四川盆地高磨地区龙王庙组储层岩石流体概率识别技术
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摘要
四川盆地高石梯—磨溪地区下寒武统龙王庙组气藏储层的岩性与流体性质地震识别难度较大,主要原因是不同岩性、不同流体性质地层的岩石物理参数往往存在着较大的重叠空间,由此增加了识别的不确定性与多解性。为破解上述难题,采用岩石流体概率识别技术进行了尝试。该方法首先依据岩石物理参数分析结果建立各种岩性、流体性质的概率分布函数,再根据联合求解来确定储层的岩性及流体性质的概率,以此开展岩性、流体性质识别。应用结果表明:较之于一般的叠前反演方法,该方法通过多弹性参数对的联合概率求解,既提高了对储层岩性、流体性质识别的精度,又为提高储层岩性、流体性质识别的可靠程度提供了量化依据,可以为油气藏勘探开发井位部署决策等提供更充足的量化参考指标和依据。
Great difficulties have been encountered in seismic identification of lithologic and fluid properties in Lower Cambrian Longwangmiao Formations in the Gaoshiti-Moxi Area,Sichuan Basin.Petrophysical parameters of formations with different lithologic and fluid properties may overlap with each other,and consequently may lead to uncertainties and multiplicity of solutions to identification results.To solve the problem,lithologic fluid probability identification techniques were deployed.First of all,functions for the probability distribution of various lithologic and fluid parameters were established in accordance with the analysis of petrophysical parameters.Then,joint solution was reached to determine the probabilities related to lithologic and fluid properties of reservoir formations to identify lithologic and fluid properties.Research results show that compared with conventional pre-stack inversion methods,the new method may solve the problem through joint probability determination of multiple elastic parameters to enhance the prediction accuracy of lithologic and fluid properties to provide quantified basis for promoting the reliability in determing lithologic and fluid properties.In conclusion,relevant research results may provide sufficient quantified indexes and foundations for the deployment of wells in the exploration and development of gas reservoirs.
引文
[1]罗德江.基于核方法的井—震多属性碎屑岩储层预测技术研究[D].成都:成都理工大学,2012.Luo Dejiang.Reservoir prediction technology-based kernel method of well logs and seismic multi-attribute in classic rocks[D].Chengdu:Chengdu University of Technology,2012.
    [2]张璐.基于岩石物理的地震储层预测方法应用研究[D].北京:中国石油大学,2009.Zhang Lu.Application of rock physics theory in seismic reservoir discrimination[D].Beijing:China University of Petroleum,2009.
    [3]Castagna JP.Recent advances in seismic lithologic analysis[J].Geophysics,2001,66(1):42-46.
    [4]肖思和,李曙光,许多,鲁红英.叠前弹性波阻抗反演在储层预测中的应用[J].物探化探计算技术,2010,32(5):476-479.Xiao Sihe,Li Shuguang,Xu Duo,Lu Hongying.Application of pre-stack elastic impedance inversion to reservoir prediction[J].Computing Techniques for Geophysical and Geochemical Exploration,2010,32(5):476-479.
    [5]黄伟传,杨长春,王彦飞.利用叠前地震数据预测裂缝储层的应用研究[J].地球物理学进展,2007,22(5):1602-1606.Huang Weichuan,Yang Changchun,Wang Yanfei.The application of pre-stack seismic data in predicting the fractured reservoir[J].Progress in Geophysics,2007,22(5):1602-1606.
    [6]杨文博,张世鑫,宗兆云,姜学庆.基于叠前地震反演的储层流体识别方法[J].甘肃科技,2010,26(15):51-53.Yang Wenbo,Zhang Shixin,Zong Zhaoyun,Jiang Xueqing.Fluid discrimination method based on the prestack inversion[J].Gansu Science and Technology,2010,26(15):51-53.
    [7]刘伟,曹思远.基于地震资料的三种岩性流体预测方法对比分析[J].地球物理学进展,2008,23(6):1918-1923.Liu Wei,Cao Siyuan.Comparison and analysis of three fluid identification technologies based on seismic data[J].Progress in Geophysics,2008,23(6):1918-1923.
    [8]邹文.基于地震资料的流体识别技术研究[D].成都:成都理工大学,2008.Zou Wen.Fluid identification technique research based on seismic data[D].Chengdu:Chengdu University of Technology,2008.
    [9]Denneman AIM,Drijkoningen GG,Smeulders DMJ,Wapenaar K.Reflection and transmission of waves at a fluid/porous-medium interface[J].Geophysics,2002,67(1):282-291.
    [10]姜文龙,杨锴.岩石物理参数高分辨率地质统计学反演[J].石油物探,2012,51(6):638-648.Jiang Wenlong,Yang Kai.High-resolution geostatistical petrophysical parameter inversion[J].Geophysical Prospecting for Petroleum,2012,51(6):638-648.
    [11]李浩.川中北部地区雷口坡组沉积、成岩作用及与储层的关系[D].成都:西南石油大学,2013.Li Hao.The relationship among deposition,diagenesis and reservoir of Leikoupo formation in north-central of Sichuan[D].Chengdu:Southwest Petroleum University,2013.
    [12]仵宗涛.贝西地区叠前、叠后联合反演及砂岩储层地震识别技术[D].北京:中国地质大学,2014.Wu Zongtao.Seismic recognition technology of pre-stack and post-stack inversion joint sandstone reservoir in the area of Beixi[D].Beijing:China University of Geosciences,2014.
    [13]李亚林,巫芙蓉,刘定锦,彭勇,陈胜,邓小江,等.乐山—龙女寺古隆起龙王庙组储层分布规律及勘探前景[J].天然气工业,2014,34(3):61-66.Li Yalin,Wu Furong,Liu Dingjin,Peng Yong,Chen Sheng,Deng Xiaojiang,et al.Distribution rule and exploration prospect of the Longwangmiao Fm reservoirs in the Leshan-Longniisi Paleouplift,Sichuan Basin[J].Natural Gas Industry,2014,34(3):61-66.
    [14]王长城,施泽进,张光荣,韩小俊.川东南嘉陵江组储层地质特征及储层预测研究[J].西南石油大学学报:自然科学版,2008,30(1):8-10.Wang Changcheng,Shi Zejin,Zhang Guangrong,Han Xiaojun.The geologic characteristics and reservoir prediction of Jialingjiang formation in the southeast area of Sichuan[J].Journal of Southwest Petroleum University:Science&Technology Edition,2008,30(1):8-10.
    [15]马丽娟,郑和荣,陈霞.隐蔽油气藏地震预测技术研究新进展[J].地球物理学进展,2007,22(1):294-300.Ma Lijuan,Zheng Herong,Chen Xia.The new progress of seismic forecast technology of subtle traps[J].Progress in Geophysics,2007,22(1):294-300.
    [16]姜传金.深海火山岩地球物理响应及储层预测技术研究[D].大庆:东北石油大学,2012.Jiang Chuanjin.Study of geophysical response and reservoir prediction of deep volcanic rocks[D].Daqing:Northeast Petroleum University,2012.
    [17]Whitcombe DN,Connolly PA,Reagan RL,Redshaw TC.Extended elastic impedance for fluid and lithology prediction[J].Geophysics,2002,67(1):63-67.
    [18]刘晓鹏,欧阳诚,彭宇,何葵.岩石物理参数分析在苏59区块的应用[J].岩性油气藏,2012,24(4):80-84.Liu Xiaopeng,Ouyang Cheng,Peng Yu,He Kui.Application of rock physical parameters in Block Su 59[J].Lithologic Reservoirs,2012,24(4):80-84.
    [19]孙兴刚,魏文,李红梅.岩石物理参数的流体敏感性分析[J].油气藏评价与开发,2012,2(1):37-40.Sun Xinggang,Wei Wen,Li Hongmei.Fluid sensitivity analysis of petrophysical parameters[J].Reservoir Evaluation and Development,2012,2(1):37-40.
    [20]应倩.基于地震岩石物理的致密砂岩流体识别及分析[D].成都:成都理工大学,2013.Ying Qian.Fluid prediction of tight sandstone based on seismic rock physics[D].Chengdu:Chengdu University of Technology,2013.
    [21]王霞,张延庆,于志龙,汪关妹,李晓曦.叠前反演结合地质统计模拟预测薄储层[J].石油地球物理勘探,2011,46(5):744-748.Wang Xia,Zhang Yanqing,Yu Zhilong,Wang Guanmei,Li Xiaoxi.Thin reservoir prediction by pre-stack inversion combined with geostatistic simulation[J].Oil Geophysical Prospecting,2011,46(5):744-748.

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