tailieunhanh - New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies

A new fast least-squares method is developed to estimate the shape factor (q-parameter) of a buried structure using normalized residual anomalies obtained from gravity data. The problem of shape factor estimation is transformed into a problem of finding a solution of a non-linear equation of the form f(q) = 0 by defining the anomaly value at the origin and at different points on the profile (N-value). Procedures are also formulated to estimate the depth (z-parameter) and the amplitude coefficient (A-parameter) of the buried structure. The method is simple and rapid for estimating parameters that produced gravity anomalies. This technique is used for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The technique is tested and verified on theoretical models with and without random errors. It is also successfully applied to real data sets from Senegal and India, and the inverted-parameters are in good agreement with the known actual values. | New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies

• Vật lý
• A fast least squares inversion
• Normalized residual gravity anomalies
• Q Parameter
• Z Parameter
• A parameter