Comprehensive recognition and distribution prediction of semi-deep and deep lacustrine source rock of the Lower Paleocene Yueguifeng Formation in Jiaojiang Sag
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摘要:
椒江凹陷是东海盆地已证实生烃但未获商业发现的低勘探程度区，落实其主力烃源岩层月桂峰组半深湖—深湖相烃源岩发育情况及规模是下步油气勘探亟待解决的首要问题。基于新采集的三维地震、钻井、古生物及有机地球化学数据，综合断陷作用、古地貌背景、物源区母岩岩性、有机质丰度和类型等四方面开展椒江东洼月桂峰组湖相优质烃源岩精细识别，并通过地震相类比分析，定量预测其平面分布及规模。结果表明：强烈断陷作用、适度遮挡的古地貌背景、洼陷周缘火成岩母岩区共同控制了椒江东洼月桂峰组半深湖—深湖相烃源岩的发育；其整体为好—优质烃源岩，以Ⅱ1-Ⅱ2型干酪根为主，有机质来源以低等水生生物为主且有陆生高等植物的贡献。受凹陷结构控制，椒江东洼月桂峰组半深湖—深湖相烃源岩主要发育在洼陷中心及陡坡带一侧。典型地震相表现为低频连续强振幅平行反射，基于多属性神经网络深度学习技术，预测椒江东洼月桂峰组半深湖—深湖相烃源岩最大面积为294 km2、总体积为109 km3。综合认为，椒江东洼具有良好的油气资源潜力与勘探前景。
Abstract:The Jiaojiang Sag is a low-level exploration area in the East China Sea Basin where hydrocarbon generation has been confirmed but no commercial discoveries yet have been made. Implementation of the development and scale of semi-deep lake-deep lake facies source rocks in the Yueguifeng Formation, the main source rock, is an urgent issue in the next step of oil and gas exploration. Based on the newly acquired 3D seismic, drilling, paleontological and organic geochemical data, the lake facies of the Yueguifeng Formation in the Jiaojiang Dong Subsag was developed in four aspects of rifting, paleogeomorphic background, source area parental rock lithology, and organic matter abundance and type. High-quality source rocks are precisely identified, and their planar distribution and scale are quantitatively predicted through seismic facies analogy analysis. Results show that the development of semi-deep lake to deep lake source rocks in the Yueguifeng Formation in Jiaojiang Dong Subsag is jointly controlled by strong faulting, moderately hilly palaeogeomorphic setting, and the igneous provenance area. As a whole, it is a good to excellent quality source rock, mainly composed of type Ⅱ1-Ⅱ2 kerogen. The organic matter is mainly composed of lower aquatic organisms with partly contributions from higher terrestrial plants, and the typical seismic facies shows low frequency continuous strong amplitude parallel reflection. Controlled by the sag structure, the semi-deep lake to deep lake source rocks of the Yueguifeng Formation in Jiaojiang Dong Subsag are mainly developed in the central area and on one side of the steep slope belt of Jiaojiang Dong Subsag. The typical seismic phase is characterized by low-frequency continuous strong amplitude parallel reflection. Using multi-attribute neural network deep-learning technology, we predicted that the maximum area and total volume of the semi-deep lake to deep lake source rock of the Yueguifeng Formation in the subsag are 294 km2 and 109 km3, respectively. Overall, we believed that Jiaojiang Dong Subsag has good potential for oil and gas resources and exploration prospect.
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图 2 丽水-椒江凹陷地层综合柱状图
Figure 2. Comprehensive stratigraphic column of the Lishui-Jiaojiang Sag
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图 3 椒江东洼洼陷结构特征
AAʹ、BBʹ剖面位置见图1。
Figure 3. Structural characteristics of Jiaojiang Dong Subsag
See Fig.1 for the location of AA' and BB' profiles.
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图 4 椒江东洼W4井月桂峰组古生物、沉积相及过井地震相特征
W4井位置见图1。
Figure 4. Characteristics of paleontology, sedimentary facies, and seismic facies in the Yueguifeng Formation of Well W4 in Jiaojiang Dong Subsag
See Fig.1 for the location of Well W4.
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图 5 椒江东洼W4井月桂峰组烃源岩有机质丰度（a）和类型判别图（b）
Figure 5. Organic matter abundance (a) and type (b) of the source rock in Yueguifeng Formation, Well W4 in Jiaojiang Dong Subsag
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图 6 椒江东洼W4井月桂峰组烃源岩质谱图和4-甲基甾烷/C29与TOC相关性图
Figure 6. Mass spectrum of source rock in Yueguifeng Formation of Well W4 in Jiaojiang Dong Subsag and correlation between 4-methylsterane/C29 and TOC
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图 7 椒东断裂月桂峰组沉积期断层活动速率（a）与W4井Pr/Ph值统计（b）
Figure 7. Fault activity rate of the Jiaodong Fault during the deposition period of Yueguifeng Formation (a), and Pr/Ph value statistics of Well W4 (b)
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图 8 椒江东洼月桂峰组典型地震相-沉积相组合
Figure 8. Typical combination of seismic facies and sedimentary facies of Yueguifeng Formation in Jiaojiang Dong Subsag
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图 9 基于神经网络深度学习的椒江东洼月桂峰组半深湖—深湖相自动识别
Figure 9. Automatic recognition of semi-deep and deep lake facies in the Yueguifeng Formation of Jiaojiang Dong Subsag by neural network deep learning
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