频变泊松阻抗在深水重力流砂体含气性预测中的应用  

Application of frequency-dependent Poisson’s impedance in prediction of gas potential of deepwater gravity flow sandbody

作　　者：李志晔 刘铮 张卫卫 杨学奇 敖威 雷胜兰 LI Zhiye;LIU Zheng;ZHANG Weiwei;YANG Xueqi;AO Wei;LEI Shenglan(CNOOC Deepwater Development Limited,Shenzhen 518054,China)

机构地区：[1]中海石油深海开发有限公司,深圳518054

出　　处：《石油科学通报》2023年第6期755-766,共12页Petroleum Science Bulletin

基　　金：中海石油(中国)有限公司项目“南海大中型天然气田形成条件、勘探潜力与突破方向”(KJZH-2021-0003-00)资助。

摘　　要：白云深水区位于南海北部陆坡前缘,已发现多个气田,是油气成藏的有利区带,但是随着勘探程度的加深,地震勘探目标越来越复杂,流体性质的不确定性是目前勘探面临的难题之一,加强流体预测研究迫在眉睫。然而常规弹性参数对含气饱和度的敏感性较弱,且受压实、岩性、厚度调谐、孔隙等因素影响,气层、低饱和度气层、好物性水层等地震响应类似,常规弹性参数反演方法难以解决含气饱和度预测的问题。泊松阻抗表现为纵横波速度差的形式,可以消去固相突出液相信息,具有流体因子性质,然而常规的坐标旋转获取泊松阻抗的方法在定量预测含气饱和度时误差较大。射线弹性阻抗可以表达为广义泊松阻抗,对叠前道集资料进行对应泊松角度部分叠加即可快速求得泊松阻抗,相对于常规泊松阻抗保留了频率特征。在相控岩石物理指导下,采用分频技术,使用频变的泊松阻抗描述流体引起的频散程度,消除利用单一振幅信息所引起的流体识别假象,增强对油气检测的准确性和敏感性。同时通过随机森林算法建立特征频率泊松阻抗与含气饱和度的非线性关联,并加入孔隙度相控体,在有效储层里实现定量油气预测。随机森林算法是一种以决策树为基础的集成算法,具有调节参数少、操作方便的优点,且具有较好的抗噪性。针对白云深水区珠江组重力流砂体储层的含气性特征,应用此技术进行含油气性预测,预测结果与井吻合性高,可以有效将受物性影响呈现强振幅特征的不含气砂岩与含气砂岩区分,验证了方法的有效性及应用前景。The Baiyun Deepwater Zone is located on the front edge of the northern slope of the South China Sea,and multiple gas fields have been discovered,making it a favorable zone for oil and gas accumulation.However,with the deepening of exploration,the seismic exploration targets are becoming increasingly complex,and the uncertainty of fluid properties is one of the current challenges in exploration.Strengthening fluid prediction research is urgent.However,the sensitivity of conventional elastic parameters to gas saturation is weak,and they are influenced by factors such as compaction,lithology,thickness tuning,porosity,etc.The seismic response of gas layers,low saturation gas layers,and good physical property water layers is similar.Conventional elastic parameter inversion methods are difficult to use to solve the problem of gas saturation prediction.Poisson's impedance is manifested in the form of velocity difference between longitudinal and transverse waves,which can eliminate the information of solid phase protrusion and liquid phase,and has fluid factor properties.However,conventional methods of obtaining Poisson's impedance through coordinate rotation have significant errors in quantitatively predicting gas saturation.The ray elastic impedance can be expressed as a generalized Poisson impedance,which can be quickly obtained by stacking the corresponding Poisson angle part of the pre-stack gather data,while retaining frequency characteristics compared to conventional Poisson impedance.Under the guidance of phase controlled rock physics,frequency division technology is adopted to describe the degree of dispersion caused by fluid using frequency dependent Poisson impedance,eliminate the false identification of fluid caused by the use of single amplitude information,and enhance the accuracy and sensitivity of oil and gas detection.At the same time,a nonlinear correlation between characteristic frequency Poisson impedance and gas saturation is established through a random forest algorithm,and porosity controlled volum

关 键 词：频变 泊松阻抗 流体识别 人工智能 随机森林 

分 类 号：P618.13[天文地球—矿床学]