Estimating depth and model type using the continuous wavelet transform of magnetic data

Geophysics ◽  
2004 ◽  
Vol 69 (1) ◽  
pp. 191-199 ◽  
Author(s):  
Marc A. Vallée ◽  
Pierre Keating ◽  
Richard S. Smith ◽  
Camille St‐Hilaire

The continuous wavelet transform has been proposed recently for the interpretation of potential field anomalies. Using Poisson wavelets, which are equivalent to an upward continuation of the analytic signal, this technique allows one to estimate the depth of burial of homogeneous field sources and to determine the nature of the source in the form of a structural index. Moreau et al. (1999) accomplish this by successively testing the least‐squares misfit on a log–log plot of the wavelet transform amplitude versus the sum of the depth and the dilation (upward continuation height). We extend this methodology by analyzing the ratio of the Poisson wavelet coefficients of the first and second orders. For simple pole sources, this ratio at one dilation is enough to estimate the depth and index uniquely; but for extended sources of finite size, we must analyze the variation of the estimates with dilations. The technique gives good results on synthetic and field examples.

Author(s):  
Tin Quoc Chanh Duong ◽  
Đẩu Hiếu Dương ◽  
Ngân Ngọc Phạm ◽  
Hải Thanh Nguyễn ◽  
An Danh

As analyzing geomagnetic data at low latitude areas for instance the Mekong Delta (latitudes 11,07o), significant problem is that both of the magnetization and ambient field are not vertical totally, making magnetic anomalies antisymmetrical and often skewed to the location of the sources. In this paper, two-dimensional continuous wavelet transform (2-D CWT), using Farshad-Sailhac complex wavelet function is studied and applied for reducing the magnetic anomaly to a symmetrical one - this located on the source of the anomaly, and then determining the position of the center of the object causing anomalies by wavelet transform modulus maxima (WTMM) method. Next, magnetic data is extracted in two perpendicular directions passing through the center of the source to perform one-dimensional continuous wavelet transform (1-D CWT) to estimate the shape, depth and size of the source. Then, using the Marquardt algorithm to solve the inverse problem by least-squares method to further identify other characteristic parameters of the source such as: vertical size, remanent magnetization vector. The reliability of the proposed method is verified through theoretical models before application for analyzing the geomagnetic data in the Mekong Delta. The results are consistency with deep hole data, having small root mean square error, contribute to a better interpretation of the geological nature of the magnetic anomaly sources in the study area.


Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1106
Author(s):  
Jagdish N. Pandey

We define a testing function space DL2(Rn) consisting of a class of C∞ functions defined on Rn, n≥1 whose every derivtive is L2(Rn) integrable and equip it with a topology generated by a separating collection of seminorms {γk}|k|=0∞ on DL2(Rn), where |k|=0,1,2,… and γk(ϕ)=∥ϕ(k)∥2,ϕ∈DL2(Rn). We then extend the continuous wavelet transform to distributions in DL2′(Rn), n≥1 and derive the corresponding wavelet inversion formula interpreting convergence in the weak distributional sense. The kernel of our wavelet transform is defined by an element ψ(x) of DL2(Rn)∩DL1(Rn), n≥1 which, when integrated along each of the real axes X1,X2,…Xn vanishes, but none of its moments ∫Rnxmψ(x)dx is zero; here xm=x1m1x2m2⋯xnmn, dx=dx1dx2⋯dxn and m=(m1,m2,…mn) and each of m1,m2,…mn is ≥1. The set of such wavelets will be denoted by DM(Rn).


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