Abstract:

There are various kinds of factors that effect producible oil reserves.It is difficult to describe the relationship between the producible oil reserves and the effecting factors by an expression simply.Neural network expert system provides a new approach to solve the problem.Particular process is like that:1. select five reservoir parameters (cumulative thickness,temperature,effective porosity and permeability,pressure) and three crude oil parameters (saturation,viscosity and density)as characteristic parameters;2.the parameters should be standardized and normalized;3.take 8 known oil recovery areas in Fanjia sub oil field as learning samples to train the network system;4.use the trained system to predict the producible oil reserves of unkown oil areas.The prediction results fitted well with actural circumstances and the errors are exceptable.

Key words: neural network, expert system, producible reserves, B-P algorism, characteristic parameter