Oilfield Output's Combined Forecast Based on Artificial Neural Networks

The exact forecast for oil output can guide the production and management in the oilfield. In this article, the question about oilfield output's forecast is discussed using the combination of artificial neural network (ANN). ANN can model the complex relationship among well-open number, ratio of containing water, exploited reserves and future output. A two-stage system is proposed with the first stage containing two ANN, a multilayer feed-forward ANN and a functional link ANN. The second stage consists of a combination module to mix the two individual ANNs produced in the first stage. Five different combination algorithms are examined, they are based on: averaging, recursive least squares, fuzzy logic, feedforward ANN, functional link ANN. The performance is tested on real data from four different oil types?The results indicate that combination strategies based on a single ANN outperform the other approaches.