A QUANTITATIVE METHOD FOR DELINEATING REGIONAL STRATIGRAPHIC CYCLES ON GAMMA-RAY LOGS FROM THE COASTAL PLAIN OF SOUTH CAROLINA

A stratigraphic database for the Coastal Plain of South Carolina is extensive, with geophysical logs, core, and biostratigraphic data available for more than forty wells that have been drilled to basement. In this study, an attempt was made to better understand the depositional environments of the Coastal Plain sediments and their relationship to transgressive-regressive sequences by applying curve-smoothing algorithms to gamma-ray logs in order to minimize local perturbations and background “noise” while maintaining a significant regional “signal.” The resulting regional trends were quantified by means of an analysis of the derivatives of the smoothed logs, which provides consistency in well log correlation and interpretation.

The gamma-ray log is analogous to a stochastic time series in that it is comprised of two components: a long-term “signal” and short-term “noise.” Local perturbations are, by nature, short-term; thus averaging several adjacent points tends to converge on the long-term “signal,” or regional trend. Regional interpretations and identifications made are therefore dependent on the curve-smoothing algorithm used. The Savitzky-Golay moving-window average was applied at increasing window sizes to the gamma-ray logs from more than twenty Coastal Plain wells, as this algorithm is best suited for minimizing the local “noise” and maximizing the regional signal, while preserving the peaks and troughs of the gamma-ray log. Once the size of the moving-window was established so as to delineate regional trends, the sign of the first and second derivatives of the smoothed logs was determined at each measured depth. When combined, the signs of the first and second derivatives yield four distinct outcomes (or curve shapes) bell-convex, bell-concave, funnel-convex, and funnel-concave. These four possible combinations are translated into a color series, and visual interpretation of the color series allows regional trends to be interpreted in terms of transgressive-regressive cycles and their constituent depositional environments.