Method and system for predicting the effect of microbes injected into an oil-bearing reservoir

A method for predicting the effect of microbes injected into an oil-bearing reservoir, the oil-bearing reservoir being capable of being represented by a first computer-generated grid comprising a first plurality of grid blocks, is provided. Measurement data representing the effect of injecting the microbes into a multiple coreflood apparatus is received. The multiple coreflood apparatus comprises at least first and second material samples indicative of a rock formation associated with said oil-bearing reservoir, the first and second samples being capable of being represented by a second computer-generated grid comprising a second plurality of grid blocks, the first and second samples being representative of different regions of the reservoir and being connected such that microbes injected into the first sample are able to flow to the second sample. Selected data of the received measurement data is input into a computer-implemented reservoir model configured to simulate said effect of microbe injection in relation to the second grid. The reservoir model is executed to generate reservoir model data indicative of the effect of injecting the microbes into the multiple coreflood apparatus. Parameters of the reservoir model are adjusted by matching the reservoir model data against the measurement data, in order to calibrate the reservoir model. The calibrated reservoir model is then executed for the first grid to predict the effect of injecting the microbes into the reservoir. A corresponding system, and a method and apparatus for generating data indicative of the effect of injecting microbes into an oil-bearing reservoir, are also provided.