Smart UGS

Claudio Srepel

Research output: ThesisMaster's Thesis


It was reported in various studies that performance of gas storage wells decreases over time, claiming the need of monitoring to identify damage. Performance is typically determined manually and limited to time consuming calculations conducted infrequently and may not provide conclusive results. Electronic flowmeters (EFM) installed in most wells today make large data volumes for monitoring available but cannot reasonably be processed and affirm the need for automation. The subsequent objective of this thesis lies in the evaluation of available methods to monitor the performance of gas storage wells using EFM data. Proposal and implementation of an automated performance monitoring approach is intended, coupled with more efficient data processing. The RAG data management system is used for the case study and was reviewed in detail. An extensive literature review was conducted, evaluating performance monitoring techniques in general and with focus on gas storage wells as well as automation. From the research, an integrated, qualitative and automated performance monitoring workflow using an adaptive sub- module system is proposed. The system is based on continuous skin monitoring over time with sub- modules including bottomhole pressure conversions, PVT add- in, test detection, graphical presentation of results and field specific, optional add- ins. Complexity and time constrains postpone the recommendation to a follow- up. From additional literature research, an alternative open- source monitoring tool with similar workflow was detected and analyzed in detail. The technically rigorous tool with limitations especially in transparency of workflow was tested for applicability to RAG wells. The numerical results indicate a consistent performance over the investigated period but cannot be taken conclusively and require more representative investigations of longer time periods and more wells. It is also shown that results have to be taken qualitatively due to complexity of the model and uncertainty in reservoir properties. A new, more efficient database system proposed was also tested using the open- source tool and showed equal accuracy using less data. In addition to well monitoring, an analytical method for quick and reliable determination of reservoir pressure from stabilized shut- in periods is presented. Extrapolation techniques are proposed for wells with limited shut- in periods available and are shown to approximate stabilization pressure accurately. The integrated system review showed that generalizations in automation are cumbersome with complexity and uniqueness of petroleum systems. Every reservoir and well has to be analyzed individually for possibilities of monitoring and when using automated systems, methods have to be reviewed and can rarely be used quantitatively. 
Translated title of the contributionSmart UGS
Original languageEnglish
  • Griess, Bernhard, Supervisor (external)
  • Hofstätter, Herbert, Supervisor (internal)
  • Pichelbauer, Johannes, Co-Supervisor (external), External person
Award date14 Dec 2012
Publication statusPublished - 2012

Bibliographical note

embargoed until 23-10-2017


  • Performance Monitoring
  • Smart
  • UGS
  • Gas Storage

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