Application of PSO LS-SVM forecasting model in oil and gas production forecast

The oil and gas production forecasting is instructive for oilfield development and operation. Based on the combination of particle swarm optimization (PSO) and least squares support vector machine (LSSVM), this paper analyzes the factors influencing the oil and gas production by adopting the historical data of oil and gas data in a company. In this paper, the oil and gas production forecasting is instructive for oilfield development and operation. The oil and gas production forecasting model was established and model validation was carried out. The experimental results show that the model of least squares support vector machine based on particle swarm optimization has good convergence, high prediction accuracy and training speed.