基于扩展弹性阻抗反演的致密砂砾岩储层定量预测技术--以玛湖凹陷达13井区为例  

Quantitative prediction technology for tight glutenite reservoirs based on EEI inversion:A case of Well Da13 Area in Mahu Sag

作　　者：王林生[1] 艾建华 伍顺伟[3] 张景[3] 户海胜 朱越 WANG Linsheng;AI Jianhua;WU Shunwei;ZHANG Jing;HU Haisheng;ZHU Yue(Xinjiang Oilfield Company,PetroChina,Karamay,Xinjiang,834000,China;Beijing Qiyuan Petroleum Technology Co.,Ltd.,Beijing,100025,China;Exploration and Development Research Institute,Xinjiang Oilfield Company,PetroChina,Karamay,Xinjiang,834000,China)

机构地区：[1]中国石油新疆油田分公司,新疆克拉玛依834000 [2]北京祺元石油科技有限公司,北京100025 [3]中国石油新疆油田分公司勘探开发研究院,新疆克拉玛依834000

出　　处：《油气地质与采收率》2022年第3期36-44,共9页Petroleum Geology and Recovery Efficiency

基　　金：国家科技重大专项“准噶尔盆地致密油开发示范工程”(2017ZX05070);中国石油重大科技专项“准噶尔南缘和玛湖等重点地区优快钻完井技术集成与试验”(2019F-33)。

摘　　要：准噶尔盆地玛湖凹陷扇三角洲沉积环境下的致密砂砾岩储层内部结构复杂、物性变化大、油藏空间展布复杂多变,需要定量地描述油藏空间展布、储层物性和含油性变化规律。但是,前期的研究证实,常规的地震属性分析和叠前/叠后反演方法不能有效地解决这一难题。为此,采用扩展弹性阻抗反演技术来进行致密砂砾岩储层定量预测是十分必要的。利用测井岩石物理分析技术,通过分析多井目的层段地质参数与扩展弹性阻抗随Chi投影角变化的相关性特征,确定最优的Chi投影角,应用已钻井数据,进行交会分析。采用AVO属性分析、叠前地震同步反演与随机反演相结合的方法,进行高分辨率的声阻抗反演和梯度阻抗反演。根据最优化的Chi投影角,估算待预测的储层参数所对应的扩展弹性阻抗属性体。将储层参数与扩展弹性阻抗属性体进行交会分析,按照神经网络岩相聚类分析结果,分类拟合关系表达式,计算储层参数,并进行误差校正。应用结果表明,基于扩展弹性阻抗反演技术,能够有效地定量描述储层的物性、含油性等关键地质参数,有助于提高致密油气藏勘探开发成功率,值得大量尝试和推广应用。Under the fan-delta sedimentary environment of Mahu Sag in Junggar Basin,the tight glutenite reservoirs feature complex internal structure,variable physical properties,and complicated spatial distribution.Therefore,the quantitative de⁃scription for the variation rules of the spatial distribution,physical properties and oil content of the reservoirs is required.However,former studies have proved that it is difficult to solve the problem efficiently by routine seismic attribute analysis and post-stack or pre-stack seismic inversion methods.Thus,the extended elastic impedance(EEI)inversion technology is adopted for the quantitative prediction of tight glutenite reservoirs.By using petrophysical analysis based on logging data,we analyzed the correlation of geological parameters and EEI of multi-well target intervals with variation of Chi projection angle.In this way,the optimal Chi projection angle was determined,and the data of drilled wells were applied to make cross-plots.We performed high-resolution acoustic impedance(AI)and gradient impedance(GI)inversion by the joint method of amplitude versus offset(AVO)attribute analysis,pre-stack simultaneous inversion and stochastic inversion.Then,given the optimal Chi projection angle,the EEI attributes corresponding to reservoir parameters to be predicted were estimated.Finally,we made cross-plots with the reservoir parameters and estimated EEI attributes,fitted relationship ex⁃pressions according to classes from the neural network clustering of lithofacies,calculated reservoir parameters,and correct⁃ed errors.The practical applications indicate that the key geological parameters of reservoirs such as physical properties and oil/gas content can be quantitatively and effectively described by the EEI inversion.The technology is conducive to raising the success rate of the prospecting and development of tight oil and gas reservoirs,which is worthy of trials and wide application.

关 键 词：EEI反演 AVO反演 储层定量预测 孔隙度 含水饱和度 玛湖凹陷 

分 类 号：TE22[石油与天然气工程—油气井工程]