Centrifuge capillary pressure data reduction with a modified Forbes method

Both implicit and explicit methods to reduce centrifuge data for capillary pressure curves suffer from various difficulties. Implicit methods have problems of the uncertainty of the assumed capillary pressure models, whereas explicit methods suffer from numerical errors arising from differentiation and/or integration. Simple yet accurate, the recently-developed Forbes method provided an alternative approach which is superior to others. Certain assumptions, however, were also introduced in this formulation. The Forbes method is modified in this paper so as to obtain better accuracy for the interpreted capillary pressure curves. The differential factor in the Forbes method is adjusted by trial-and-error for centrifugation production history matching. Examples are given to illustrate such procedures. Also the importance of data quality is stressed for the determination of an accurate capillary pressure curve.