Porous medium permeability prediction method, electronic equipment and storage medium

The invention relates to a porous medium permeability prediction method. The method comprises the steps that N pore structure parameters of the porous medium are obtained, the N pore structure parameters can represent the porous medium, and N is an integer larger than 1; inputting the N pore structure parameters into a radial basis function (RBF) neural network model; and outputting to obtain the permeability of the porous medium. According to the scheme provided by the invention, the permeability of the porous medium is obtained by inputting the plurality of pore structure parameters capable of representing the porous medium into the RBF neural network model, and the permeability of the porous medium can be accurately predicted because the plurality of pore structure parameters can realize three-dimensional representation of the porous medium. 本申请是关于一种多孔介质渗透率预测方法。该方法包括：获取多孔介质的N个孔隙结构参数，所述N个孔隙结构参数能够表征所述多孔介质，所述N为大于1的整数；将所述N个孔隙结构参数输入径向基函数RBF神经网络模型；输出得到所述多孔介质的渗透率。本申请提供的方案通过将多个可以表征多孔介质的孔隙结构参数输入RBF神经网络模型，得到多孔介质的渗透率