【摘要】 利用地震属性进行储层物性参数(孔隙度)的预测研究,其精度和准确性一直是油气田勘探开发期间所关注的问题,而属性优化方法是其中的关键环节。本文从优化方法入手,将灰关联、遗传算法和BP网络有机结合,以提高储层物性参数(孔隙度)的预测能力。首先依据反演成果开展精细储层解释,并进行沿层相关属性提取和灰关联分析,寻找较敏感的属性;然后利用遗传算法和BP网络进行属性组合优化,获取最优属性组合,最终达到预测储层物性参数(孔隙度)的目的。应用实例表明,此法的储层预测精度较高。更多还原

【Abstract】 When applying seismic attributes in prediction studies of reservoir physical property (porosity),its precision and accuracy are always the main concern in the oil-field exploration and development,and the attribute optimization method is the focal point.Based on optimization method the rational integration of grey relational analysis,genetic algorithm and BP network could raise the prediction ability of reservoir physical property (porosity).The work can be done as below,at first using inversion results to conduct detailed reservoir interpretation,extracting related attributes along the layers and conducting grey relational analysis and looking for sensitive attributes,then utilizing genetic algorithm and BP network to optimize the attribute combination,and obtaining optimum attribute combination,at last the prediction of reservoir physical property (porosity) was realized.The application results show that the method is a precise in reservoir prediction.更多还原