Hierarchical Geomodeling Approach for Ultra High Permeability Reservoir

W. Xu, K. Chen, L. Fang, Yingchun Zhang, Z. Jing, Jun Liu, Jingyun Zou
{"title":"Hierarchical Geomodeling Approach for Ultra High Permeability Reservoir","authors":"W. Xu, K. Chen, L. Fang, Yingchun Zhang, Z. Jing, Jun Liu, Jingyun Zou","doi":"10.2118/195861-ms","DOIUrl":null,"url":null,"abstract":"\n The lacustrine delta sandbody deposited in the north of Albert Basin is unconsolidated due to the shallow burial depth, which leads to an ultra-high permeability (up to 20 D) with large variation and poor diagenesis. Log derived permeability differs greatly with DST results. Thus, permeability simulation is challenging in 3D geomodeling. A hierarchical geomodeling approach is presented to bridge the gap among the ultra-high permeability log, model and DST results. The ultimate permeability model successfully matched the logging data and DST results into the geological model.\n Based on the study of sedimentary microfacies, the new method identifies different discrete rocktypes (DRT) according to the analyis of core, thin section and conventional and special core analysis (e.g., capillary pressure). In this procedure, pore throat radius, flow zone index (FZI) and other parameters are taken into account to identify the DRT. Then, hierarchical modeling approach is utilized in the geomodeling. Firstly, the sedimentary microfacies model is established within the stratigraphic framework. Secondly, the spatial distribution model of DRT is established under the control of sedimentary microfacies. Thirdly, the permeability distribution is simulated according to the different pore-permeability relation functions derived from each DRT. Finally, the permeability model is compared with the logging and testing results.\n Winland equation was improved based on the capillary pressure (Pc) data of special core analysis. It is found that the highest correlation between pore throat radius and reservoir properties was reached when mercury injection was 35%. The corresponding formula of R35 is selected to calculate the radius of reservoir pore throat. Reservoirs are divided into four discrete rock types according to parameters such as pore throat radius and flow zone index. Each rock type has its respective lithology, thin section feature and pore-permeability relationship. The ultra-high permeability obtained by DST test reaches up to 20 D, which belongs to the first class (DRT1) quality reservoir. It is located in the center of the delta channel with high degree of sorting and roundness. DRT4 is mainly located in the bank of the channels. It has a much higher shale content and the permeability is generally less than 50 mD. Through three-dimensional geological model, sedimentary facies, rock types and pore-permeability model are coupled hierarchically. Different pore-permeability relationships are given to different DRTs. After reconstructing the permeability model, the simulation results are highly matched with the log and DST test results.\n This hierarchical geomodeling approach can effectively solve the simulation problem in the ultra-high permeability reservoir. It realizes a quantitative characterization for the complex reservoir heterogeneity. The method presented can be applied to clastic reservoir. It also plays a significant positive role in carbonate reservoir characterization.","PeriodicalId":10909,"journal":{"name":"Day 2 Tue, October 01, 2019","volume":"2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, October 01, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/195861-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The lacustrine delta sandbody deposited in the north of Albert Basin is unconsolidated due to the shallow burial depth, which leads to an ultra-high permeability (up to 20 D) with large variation and poor diagenesis. Log derived permeability differs greatly with DST results. Thus, permeability simulation is challenging in 3D geomodeling. A hierarchical geomodeling approach is presented to bridge the gap among the ultra-high permeability log, model and DST results. The ultimate permeability model successfully matched the logging data and DST results into the geological model. Based on the study of sedimentary microfacies, the new method identifies different discrete rocktypes (DRT) according to the analyis of core, thin section and conventional and special core analysis (e.g., capillary pressure). In this procedure, pore throat radius, flow zone index (FZI) and other parameters are taken into account to identify the DRT. Then, hierarchical modeling approach is utilized in the geomodeling. Firstly, the sedimentary microfacies model is established within the stratigraphic framework. Secondly, the spatial distribution model of DRT is established under the control of sedimentary microfacies. Thirdly, the permeability distribution is simulated according to the different pore-permeability relation functions derived from each DRT. Finally, the permeability model is compared with the logging and testing results. Winland equation was improved based on the capillary pressure (Pc) data of special core analysis. It is found that the highest correlation between pore throat radius and reservoir properties was reached when mercury injection was 35%. The corresponding formula of R35 is selected to calculate the radius of reservoir pore throat. Reservoirs are divided into four discrete rock types according to parameters such as pore throat radius and flow zone index. Each rock type has its respective lithology, thin section feature and pore-permeability relationship. The ultra-high permeability obtained by DST test reaches up to 20 D, which belongs to the first class (DRT1) quality reservoir. It is located in the center of the delta channel with high degree of sorting and roundness. DRT4 is mainly located in the bank of the channels. It has a much higher shale content and the permeability is generally less than 50 mD. Through three-dimensional geological model, sedimentary facies, rock types and pore-permeability model are coupled hierarchically. Different pore-permeability relationships are given to different DRTs. After reconstructing the permeability model, the simulation results are highly matched with the log and DST test results. This hierarchical geomodeling approach can effectively solve the simulation problem in the ultra-high permeability reservoir. It realizes a quantitative characterization for the complex reservoir heterogeneity. The method presented can be applied to clastic reservoir. It also plays a significant positive role in carbonate reservoir characterization.
超高渗透储层分层地质建模方法
阿尔贝盆地北部沉积的湖相三角洲砂体由于埋藏深度较浅而松散,形成超高渗透率(可达20 D),变化大,成岩作用差。测井计算的渗透率与DST结果差异很大。因此,渗透率模拟在三维地质建模中具有挑战性。提出了一种分层地质建模方法,以弥补超高渗透测井、模型和DST结果之间的差距。最终渗透率模型成功地将测井数据和DST结果与地质模型相匹配。该方法在沉积微相研究的基础上,通过岩心分析、薄片分析、常规岩心分析和特殊岩心分析(如毛管压力)识别不同的离散岩石类型(DRT)。在此过程中,考虑孔喉半径、流区指数(FZI)等参数来识别DRT。然后,采用分层建模方法进行地质建模。首先,在地层格架内建立沉积微相模型。其次,建立了沉积微相控制下DRT的空间分布模型。第三,根据各DRT导出的不同孔渗关系函数,模拟渗透率分布;最后,将渗透率模型与测井、测试结果进行了对比。基于特殊岩心分析的毛细管压力(Pc)数据,对Winland方程进行了改进。当压汞量为35%时,孔喉半径与储层物性相关性最高。采用R35的相应公式计算储层孔喉半径。根据孔喉半径、流区指数等参数,将储层划分为4种离散的岩石类型。每种岩石类型都有各自的岩性、薄片特征和孔渗关系。DST测试获得的超高渗透率达20 D,属于一级(DRT1)优质储层。它位于三角洲河道的中心,分选度高,圆度大。DRT4主要位于河道岸边。页岩含量高,渗透率一般小于50 mD。通过三维地质模型,将沉积相、岩石类型和孔隙渗透率模型分层耦合。不同的DRTs具有不同的孔渗关系。重建渗透率模型后,模拟结果与测井和DST测试结果吻合较好。这种分层地质建模方法可以有效地解决超高渗透储层的模拟问题。实现了复杂储层非均质性的定量表征。该方法可应用于碎屑储层。对碳酸盐岩储层的表征也具有重要的积极作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信