【摘要】 裂缝带的预测与刻画对裂缝型油气藏的勘探开发具有重要意义。为了减少单属性预测结果的多解性,通常采用多种地震属性综合预测。裂缝发育程度与地震属性之间主要为非线性关系,为此,首先应用随机森林算法对地震属性特征与裂缝发育程度之间的对应关系进行学习,然后根据学习结果综合判别研究区裂缝发育程度,以提高裂缝带预测精度与准确率。实例表明,随机森林算法对裂缝带预测结果准确度较高,同时该方法也具有较强的普适性。更多还原

【Abstract】 Fracture zone prediction and characterization are of great significance for the exploration and development of fractured oil and gas reservoirs.In order to solve the multi-solution problem of the prediction methods using single attribute,multiple seismic attributes were used comprehensively.The relationships between fracture development degree and seismic attributes are often non-linear.Therefore,random forest algorithm was used to learn the correspondence between seismic attribute characteristics and fracture development degree,and then the fracture development degree in the study area was determined comprehensively according to the learning results,aiming to improve the prediction precision of fracture zone.The application in real data demonstrated that random forest algorithm achieved fracture zone prediction results with high accuracy,and the method is universal generally.更多还原