In Situ Viscosity of Oil Sands Using Low Field NMR

Abstract

Abstract In heavy oil and bitumen reservoirs, oil viscosity is a vital piece of information that will have great bearing on the chosen EOR scheme and the recovery expected. Prediction of in situ viscosity with a logging tool would be very beneficial in reservoir characterization and exploitation design. Low field NMR is a technology that has shown great potential as a tool for characterizing hydrocarbon properties in heavy oil and bitumen reservoirs. An oil viscosity correlation has previously been developed that is capable of providing order of magnitude viscosity estimates for a wide range of oils taken from various fields in Alberta. This paper presents tuning procedures to improve the NMR predictions for different viscosity ranges, and extends the NMR viscosity model to in situ heavy oil in unconsolidated sands. The results of this work show that the NMR oil peak can be de-convoluted from the in situ signals of the oil and water, and the bulk viscosity correlation that was developed for bulk oils can be applied to predict the in situ oil viscosity. These results can be translated to an NMR logging tool algorithm, allowing for in situ measurements of oil viscosity at the proper reservoir conditions. Introduction Canada contains vast reserves of heavy oil and bitumen. With approximately 2.7 trillion barrels of oil in place, the Canadian deposits of heavy oil and bitumen are comparable in volume to the total of all the known deposits of conventional crude oil worldwide(1). As conventional oil reserves begin to decline in Canada, while worldwide demand for oil continues to increase, the industry focus is now shifting rapidly to the recovery of these heavy oil and bitumen reserves. Due to advances in technology, operating costs for heavy oil recovery are decreasing, and these reserves are now becoming economic to produce. The most important physical property of heavy oil that governs the recovery process is its viscosity. This parameter dictates both the economics and the technical possibility of success for any chosen recovery scheme. As a result, oil viscosity is often correlated directly to estimates of recoverable reserves(2). Unfortunately, laboratory measurements become less accurate and more difficult to obtain as viscosity increases. The oil that is removed from the core may also have been physically altered during the transport and handling of the sample, so the oil viscosity measured in the lab may not be representative of the actual oil properties in situ(2). In light of the shortcomings of conventional viscosity measurements, low field nuclear magnetic resonance (NMR) is considered as an alternative for estimating heavy oil and bitumen viscosity. The idea of using low field NMR as a tool for predicting oil viscosity is not a new one. Several models have been proposed in the literature(3–6), which can predict oil viscosities for conventional and heavy oil. An NMR oil viscosity model was also previously presented(7, 8) that is capable of making order of magnitude oil viscosity predictions for samples with measured viscosities ranging from under 1 mPa.s (cP) to over 3,000,000 mPa.s.