A GENETIC APPROACH TO THE PREDICTION OF PETROPHYSICAL PROPERTIES

The importance of the flow unit approach to reservoir description has been recognised recently, but its application to predict porosity, per meability and water saturation from well logs has not been attempted i n previous studies. This Paper describes a genetic approach to reservo ir description, which combines lithofacies analysis with discriminant analysis and probability field simulation for the identification and c haracterisation of flow units on the basis of core and log data. Litho facies with distinct depositional, diagenetic and petrophysical charac teristics, which essentially act as lithohydraulic flow units, have be en identified from cores. A set of discriminant functions is then comp uted using log data from cored wells to identify lithofacies from wire line logs in uncored wells. Each lithofacies has been found by regress ion analysis to possess a distinct porosity and permeability relations hip. The lithofacies-specific relationships between sonic travel time and core porosity is also established by regression analysis. Porosity and permeability values predicted from regression analysis lack varia bility when compared to actual core data. Hence, probability field sim ulation is applied to add fine-scale variation to the values predicted from regression analysis. The techniques described here can be applie d to any type of reservoir. The application of these techniques has re sulted in an improved prediction of porosity, permeability and water s aturation for a shaly, glauconitic reservoir in the North West Shelf a rea of Australia, where traditional log analysis has been proved to be difficult to apply.