Submarine fan lithofacies identification with depositional model and seismic attributes
Wang Zhiguo1, Yin Cheng2, Tang Hebing3, Lei Xiaolan4
1. National Engineering Laboratory for Offshore Oil Exploration, Institute of Wave and Information, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China;
2. School of Geoscience and Technology, Southwest Petroleum University, Chengdu, Sichuan 610500, China;
3. Exploration and Development Institute of Bohai Oil Field, CNOOC Ltd, Tianjin Branch, Tianjin 300451, China;
4. The Second Gas Production Plant, Changqing Oilfield Company, PetroChina, Xi'an, Shaanxi 710200, China
Abstract：Submarine fan is an important lithologic reservoir. However, it is still a challenge to precisely estimate the lithofacies of submarine fan in exploration geophysics. Therefore, we propose significance indicators based on the depositional model to solve lack of well data in the exploration period. With submarine fan facies model analysis, sandstone and conglomerate contents are selected as significance indicators to quantify lithofacies of submarine fan in Dongying Formation, Liaodong Depression, China. These indicators have not only clear geological significance, but also response of seismic reflection. The fuzzy radial function neural network maps the relation between "sandstone and conglomerate contents" and "seismic attributes" to estimate lithofacies of submarine fan, which improve the precision of large-scale reservoir characterization in exploration period. Our objective is to find out quantitative indicators between fan depositional model and seismic data as a potential approach to estimate the submarine fan lithofacies.
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