基于岩石物理模型的凝灰质砂岩的识别与刻画--以珠江口盆地惠州凹陷古近系砂岩储层为例  

Identification and characterization of tuffaceous sandstone based on petrophysical model:A case study of Paleogene sandstone reservoir in Huizhou Sag of the Pearl River Mouth Basin

作　　者：刘灵 张卫卫 朱焱辉 何叶 罗明 杨学奇 LIU Ling;ZHANG Weiwei;ZHU Yanhui;HE Ye;LUO Ming;YANG Xueqi(Research Institute of Shenzhen Branch of CNOOC(China)Ltd.,Shenzhen 518054,China)

机构地区：[1]中海石油(中国)有限公司深圳分公司研究院,广东深圳518054

出　　处：《石油物探》2024年第2期336-345,共10页Geophysical Prospecting For Petroleum

基　　金：中海石油有限公司“十四五”重大科技项目“海上深层/超深层油气勘探技术”(KJGG2022-0403)资助。

摘　　要：惠州H5油田位于珠江口盆地惠州凹陷,古近系恩平组下段砂岩储层是其主力油层,但储层中因火山作用而发育了致密的凝灰质砂岩。此类致密砂岩导致储层性能下降,使得优质储层的预测面临挑战。准确识别凝灰质砂岩并刻画其分布范围是惠州H5油田优质储层预测的关键。为此,根据已钻井资料和地震资料进行了含凝灰质砂岩的岩石物理建模,得到了识别凝灰质砂岩的敏感岩石物理弹性参数;在此基础上,开展了地震资料叠前反演和人工智能深度学习的储层定量预测;在储层预测结果的基础上,识别并刻画了致密的凝灰质砂岩及其分布范围,从而突出优质砂岩储层。提出了凝灰质砂岩岩石物理建模和岩石物理模型驱动下的人工智能储层预测技术及其流程。该技术应用于惠州H5油田的储层评价,在钻前成功识别了H5-3d井区和H5-5d井区恩平组下段发育的凝灰质砂岩,准确刻画了其分布范围和边界,为后续评价井的钻探和储量申报提供了重要依据。In Huizhou H5 Oilfield in the Huizhou Sag of the Pearl River Mouth Basin,the sandstone reservoir in the lower section of the Paleogene Enping Formation is the major oil reservoir.Tight tuffaceous sandstone is developed in the reservoir due to volcanism.Such sandstone has led to the degradation of reservoir performance.The prediction of high-quality reservoirs is challenging.Accurate identification of tuffaceous sandstone and characterization of its distribution are crucial to the prediction of high-quality reservoirs in Huizhou H5 Oilfield.In this paper,petrophysical modeling of tuffaceous sandstone was conducted using available drilling and seismic data,and sensitive petrophysical elastic parameters for identifying tuffaceous sandstone were obtained.Then,quantitative reservoir prediction was performed through seismic data prestack inversion and artificial intelligence deep learning.Furthermore,tight tuffaceous sandstone and its distribution were identified and characterized,highlighting high-quality sandstone reservoirs.Finally,the technology and process of artificial intelligence reservoir prediction driven by petrophysical modeling of tuffaceous rocks and petrophysical models were proposed.This technology was applied to the reservoir evaluation of Huizhou H5 Oilfield,contributing to the successful identification of the tuffaceous sandstone in the H5-3d well area and the lower section of the Enping Formation in the H5-5d well area before drilling,and to the accurate characterization of the tuffaceous sandstone distribution,which provide an important basis for the subsequent drilling of appraisal wells and reserve declaration.

关 键 词：凝灰质砂岩物理模型 叠前反演 人工智能深度学习 储层定量预测 

分 类 号：P631[天文地球—地质矿产勘探]