Canada contains vast reserves of heavy oil and bitumen, which are rapidly becoming more important as conventional reserves begin to dwindle. Production costs are also decreasing to due to advances in technology, and heavy oil reserves all over the world are now becoming economic to produce. In these reservoirs, oil viscosity is a vital piece of information that will have great bearing on the chosen method of recovery. Prediction of in situ viscosity with a logging tool can be benefitial 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 model 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 model results for different viscosity ranges, and extends the NMR model viscosity predictions 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 oil viscosity model can be applied to predict the oil viscosity. These results can be translated to an NMR logging tool algorithm. In situ measurements of oil viscosity at the proper reservoir conditions can then be obtained.
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 oils worldwide1,2. 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 these heavy oil and bitumen reserves. Due to advances in technology, production costs in heavy oil prices 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 chance of success for any chosen recovery scheme. As a result, oil viscosity is often correlated directly to estimates of recoverable reserves3. 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 situ2. 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 literature3–5, which can predict oil viscosities for conventional and heavy oil.
