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针对湖相复杂致密岩性地震预测难点多的特点,提出一种在高分辨率层序约束下利用贝叶斯统计方法识别致密岩性的思路。应用地震时频旋回技术和Wheeler变换与反变换技术建立三维高分辨率层序格架,划分沉积体系域。运用中观尺度测井数据开展岩石物理交会分析,利用实验室X-射线衍射数据(XRD)和等效介质模型进一步从微观尺度分析,最终确定拟声波阻抗和纵、横波速度比是区分岩性的敏感参数。在此基础上,开展高分辨率层序约束下的波阻抗及纵、横波速度比反演,而后利用反演属性进行贝叶斯统计,在井上岩性识别精度高的前提下,利用得到的条件概率分布预测空间岩性最佳分布,最后对岩性分类结果进行对比分析。实际应用证明,在高分辨率层序约束反演的基础上利用贝叶斯统计识别复杂致密岩性具有较高的吻合率,该项技术适用于湖相复杂致密岩性识别。
Aiming at the characteristics of many difficult predictions of the complex and tight lithology of the lake facies, a new idea of using Bayesian statistical method to recognize the tight lithology under the constraint of high resolution sequence is proposed. The three-dimensional high-resolution sequence framework is established by using the seismic time-frequency cyclization technique and the Wheeler transform and inverse transform technique to divide the sedimentary system domain. The petrophysical intersection analysis is carried out by using mesoscale log data. Based on the X-ray diffraction (XRD) and equivalent medium model of the laboratory, further analysis is conducted from the microscopic scale to determine the quasi-acoustic impedance and longitudinal-shear-wave velocity ratio Sensitive parameters. On the basis of this, the wave impedance and velocity-to-shear-wave velocity inversion under the constraint of high-resolution sequence are carried out, and then the Bayesian statistics is derived by using the inversion properties. Under the premise of high lithology recognition accuracy, Conditional probability distribution predicts the best spatial distribution of lithology. Finally, the lithologic classification results are compared and analyzed. The practical application shows that Bayesian statistics are used to identify complex and tight lithologies based on high-resolution sequence-constrained inversion with high coincidence rate. This technique is suitable for the identification of complex and tight lithology in lacustrine facies.