The Department of Petroleum Engineering at Heriot-Watt University has been studying the water alternating gas (WAG) injection processes, using experimental (micromodels) and theoretical (network modelling) methods during the past 3 years. Last year we presented to the IEA the results of the micromodel studies on water-wet systems. This paper presents the results of the experiments on oil-wet and mixed-wet systems and compares them with those of the water-wet models.
Many of the oil reservoirs are produced by waterflooding. When the water-cut is too high, for further production to be economical, the field is usually abandoned. At this stage a significant quantity of oil will still remain in the reservoir. It is known that using the water-alternating-gas injection schemes, some of that oil can be produced. Unfortunately, the underlying physics of the three-phase flow is not well understood to allow reliable predictions to be made for economic evaluation. This recovery method will involve drainage and imbibition processes taking place sequentially. Their three-phase relative permeability and capillary pressure functions are, therefore, extremely complex. It is practically impossible to develop such functions for realistic reservoir situations, using core displacement methods.
The approach we have adopted is to develop a mathematical network simulator, which covers all the significant physical flow processes involved in this recovery method. But to gain confidence that such a simulator can indeed reflect the physics of the flow realistically, we test it against the actual physical micromodel observations. If the predictions of the network simulator agree with those observed in the micromodel, we can then operate it with real reservoir fluid data and basic rock properties in 3-D, to calculate the required pore scale relative permeability functions. Observations made in the micromodel studies have considerably improved our understanding of the underlying physical principles. This knowledge is extremely valuable in formulation of the network model simulator.
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