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Multiscale analysis and large-scale parallelization of heterogeneous reservoir models

Multiscale analysis and large-scale parallelization of heterogeneous reservoir models
非均质油藏模型的多尺度分析和大规模并行化
批准号:
452657-2013
负责人:
Minev, Peter
金额:
$3.06万
依托单位:
依托单位国家:
加拿大
项目类别:
Collaborative Research and Development Grants
财政年份:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

项目摘要

项目成果

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中文摘要
翻译
阿尔伯塔的大部分石油产自稠油和超稠油油藏。 在这种情况下,提取过程是基于新技术,要求㈠能源效率; ㈡环境安全。 数值模拟极大地促进了这些目标的实现,该数值模拟为工程师提供了对威尔斯的各种参数的准确估计,并允许生产过程的有效优化。 这种模拟还大大降低了环境风险,因为它们可以最大限度地减少昂贵和危险的实地实验的需要。 Laricina能源有限公司,作为阿萨巴斯卡油田开发的主要参与者之一,开发了自己的开放式油藏模拟器,专门用于模拟非等温稠油油藏。 它包括最先进的数学模型和数值求解技术。 本项目旨在进一步发展这些解决办法的技术和代码,其中包括:(一)开发适当的预处理器,考虑到所使用的模型的具体情况,并允许在非常大规模的并行分布式计算机集群上进行有效的模拟; ㈡开发简化的数学模型,以便能够非常快速而又相对准确地模拟非常大的重油储层。 这些发展的好处是,一方面,开发的预处理技术和软件将大大提高效率的数值求解器,这将允许更准确的计算。 另一方面,降阶模型将允许非常快速的模拟,可用于在对其中几个场景进行全面且非常精确的计算之前,以大大降低的计算成本运行给定生产现场的许多不同场景。 这些技术将使Laricina能源有限公司继续处于稠油和超稠油油藏生产技术开发的最前沿。 开发的开放获取软件也将提供给其他用户,因此将有利于北方阿尔伯塔稠油油田的整体开发。
英文摘要
A large portion of the oil in Alberta is produced from heavy and superheavy oil reservoirs. The extraction process in such cases is based on new technologies that are required to be (i) energy efficient; (ii) environmentally safe. The achievement of these goals is greatly facilitated by numerical simulations that provide the engineers with accurate estimates for various parameters of the wells and allow for an efficient optimization of the production process. Such simulations also greatly reduce the environmental risks since they allow to minimize the needs of expensive and hazardous field experiments. Laricina Energy Ltd., being one of the major players in the development of the Athabasca oil field, has developed its own open access reservoir simulator which is specialized in the simulation of non-isothermal heavy oil reservoirs. It comprises state-of-the-art mathematical models and numerical solution techniques. The present project is aimed at the further development of these solution techniques and the code which will include: (i) development of proper preconditioners that take into account the specifics of the models used and allow for efficient simulations on very large scale parallel distributed computer clusters; (ii) development of reduced mathematical models that allow for very fast and yet relatively accurate simulations of very large heavy oil reservoirs. The benefits of these developments are that on one hand the developed preconditioning techniques and software will greatly increase the efficiency of the numerical solvers which will allow for more accurate computations. On the other hand, the reduced order models will allow for very fast simulations that can be used to run many different scenarios for a given production site with much reduced computational costs, before running a full-scale and very precise computations of just several of them. These techniques will enable Laricina Energy Ltd. to continue to be at the cutting edge of the technological development for production from heavy and superheavy oil reservoirs. The developed open access software will be also accessible to other users and therefore will benefit the entire development of the heavy oil fields in Northern Alberta.
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Multiscale analysis and large-scale parallelization of heterogeneous reservoir models
  • 批准号:
    452657-2013
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $2.55万
  • 财政年份:
    2015
  • 负责人:
    Minev, Peter
  • 依托单位:
Massively parallel direction splitting algorithms for complex flow
  • 批准号:
    216926-2012
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2015
  • 负责人:
    Minev, Peter
  • 依托单位:
Massively parallel direction splitting algorithms for complex flow
  • 批准号:
    216926-2012
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2014
  • 负责人:
    Minev, Peter
  • 依托单位:
Massively parallel direction splitting algorithms for complex flow
  • 批准号:
    216926-2012
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.89万
  • 财政年份:
    2013
  • 负责人:
    Minev, Peter
  • 依托单位:
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