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: University of Calgary
• 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
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=572594
• 关键词: Advanced; Modeling; Simulation; Techniques; Heavy

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.

就已探明或可采原油储量而言，艾伯塔省已拥有 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前三大国家之一。回收这些资源的关键问题是：回收它们的最佳技术是什么？在哪里以及如何改善可持续复苏？可以追回多少钱？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% 以上的丰富能源资源都存在于地下深处，无法在地表开采。因此，必须使用 EOR 方法将糖蜜状沥青（“原始”重质原油）引至地面。稠油和油砂储量常用的EOR方法是蒸汽辅助重力泄油（SAGD）和循环蒸汽吞吐（CSS）等热采方法。这些方法利用了油相粘度对温度的依赖性。这些过程对环境的影响以及其中大量水和天然气的使用表明，需要进行广泛的研究来经济且环保地开发这些储层。 开发具有详细地质描述的新型油藏 EOR 采油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。还需要具有非结构化网格功能的油藏模拟器来处理自适应网格细化，以将网格集中到发生小规模现象的域区域。拟议的研究计划将开发能够预测各种操作条件下重油和油砂储层性能的数学模型和模拟技术。它将包括先进的并行热储模拟器和流程优化工具包的设计，适用于快速、多次运行，从而能够在实际时间范围内进行风险和不确定性分析和决策。