Petroleum Science >2020,??Issue 2:??1-17 DOI: https://doi.org/10.1007/s12182-019-00415-y
3D modeling of deepwater turbidite lobes: a review of the research status and progress Open?Access
文章信息
作者：Lei-Fu Zhang, Mao Pan, Zhao-Liang Li
作者單位：
Fault Analysis Group, School of Geological Sciences, University College Dublin, Dublin, Ireland; PetroChina Research Institute of Petroleum Exploration and Development, Beijing, China; National Energy Shale Gas Research (Experiment) Center, Beijing, China; CNPC Key Laboratory of Unconventional Oil and Gas, Beijing, China; School of Earth and Space Science, Peking University, Beijing, China; China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, China;
投稿時(shí)間：2018-11-16
引用方式：Zhang, L., Pan, M. & Li, Z. 3D modeling of deepwater turbidite lobes: a review of the research status and progress. Pet. Sci. (2020). https://doi.org/10.1007/s12182-019-00415-y
文章摘要
Deepwater turbidite lobe reservoirs have massive hydrocarbon potential and represent one of the most promising exploration targets for hydrocarbon industry. Key elements of turbidite lobes internal heterogeneity include the architectural hierarchy and complex amalgamations at each hierarchical level leading to the complex distribution of shale drapes. Due to limitation of data, to build models realistically honoring the reservoir architecture provides an effective way to reduce risk and improve hydrocarbon recovery. A variety of modeling techniques on turbidite lobes exist and can be broadly grouped into pixel-based, process-based, process-oriented, surface-based, object-based and a hybrid approach of two or more of these methods. The rationale and working process of methods is reviewed, along with their pros and cons. In terms of geological realism, object-based models can capture the most realistic architectures, including the multiple hierarchy and the amalgamations at different hierarchical levels. In terms of data conditioning, pixel-based and multiple-point statistics methods could honor the input data to the best degree. In practical, different methods should be adopted depending on the goal of the project. Such a review could improve the understanding of existing modeling methods on turbidite lobes and could benefit the hydrocarbon exploration activities of such reservoirs in offshore China.
關(guān)鍵詞
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Turbidite lobes, Architectural hierarchy, Architecture element, Stochastic modeling, Sand amalgamation