含可信度地层破裂压力的钻前预测方法
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摘要
地层破裂压力是钻井工程设计的基础数据,由于海上深井苛刻地层环境的复杂性、基础资料的不完备性以及预测模型的适用性等问题,地层破裂压力的解释结果存在一定的不确定性。文中首先分析了地层破裂压力预测模型中地质力学参数的测井解释方法,然后以相似构造井同一层组内的地质力学参数的测井解释结果为样本,构建样本库,并基于正态信息扩散原理,得到了地质力学参数的概率分布函数,再将地质力学参数的概率分布函数代入地层破裂压力计算模型中,基于Monte Carlo模拟得到待钻井任意井深处的地层破裂压力概率分布,最终建立了具有置信度的地层破裂压力区间。实例分析表明,计算得到的含可信度地层破裂压力更切合钻井工程实际,文中建立的方法对于分析海上深井苛刻地层破裂压力的不确定性具有一定参考价值。
The formation fracture pressure is the basic data of drilling engineering design.Due to the complexity of offshore petroleum geology,incomplete data,the adaptability of the mathematical model and other issues,the true value of formation fracture pressure cannot be obtained.There are some uncertainties in the interpretation of results.In this paper,we firstly analyzed the logging interpretation methods of the calculation parameters in the prediction model of formation fracture pressure.And the sample library was constructed by using the logging interpretation results of the calculated parameters in the same layer of the adjacent wells in the area.Then probability distribution of parameters was built based on the method of normal information diffusion.Finally parameters with probability distribution were inducted into the model and the probability distribution and cumulative probability distribution of formation fracture pressure were built up using the Monte Carlo simulation.An example analysis shows that the results of the formation fracture pressure with credibility are more practical.This method has certain references to the analysis of the uncertainty of formation fracture pressure in complex deep offshore well formation.
The formation fracture pressure is the basic data of drilling engineering design.Due to the complexity of offshore petroleum geology,incomplete data,the adaptability of the mathematical model and other issues,the true value of formation fracture pressure cannot be obtained.There are some uncertainties in the interpretation of results.In this paper,we firstly analyzed the logging interpretation methods of the calculation parameters in the prediction model of formation fracture pressure.And the sample library was constructed by using the logging interpretation results of the calculated parameters in the same layer of the adjacent wells in the area.Then probability distribution of parameters was built based on the method of normal information diffusion.Finally parameters with probability distribution were inducted into the model and the probability distribution and cumulative probability distribution of formation fracture pressure were built up using the Monte Carlo simulation.An example analysis shows that the results of the formation fracture pressure with credibility are more practical.This method has certain references to the analysis of the uncertainty of formation fracture pressure in complex deep offshore well formation.
引文
[1]李敏,练章华,陈世春,等.岩石力学参数试验与地层破裂压力预测研究[J].石油钻采工艺,2009,31(5):15-18.
[2]葛洪魁,林英松,马善洲,等.修正Holbrook地层破裂压力预测模型[J].石油钻探技术,2001,29(3):20-22.
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[4]夏宏泉,梁常宝.基于灰色神经网络的测井预测地层破裂压力[J].西南石油学院学报(自然科学版),1996,18(4):1-8.
[5]柯珂,王志远,周宇阳,等.高陡构造易漏地层钻前裂缝定量描述方法[J].断块油气田,2015,22(2):263-266.
[6]金衍,陈勉,杨小奇.利用层速度钻前预测安全泥浆密度窗口研究[J].岩石力学与工程学报,2004,23(14):2430-2433.
[7]胡国忠,王宏图,贾剑青,等.岩石的动静弹性模量的关系[J].重庆大学学报(自然科学版),2005,28(3):102-105.
[8]ANDERSON R A.Determining fracture pressure gradients from well logs[J].Journal of Petroleum Technology,1973,5(11):1259-1267.
[9]邓金根,刘杨,蔚宝华,等.高温高压地层破裂压力预测方法[J].石油钻探技术,2009,37(5):43-46.
[10]樊洪海.地层孔隙压力预测检测新方法与应用[D].北京:中国石油大学(北京),2001.
[11]CATYNEANU O.层序地层学原理[M].吴因业,译.北京:石油工业出版社,2009:63-65.
[12]SANSTROM W C,HAWKINS M J.Perceiving drilling learning through visualization[R].SPE 62759,2000.
[13]李黎,王永刚.地质统计学应用综述[J].勘探地球物理进展,2006,29(3):163-169.
[14]宫凤强,侯尚骞,岩小明.基于正态信息扩散原理的Mohr-Coulomb强度准则参数概率模型推断方法[J].岩石力学与工程学报,2013,32(11):2225-2234.
[15]茆诗松,程依明,濮晓龙.概率论与数理统计教程[M].北京:高等教育出版社,2004:45-48.
[16]胜亚楠,管志川,张国辉,等.基于钻前风险预测的井身结构优化方法[J].石油钻采工艺,2016,38(4):415-421.
[2]葛洪魁,林英松,马善洲,等.修正Holbrook地层破裂压力预测模型[J].石油钻探技术,2001,29(3):20-22.
[3]SANTOS H.Consequences and relevance of drillstring vibration on wellbore stability[R].SPE 52820,2001.
[4]夏宏泉,梁常宝.基于灰色神经网络的测井预测地层破裂压力[J].西南石油学院学报(自然科学版),1996,18(4):1-8.
[5]柯珂,王志远,周宇阳,等.高陡构造易漏地层钻前裂缝定量描述方法[J].断块油气田,2015,22(2):263-266.
[6]金衍,陈勉,杨小奇.利用层速度钻前预测安全泥浆密度窗口研究[J].岩石力学与工程学报,2004,23(14):2430-2433.
[7]胡国忠,王宏图,贾剑青,等.岩石的动静弹性模量的关系[J].重庆大学学报(自然科学版),2005,28(3):102-105.
[8]ANDERSON R A.Determining fracture pressure gradients from well logs[J].Journal of Petroleum Technology,1973,5(11):1259-1267.
[9]邓金根,刘杨,蔚宝华,等.高温高压地层破裂压力预测方法[J].石油钻探技术,2009,37(5):43-46.
[10]樊洪海.地层孔隙压力预测检测新方法与应用[D].北京:中国石油大学(北京),2001.
[11]CATYNEANU O.层序地层学原理[M].吴因业,译.北京:石油工业出版社,2009:63-65.
[12]SANSTROM W C,HAWKINS M J.Perceiving drilling learning through visualization[R].SPE 62759,2000.
[13]李黎,王永刚.地质统计学应用综述[J].勘探地球物理进展,2006,29(3):163-169.
[14]宫凤强,侯尚骞,岩小明.基于正态信息扩散原理的Mohr-Coulomb强度准则参数概率模型推断方法[J].岩石力学与工程学报,2013,32(11):2225-2234.
[15]茆诗松,程依明,濮晓龙.概率论与数理统计教程[M].北京:高等教育出版社,2004:45-48.
[16]胜亚楠,管志川,张国辉,等.基于钻前风险预测的井身结构优化方法[J].石油钻采工艺,2016,38(4):415-421.