Title
Data-driven detection of well events in mature gas fields
Author
Poort, J.P.
Shoeibi Omrani, P.S.
Vecchia, A.L.
Publication year
2020
Abstract
The production optimization of mature gas fields is severely complicated by the occurrence of certain undesired well events such as salt precipitation, liquid loading, or gas/water coning. Learning from production data of periods in which such events have taken place could help operators improve the process optimization. However, due to the current manual process of interpreting production data, many well events can go unreported. Reanalyzing historic data could retrieve missed events, but this is a time-consuming and costly process. In this study, the dynamic time warping (DTW) algorithm was used in a developed workflow that automates the process of detecting well events which can be operational both in an offline and real-time manner. Such a workflow supports operators in finding well events within production data based on characteristics of target events provided by operators. Based on a case study using field data for a gas well suffering from salt precipitation, the workflow has been proven to be accurate and significantly computational-efficient in finding 8 new events which were not detected by the operator. Additionally, the algorithm was robust in detecting well events even after introducing up to 10% of added noise.
Subject
Natural gas well production
Optimization
Precipitation (chemical)
Dynamic time warping algorithms
Liquid loading
Manual process
Mature gas field
Production data
Production optimization
Salt precipitation
Workflow support
Gas industry
To reference this document use:
http://resolver.tudelft.nl/uuid:4d25454c-c980-4db1-acc4-e4141c5ea8f5
DOI
https://doi.org/10.3997/2214-4609.202032034
TNO identifier
955343
Publisher
European Association of Geoscientists and Engineers EAGE
Source
1st EAGE Digitalization Conference and Exhibition, 30 November - 3 December 2020, Vienna, Austria
Document type
conference paper