Comparison of grid Euler deconvolution with and without 2D constraints using a realistic 3D magnetic basement model

We describe the application of a 2D-constrained grid Euler deconvolution method which is able to determine for each solution window whether the source structure is two dimensional, three dimensional, or poorly defined and to estimate the source location and depth. In each solution window, eigenvalues and eigenvectors are derived from the Euler equations and compared to threshold levels. A single eigenvalue below the given threshold and lying in the x–y-plane is shown to indicate a 2D source, while the absence of such an eigenvalue indicates a 3D source geometry. Two small eigenvalues indicate the field in the window has no distinct source. Applying these criteria to each solution window allows us to generate a map of source-geometry distribution. We evaluate the effectiveness of 2D-constrained grid Euler deconvolution using synthetic magnetic data generated from a 3D basement model based on real topography from an area with surface-exposed faulting. This modeling strategy provides a complex, nonidealized data set that compares Euler depth estimates directly to the known basement surface depth. Our results indicate that noninteger structural indices can be the most appropriate choice for some data sets, and the 2D-constrained grid Euler method images magnetic basement structure more clearly and unambiguously than the conventional grid Euler method.