生产

生产监控-2023

新传感器和现有技术的创新使用允许访问各种数据,这些数据可以合并到集成工作流程和建模工具中,以便更好地了解生产系统。初步迹象表明,运营正在转向使用实时模型。

生产监控重点介绍

石油和天然气行业继续面临挑战。我们目睹了大宗商品价格的波动(石油供应超过需求,导致整体市场放缓)、影响全球生产和供应链的 COVID-19 大流行、劳动力短缺、设施安全问题以及为能源做好准备的需要过渡,仅举几例。运营商现在比以往任何时候都更需要充分利用其资产,不仅要维持生产,还要了解全天候发生的情况,以便能够防止潜在威胁或可能升级并影响运营的情况。

新传感器和现有技术的创新使用允许访问各种数据,这些数据可以合并到集成工作流程和建模工具中,以便更好地了解生产系统。初步迹象表明,运营正在转向使用支持决策的实时模型,从而能够快速响应外部变化并改进预测,从而整体提高资产绩效。

生产监控的新技术和创新越来越关注数据集成和集成工作流程的使用。人们非常重视利用数字技术(例如远程操作、先进的数据分析工具)和提高测量数据的准确性,以便更好地制定旨在提高效率的监测规划。去年取得的一些进展包括:

成功地将永久性油藏监测系统的数据集成到油藏模型中,可以更好地了解水驱应用中的油藏变化,显示出4D数据的价值

演示使用光纤(例如,用于分布式声学和分布式温度传感)在各种用例中的价值,包括井流剖面、裂缝扩展模型校准以及理解井干扰

新传感器可监测间隙减小区域中井完整性屏障之外的压力和温度,为现场测试做好准备

使用传统采集的数据(例如压力)来推断井间和区域内的干扰,以经济实惠的方式将示踪剂与套管技术集成,以实现水平井的完井和储层诊断

机器学习和人工智能等数字方法用于数据解释和预测,甚至作为替代测量来提供多相流数据(即虚拟流量计)。

本月的技术论文

永久光纤 DTS 评估生产增强

将 4D 数据集成到动态模型中改进了 Johan Sverdrup 油田开发

Multiannuli解决方案使用智能管道进行实时监控

推荐补充阅读

SPE 210270 油溶性示踪剂在未增产和增产多级水平井中的创新应用,以实现长期流量保证和生产监测, 作者:Venky Ramanathan、Torxen Energy 等。

URTeC 3723767 用于非常规井连续实时生产监控的虚拟流量计量,作者:Torgeir Vanvik、Turbulent Flux 等。

SPE 204662 用于虚拟流量计量的人工智能和数据分析, 作者:Anton Gryzlov、Aramco Innovations 等。


Mariela Araujo, SPE,是壳牌全球解决方案的首席科学专家,目前担任商业创新合作伙伴经理。在担任此职务之前,她曾从事生产优化、油藏管理和地下整合的技术开发工作。Araujo 拥有物理学学士和博士学位,一直在该行业担任油藏工程师,专注于涵盖从实验室到现场应用的各种技术领域。她热衷于数据集成、地下建模和优化,曾在委内瑞拉、英国、美国、加拿大和约旦的石油和天然气项目工作过。目前,Araujo 正在支持多个技术项目,包括资产管理和离岸技术、CO 2减排和电气化计划。

原文链接/jpt
Production

Production Monitoring-2023

New sensors and innovative uses of existing technology are allowing access to a variety of data that can be incorporated into integrated work flows and modeling tools for better understanding of the production system. There are initial signs of operations moving toward the use of real-time models.

Production Monitoring Focus intro

The oil and gas industry continues to face challenges. We have witnessed volatility in commodity prices (oil supply outstripping demand, leading to overall market slowdown), the COVID-19 pandemic affecting production and supply chains around the world, labor shortages, facilities-security issues, and the need to prepare for the energy transition, just to name a few. Operators, now more than ever, need to make the most of their assets, not only maintaining production but also understanding what is happening around the clock to be able to prevent potential threats or situations that may escalate and affect operations.

New sensors and innovative uses of existing technology are allowing access to a variety of data that can be incorporated into integrated work flows and modeling tools for better understanding of the production system. There are initial signs of operations moving toward the use of real-time models supporting decision making, enabling fast response to external changes, and improved forecasting, resulting in overall improved asset performance.

New technology and innovation in production monitoring is focusing more and more on data integration and the use of integrated work flows. Significant attention is being paid to leveraging digital technology (e.g., remote operations, advanced data analysis tools) and improving the accuracy of measured data for better surveillance planning aiming at efficiency gains. Some examples of advances in the past year include the following:

Successful integration of data from permanent reservoir monitoring systems into reservoir models, allowing a better understanding of reservoir changes in waterflooding applications, showing the value of 4D data

Demonstration of the value of using fiber optics (e.g., for distributed acoustic and distributed temperature sensing) for a variety of use cases including well-flow profiling, calibration of fracture propagation models, and understanding well interference

New sensors to monitor pressure and temperature beyond well-integrity barriers in zones with reduced clearance, just ready for field testing

Use of traditional acquired data (e.g., pressure) to infer inter- and intrazone well interference, affordable integration of tracers with sleeve technology for completion and reservoir diagnostic in horizontal wells

Digital methods such as machine learning and artificial intelligence for data interpretation and forecasting and even to serve as surrogate measurements to provide multiphase flow data (i.e., virtual flowmeters).

This Month’s Technical Papers

Permanent Fiber-Optic DTS Evaluates Production Enhancement

Integrating 4D Data Into Dynamic Model Improves Johan Sverdrup Field Development

Multiannuli Solution Uses Intelligent Pipe for Real-Time Monitoring

Recommended Additional Reading

SPE 210270 Innovative Applications of Oil-Soluble Tracers in Unstimulated and Stimulated Multistage Horizontal Wells for Long-Term Flow Assurance and Production Monitoring by Venky Ramanathan, Torxen Energy, et al.

URTeC 3723767 Virtual Flow Metering for Continuous Real-Time Production Monitoring of Unconventional Wells by Torgeir Vanvik, Turbulent Flux, et al.

SPE 204662 Artificial Intelligence and Data Analytics for Virtual Flow Metering by Anton Gryzlov, Aramco Innovations, et al.


Mariela Araujo, SPE, is a principal science expert at Shell Global Solutions, currently in the role of commercial innovation partnerships manager. Before taking this role, she held roles in technology development for production optimization, reservoir management, and subsurface integration. Araujo holds BS and PhD degrees in physics and has been working in the industry as a reservoir engineer with a focus on a variety of technology areas covering applications from the laboratory to the field. She is passionate about data integration, subsurface modeling, and optimization, and has worked for oil and gas projects in Venezuela, the UK, the US, Canada, and Jordan. Currently, Araujo is supporting several technology programs, including asset management and offshore technologies, CO2 abatement, and electrification initiatives.