INSIM-FT-3D: A Three-Dimensional Data-Driven Model for History Matching and Waterflooding Optimization

Zhenyu Guo, A. Reynolds
{"title":"INSIM-FT-3D: A Three-Dimensional Data-Driven Model for History Matching and Waterflooding Optimization","authors":"Zhenyu Guo, A. Reynolds","doi":"10.2118/193841-MS","DOIUrl":null,"url":null,"abstract":"\n We previously published a two-dimensional data-driven model (INSIM-FT) for history matching waterflooding production data and to identify flow barriers and regions of high connectivity between injector-producer pairs. This two-dimensional INSIM model assumed vertical wells. The history-matched models can be used for prediction of waterflooding performance and life-cycle waterflooding optimization. The INSIM-FT-3D model presented here extends INSIM-FT to three dimensions, considers gravity and enables the use of arbitrary well trajectories. INSIM-FT-3D places nodes at each well perforation and then adds nodes throughout the reservoir. Flow occurs through \"streamtubes\" between each pair of connected nodes. Mitchell's best candidate algorithm is used to place nodes and a three-dimensional (3D) connection map is generated with Delaunay triangulation. Pressures and saturations at nodes, respectively, are obtained from IMPES-like pressure equations and a Riemann solver that include gravity effects. With history-matched model(s) as the forward model(s), we estimate the optimal well controls (pressure or rates at control steps) that maximize the life-cycle net-present-value (NPV) of production under waterflooding using a gradient-based method that employs a stochastic gradient. Two 3D reservoirs are considered to establish the viability of using INSIM-FT-3D history-matched models for waterflooding optimization, a channelized reservoir and the Brugge reservoir. Unlike history-matching and waterflooding optimization based on reservoir simulation models, INSIM-FT-3D is not a detailed geological model. Moreover, the time required to run INSIM-FT-3D is more than one order of magnitude less the cost of running a comparable reservoir simulation model.","PeriodicalId":246878,"journal":{"name":"Day 2 Thu, April 11, 2019","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Thu, April 11, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/193841-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

We previously published a two-dimensional data-driven model (INSIM-FT) for history matching waterflooding production data and to identify flow barriers and regions of high connectivity between injector-producer pairs. This two-dimensional INSIM model assumed vertical wells. The history-matched models can be used for prediction of waterflooding performance and life-cycle waterflooding optimization. The INSIM-FT-3D model presented here extends INSIM-FT to three dimensions, considers gravity and enables the use of arbitrary well trajectories. INSIM-FT-3D places nodes at each well perforation and then adds nodes throughout the reservoir. Flow occurs through "streamtubes" between each pair of connected nodes. Mitchell's best candidate algorithm is used to place nodes and a three-dimensional (3D) connection map is generated with Delaunay triangulation. Pressures and saturations at nodes, respectively, are obtained from IMPES-like pressure equations and a Riemann solver that include gravity effects. With history-matched model(s) as the forward model(s), we estimate the optimal well controls (pressure or rates at control steps) that maximize the life-cycle net-present-value (NPV) of production under waterflooding using a gradient-based method that employs a stochastic gradient. Two 3D reservoirs are considered to establish the viability of using INSIM-FT-3D history-matched models for waterflooding optimization, a channelized reservoir and the Brugge reservoir. Unlike history-matching and waterflooding optimization based on reservoir simulation models, INSIM-FT-3D is not a detailed geological model. Moreover, the time required to run INSIM-FT-3D is more than one order of magnitude less the cost of running a comparable reservoir simulation model.
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
INSIM-FT-3D:历史匹配和注水优化的三维数据驱动模型
我们之前发布了一个二维数据驱动模型(INSIM-FT),用于匹配水驱生产数据的历史数据,并识别注入-生产对之间的流动障碍和高连通性区域。该二维INSIM模型假设为直井。历史拟合模型可用于水驱性能预测和全生命周期水驱优化。本文提出的INSIM-FT- 3d模型将INSIM-FT扩展到三维,考虑了重力,并能够使用任意井眼轨迹。INSIM-FT-3D在每口井的射孔处放置节点,然后在整个油藏中添加节点。流动通过“流管”在每一对连接的节点之间发生。Mitchell的最佳候选算法用于放置节点,并使用Delaunay三角剖分生成三维(3D)连接图。节点上的压力和饱和度分别由类似impes的压力方程和包括重力效应的黎曼解算器获得。将历史匹配模型作为正演模型,我们使用基于梯度的随机梯度方法来估计最佳井控(控制步骤的压力或速率),从而最大化水驱下生命周期净现值(NPV)。为了确定使用INSIM-FT-3D历史匹配模型进行水驱优化的可行性,研究人员考虑了两个三维油藏,一个是水道化油藏,另一个是布鲁日油藏。与基于油藏模拟模型的历史匹配和水驱优化不同,INSIM-FT-3D并不是一个详细的地质模型。此外,运行INSIM-FT-3D所需的时间比运行类似油藏模拟模型的成本低一个数量级以上。
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
Unconventional Reservoir Management Modeling Coupling Diffusive Zone/Phase Field Fracture Modeling and Fracture Probability Maps Adjoint-Based Adaptive Convergence Control of the Iterative Finite Volume Multiscale Method A Calibrated Model for the Carbonate-Brine-Crude Oil Surface Chemistry and its Effect on the Rock Wettability, Dissolution, and Mechanical Properties An Open Source Numerical Framework for Dual-Continuum Geomechanical Simulation Dynamic Modeling and Design Optimization of Cyclonic Autonomous Inflow Control Devices
×
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:604180095
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