公开(公告)号：US11946374B2

公开(公告)日：2024-04-02

申请号：US18347179

申请日：2023-07-05

申请人： Southwest Petroleum University

发明人： Yang Tang ,  Miantao Guan ,  Yulin Zhang ,  Peng Zhao ,  Guorong Wang ,  Jinhai Zhao ,  Qingyou Liu ,  Jinzhong Wang ,  Xiang Gao ,  Yufa He ,  Hu Deng ,  Liming Fan ,  Rutao Ma

IPC分类号： E21B7/06 ,  E21B23/00 ,  E21B23/04

CPC分类号： E21B7/061 ,  E21B23/006 ,  E21B23/0411

摘要： The disclosure relates to an omni-directional horizontally oriented deflecting tool for a coiled tubing, which includes an inner central pipe, an outer central pipe, a conical outer cylinder, a piston outer cylinder, an anchoring mechanism, a sealing mechanism, a reversing mechanism and a steering mechanism. The anchoring mechanism includes a cone, an O-shaped sealing ring I, a cone spring, a slip, a slip spring, a slip seat, a claw I and a pin shaft I, and the sealing mechanism includes a piston, an O-shaped sealing ring II, a claw II, a pin shaft II, an upper rubber cylinder seat, a rubber cylinder, a connecting cylinder, a lower rubber cylinder seat and a gasket.

公开(公告)号：US11649714B1

公开(公告)日：2023-05-16

申请号：US17714164

申请日：2022-04-06

申请人： Southwest Petroleum University

发明人： Yan Chen ,  Yuchuan An ,  Xiangchao Shi ,  Yu Yi ,  Yang Wang ,  Zhicheng Li ,  Gaocheng Feng ,  Yangbing Li ,  Ping Li ,  Yuan Zhong ,  Ming Xian ,  Hu Deng ,  Yuming Wang ,  Yuehao Liu

IPC分类号： E21B45/00 ,  G06F30/27

CPC分类号： E21B45/00 ,  G06F30/27

摘要： A method for predicting and optimizing an ROP for oil and gas drilling based on Bayesian optimization includes: acquiring raw drilling data according to a preset sampling period, constructing an initial sample data set based on the raw drilling data, constructing an ROP prediction model based on the initial sample data set, and predicting an ROP at a next sample point through a Gaussian process regression based on the ROP prediction model. The present invention realizes rapid analysis of historical drilling data and accurate prediction of an ROP range at a sample point in a feasible domain. The method can obtain an optimized ROP and an optimized engineering parameter through Bayesian optimization, and obtain an engineering parameter corresponding to an optimal ROP. The method has few restrictions on the drilling engineering parameter and the raw formation parameter, improves prediction accuracy, and avoids the problem of blurred parameter value boundaries.