摘要:
地层参数的变化引起地震属性的变化,但是地层参数与地震属性的变化并没有一一对应的关系,这就带来了通过地震数据反演储层、岩性参数的多解性问题,因而采用多属性综合研究是重要的手段之一。南黄海盆地钻井较少,单井控制面积较大,利用地震属性信息研究了南黄海盆地二叠系沉积特征;并采用神经网络算法,提取了对岩性参数敏感的均方根振幅、反射强度、相对波阻抗、主频、平均瞬时频率5种地震属性;对南黄海盆地二叠系地层进行属性聚类分析,刻画出砂岩和灰岩2种岩相的分布特征,不仅避免了单一地震属性的多解性问题,同时突显了二叠系下统栖霞组灰岩之上的碎屑岩特征。结合井—震分析,确定南黄海盆地二叠系龙潭—大隆组沉积时期主要发育陆棚相、潮坪—潟湖—沼泽相及河流相。
Abstract:
The change in formation parameters causes the change in seismic attributes. But it is not a one-to-one relationship between the changes. Multi-solution problem comes from the reservoir parameters inversion of seismic data, and multi-attribute integration is one of the important means to solve the problem. In the South Yellow Sea Basin, drilling holes are rare and the single well control area is very large. Therefore, it becomes a necessity to make full use of seismic attributes information for facies analysis of the Permian Longtan and Dalong Formations. In this paper, the RMS amplitude, reflection intensity, relative acoustic impedance, dominant frequency, and average instantaneous frequency are all used to cluster analysis of Permian Formations by neural network algorithm. The results show the distribution pattern of sandstone and limestone lithofacies. The process not only avoids the multi-solution problem of a seismic attribute, but also reveals the characteristics of the clastic rock above the lower Permian Qixia limestone. Combined with well-seismic analysis, it is concluded that various facies, such as continental shelf facies, tidal flat-lagoon-swamp facies and fluvial facies are well developed during the Longtan-Dalong sedimentary period of Permian
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