Active reservoir management for improved hydrocarbon recovery

积极的油藏管理可提高碳氢化合物采收率

• 批准号: NE/J006483/1
• 负责人: Ian Main
• 金额: $ 14.95万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2012
• 资助国家: 英国
• 起止时间: 2012 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FJ006483%2F1
• 关键词: Active; reservoir; management; improved; hydrocarbon

Hydrocarbon extraction for energy supply, or injection of CO2 to mitigate climate change, both require a detailed knowledge of the structure of underground reservoirs, and how they evolve in response to engineering decisions (when and where to inject or extract, how fast etc.). In this project we will develop a commercial version of a new statistical reservoir analysis technique discovered during a NERC grant as an aid to understanding and engineering such reservoirs. The new model is a way of extracting information directly from flow rate data already recorded at injector or producer wells without significantly adding to the cost of acquiring the data. It has proven successful in a number of field trials as a scientific concept, but it has been harder to prove commercial value without a version that could be run in trials by a practitioner. This project will provide such a platform, engage with potential end-users to make it as fit-for-purpose in its design, and extend the range of applications to a wider range of operational and commercial problems.The method was developed initially as a means of calibrating the response of faults and fractures to fluid injection and withdrawal. Faults and fractures provide key barriers or pathways to fluid flow underground, and their response is critical in determining extraction rates of oil and gas and the long-term integrity of underground CO2 storage sites. At present the method can (1) identify if a geo-mechanical response exists (so that more costly full-scale geo-mechanical modelling exercise can be justified where necessary), (2) identify which mapped or unmapped major fault structures are dominating this response, (3) identify changes in this response in time-lapse mode. A recent Market Research Report funded by a NERC pathfinder grant has (a) confirmed significant user interest in applying the method and in participating in early field trials and (b) highlighted the priority areas for potential applications in enhanced recovery of oil and gas. Accordingly, the major deliverable of this project will be a free-standing desktop tool to enable users to apply our technique to these problems on specific test cases where conventional analyses have proven insufficient, allowing the market to decide on its utility. Initial functionality will be based on the priority areas identified by the market research.The technology is based on establishing a multivariate regression model to forecast oil and gas production rates from past injection and production data. It provides a low-cost, optimised targeted search for the relevant well pairs that respond to each other, and quantifies the strength of the correlation. The scientific concept has been proven in a number of research articles and test cases, and in an independently-refereed, 'blind test' forecast of data not available to our team. End users will benefit primarily from having independent access to the technology, and being able to condition the functionality of the tool after the project in an explicitly commercial environment, particularly early adopters. The tool will add an independent constraint to current reservoir models used to optimise the extraction of oil and gas, at little extra cost compared to acquiring the data or carrying out a conventional reservoir model. They will be able to evaluate the commercial value in the applications identified above, and to extend the range to new ones.

用于能源供应的碳氢化合物提取或注入二氧化碳以减轻气候变化，都需要详细了解地下储层的结构，以及它们如何响应工程决策（何时何地注射或提取，何时何地，速度等）来发展。在此项目中，我们将开发一种商业版的新统计储层分析技术，该技术在NERC赠款期间发现，以帮助理解和工程此类储层。新模型是一种直接从已经记录在喷油器或生产者井的流量数据中提取信息的方法，而无需显着增加获取数据的成本。事实证明，它在许多现场试验中成功地是一种科学概念，但是很难证明没有从业者可以在试验中运行的版本的商业价值。该项目将提供这样一个平台，与潜在的最终用户互动，以使其在设计中成为适合用途，并将应用程序的范围扩展到更广泛的操作和商业问题。该方法最初是作为校准缺陷和裂缝对流体受伤和撤离的响应的一种手段而开发的。断层和断裂为地下流体流动提供了关键的障碍或途径，它们的响应对于确定石油和天然气的提取速率以及地下二氧化碳存储地点的长期完整性至关重要。目前，该方法可以（1）确定是否存在地理机械响应（因此，在必要时可以证明更昂贵的全尺度地理机械建模练习可以证明是合理的），（2）确定哪些映射或未映射的主要断层结构在此响应中占主导地位，（3）确定该响应中这种响应的变化。 NERC探路者赠款资助的最新市场研究报告（a）证实了用户对应用该方法和参与早期试验的浓厚兴趣，并且（b）强调了在增强石油和天然气恢复的潜在应用中的优先领域。因此，该项目的主要交付将是一种独立的桌面工具，使用户能够将我们的技术应用于这些问题，这些问题在传统的测试案例上证明不足，从而使市场可以决定其实用性。初始功能将基于市场研究确定的优先领域。该技术基于建立多元回归模型，以预测从过去的注射和生产数据中预测石油和天然气的生产率。它为相互响应的相关井对提供了低成本，优化的目标搜索，并量化了相关的强度。科学概念已在许多研究文章和测试用例中得到了证明，并在我们团队无法获得的数据预测中进行了独立的“盲测”预测。最终用户将主要从独立访问该技术中受益，并能够在项目明确的商业环境（尤其是早期采用者）中调节该工具的功能。该工具将对用于优化石油和天然气提取的当前储层模型增加独立的约束，与获取数据或执行常规储层模型相比，几乎没有额外的成本。他们将能够评估上述应用程序中的商业价值，并将范围扩展到新范围。