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.

提取碳氢化合物以供应能源，或注入二氧化碳以缓解气候变化，都需要详细了解地下水库的结构，以及它们如何响应工程决策而演变（注入或提取的时间和地点、注入或提取的速度等）。在这个项目中，我们将开发 NERC 拨款期间发现的新统计油藏分析技术的商业版本，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记录的流量数据中提取信息的方法，而不会显着增加获取数据的成本。作为一个科学概念，它已经在许多现场试验中被证明是成功的，但如果没有一个可以由从业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，与潜在的最终用户互动，使其在设计中适合目的，并将应用范围扩展到更广泛的运营和商业问题。该方法最初是作为校准断层和裂缝对流体注入和抽取的响应的一种手段而开发的。断层和裂缝为地下流体流动提供了关键障碍或通道，它们的响应对于确定石油和天然气的开采率以及地下二氧化碳储存地点的长期完整性至关重要。目前，该方法可以（1）识别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面地质力学建模练习是合理的），（2）识别哪些已绘制或未绘制的主要断层结构主导该响应，（3）识别延时模式下该响应的变化。最近由 NERC 探路者赠款资助的一份市场研究报告 (a) 确认了用户对应用该方法和参与早期现场试验的浓厚兴趣，以及 (b) 强调了提高石油和天然气采收率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，使用户能够在传统分析已被证明不足的特定测试用例上应用我们的技术来解决这些问题，从而让市场决定其效用。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，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。这一科学概念已在许多研究文章和测试案例以及我们团队无法获得的数据的独立参考“盲测”预测中得到证实。最终用户将主要受益于独立访问该技术，并能够在项目结束后在明确的商业环境中调节工具的功能，特别是早期采用者。该工具将为当前用于优化石油和天然气开采的油藏模型添加独立约束，与获取数据或执行传统油藏模型相比，几乎不需要额外成本。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。