Application of gas chimney-type gas cloud recognition method based on attribute optimization in the eastern Bohai Bay Basin
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摘要:
渤海地区气云表现形式多样，目前还没有系统的分类。根据不同气云带的分布范围，将渤海地区的气云从深至浅划分为气烟囱型、亮点型和麻坑型3类，并分析其成因机理。针对气烟囱型气云，利用单一地震属性进行气云识别和预测，具有一定局限性，且神经网络方法就是一个“黑匣子”，无法判断属性在计算过程中发挥的作用。文中提出利用具有 “多属性融合神经网络”技术体系，对不同的属性组合进行分类，突出对气云敏感的属性，从而对气云准确识别，精细刻画气云的空间分布范围。该方法在渤东地区蓬莱A油田取到较好的应用效果，为下一步寻找大中型油气藏提供了依据。
Abstract:Gas cloud in the eastern Bohai Bay Basin shows various forms and there is no systematic classification at present. According to the distribution of different gas clouds in vertical direction, gas cloud of Bohai Sea could be classified into three types from deep to shallow: gas chimney type, bright spot type, and flax pit type; and their formation mechanism were analyzed. For the gas chimney type, conventional methods use a single seismic attribute to identify and predict the gas cloud, which have certain limitations, and previous neural network method is a "black box", unable to judge the effect of attributes in the calculation process. We developed a "multi-attribute fusion neural network" technology system to classify different attribute combinations, highlight the sensitive attributes of gas cloud, to accurately identify the gas cloud and finely determine the spatial distribution range of gas cloud. This method has been successfully applied in Penglai A Oilfield in the eastern Bohai Bay Basin, which provides a basis for further exploration of large and medium-sized reservoirs.
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表 1 气云带成因、分类及特征
Table 1. Origin, classification and characteristics of gas clouds
气云类型 特征 成因 扩散机理 模式图 分布位置 气烟囱型 弱振幅，反射波杂乱，频率低、相干值低、速度低 断涌式 垂向断裂和侧向运移 
油气充注能力强的高凸起之上 亮点型 强振幅、低频阴影、偶极相位、极性反转 断渗式 断层相关，排放至浅层或地表 
凸起周边，断裂发育区尤为发育 麻坑型 强振幅、速度低 缝渗式 扩散或裂缝 
渤海海域广泛分布 
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