摘要
本文从数据驱动的角度出发,建立一种Kmeans聚类算法和随机森林算法相结合的机械钻速预测模型,并以顺北区块奥陶系地层为例进行验证。结果表明:基于KMeans-RF算法的机械钻速预测模型预测结果与实钻结果预测精度较高,具有有效性和实用性。
From a data-driven perspective,this paper establishes a ROP prediction model combining K-Means clustering algorithm and RandomForest algorithm,and takes the Ordovician strata in the Shunbei block as an example to verify.The results show that the prediction results of the ROP prediction model based on the KMeans-RF algorithm and the actual drilling results have higher prediction accuracy and are effective and practical.
作者
陈宗琦
陈修平
李轲
王六鹏
ChenZongqi;Chen Xiuping;Li Ke;Wang Liupeng(Petroleum Engineering Technology Research Institute,Sinopec Northwest Oilfield Branch,Urumqi Xinjiang 830011;Key Laboratory of Enhanced Recovery for Fracture-Cave Oil Reservoir,Sinopec,Urumqi Xinjiang,830011;College of Petroleum Engineering,Xi’an ShiyouUniversity,Xi’an Shanxi 710065)
出处
《石化技术》
CAS
2022年第6期117-119,共3页
Petrochemical Industry Technology
