Abstract: By applying integrative approach of indicator flow zone (12) with principal component discriminating analysis, the core data from Lower Sha-2 reservoir in District Shang-1, ShangHe oilfield are elaborated in sedimentology and diagenesis, and based on which four types of the petrophysical facies are classified. Al- so, its petrophysical properties of this horizon are predicted using artificial neural network model (BP)， its IFZ is calculated and distribution and controlling factors of the petrophysical facies are discussed. Study shows that using well log data for appraisal of petrophysical facies is one of an important tool to evaluate reservoir quality.

Key words: ShangHe oilfield, petrophysical facies, well logging, evaluation, artificial neural network