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Improving reservoir thickness prediction using seismic attributes and attributes fusion
Authors:Haojie Liu  Xinhua Lei  Chuanlong Mao  Songnan Li
Affiliation:1. School of Information Engineering, China University of Geosciences, Beijing, China
2. Research Institute of Exploration and Development, DianQianGui Oil Company, Sinopec Group, Kunming, Yunnan, China
3. Research Institute of Exploration and Development, QingHai Oil Company, CNPC, Dunhuang, Gansu, China
Abstract:Usage of any single attribute would introduce unacceptable uncertainty due to limited reservoir thickness and distribution, and strong lateral variations in lithological traps. In this paper, a wide range of prestack and post-stack seismic attributes is utilized to identify a range of properties of turbidity channel sandstone reservoir in Block L118 of J Oilfield, China. In order to better characterize the turbidity channel and lower the uncertainty, we applied multi-attribute fusion to weight a variety of seismic attributes in terms of their relevance to the identification of turbidity channel reservoir. Turbidity channel boundary is clearly present in the new attribute and the reservoir thickness prediction is improved. Additionally, fluid potential of reservoir was predicted using this fused attribute with a high value anomaly indicating high fluid potential. The multi-attribute fusion is a valid approach for the fine prediction of lithologic reservoirs, reducing the risks typically associated with exploration.
Keywords:
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