests on theoretical magnetic fields give good depth evaluations for derivative orders ranging from 0 to 3. For actual magnetic data with borehole controls, the first and second derivatives seem to provide the most satisfactory depth estimations.

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