Research on well capacity prediction algorithm based on improved sparrow search algorithm fused with SVR

China is a large industrial country. In the process of oilfield development, it is of great significance to predict and analyze the oil well productivity of the oilfield. Aiming at the problems that sparrow search algorithm (SSA) is easy to fall into local optimization, insufficient search space and slow convergence speed when dealing with complex optimization problems, this paper proposes an improved sparrow search algorithm (ISSA) and integrates it into the training of support vector regression (SVR), so as to avoid the problems of local optimization and over fitting caused by improper selection of initial parameters of support vector regression machine, The accuracy of oil well production capacity prediction is improved, and the oil field production data is used for comparative analysis and verification.