Zhang, Yingchun (CNOOC Research Institute Co., Ltd.) | Xu, Wei (CNOOC Research Institute Co., Ltd.) | Zou, Jingyun (CNOOC Research Institute Co., Ltd.) | Jing, Zhiyi (CNOOC Research Institute Co., Ltd.) | Fang, Lei (CNOOC Research Institute Co., Ltd.) | Liu, Jun (CNOOC International Limited)
In complex clastic reservoirs, deviation often exists in oil saturation derived from logging interpretation due to the borehole conditions and log quality. Especially in thin-sand reservoirs, oil saturation is generally lower than actual results because of boundary effect. An innovative approach of saturation height function coupled with rocktype is provided to improve the accuracy of saturation prediction in well logs and spatial distribution. The model results are compared with log derived results.
The new approach is based on the routine and special core analysis of over 100 core samples from the complex clastic reservoir in the north of Albert Basin in Uganda. Discrete rocktypes (DRT) are determined by flow zone index and pore throat radius which indicate the fluid flows. After converting the capillary pressure (Pc) data to reservoir conditions, Lambda curve fitting (Sw = A * PcB + C) is used to fit each capillary pressure curve. Then, a robust relationship between the fitting coefficients (A, B, C) and rock properties (i.e. porosity and permeability) is expressed as a nonlinear function for each DRT. Combined with the height above free water level, a water saturation (Sw) model is constructed by SHF within DRT model.
Using the porosity and permeability obtainedfrom routine core analysis, FZI and pore throat radius are calculated (e.g., by Winland function). Five different rocktypes (DRT1-5) are defined in the delta sand reservoir in the north of Albert Basin with distinct pore textures. The distinguishment is in accordance with the shape of capillary pressure curve, that is, the flow capability increases from DRT1 to DRT5. A strong correlation between Pc and Sw processed by Lambda curve is acquired for each core sample. Meanwhile, 3 coefficients A, B and C can be obtained in Lambda formula. By nonlinear regression, coherent relation between each factor and reservoir properties (porosity and permeability) for each DRT are obtained. Height above the free water level is estimated by geometrical modeling on the oil water contact. The Sw model is constructed by the new SHF function coupled with DRT model. It showed that the water saturation derived from SHF is highly consistent with log derived results and NMR results. Moreover, it provides more precise results in thinner sands and in spatial distribution.
Based on the identified different rocktype, a new SHF derived from capillary pressure data is utilized to establish the relationship between saturation, the height above the free water level and rock properties. The approach can significantly improve the accuracy of saturation prediction of thin reservoir and reasonably depict the spatial distribution characteristics of saturation. Furthermore, the approach will provide a more precise result in hydrocarbon volume calculation and numerical simulation.