Research on Production Prediction and Control of Mechanized Production Wells based on Neural Networks

Abstract

In order to improve the overall operational efficiency of the mechanical production well group, save production costs, and accurately regulate the liquid production of the oil production well in the future, this paper proposes a neural network-based prediction and control model for mechanical production wells. This model includes two parts: prediction and regulation. Firstly, based on LSTM neural network, the oil and liquid production of single wells and well groups are predicted, and the oil and liquid production trends of single wells are obtained; Secondly, predict the water content within the next year based on the trend of oil and liquid production changes, and quantitatively analyze the controlled amount based on BP neural network combined with water content. Taking a certain well group in Daqing Oilfield as an example, simulation and on-site experiments were conducted. While the liquid production remained basically unchanged, the oil production increased by 5.7%, and with the same oil production, the energy consumption decreased by 6.67%.