#TITLE_ALTERNATIVE# - ISKANDAR (NIM: 12305002), NERIDAWITA
Duri Formation is a formation that has a huge the prospect to be developed better. This research will be discussed about the prediction of lithology and porosity distribution in this formation, especially top sand "A". The method that used is Seismic Multiattribute within the application of Neural Network PNN (Probabilistic Neural Network). Multiattribute method is used to predict the gamma ray log, density log and the porosity log. To earn the capacity amount of the attribute that are used, we will use a process called Step Wise Regression. The result of this attribute will then be used in the Neural Network PNN process. PNN is used of because it has the best correlation than other neural network methods. The result of the multiattribute analysis is pseudo-gamma ray volume, pseudo-density volume and pseudo-porosity volume with an integrated result of the lithology, density and porosity distribution. From this volume, then we will get the horizon slice for each volume. This horizon slice has a 10 ms window below top A. From this horizon slice, the result estimated is that the North part from the research location is sand region that has a lower density compare on the South part of the area. As for the porosity, the North part of the area has a higher porosity compare on the South part.