克拉玛依油田八区克上组砾岩油藏参数及剩余油分布

Conglomerate Reservoir Parameters and Remaining Oil Distri-bution of Block Ⅷ Keshang Group in Kelamayi Oilfield

利用灰色系统与神经网络技术分析软件系统,通过克拉玛依油田八区克上组砾岩油藏储层实际应用,处理区内克上组砾岩油藏相应井段117口井测井地质资料,分别利用砾岩油藏测井解释、沉积微相分布研究成果,提取、集总和描述了各层段砾岩油藏储层参数分布,阐明了克上组各小层砾岩油藏的分布富集范围。从而,分析砾岩油藏开发动态资料,研究了该区克上组砾岩油藏储量及采出情况,指出了剩余油分布富集层位、井区和位置,为合理选择区块开发决策和改善油田开发效果提供了相应的地质依据。

Cray system and neural network technique analysis software is introduced in reservoir layers of block Ⅷ Keshang group, Conglomerate reservoir of Kelamayi oilfield. The software has been used to process 117 wells reservoir formation logging and geological data. The reservoir formation parameters are extracted, assembled and described by applying conglomerate reservoir log interpretation and sedimentary microfacies distribution research achievement, through which the enriched distribution of layers of Keshang group are determined. Accordingly, the development performance is analyzed. The reserve volume and the development status is gained. These provide geological basis for development decision-making of block and improving reservoir development effect.