A New Method for Predicting Oil Saturation of Tight Conglomerate Reservoirs Via Nuclear Magnetic Resonance Logs

Abstract

Summary Due to complex lithology, strong heterogeneity, low porosity and permeability; resistivity logging faces great challenges in oil saturation prediction of tight conglomerate reservoirs. First, 10 typical cores were selected to measure and analyze petrophysical parameters. Second, an empirical method is proposed for reconstructing NMR T2 spectrum under completely watered condition using MICP curve based on the “three-piece” power function. The parameters of different models are calibrated via the experimental data. The 180 core experimental data of MICP curve are used as the input database. The porosity and permeability are regarded as the MICP data selection criteria for formation evaluation. The comparison results show good application effects. Finally, in order to reflect oil saturation, the ratio of T2 geometric means of NMR T2 spectra under oil-bearing and completely watered conditions is proposed. Then, the quantitative relation between oil saturation and the proposed ratio is established via experimental data of the sealed cores. It shows good application effect. The average relative error and the root mean square error (RMSE) of the predicted oil saturation and sealed coring measurement are around 10% and 3% respectively. It is important for identifying oil layers and improving log interpretation accuracy in tight conglomerate reservoirs.