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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. [ABSTRACT FROM AUTHOR]

Based on the analysis of mercury injection capillary pressure (MICP) and nuclear magnetic resonance (NMR) experimental data for core plugs, which were drilled from two Chinese tight sandstone reservoirs, permeability prediction models, such as the classical SDR, Timur-Coates, the Swanson parameter, the Capillary Parachor, the R10 and R35 models, are calibrated to estimating permeabilities from field NMR logs, and the applicabilities of these permeability prediction models are compared. The processing results of several field examples show that the SDR model is unavailable in tight sandstone reservoirs. The Timur-Coates model is effective once the optimal T2cutoff can be acquired to accurately calculate FFI and BVI from field NMR logs. The Swanson parameter model and the Capillary Parachor model are not always available in tight sandstone reservoirs. The R35 based model cannot effectively work in tight sandstone reservoirs, while the R10 based model is optimal in permeability prediction. [ABSTRACT FROM AUTHOR]