地质力学特征评价新方法在导向钻井优化中的应用
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摘要
针对常规导向钻井技术在适用范围、预测能力与运行成本等方面的局限性,在考察岩石物理及力学参数和地球物理信息之间定量关系的基础上,将地震反演、地质统计、地震属性分析、岩石力学方法与钻井工程实际需求密切结合,提出地质力学特征评价新方法,基于其对导向钻井系统进行优化。新技术以常规地震和测井资料为基础,充分结合钻井、录井等实钻信息,钻前建立地质力学初始模型用于钻井设计,钻进过程中参考实钻资料随钻修正并更新钻前模型用于钻井工艺实时优化,其关键环节是准确预测钻头前方待钻地层的强度、地应力、孔隙压力、坍塌压力、破裂压力等力学参数。以井壁稳定预测及其工程运用为重点,论述导向钻井优化中岩石力学理论和地球物理算法结合运用的思路与技术流程,将该方法在西南、西北复杂探区进行应用。现场应用表明,优化的导向钻井系统可以达到理想的参数预测精度与工艺优化效果,指导安全、优质、快速、低成本钻井的能力得到了提高。
In consideration of the limitations of the conventional steerable drilling technology in terms of its application scope,forecasting ability and operation cost,a new evaluation method for geomechanical characterisation was proposed to optimize the steerable drilling system.The evaluation method is based on the quantitative relationships between the physical and mechanical parameters of rocks and the geophysical information,combining with seismic inversion,geological statistics,seismic attribute analysis,rock mechanics and the actual requirement of drilling engineering.The key of the optimized steerable drilling technology is to accurately predict the rock strength,in-situ stress,pore pressure,collapse pressure and fracture pressure of the formation based on conventional seismic and well logging data and by making full use of drilling and well log data obtained in real-time drilling process.Before drilling,an initial geomechanical model can be developed for drilling design,and during the drilling process,the initial model will be corrected and updated for real-time optimization of drilling technology measures.Emphasizing on the borehole stability prediction and its engineering application,this paper describes the ideas and operation process of the combination of rock mechanics theory and geophysical algorithm in the optimization of steerable drilling technology.It also presents the application of the optimized steerable drilling technology in complex exploration regions of southwestern and northwestern areas of China.The field application results show that the proposed technology can provide precise predictions of various drilling parameters and achieve effective optimization of the drilling process,and its capability for guiding safe,high quality,fast and low cost drilling has been improved.
In consideration of the limitations of the conventional steerable drilling technology in terms of its application scope,forecasting ability and operation cost,a new evaluation method for geomechanical characterisation was proposed to optimize the steerable drilling system.The evaluation method is based on the quantitative relationships between the physical and mechanical parameters of rocks and the geophysical information,combining with seismic inversion,geological statistics,seismic attribute analysis,rock mechanics and the actual requirement of drilling engineering.The key of the optimized steerable drilling technology is to accurately predict the rock strength,in-situ stress,pore pressure,collapse pressure and fracture pressure of the formation based on conventional seismic and well logging data and by making full use of drilling and well log data obtained in real-time drilling process.Before drilling,an initial geomechanical model can be developed for drilling design,and during the drilling process,the initial model will be corrected and updated for real-time optimization of drilling technology measures.Emphasizing on the borehole stability prediction and its engineering application,this paper describes the ideas and operation process of the combination of rock mechanics theory and geophysical algorithm in the optimization of steerable drilling technology.It also presents the application of the optimized steerable drilling technology in complex exploration regions of southwestern and northwestern areas of China.The field application results show that the proposed technology can provide precise predictions of various drilling parameters and achieve effective optimization of the drilling process,and its capability for guiding safe,high quality,fast and low cost drilling has been improved.
引文
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[10]ADLER F,BAINA R,SOUDANI M A,et al.Nonlinear3D tomographic least-squares inversion of residual moveout in Kirchhoff prestack-depth-migration commonimage gathers[J].Geophysics,2008,73(5):13-23.
[11]PEREZ D O,VELIS D R,SACCHI M D.High-resolution prestack seismic inversion using a hybrid FISTA least-squares strategy[J].Geophysics,2013,78(5):185-195.
[12]郭振波,田坤,李振春,等.利用非线性最优化方法构建近似常Q黏弹模型[J].中国石油大学学报(自然科学版),2014,38(2):52-58.GUO Zhenbo,TIAN Kun,LI Zhenchun,et al.Constructing nearly constant-Q viscoelastic model using the nonlinear optimization method[J].Journal of China University of Petroleum(Edition of Natural Science),2014,38(2):52-58.
[13]张文彪,段太忠,刘志强,等.深水浊积水道多点地质统计模拟:以安哥拉Plutonio油田为例[J].石油勘探与开发,2016,43(3):403-410.ZHANG Wenbiao,DUAN Taizhong,LIU Zhiqiang,et al.Application of multi-point geostatistics in deep-water turbidity channel simulation:a case study of Plutonio oilfield in Angola[J].Petroleum Exploration and Development,2016,43(3):403-410.
[14]张繁昌,肖张波,印兴耀.地震数据约束下的贝叶斯随机反演[J].石油地球物理勘探,2014,49(1):176-182.ZHANG Fanchang,XIAO Zhangbo,YIN Xingyao.Bayesian stochastic inversion constrained by seismic data[J].Oil Geophysical Prospecting,2014,49(1):176-182.
[15]吴胜和.储层表征与建模[M].北京:石油工业出版社,2010.
[16]刘钰铭,侯加根,胡向阳,等.塔河油田古岩溶储集体三维建模[J].中国石油大学学报(自然科学版),2012,36(2):34-38.LIU Yuming,HOU Jiagen,HU Xiangyang,et al.3D modeling paleokarst reservoir in Tahe Oilfield[J].Journal of China University of Petroleum(Edition of Natural Science),2012,36(2):34-38.
[17]张阳,邱隆伟,李际,等.基于模糊C均值地震属性聚类的沉积相分析[J].中国石油大学学报(自然科学版),2015,39(4):53-61.ZHANG Yang,QIU Longwei,LI Ji,et al.Sedimentary facies analysis based on cluster of seismic attributes by fuzzy C-means algorithm[J].Journal of China University of Petroleum(Edition of Natural Science),2015,39(4):53-61.
[18]肖佃师,卢双舫,王海生,等.三角洲外前缘薄砂体地震综合预测方法[J].中国石油大学学报(自然科学版),2015,39(4):62-69.XIAO Dianshi,LU Shuangfang,WANG Haisheng,et al.Comprehensive prediction method of seismic to thin sandstone reservoir in delta-frontal[J].Journal of China University of Petroleum(Edition of Natural Science),2015,39(4):62-69.
[19]NEVES F A,ZAHRNI M S,BREMKAMP S W.Detection of potential fractures and small faults using seismic attributes[J].The Leading Edge,2004,23(9):903-906.
[20]TALKHESTANI A A.Prediction of effective porosity from seismic attributes using locally linear model tree algorithm[J].Geophysical Prospecting,2015,63(3):680-693.
[21]吴超,陈勉,金衍.基于地震属性技术的井壁稳定随钻预测新方法[J].中国石油大学学报(自然科学版),2007,31(6):141-146.WU Chao,CHEN Mian,JIN Yan.A new method of predicting borehole stability while drilling based on seismic attribute technology[J].Journal of China University of Petroleum(Edition of Natural Science),2007,31(6):141-146.
[22]彭琦,张茹,谢和平,等.基于AE时间序列的岩爆预测模型[J].岩土力学,2009,30(5):1436-1440.PENG Qi,ZHANG Ru,XIE Heping,et al.Prediction model for rockburst based on acoustic emission time series[J].Rock and Soil Mechanics,2009,30(5):1436-1440.
[2]姜伟,蒋世全,付鑫生,等.旋转导向钻井技术应用研究及其进展[J].天然气工业,2013,33(4):75-79.JIANG Wei,JIANG Shiquan,FU Xinsheng,et al.Application of rotary steering drilling technology and its research progress[J].Natural Gas Industry,2013,33(4):75-79.
[3]黄伟传,葛洪魁,吴何珍,等.地震干涉处理方法在随钻地震资料处理中的应用[J].石油地球物理勘探,2012,47(1):32-36.HUANG Weichuan,GE Hongkui,WU Hezhen,et al.The application of seismic interferometry in SWD data processing[J].Oil Geophysical Prospecting,2012,47(1):32-36.
[4]吴超,刘建华,张东清,等.基于地震波阻抗的预探井随钻井壁稳定预测[J].石油勘探与开发,2015,42(3):390-395.WU Chao,LIU Jianhua,ZHANG Dongqing,et al.A prediction of borehole stability while drilling preliminary prospecting wells based on seismic impedance[J].Petroleum Exploration and Development,2015,42(3):390-395.
[5]WU C,CHEN M,JIN Y.A prediction method of borehole stability based on seismic attribute technology[J].Journal of Petroleum Science and Engineering,2009,65(3/4):208-216.
[6]吴超,刘建华,张东清,等.基于地震属性技术的井壁稳定随钻预测新方法[J].岩土工程学报,2015,37(10):1810-1817.WU Chao,LIU Jianhua,ZHANG Dongqing,et al.Predicting borehole stability while drilling based on nonlinear inversion[J].Chinese Journal of Geotechnical Engineering,2015,37(10):1810-1817.
[7]吴超,臧艳彬,张东清,等.定向井随钻井壁稳定预测方法及其应用[J].石油学报,2015,36(10):1290-1298.WU Chao,ZANG Yanbin,ZHANG Dongqing,et al.A method of borehole stability prediction while drilling directional wells and its application[J].Acta Petrolei Sinica,2015,36(10):1290-1298.
[8]陈勉,金衍,张广清.石油工程岩石力学[M].北京:科学出版社,2008.
[9]魏凯,管志川,廖华林,等.井壁失稳风险评价方法[J].中国石油大学学报(自然科学版),2013,37(2):62-66.WEI Kai,GUAN Zhichuan,LIAO Hualin,et al.Assessment method of borehole instability risk[J].Journal of China University of Petroleum(Edition of Natural Science),2013,37(2):62-66.
[10]ADLER F,BAINA R,SOUDANI M A,et al.Nonlinear3D tomographic least-squares inversion of residual moveout in Kirchhoff prestack-depth-migration commonimage gathers[J].Geophysics,2008,73(5):13-23.
[11]PEREZ D O,VELIS D R,SACCHI M D.High-resolution prestack seismic inversion using a hybrid FISTA least-squares strategy[J].Geophysics,2013,78(5):185-195.
[12]郭振波,田坤,李振春,等.利用非线性最优化方法构建近似常Q黏弹模型[J].中国石油大学学报(自然科学版),2014,38(2):52-58.GUO Zhenbo,TIAN Kun,LI Zhenchun,et al.Constructing nearly constant-Q viscoelastic model using the nonlinear optimization method[J].Journal of China University of Petroleum(Edition of Natural Science),2014,38(2):52-58.
[13]张文彪,段太忠,刘志强,等.深水浊积水道多点地质统计模拟:以安哥拉Plutonio油田为例[J].石油勘探与开发,2016,43(3):403-410.ZHANG Wenbiao,DUAN Taizhong,LIU Zhiqiang,et al.Application of multi-point geostatistics in deep-water turbidity channel simulation:a case study of Plutonio oilfield in Angola[J].Petroleum Exploration and Development,2016,43(3):403-410.
[14]张繁昌,肖张波,印兴耀.地震数据约束下的贝叶斯随机反演[J].石油地球物理勘探,2014,49(1):176-182.ZHANG Fanchang,XIAO Zhangbo,YIN Xingyao.Bayesian stochastic inversion constrained by seismic data[J].Oil Geophysical Prospecting,2014,49(1):176-182.
[15]吴胜和.储层表征与建模[M].北京:石油工业出版社,2010.
[16]刘钰铭,侯加根,胡向阳,等.塔河油田古岩溶储集体三维建模[J].中国石油大学学报(自然科学版),2012,36(2):34-38.LIU Yuming,HOU Jiagen,HU Xiangyang,et al.3D modeling paleokarst reservoir in Tahe Oilfield[J].Journal of China University of Petroleum(Edition of Natural Science),2012,36(2):34-38.
[17]张阳,邱隆伟,李际,等.基于模糊C均值地震属性聚类的沉积相分析[J].中国石油大学学报(自然科学版),2015,39(4):53-61.ZHANG Yang,QIU Longwei,LI Ji,et al.Sedimentary facies analysis based on cluster of seismic attributes by fuzzy C-means algorithm[J].Journal of China University of Petroleum(Edition of Natural Science),2015,39(4):53-61.
[18]肖佃师,卢双舫,王海生,等.三角洲外前缘薄砂体地震综合预测方法[J].中国石油大学学报(自然科学版),2015,39(4):62-69.XIAO Dianshi,LU Shuangfang,WANG Haisheng,et al.Comprehensive prediction method of seismic to thin sandstone reservoir in delta-frontal[J].Journal of China University of Petroleum(Edition of Natural Science),2015,39(4):62-69.
[19]NEVES F A,ZAHRNI M S,BREMKAMP S W.Detection of potential fractures and small faults using seismic attributes[J].The Leading Edge,2004,23(9):903-906.
[20]TALKHESTANI A A.Prediction of effective porosity from seismic attributes using locally linear model tree algorithm[J].Geophysical Prospecting,2015,63(3):680-693.
[21]吴超,陈勉,金衍.基于地震属性技术的井壁稳定随钻预测新方法[J].中国石油大学学报(自然科学版),2007,31(6):141-146.WU Chao,CHEN Mian,JIN Yan.A new method of predicting borehole stability while drilling based on seismic attribute technology[J].Journal of China University of Petroleum(Edition of Natural Science),2007,31(6):141-146.
[22]彭琦,张茹,谢和平,等.基于AE时间序列的岩爆预测模型[J].岩土力学,2009,30(5):1436-1440.PENG Qi,ZHANG Ru,XIE Heping,et al.Prediction model for rockburst based on acoustic emission time series[J].Rock and Soil Mechanics,2009,30(5):1436-1440.
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