Abstract
Abstract
A number of heavy oil or tar accumulations have been reported in several Middle East reservoirs. Heavy oil is often overlooked as a resource because of the expense and technical challenges associated with producing it.
But more than 6 trillion barrels of oil in place attributed to the heaviest hydrocarbon. Most of the conventional onshore hydrocarbon reservoirs have been depleted, and time of easy hydrocarbon is over; so, it is prudent to look into the unconventional reservoirs like heavy oil. An accurate evaluation and characterization is obviously crucial to its efficient exploitation. The evaluation and characterization of heavy oil depends on its identification, quantification, analysis of representative fluid sample and reservoir properties.
The methods proposed in the literature might be successful in identifying heavy oil reservoirs but are less reliable for quantifying the amount of heavy oil, and are insensitive to oil viscosity, the key property that controls the producibility of heavy oil. Heavy oil characterization is incomplete without the sampling of fluid in the reservoir environment. It is often desirable to acquire the sample with wireline formation tester tool and integrate the in-situ fluid properties with NMR logs.
In this study we successfully integrate, conventional logs, NMR logs, in-situ fluid sample, PVT data and conventional core data for identification and quantification of heavy oil present in the pore space. This integrated study overcomes the limitations of individual techniques. Our case study shows that the porosity deficit between conventional total porosity and NMR porosity gives the identification of heavy oil present in the pore space, this difference between two porosities represents the extra viscous component of fluid that are not observable by the NMR tool. The amount of porosity deficit is the amount of extra heavy oil / tar in the pore space and this gives the quantification of the same.
Conventional and NMR derived reservoir properties are required to be integrated with conventional core porosity, permeability, water saturation and viscosity derived from PVT sample in order to characterize Heavy Oil in Clastic Reservoirs.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献