The combination of seismic data and wells, geological information of reservoir properties at distances farther from wells can also be estimated. One of the methods for obtaining reservoir parameters using inversion of well and seismic data is based on the capability of artificial neural networks. We use artificial neural networks to find an inversion operator with the help of well data sets and near-well seismograms. In this study, two wells and a seismic section of Whicher-Range in the Perth Basin, Australia were used for inversion. Using attributes, density estimation was performed by artificial intelligence and ant colony algorithm. We found that the neural network and ant colony can be used to predict the types of logs. Comparison between the two methods, we found that ant colony algorithm has the highest percentage of prediction compared to the neural network.