3D Euler deconvolution: Theoretical basis for automatically selecting good solutions
We derive the analytical estimators for the horizontal and vertical source positions in 3D Euler deconvolution as a function of the x‐, y‐, and z‐derivatives of the magnetic anomaly within a data window. From these expressions we show that, in the case of noise‐corrupted data, the x‐, y‐, and z‐coordinate estimates computed at the anomaly borders are biased toward the respective horizontal coordinate of the data window center regardless of the true or presumed structural indices and regardless of the magnetization inclination and declination. On the other hand, in the central part of the anomaly, the x‐ and y‐coordinate estimates are very close to the respective source horizontal coordinates regardless of the true or presumed structural indices and regardless of the magnetization inclination and declination. This contrasting behavior of the horizontal coordinate estimates may be used to automatically delineate the region associated with the best solutions. Applying the Euler deconvolution operator inside this region would decrease the dispersion of all position estimates, improving source location precision.