NMR well logging technology has become a recognised and effective method for characterising hydrocarbons in porous media. Many recent publications have attested to its suitability for this purpose. NMR can be used to determine porosity, permeability and viscosity in situ, to estimate pore size distribution, to indicate wettability alteration during the recovery process and to determine many other important parameters. All previous NMR applications were developed for investigating conventional oil reservoirs. Extending the detection capabilities of NMR Logging tools into heavy oil and bitumen reservoirs for in situ characterisation is very important for oil producers in the Province of Alberta, Canada and other heavy oil and bitumen areas (Venezuela, California, Russia, etc.). The main problem encountered when trying to use NMR technology to evaluate these reservoirs is that the relaxation characteristics of heavy oils and bitumen are at the limits of the logging tools' detection capabilities. The NMR signal obtained from conventional oil, heavy oil and bitumen formations can consist of both hydrocarbon signal and water signal. Each NMR signal can further characterise both mobile and immobile fluids in the porous media. However, as the viscosity of the hydrocarbon phase increases and the NMR signal shifts towards lower relaxation times, the composite NMR signal for the hydrocarbon bearing formation becomes very complicated. As the viscosity of the bitumen exceeds 100,000 cP (at natural conditions), the relaxation characteristics of bitumen become partially non-detectable by both the logging and laboratory NMR tools. As a result, the conventional methods of NMR detection fail to recognise precisely the hydrocarbon components. Laboratory NMR measurements of bitumen bearing porous media under different temperatures were performed. THis method delivered new information about bitumen reserves in situ. The results show that low field NMR holds promise for the characterisation of heavy oil and bitumen recoverable reserves. This new approach can be applicable for real time monitoring of thermal extraction including monitoring the efficiency of thermal recovery methods.
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