The precise correlation of extracted core to geophysical borehole logs is often problematic in intervals in which no sufficiently large or distinctive features span the gap between the outer core surface and the borehole wall. This impairs our ability to use techniques that require accurate correlation as a prerequisite (e.g., to develop field-based, upscaling and downscaling relationships of porosity distributions at or below log resolution). We propose a new method for such situations in which we correlate a cascade of statistics of core features with those of image logs taken from the borehole wall. Each statistic is used individually to calculate a likelihood function of possible correlation locations. These results are combined using a joint-likelihood function, and with other prior information using Bayesian techniques, to bring all available information to apply to the final correlation solution. The technique is demonstrated with computerized tomography for a core section and image-log data extracted from a typical Middle Eastern carbonate reservoir. Using lithologic criteria alone, the correlation was constrained to a region, which constitutes prior information. Using the mean, variance, and geostatistical-range parameter, our method further constrains the correlation to , only seven times larger than Fullbore Formation MicroImager resolution. Thus our method allows further interpretation to be based on correlation accuracies as small as .