A New Automated Workflow for Well Monitoring Using Permanent Pressure and Rate Measurements

Author:

Shchipanov A.1,Cui B.2,Starikov V.3,Muradov K.3,Khrulenko A.1,Zhang N.2,Demyanov V.3

Affiliation:

1. NORCE-Norwegian Research Centre, Bergen, Norway

2. Department of Electrical Engineering and Computer Science, University of Stavanger, Stavanger, Norway

3. Institute of GeoEnergy Engineering, Heriot-Watt University, Edinburgh, Scotland, UK

Abstract

Abstract Pressure and rate measurements are essential for the well and reservoir surveillance workflows used in petroleum, geological carbon storage, and geothermal industries. Such well monitoring data are now analyzed in manual, semi-automated and automated modes or in a combination. Automated workflows are widely adopted by the industry nowadays, enabling most efficient knowledge extraction from the data both already accumulated and being received in real-time. The paper describes a new integrated workflow for automated well monitoring using pressure and rate measurements obtained with permanent gauges and flowmeters. The workflow is based on time-lapse Pressure Transient Analysis (PTA) and integrates the following components: virtual flow-metering, transient identification, feature extraction and pattern recognition in transient pressure responses, and assessment of well performance based on PTA-metrics. The methodology behind the workflow combines different physics-informed and data-driven methods described in the paper. Application of the workflow is illustrated on a field case example from the Norwegian Continental Shelf, where changes in the well, reservoir, and well-reservoir connection performances are automatically monitored during its three-year long injection history. Reliability and accuracy of the automated monitoring results are verified via comparison with the conventional model-based time-lapse PTA. The automated workflow may be used for a variety of use cases. Being applied to the well history, the workflow enables establishing a historical performance profile and identifying trends and issues in the past. In everyday well monitoring, it may be employed to detect well performance issues early and indicate their possible reasons. Further, it may provide valuable input for in-depth model-based analysis and other reservoir engineering studies. Using the workflow unlocks knowledge hidden in abundant well-monitoring datasets available at operating companies and empowers reservoir engineers to instantly assess well and reservoir performances, understand their interconnectivity, and make prompt, informed decisions.

Publisher

SPE

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3