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.

为能源供应而开采碳氢化合物，或注入二氧化碳以缓解气候变化，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（何时何地注入或提取，多快等）。在这个项目中，我们将开发一个新的统计油藏分析技术的商业版本，该技术是在NERC赠款期间发现的，以帮助理解和设计此类油藏。新模型是一种直接从注入井或生产井威尔斯已记录的流量数据中提取信息的方法，而不会显著增加获取数据的成本。作为一个科学概念，它已经在许多实地试验中证明是成功的，但是如果没有一个可以由实践者在试验中运行的版本，就很难证明商业价值。该项目将提供这样一个平台，与潜在的最终用户合作，使其在设计中符合目的，并将应用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断层和裂缝对流体注入和抽出的响应的手段而开发的。断层和裂缝为地下流体流动提供了关键的屏障或通道，它们的反应对于确定石油和天然气的开采率以及地下CO2储存地点的长期完整性至关重要。目前，该方法可以（1）确定是否存在地质力学响应（以便在必要时可以证明更昂贵的全尺寸地质力学建模工作是合理的），（2）确定哪些映射或未映射的主要断层结构主导这种响应，（3）以时间推移模式确定这种响应的变化。最近由NERC开拓者赠款资助的一份市场研究报告（a）证实了用户对应用该方法和参与早期现场试验的浓厚兴趣，（B）强调了在提高石油和天然气采收率方面潜在应用的优先领域。因此，该项目的主要交付成果将是一个独立的桌面工具，使用户能够将我们的技术应用于这些问题的特定测试案例中，传统的分析已被证明是不够的，让市场决定其效用。最初的功能将基于市场研究确定的优先领域。该技术基于建立一个多元回归模型，根据过去的注入和生产数据预测石油和天然气生产率。它为相互响应的相关井对提供了低成本、优化的目标搜索，并量化了相关性的强度。这一科学概念已经在许多研究文章和测试案例中得到了证明，并且在我们团队无法获得的独立参考数据的“盲测”预测中得到了证明。最终用户将主要受益于独立获得技术，并能够在项目结束后在明确的商业环境中调整工具的功能，特别是早期采用者。该工具将为用于优化石油和天然气开采的当前储层模型添加独立约束，与获取数据或执行传统储层模型相比，几乎没有额外成本。他们将能够评估上述应用的商业价值，并将范围扩展到新的应用。