The invention relates to the field of geophysical data processing, in particular to a logging curve reconstruction method based on a genetic neural network algorithm. The method mainly comprises the following steps of: 1, standardizing a logging curve; standardizing a conventional logging curve to be unified to the same dimension level; 2, establishing a neural network structure and training a network; determining neural network input and output, establishing a neural network structure according to the number of network layers, and training the network; 3, performing genetic manipulation; calculating a training error and a fitness function, and optimizing a network structure and a weight threshold by utilizing three genetic operators of selection, crossover and variation; and 4, performingwell logging curve reconstruction by utilizing the optimized network structure until the precision requirement is met, and outputting a result. Compared with a traditional well logging curve reconstruction method, the method has higher precision, the production cost can be reduced, the operation efficiency is improved, and the well logging curve reconstruction effect is improved.