Method to predict permeability of coal reservoir with BP neural network based on logging information

In order to solve the limited information of the test well and not to fully hold the difficult permeability distribution of the coal reservoir,the logging information was provided to be the factors affected to the permeability of the coal reservoir. With the relationship between the reservoir permeability and the known logging information, a BP neural network model was established. On the premise of certain study,a prediction method was conducted on the unknown samples. With comprehensive application of the BP neural network model and the fuzzy queuing algorithm,based on 56 test wells and logging well information in Liulin Block,with a fuzzy curve analysis method was applied to optimize the input variation,a prediction model of the seam permeability was established with the BP neural network and a prediction was conducted on the perm eability. There was a high ftting between the predicted results and the measured results and the results showed that the method could have a good adaptbility to predict t he permeability of coal reservoir. With the prediction on the permeability distribution of seam in Liulin Block,the plane layout mode of the permeability in the full block was C leared. The paper pointed out that the permeability in the northeast part of Liulin Block was high and the northeast part could be a favorable block of exploration and devel opment.