关键词: 压裂, 加砂规模, 支持向量机, 优化

Abstract:

Fracturing effect is affected by many factors.There is the nonlinear relationship between the effect and reservoir parameters and reservoir conditions.In view of the difficulty of determining the sanding scale in designing fracturing process，the data of pre-fracturing well are used as sample data，the influence of net thickness，oil saturation，porosity，permeability，sanding scale and sand ratio on fracture effect should be considered，samples are learned by SVM，the forecasting model between influencing factors and fracture effect is established in the purpose of predicting the fracture effect under the different sanding scale，thereby the sanding scale is optimized.It is showed by calculation of case study in fracturing wells and the field implement that SVM has a fast convergence speed and can overcome effectively the problem of small samples，and optimal results effectively coincide with the actual fracturing effect，so it has a certain guiding sense to designed the sanding scale in fracturing.

Key words: fracturing, sanding scale, SVM, optimization