Predicting oil saturation of tight conglomerate reservoirs via well logs based on reconstructing nuclear magnetic resonance T2 spectrum under completely watered conditions

Abstract

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 core samples were selected to measure and analyse the porosity, permeability, nuclear magnetic resonance (NMR) T2 spectrum and mercury injection capillary pressure (MICP) curve. Second, an empirical method was proposed for reconstructing the NMR T2 spectrum under completely watered conditions using MICP curve based on the ‘three-piece’ power function. The parameters of different models were calibrated via experimental data analysis, respectively. The 180 core experimental data from an MICP curve were used as the input database. Porosity and permeability were regarded as the MICP data selection criteria to apply this model in formation evaluation. The comparison results show good application effects. Finally, to reflect oil saturation, the ratio of T2 geometric means of NMR T2 spectra under oil-bearing and completely watered conditions was proposed. Then, the quantitative relation between oil saturation and the proposed ratio was established via experimental data from the sealed cores, which established a quantitative prediction on oil saturation of tight conglomerate reservoirs. This showed a good application effect. The average relative error and the root mean square error (RMSE) of the predicted oil saturation and sealed coring measurement were around 10 and 3%, respectively. As the proposed method is only influenced by the wettability of reservoir and viscosity of oil, it is not only appropriate for the studied area, but also for other water-wet reservoirs containing light oil. It is important for identifying oil layers, calculating oil saturation and improving log interpretation accuracy in tight conglomerate reservoirs.

A Novel Empirical and Deep Ensemble Super Learning Approach in Predicting Reservoir Wettability via Well Logs

“…In contrast, the peak relaxation of oil is around 1000 ms, although this is mainly for oil with high gas-oil-ratio. At 100% water saturation, T 2 is usually around 10 ms [57]. When oil is encountered in the interval, T 2 tends to peak, signifying the additional oil relaxivity.…”

Control of Generalized Capillary Number on Immiscible Displacement Path: NMR Online and Network Simulation of Fluid Displacement Mechanism

“…Immiscible fluid displacement path, controlled by the fluid viscosity ratio and capillary numbers, has significant influences on the efficiencies in the oil recovery and reservoir development. Over the past decade, much effort has been made to study the immiscible displacement paths and control factors of tight oil reservoirs using simulation and experimental methods. − In particular, many pore-scale studies have indicated that the transfer across the fluid–fluid interface is primarily controlled by the relative magnitude of viscous stress and capillary force. − Lenormand et al first investigated the effect of the competition of capillary forces and viscous stress on immiscible displacement fluid paths in two-dimensional micromodels. Capillary number ( Ca ), which is a function of the displacement speed, contact angle, and viscosity ratio, can characterize the effect of these forces on immiscible displacement processes.…”

“…Glass beads have been widely used to characterize immiscible flow behavior in porous media. ,− Kamari et al used nonwetting fluid to perform immiscible displacement under a high capillary number in a glass model with a single crack. The authors indicated that the rock heterogeneity causes an earlier breakthrough and suggested that the unstable displacement front due to high Ca will lead to a low recovery ratio.…”