STRUCTURAL DIPS OF INTERFACES INFERRED FROM POTENTIAL FIELD DATA

It has been known since the 1930’s that for an interface between two lithologies of differing density or magnetization dipping at less than vertical the location of the maximum horizontal gradient is located a distance down dip from the upper edge of the interface. The analytic signal maximum is always located above the upper edge of the interface and so the distance between the two maxima can be used to estimate the dip of the interface. Some modern potential field software can be used to map both the maximum horizontal gradient and the maximum analytic signal. Measurement of the separation between the two can be used to estimate the dip of the interface when combined with an estimate of the depth to the top of the dipping layer and its thickness. Most geophysical interpretations include depth-to-source estimates, and in some cases, the source thickness, so that the dip can be estimated. In cases where the source thickness is unknown, estimates based on the geologic scenario can give a range of dips, that usually varies less than ten degrees.

The technique was employed on a map of gravity and magnetic anomaly interfaces from the Upper Santa Cruz basin in south-central Arizona that included reduced-to-pole magnetic and gravity anomaly horizontal gradient and analytic signal maxima. Cases were selected where the analytic signal and horizontal gradient maxima were certainly from the same interface, and measured separations together with depth estimates from the geophysical interpretation were used to estimate interface dip. Since most of the interfaces examined were in bedrock below basin fill, a thickness of three kilometers was used. Dips for the aeromagnetic data were generally steeper and often different from those for nearby gravity anomalies. We interpret this as the aeromagnetic interfaces being due to the Basin and Range deformation and the gravity interfaces reflecting more of the older structure, although the large younger faults, such as the Mount Benedict Fault, show up clearly in both datasets. When taken together with other structural information gleaned from geophysical and geological data, dip estimates improve the interpretation of subsurface geologic structure.