Application of Time⁃Frequency Difference Attribute Analysis of Bright Spot Type Gas Reservoir in Deep⁃Water Qiongdongnan Basin
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摘要: 受深水区探井少、不同流体AVO类型相近影响，利用常规P（拟合截距）、G（拟合梯度）、P×G、P+G等衍生烃类检测属性已不能有效识别深水区储层的流体性质，亟需寻找适合该区有效储层的烃类检测方法. 实际上，地震波在地下地层传播过程中会产生明显的吸收衰减现象，通过含气砂岩会产生低频增加现象，因此联合谱分解和AVO技术是解决深水烃类检测的有效途径. 利用时频属性的峰值振幅和平均振幅，提出了能更好地描述流体性质变化的差异属性，可以增强深水区含气性识别的敏感度，在深水浊积岩储层烃类检测中取得良好的应用效果，有效降低深水区烃类检测的多解性.Abstract: Due to the small number of exploration Wells in the deep⁃water area and the similar number of AVO types of different fluids, the derived hydrocarbon detection properties such as conventional P (fitting intercept), G (fitting gradient), P×G and P+G have been unable to effectively identify the fluid properties of the deep water area, so it is urgent to find a hydrocarbon detection method suitable for the effective reservoirs in this area. In fact, seismic waves will produce obvious absorption and attenuation phenomenon in the propagation process of underground strata, especially through the gas⁃bearing sandstone will produce low⁃frequency increase phenomenon, so the combined spectral decomposition and AVO technology is an effective way to solve the deep⁃water hydrocarbon detection. By using the peak amplitude and average amplitude, can better describe the difference of fluid properties change, can enhance the sensitivity of the deep⁃water gas identification, in deep⁃water turbidity reservoir hydrocarbon detection good application results, progress to improve the reliability of deep⁃water reservoir hydrocarbon detection, effectively reduce the solution of deep⁃water hydrocarbon detection.
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图 2 过研究区中央峡谷水道地震剖面
Fig. 2. Seismic profile of the central canyon waterway in the deep⁃water area
图 3 LS⁃X⁃1井不同气组AVO正演分析
Fig. 3. AVO forward analysis of different gas groups in the LS⁃X⁃1 well
图 5 多分量信号不同Wigner⁃Ville分布时频分析方法
a. Wigner⁃Ville分布；b.伪Wigner⁃Ville分布；c.平滑伪Wigner⁃Ville分布；d.匹配追踪Wigner⁃Ville分布
Fig. 5. Time⁃frequency analysis method of different Wigner⁃Ville distribution of multi⁃component signals
图 7 两个不同采样点的频谱示意图
Fig. 7. Schematic representation of the spectrum of the two different sampling points
图 8 中远道时频差异属性剖面
Fig. 8. The time⁃frequency difference attributes profile from far⁃gather stack
图 10 过LS⁃Y⁃1目标地震剖面及单点AVO特征
Fig. 10. Seismic profile and single⁃point AVO characteristics of crossing LS⁃Y⁃1
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