The Application of BP Neural Network In Oil-Field - Pei-Ying ZHANG; Meng-Meng ZHAO (Indonesian Journal of Electrical Engineering and Computer Science, 2013)
Aiming at the situation that many techniques of production performance analysis acquire lots of data and are expensive considering the computational and human resources, and their applications are limited, this paper puts forward a new method to analyze the production performance of oil-field based on the BP neural network. It builds a dataset with some available measured data such as well logs and production history, then, builds a field-wide production model by neural network technique, a model will be used to predict. The technique is verified, which shows that the predicted results are consistent with the maximum error of rate of oil production lower than 7% and maximum error of rate of water production lower than 5%, having certain application and research value. DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3280