论文详情
随着油气勘探目标的日趋复杂，对裂缝预测的精度要求不断提高，裂缝预测的重要性越发突出。在分析曲率、相干、各向异性等常用裂缝预测技术的原理与适用性的基础上，提出了通过解释性处理提高裂缝预测精度的两类方法:一是对输入数据进行突出裂缝特征的预处理，如各种滤波、限偏移距叠加、各向异性背景校正等，以提高输入数据与预测方法的匹配度，从而提高裂缝预测的信噪比与可靠性。二是对输出结果进行图像处理、蚂蚁追踪、数据融合等强化处理，提取并突显反映裂缝的弱信号，从而提高裂缝预测的分辨率。将构造导向滤波、限偏移距叠加、各向异性背景校正、线形增强以及线形增强+蚂蚁追踪等解释性处理技术应用于塔里木盆地不同工区的地震资料处理，结果表明，在常规裂缝预测方法的基础上，根据目标体的地质特征优选解释性处理技术进行预处理或级联处理，能够有效提高裂缝预测精度。
As the exploration targets becoming more and more complicated,the fracture prediction is more and more important,and the demand for improving the fracture prediction accuracy is becoming urgent.Based on the analysis on the principles and applicability of the most commonly used fracture prediction attributes,such as curvature,coherence and anisotropy,we propose two methods for improving fracture prediction accuracy by interpretative processing.The first type of methods is conducting special preprocessing on input data before calculating fracture attributes.All the methods beneficial for highlighting the characteristics of fractures can be used in this procedure,such as filtering,limited-offset stacking and overburden anisotropy correction.They are helpful to make the input data match better with fracture prediction algorithms,and will finally increase the signal-to-noise-ratio and reliability of the prediction results.The second type of methods is enhancing the output results by applying techniques such as image processing,ant tracking and data fusion.They are beneficial to obtain and enhance weak signals resulted from fractures,and therefore can improve the signal-to-noise-ratio and resolution of the fracture prediction maps.The application results in Tarim Basin including structure-guided filtering,limited-offset stacking,overburden anisotropy correction,linear enhancement,and linear enhancement plus ant tracking are presented,which demonstrate that the fracture prediction accuracy can be improved effectively by employing proper interpretative processing before or after traditional fracture prediction according to the specific geological features.
国家油气重大专项“海相碳酸盐岩储层地震描述与油气藏有效预测技术研究”(2011ZX05004003)项目资助。