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Advanced Modeling and Simulation Techniques for Heavy Oil and Oil Sands Reservoirs

Advanced Modeling and Simulation Techniques for Heavy Oil and Oil Sands Reservoirs
稠油和油砂油藏先进建模和仿真技术
批准号:
355518-2013
负责人:
Chen, Zhangxing
金额:
$3.41万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2015
资助国家:
加拿大
项目状态:
已结题
起止时间:
2015-01-01 至 2016-12-31

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中文摘要
翻译
艾伯塔省现有的1,740亿桶油砂储量使加拿大与沙特阿拉伯和委内瑞拉一起成为全球已探明或可开采原油储量最多的三个国家之一。回收这些资源的关键问题是:回收这些资源的最佳技术是什么?在哪里以及如何改善可持续复苏?可以收回多少钱?目前油砂储量的主要生产方法包括采矿法和提高采收率(EOR)法。艾伯塔省90%以上的巨大能源资源是在地下太深而无法在地表开采的矿藏中找到的。因此,必须使用提高采收率的方法来哄骗糖蜜状沥青--“未加工的”重质原油--浮出地面。稠油和油砂储量常用的提高采收率方法有蒸汽辅助重力排水(SAGD)和蒸汽吞吐(CS)等热采方法。这些方法利用了油相粘度对温度的依赖关系。这些过程对环境的影响以及在这些过程中大量使用水和天然气表明,需要进行广泛的研究,以经济和环境友好的方式开发这些油藏。 开发具有详细地质描述的油藏提高采收率的新方法,需要先进的数学模型、求解算法、并行技术和能够处理多尺度现象的技术。还需要一个具有非结构化网格功能的油藏模拟器,以处理自适应网格细化,将网格集中到发生小规模现象的区域。拟议的研究计划将开发能够预测不同运行条件下稠油和油砂油藏动态的数学模型和模拟技术。它将包括设计先进的并行热储模拟器和适用于快速、多次运行的过程优化工具包,使风险和不确定性分析和决策能够在实际时间框架内进行。
英文摘要
Alberta's 174 billion barrels of established oil sands reserves make Canada one of the top three countries globally - along with Saudi Arabia and Venezuela - in terms of proven or recoverable crude oil reserves. The key questions in recovering these resources are: What is the best technology available to recover them? Where and how can sustainable recovery be improved? How much is recoverable? The current major production methods for oil sands reserves include mining and enhanced oil recovery (EOR) methods. More than 90% of the vast energy resources in Alberta is found in deposits too deep underground to be mined at the surface. Thus the EOR methods must be used to coax the molasses-like bitumen, the "raw" heavy crude oil, to the surface. The commonly used EOR methods for heavy oil and oil sands reserves are thermal recovery methods such as steam assisted gravity drainage (SAGD) and cyclic steam stimulation (CSS). These methods take advantage of the dependence of the oil phase viscosity on temperature. Environmental impacts of these processes and the use of a high volume of water and natural gas in them suggest that extensive research is required for the economical and environmentally friendly development of these reservoirs. The development of novel EOR recovery methods for reservoirs with detailed geological description requires advanced mathematical models, solution algorithms, parallel techniques, and techniques capable of treating multi-scale phenomena. Also required is a reservoir simulator with unstructured grid capabilities to handle adaptive grid refinement to focus the grid to regions of the domain where small-scale phenomena occur. The proposed research program will develop mathematical models and simulation technologies capable of predicting heavy oil and oil sands reservoir performance under various operating conditions. It will include the design of advanced parallel, thermal reservoir simulators and process optimization toolkits suitable for fast, multiple runs that enable risk and uncertainty analysis and decision making in practical timeframes.
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Integrated Numerical Simulation for Shale Gas Reservoirs
  • 批准号:
    RGPIN-2018-04307
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.35万
  • 财政年份:
    2022
  • 负责人:
    Chen, Zhangxing
  • 依托单位:
NSERC / Energi Simulation Industrial Research Chair in Reservoir Simulation
  • 批准号:
    365863-2017
  • 项目类别:
    Industrial Research Chairs
  • 资助金额:
    $54.86万
  • 财政年份:
    2021
  • 负责人:
    Chen, Zhangxing
  • 依托单位:
Development of a hybrid quantum-classical reservoir simulator and evaluation of quantum computing hardware
  • 批准号:
    561106-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $3.64万
  • 财政年份:
    2021
  • 负责人:
    Chen, Zhangxing
  • 依托单位:
Extended Reality Innovations for Reservoir Engineering
  • 批准号:
    554596-2020
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $5.46万
  • 财政年份:
    2021
  • 负责人:
    Chen, Zhangxing
  • 依托单位:
国内基金
海外基金
Galaxy Analytical Modeling Evolution (GAME) and cosmological hydrodynamic simulations.
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2025
  • 负责人:
    Antonios Katsianis
  • 依托单位: