A Least-squares Approach to Shape Determination from Residual Self-potential Anomalies

1997 ◽  
Vol 150 (1) ◽  
pp. 121-128 ◽  
Author(s):  
E. M. Abdelrahman ◽  
T. M. El-Araby ◽  
A. A. Ammar ◽  
H. I. Hassanein
Keyword(s):  
Least Squares ◽  
Shape Determination ◽  
Self Potential ◽  
Least Squares Approach

A least‐squares approach to depth determination from self‐potential anomalies caused by horizontal cylinders and spheres

Geophysics ◽  
1997 ◽  
Vol 62 (1) ◽  
pp. 44-48 ◽  
Author(s):  
El‐Sayed Mohamed Abdelrahman ◽  
Sharafeldin Mahmoud Sharafeldin
Keyword(s):  
Least Squares ◽  
Maximum Error ◽  
Polarization Angle ◽  
Data Errors ◽  
Depth Determination ◽  
Horizontal Cylinders ◽  
Cylinders And Spheres ◽  
Self Potential ◽  
True Values ◽  
Least Squares Approach

We have developed a least‐squares approach to depth determination from self‐potential anomalies caused by horizontal cylinders and spheres. By defining the zero‐anomaly distance and the anomaly value at the origin on the profile, the problem of depth determination from self‐potential data has been transformed into finding a solution to a nonlinear equation. Procedures are also formulated to estimate the electric dipole moment and the polarization angle. The error in the depth parameter estimation introduced by data errors was also studied through imposing 1 to 10% errors in the zero‐anomaly distance and the anomaly value at the origin in one synthetic profile caused by a sphere. When the zero‐anomaly distance and the anomaly value at the origin possess errors of equal magnitude and of the same signs, the results will not differ much from the true values. When errors have opposite signs, the maximum error in depth is 10%. Finally, the validity of the method is tested on a field example from Ergani Copper district, Turkey.

A Least-squares Approach to Depth Determination from Numerical Horizontal Self-potential Gradients

2004 ◽  
Vol 161 (2) ◽  
pp. 399-411 ◽  
Author(s):  
E. M. Abdelrahman ◽  
H. S. Saber ◽  
K. S. Essa ◽  
M. A. Fouda
Keyword(s):  
Least Squares ◽  
Depth Determination ◽  
Potential Gradients ◽  
Self Potential ◽  
Least Squares Approach
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