井眼轨迹预测及井眼轨迹三维可视化研究

发布时间：2018-05-08 00:42

本文选题：井眼轨迹预测 + 支持向量机　；参考：《东北石油大学》2017年硕士论文

【摘要】：随着石油工业的飞速发展,石油钻探的力度不断增大,相关钻井技术也在不断地完善,类似于定向井、水平井这样的高难度井,在石油钻采中占据着越来越多的比例。由于钻井的井眼轨迹都存在于地下,只能通过随钻监测得到大量的井眼轨迹数据来对井眼轨迹进行监控,但是这些数据数据量大、不易于理解;且钻探取得的各种数据是由底部钻具组合(BHA)上的随钻监测传感器(MWD)得到的,它距离井底钻头一般还有8-20m的测量盲区距离,测点传回的数据并不能很好的反映钻头处的实际井眼情况;钻井现场的工作人员的更新换代速度也在加快,年轻化、工作经验少的人员大量加入到钻井施工的工作中,这些人不能很好的通过传统的井眼轨迹数据分析和二维的井眼轨迹描述来分辨井下井眼轨迹的情况,这些情况都为井眼轨迹控制带来了困难,为钻井的安全生产带来了隐患。结合现场的这些困难情况,本文在研究井眼轨迹几何分析的相关理论基础上,侧重于钻井现场施工方面,并结合计算机的相关方法,通过选取简便可行的测斜方法建立井眼轨迹的方位坐标;通过基于支持向量机的方法建立井眼轨迹的智能预测方法,通过现场随钻取得的数据验证这种预测方法的可行性与准确性,并利用粒子群算法对其进行优化;通过对计算机三维图形学和可视化的研究,建立井眼轨迹的三维可视化,以便于现场人员直观的观察、分析,以便于有效的对井眼轨迹进行控制。
[Abstract]:With the rapid development of petroleum industry, the intensity of oil drilling is increasing, and the related drilling technology is also improving. The high difficulty wells such as directional wells and horizontal wells occupy more and more proportion in oil drilling and production. Because the borehole trajectory of drilling exists underground, the borehole trajectory can only be monitored by monitoring while drilling, but these data are large and difficult to understand. All kinds of data obtained from drilling are obtained from MWD (a monitoring sensor while drilling) on the bottom drilling tool combination (BHA), which generally has a blind area of 8-20 m from the bottom hole bit. The data from the measured points do not well reflect the actual borehole situation in the drill bit; the replacement speed of the drilling site staff is also speeding up, and the younger and less experienced personnel are joining the drilling work in large numbers. These people can not distinguish the downhole trajectory through the traditional well trajectory data analysis and two-dimensional well trajectory description. These conditions bring difficulties to hole trajectory control and bring hidden trouble to the safe production of drilling. Combined with these difficulties, this paper focuses on drilling site construction based on the relevant theory of borehole trajectory geometric analysis, and combined with computer related methods. The azimuth coordinates of borehole trajectory are established by selecting a simple and feasible slant measuring method, and the intelligent prediction method of wellbore trajectory is established by using support vector machine (SVM). The feasibility and accuracy of the prediction method are verified by the data obtained while drilling, and the particle swarm optimization algorithm is used to optimize the prediction method, and through the research of computer 3D graphics and visualization, the 3D visualization of borehole trajectory is established. It is convenient for field personnel to observe and analyze directly, so as to control well trajectory effectively.
【学位授予单位】：东北石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TE24

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