Abstract 3D lithofacies modeling is a key step in depositional environment analysis. 1D lithofacies modeling along the wellbore is an essential contributor to the 3D modeling. This paper introduces an integrated workflow from 1D to 3D lithofacies modeling and the application of this workflow in an oil and gas field. This study focused on the integration of core description, conventional log curves, image logs data and interpretation. All the core descriptions have been digitally described or digitized and coded so those can be easily loaded and recognized by digital applications. After data loading, 1D lithofacies models were built using the Artificial Neural Network (ANN) method and a blind test was then conducted to check if the models meet the requirement. When the blind test results were satisfactory, the ANN models would then be applied to the un-cored wells to predict the lithofacies at those wells. Wellbore image logs were then used to smooth the final results which would be used to build the 3D lithofacies models throughout the whole field. The workflow was applied in one of the oil field in the study area and the results were quite exciting. There are five types of lithofacies in the studied reservoirs but there is only one lithofacies predicted before using the porosity cutoff. With this new workflow, all five lithofacies were predicted and the accuracy of the prediction was greatly improved. An overall matching rate between the core description and the prediction is above 70% after smoothing with wellbore image logs. A 3D lithofacies model was then created using the result from the 1D lithofacies modeling. With the 3D model, the lithofacies distribution can be easily captured and the depositional environment can be analyzed to determine the potential good reservoirs.