In the field of synthetic information forecast for mineral product

extremum lines (curves) of the first order differential coefficient of aeromagnetic and gravitational maps reflect the ruptures of magnetism and the densities of geologic bodies respectively. In order to deduce the rupture conformation

the similarities of attitude and size of geologic bodies in different deepness

curves of aeromagnetic and gravitational maps in different deepness and directions must be compared; only those ruptures of reflection with similar curves are reliable. In order to deduce and analyze the situation automatically

in this paper

we first introduced the conventional estimation approach of spatial relation between curves. Later on

we also described the Neural Networks approach of reasoning of spatial relation between curves. The result indicate that these estimations of spatial relations between curves obtained by the Neural Networks approaches matched perfectly with the estimations of authoritative geological experts

and achieved triumphs in practical applications.