An In-Depth Review of the Recovery Mechanisms for the Cyclic Gas Injection Process in Shale Oil Reservoirs

Hilario Martin Rodriguez, Y. Barzin, G. Walker, M. Gruenwalder, Matias Fernandez-Badessich, M. Manohar
{"title":"An In-Depth Review of the Recovery Mechanisms for the Cyclic Gas Injection Process in Shale Oil Reservoirs","authors":"Hilario Martin Rodriguez, Y. Barzin, G. Walker, M. Gruenwalder, Matias Fernandez-Badessich, M. Manohar","doi":"10.2118/205194-ms","DOIUrl":null,"url":null,"abstract":"\n This study has double objectives: investigation of the main recovery mechanisms affecting the performance of the gas huff-n-puff (GHnP) process in a shale oil reservoir, and application of optimization techniques to modelling of the cyclic gas injection.\n A dual-permeability reservoir simulation model has been built to reproduce the performance of a single hydraulic fracture. The hydraulic fracture has the average geometry and properties of the well under analysis. A history match workflow has been run to obtain a simulation model fully representative of the studied well. An optimization workflow has been run to maximize the cumulative oil obtained during the GHnP process. The operational variables optimized are: duration of gas injection, soaking, and production, onset time of GHnP, injection gas flow rate, and number of cycles. This optimization workflow is launched twice using two different compositions for the injection gas: rich gas and pure methane. Additionally, the optimum case obtained previously with rich gas is simulated with a higher minimum bottom hole pressure (BHP) for both primary production and GHnP process. Moreover, some properties that could potentially explain the different recovery mechanisms were tracked and analyzed.\n Three different porosity systems have been considered in the model: fractures, matrix in the stimulated reservoir volume (SRV), and matrix in the non-SRV zone (virgin matrix). Each one with a different pressure profile, and thus with its corresponding recovery mechanisms, identified as below: Vaporization/Condensation (two-phase system) in the fractures.Miscibility (liquid single-phase) in the non-SRV matrix.Miscibility and/or Vaporization/Condensation in the SRV matrix: depending on the injection gas composition and the pressure profile along the SRV the mechanism may be clearly one of them or even both.\n Results of this simulation study suggest that for the optimized cases, incremental oil recovery is 24% when the gas injected is a rich gas, but it is only 2.4% when the gas injected is pure methane. A higher incremental oil recovery of 49% is obtained, when injecting rich gas and increasing the minimum BHP of the puff cycle above the saturation pressure. Injection of gas results in reduction of oil molecular weight, oil density and oil viscosity in the matrix, i.e., the oil gets lighter. This net decrease is more pronounced in the SRV than in the non-SRV region. The incremental oil recovery observed in the GHnP process is due to the mobilization of heavy components (not present in the injection gas composition) that otherwise would remain inside the reservoir.\n Due to the main characteristic of the shale reservoirs (nano-Darcy permeability), GHnP is not a displacement process. A key factor in success of the GHnP process is to improve the contact of the injected gas and the reservoir oil to increase the mixing and mass transfer. This study includes a review of different mechanisms, and specifically tracks the evolution of the properties that explain and justify the different identified mechanisms.","PeriodicalId":10904,"journal":{"name":"Day 2 Tue, October 19, 2021","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, October 19, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/205194-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

This study has double objectives: investigation of the main recovery mechanisms affecting the performance of the gas huff-n-puff (GHnP) process in a shale oil reservoir, and application of optimization techniques to modelling of the cyclic gas injection. A dual-permeability reservoir simulation model has been built to reproduce the performance of a single hydraulic fracture. The hydraulic fracture has the average geometry and properties of the well under analysis. A history match workflow has been run to obtain a simulation model fully representative of the studied well. An optimization workflow has been run to maximize the cumulative oil obtained during the GHnP process. The operational variables optimized are: duration of gas injection, soaking, and production, onset time of GHnP, injection gas flow rate, and number of cycles. This optimization workflow is launched twice using two different compositions for the injection gas: rich gas and pure methane. Additionally, the optimum case obtained previously with rich gas is simulated with a higher minimum bottom hole pressure (BHP) for both primary production and GHnP process. Moreover, some properties that could potentially explain the different recovery mechanisms were tracked and analyzed. Three different porosity systems have been considered in the model: fractures, matrix in the stimulated reservoir volume (SRV), and matrix in the non-SRV zone (virgin matrix). Each one with a different pressure profile, and thus with its corresponding recovery mechanisms, identified as below: Vaporization/Condensation (two-phase system) in the fractures.Miscibility (liquid single-phase) in the non-SRV matrix.Miscibility and/or Vaporization/Condensation in the SRV matrix: depending on the injection gas composition and the pressure profile along the SRV the mechanism may be clearly one of them or even both. Results of this simulation study suggest that for the optimized cases, incremental oil recovery is 24% when the gas injected is a rich gas, but it is only 2.4% when the gas injected is pure methane. A higher incremental oil recovery of 49% is obtained, when injecting rich gas and increasing the minimum BHP of the puff cycle above the saturation pressure. Injection of gas results in reduction of oil molecular weight, oil density and oil viscosity in the matrix, i.e., the oil gets lighter. This net decrease is more pronounced in the SRV than in the non-SRV region. The incremental oil recovery observed in the GHnP process is due to the mobilization of heavy components (not present in the injection gas composition) that otherwise would remain inside the reservoir. Due to the main characteristic of the shale reservoirs (nano-Darcy permeability), GHnP is not a displacement process. A key factor in success of the GHnP process is to improve the contact of the injected gas and the reservoir oil to increase the mixing and mass transfer. This study includes a review of different mechanisms, and specifically tracks the evolution of the properties that explain and justify the different identified mechanisms.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
页岩油藏循环注气采收率机理研究进展
本研究有两个目标:一是研究影响页岩油储层气吞吐(GHnP)过程性能的主要采收率机制,二是将优化技术应用于循环注气建模。建立了双渗透储层模拟模型,再现了单条水力裂缝的动态。水力裂缝具有所分析井的平均几何形状和性质。通过运行历史匹配工作流,获得了完全代表所研究井的仿真模型。为了使GHnP过程中获得的累积油量最大化,已经运行了一个优化工作流程。优化的操作变量为:注气、浸泡和生产持续时间、GHnP开始时间、注气流速和循环次数。该优化工作流程使用两种不同的注入气体成分(富气和纯甲烷)启动了两次。此外,在一次生产和GHnP过程中,采用更高的最低井底压力(BHP)模拟了先前获得的富气最佳情况。此外,还跟踪和分析了可能解释不同恢复机制的一些属性。该模型考虑了三种不同的孔隙系统:裂缝、增产储层体积(SRV)中的基质和非SRV区域的基质(原生基质)。每一种都具有不同的压力分布,因此具有相应的采收率机制,确定如下:裂缝中的汽化/冷凝(两相系统)。非srv基质中的混相(液相单相)。SRV基体中的混相和/或汽化/冷凝:根据注入气体成分和SRV沿线的压力分布,其机制可能是其中之一,甚至两者兼有。模拟研究结果表明,在优化情况下,注气为富气时,采收率增量为24%,注气为纯甲烷时,采收率增量仅为2.4%。当注入富气并将吞吐循环的最小BHP提高到饱和压力以上时,可获得更高的原油采收率,增量为49%。注气使基质中的油分子量、油密度和油粘度降低,即油变轻。这种净减少在SRV地区比在非SRV地区更为明显。在GHnP过程中观察到的石油采收率增加是由于调动了重成分(不存在于注入气体成分中),否则这些成分将留在储层中。由于页岩储层的主要特征(纳米达西渗透率),GHnP不是一个驱替过程。GHnP工艺成功的一个关键因素是改善注入气与储层油的接触,增加混合和传质。本研究包括对不同机制的回顾,并特别跟踪解释和证明不同已确定机制的性质的演变。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Control of malodorous gases emission from wet-end white water with hydrogen peroxide Application of spruce wood flour as a cellulosic-based wood additive for recycled paper applications— A pilot paper machine study Corrosion damage and in-service inspection of retractable sootblower lances in recovery boilers Kraft recovery boiler operation with splash plate and/or beer can nozzles — a case study Application of Machine Learning in Gas-Hydrate Formation and Trendline Prediction
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1