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作 者:陈肖 缪云 李伟 王伟峰 廖梦娜 施浩 Chen Xiao;Miao Yun;Li Wei;Wang Weifeng;Liao Mengna;Shi Hao(Shenzhen Branch of CNOOC Co.,Ltd.,Shenzhen 518054,Guangdong,China)
机构地区:[1]中海石油(中国)有限公司深圳分公司,广东深圳518054
出 处:《科技通报》2023年第12期16-22,54,共8页Bulletin of Science and Technology
摘 要:海上水驱油田开发过程中,基于地质信息和动态资料建立的流线数值模拟过程复杂且存在较大不确定性,动态反演是矿场实践中快速获取注采连通性认识的一种重要方法。基于水电相似原理的阻容模型作为一种经典动态反演方法得到了广泛的应用。然而,研究表明该方法将复杂的注采动态转化为简单的信号处理过程中存在较大不确定性,导致注采连通性认识失真。为更准确地获取注采连通系数,本文提出基于卡尔曼滤波补偿的注采井间连通性反演方法:首先通过卡尔曼滤波算法过滤观测数据中的噪点,降低观测误差;然后通过连通性分段评价和添加补偿因子降低动态快速波动导致的计算误差,提高模型预测稳定性与准确性。应用机理模型证实该改进模型具有准确性,可作为动态反演获取连通性认识的有效方法。During the development of offshore water drive oilfield,streamline numerical simulation is complex and uncertain based on geological information and dynamic data.Dynamic inversion is an important method to quickly acquire the knowledge of injection production connectivity in field practice.As a classical dynamic inversion method,the resistance capacitance model based on the principle of hydroelectricity similarity has been widely used.However,the research shows that there is great uncertainty in the process of transforming complex injection production performance into simple signal processing,which leads to distortion in the recognition of injection production connectivity.In order to obtain the connectivity coefficient more accurately,a connectivity inversion method based on compensation of Kalman filter is proposed.Firstly,the Kalman filtering algorithm is used to filter the noise in the observation data to reduce the error.Then,the calculation error caused by rapid dynamic fluctuation,which is reduced through connectivity segmentation evaluation and adding compensation factors.The stability and accuracy of model prediction results are improved.The accuracy of the improved model is verifred by the mechanism model,which can be used as an effective method to obtain connectivity knowledge through dynamic inversion.
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