An Efficient Approach for History-Matching Coal Seam Gas CSG Wells Production

Gladys Chang, Aibassov Gizat
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Abstract

QGC's current full-field reservoir model comprises hundreds to thousands of CSG wells. This presents a considerable challenge from a history-matching standpoint compared to a conventional workflow where well-level adjustments may be made on one well at a time. In QGC, a model with an improved well-level match is desired as the resulting well forecast will enable decisions on a well-level to be made more confidently, such as the prioritization of well workovers. Previously a field-level history-match was deemed acceptable when the model was only used for field development planning. The method parameterizes the well-level relative error in simulated production from the model versus observed production. The workflow utilizes this data, known as well-level modifiers, to alter subsurface properties. This has been achieved with a semi-automated workflow to make the process efficient and repeatable, but also to enable engineering judgement to be incorporated in the history-matching process. The feedback loop is also an essential component of the workflow as it allows the well-level modifiers to be sense checked against the regional geological trends. This further encourages collaboration within a multi-disciplinary team. These well-level modifiers can also be used to create history-match metrics, which can be spatially mapped to help target specific areas for improvement in history-match quality. Some powerful use of visualization techniques discussed in this paper has not only minimized the mismatch but ensures the characteristics of the production history and geological trends are honoured to assure the robustness of the history-match and the resulting model predictability. The workflow has significantly reduced the time and efforts spent in delivering an improved well forecast when required. The technical development community in QGC has actively nurtured a culture of ideas sharing and innovation, which made the development of this workflow possible.
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煤层气CSG井生产历史匹配的有效方法
QGC目前的全油田储层模型包括数百至数千口CSG井。与常规工作流程相比,从历史匹配的角度来看,这是一个相当大的挑战,常规工作流程一次只能对一口井进行井位调整。在QGC中,需要一个具有改进井位匹配的模型,因为由此产生的井预测可以更自信地做出井位决策,例如修井的优先级。以前,当模型仅用于油田开发规划时,油田级别的历史匹配被认为是可以接受的。该方法参数化了模型与实际产量在模拟生产中的井位相对误差。该工作流程利用这些数据(称为井级修改器)来改变地下属性。这是通过半自动化的工作流程实现的,使过程高效且可重复,同时也使工程判断能够纳入历史匹配过程。反馈回路也是工作流程的重要组成部分,因为它允许根据区域地质趋势对井位调节器进行检测。这进一步鼓励了多学科团队的合作。这些井级修饰符还可以用于创建历史匹配指标,这些指标可以在空间上进行映射,以帮助改善特定区域的历史匹配质量。本文所讨论的一些可视化技术的强大应用不仅最大限度地减少了错配,而且确保了生产历史和地质趋势的特征,以确保历史匹配的鲁棒性和结果模型的可预测性。该工作流程大大减少了在需要时提供改进的井眼预测所需的时间和精力。QGC的技术开发社区积极培养了一种思想分享和创新的文化,这使得该工作流程的开发成为可能。
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