Samarang field is located offshore Sabah, East Malaysia with first oil in 1975. Majority of the platforms are provided with fully pneumatic instrumentation / control and shutdown systems, with no provision for remote monitoring/control. This has caused limitation in acquiring data for monitoring and analyzing hence optimizing the asset. The field is undergoing a major redevelopment project with Integrated Operations (IO) being part of initiatives that covers re-instrumentation, telemetry and telecommunication infrastructure installation, Collaborative Working Environment construction and Workflows implementation.

The limitation of status quo instrumentation situation has posed challenges for Samarang asset to monitor flowing status of the wells. Consequently, a number of indirect inferences were being used to determine the status and uptime of the wells including sporadic well head observation (i.e. "feeling" or "touching" the well head assembly for vibrations) and well head fluid sampling. Added to the complexity is the flow from multiple strings and wells commingling in production headers in each of the well platforms, it is not uncommon to have cases wherein the individual string or well’s actual status and production contribution is unknown for many days (or even weeks). At best, Well Testing, which is a direct measurement of the well or string’s deliverability, is carried out once a month.

This paper describes a novel methodology of implementing workflow to achieve continuous well status monitoring objective. Workflow that combines the data feeding and processing through data driven logics as well as well models driven logics has enabled continuous well status awareness. The workflow has enabled the followings:

  1. Continuous well rate estimation using nodal analysis well model by automating data input and result output process

  2. Well flowing or quitting status inference by using wellhead pressure, temperature, valve status, gas lift injection pressure, MIG, pump voltage and frequency for natural, gas lifted as well as ESP wells

  3. Automated notification of well status through Tri-node Collaborative Working Environment

  4. Faster reaction and decision

  5. Reduction of production deferment and increase awareness to the well status and performance

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