Automatic dips are dips that have been calculated by a computer from a dipmeter or borehole image. A large range of processing methods have been developed to derive computed dips and provide a speedy first pass data set for the interpretation of a well section. These techniques fall into two broad categories, interval correlation and feature recognition. Interval correlation depends upon the matching of dipmeter microresistivity curves with each other. In effect, the curves are run against each other in steps with a correlation computed at each step, producing a correlogram. Peaks in the correlogram correspond with a similar response in all the resistivity curves; from knowing the spatial positions of the microresistivity curves this can be converted to a dip. Three main parameters control this processing method: correlation interval, step distance and search angle. Correlation interval is the segment length used in the correlation. Step distance is the interval at which the computation is repeated, it is usually half the correlation length. Search angle is a measure of the maximum amount of how far the curves are moved against each other in the correlation processes.
Computation of dips by feature recognition is a more sophisticated approach to dip evaluation. It depends on a pattern matching approach applied to the microresistivity curves. The curves are broken down into a series of scaled peaks and troughs, which are then matched to similar responses from the other curves. It allows for the recognition of boundaries, and generates more geologically significant dips than interval processing.
See also manual dips, mirror image dips, dip quality and bedding types.
LUTHI, S. M. 2000. Geological Well Logs. Springer, Berlin, p373.
RIDER, M., 1996. The Geological Interpretation of Well Logs, Whittles Publishing, Caithness, p280.