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川东北地区恶性井漏层段地震预测技术探索
引用本文:黄花香,熊艳,邓瑛,李志荣,覃发兰,成竹. 川东北地区恶性井漏层段地震预测技术探索[J]. 石油物探, 2005, 45(2): 142-146
作者姓名:黄花香  熊艳  邓瑛  李志荣  覃发兰  成竹
作者单位:四川石油管理局地调处成都物探研究中心,四川,成都,610212
摘    要:针对川东北地区嘉陵江组层段存在的恶性井漏现象,选取了LJZ,DKH和QLX等构造上在钻井过程中漏失严重的井,分析研究了恶性漏失层段的地质特征、测井及地震响应特征。通过多种特殊处理方法效果的分析,总结了一套较为有效的恶性井漏地震预测技术,如相干体分析、频谱分析等。利用这些技术对LJ11H井和LJ16H井是否存在严重漏失层进行了钻前预测,预测结果与钻井显示吻合得很好。

关 键 词:川东北地区 预测技术 恶性 层段 井漏 地震响应特征 嘉陵江组 钻井过程 地质特征 处理方法 频谱分析 钻前预测 预测结果 相干体 漏失层
文章编号:1000-1441(2005)02-0142-05
收稿时间:2004-03-08
修稿时间:2004-06-08

Preliminary study on seismic prediction for severe leakage horizons in the Northeast Sichuan
Huang Huaxiang,Xiong Yan,Deng Ying,Li Zhirong,Qin Falan,Cheng Zhu. Preliminary study on seismic prediction for severe leakage horizons in the Northeast Sichuan[J]. Geophysical Prospecting For Petroleum, 2005, 45(2): 142-146
Authors:Huang Huaxiang  Xiong Yan  Deng Ying  Li Zhirong  Qin Falan  Cheng Zhu
Affiliation:Huang Huaxiang,Center of Geophysical Research,Geological Survey Office in Sichuan Oil Administrative Bureau,Chengdu 610212,ChinaXiong Yan,Deng Ying,Li Zhirong,Qin Falan and Cheng Zhu.
Abstract:The slop leakages of the drilling wells are very serious. in the northeast Sichuan, and impacted the oil and gas exploration effects in this region to analyze and research the geologic properties, logging and seismic response properties in Jialingjiang severe leakage horizons are studied the leakage wells on LJZ, DKH and QLX structures. By the effect analysis of various special processing methods, a set of seismic prediction techniques of malignant leakage such as coherent analysis and frequency spectrum analysis are summarized. Applied this technique to make pre-drilling prediction to determine if there are serious leakage horizons in well LJ11H and LJ16H,the prediction results are very consistent with the drilling results. This research achievement can effectively guide the drilling design keep away from malignant leakage horizons, reduce drilling loss.
Keywords:severe well leakage  seismic prediction  logging feature  seismic response feature  pre-drilling prediction
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