Abstract: Most oilfields developed in China up to now have already entered into the stage of production decline, so the theories about this stage are in urgent demand. But the shortages of conventional theory about it cause its application to be greatly restricted for the key problem of solution for decline index. The generalized regression neural network (GRNN) and the genetic algorithm (GA) are regarded as the artificial intelligence techniques. GRNN has little demand on data sampling, easily approaching to any type of functions; GA can be used to look for the best results in full and partial ranges. The combined application of these two techniques will overcome the shortages of conventional theory. This paper established the GRNN and uses an improved GA to search for the optimum smoothing factor in full range, hence proposes a model. By application of this model to Gudao oilfield in the stage of production decline, good effects are gained.

Key words: production decline, generalized regression neural network (GRNN), genetic algorithm (GA), Gudao oilfield