Characterization of strongly heterogeneous reservoir architecture and intelligent classification evaluation of flow units

To evaluate the reservoir quality and fluid seepage law of reservoir ZJ452 that is strongly heterogeneous in the Zhujiang Formation in Huizhou A Oilfield in the Pearl River Mouth Basin, reservoir architecture analysis was carried out and multi-level automatic clustering algorithm were used to classify and evaluate the strongly heterogeneous reservoir. Porosity, permeability, flow zone index, and reservoir quality parameters were selected for discrimination. Self-organizing mapping neural network and Bayesian discriminant flow unit intelligent classification technology were applied, from which three types of flow units in reservoir ZJ452 were recognized: Class I, Class II, and Class III. In addition, volume calculation was perform with flow unit discrimination formulas, a three-dimensional flow unit model was established, and the spatial distribution characteristics of flow units was analyzed. Results show that although the reservoir ZJ452 was strongly heterogeneity in space; Class I and Class II flow units were connected in a continuous distribution on the plane. This study pointed out the direction for tapping the potential of the highly heterogeneous reservoir ZJ452 in Huizhou A Oilfield.