Abstract: Lithology identification model is developed in Well Block Cai 9 of Cainan oilfield by using neural network technology. The classification can reach 93.75% of coincident rate with the test samples. Also, porosity and permeability model in studied area is developed, by which unknown samples are predicted, obtaining average absolute errors of 0.54% for porosity and 1.68×10^-3 μm² for permeability; average relative errors of 3.5% for porosity and 32% for permeability. The accuracy of prediction is greatly improved compared with traditional methods.

Key words: Cainan oilfield, neural networks, reservoir description, lithology, porosity, permeability