Towards a Fully Automated Well Management System for ESP Surveillance and Optimization in PDO
- Rahul Kulkarni (Petroleum Development Oman) | Atika Al-Bimani (Petroleum Development Oman) | Antonio Andrade Marin (Petroleum Development Oman) | Abdullah Awaid (Petroleum Development Oman) | Issa Balushi (Petroleum Development Oman) | Salim Al-Busaidy (Petroleum Development Oman) | Mohammed Al-Murad (Petroleum Development Oman) | Nitish Kumar (Weatherford) | Rahul Gala (Weatherford) | Eduardo Marin (Weatherford)
- Document ID
- Society of Petroleum Engineers
- SPE Middle East Artificial Lift Conference and Exhibition, 28-29 November, Manama, Bahrain
- Publication Date
- Document Type
- Conference Paper
- 2018. Society of Petroleum Engineers
- 7.6.4 Data Mining, 2 Well completion, 2.3 Completion Monitoring Systems/Intelligent Wells, 3.1 Artificial Lift Systems, 3 Production and Well Operations, 3 Production and Well Operations, 7.6 Information Management and Systems, 5.6 Formation Evaluation & Management, 3 Production and Well Operations, 3.1.2 Electric Submersible Pumps, 2.3.2 Downhole Sensors & Control Equipment, 5 Reservoir Desciption & Dynamics, 3.1.7 Progressing Cavity Pumps, 5.6.4 Drillstem/Well Testing, 7 Management and Information, 3.1.1 Beam and related pumping techniques
- Exception Based Surveillance, Production Optimization, Electrical Submersible Pump, Pattern Recognition, Automated Well Modeling
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Achieve operational excellence in field of Electrical Submersible Pump (ESP) surveillance and optimization by benefitting Petroleum Development Oman (PDO) asset teams in identifying optimization opportunities, use of real time data for well test validation and improving overall asset KPIs (Key Performance Indicator) through a fully automated Well Management System (WMS).
The ESP well models are built and sustained in WMS by automated processes to update recent well model information from PDO corporate databases.
WMS provides real time well and pump information, along with well model based calculated outputs, pump operational status, workbenches to validate well tests, design inputs, modeling sensitivities for users to perform daily tasks using well-defined standard operating procedures.
Operating envelopes based Exception Based Surveillance (EBS) were improved by replacing them with pattern recognition based EBS to improve accuracy, avoid wastage of time and resources. Continuous hands on coaching were conducted to users to strengthen their skills.
Since implementation of WMS, it has maintained more than 1600 ESP well by building well models automatically for new or workover ESP wells successfully saving huge effort and time from engineers in gathering data and building model.
Production Engineers have created more than 100 ESP design input datasheet using the WMS resulting in improved ESP design by avoiding human errors.
WMS have already supported assets in identifying around 138 ESP wells with optimization opportunity resulting in increasing around 3 % net oil gain only in year 2017.
Real time pump operational status calculation from WMS and sensitivity (Tubing Head Pressure and Hz) based operating point analysis reduced upthrust / downthrust ESP wells by ~50% across PDO in few months.
Early detection through Pattern Recognition based EBS has resulted in minimizing ESP downtime by around 30% through quick realization of sub-optimum wells.
Validating well tests utilizing downhole gauge data has helped in identifying dubious well tests because of faulty well test equipments thus saving time and money for sequencing the well for re-test and improving allocation.
A proper tool and SOPs utilization tracking mechanism is already in place highlighting areas for continuous improvement.
The utilization of real time data and well model together has proven to be a unique and novel way in improving ESP surveillance and optimization for managing around 1600 wells.
The replication of same methodology is already undertaken for Progressive Cavity Pump (PCP) and Beam Pump (BP) surveillance and optimization utilizing WMS for PDO assets.
|File Size||3 MB||Number of Pages||23|
SPE Paper IPTC 17413 on ESP Well Surveillance using Pattern Recognition Analysis - PDO, by Harith Al-Muqbali; Abdullah Awaid; Atika Al-Bimani; Zeyana Al-Yazeedi,, Humood Al-Sukaity, Khalfan Al-Harthy - Petroleum Development Oman; Alastair Baillie; Engineering Insights Ltd. Presented also before SPE - Gulf Coast Section Electric Submersible Pump Workshop, The Woodlands, Texas April 24-26 2013
SPE Paper presented on ESP Surveillance & Optimization by Integrating automated Well models & measured down-hole data & ESP pump Curves at Real Time Atika Al-Bimani, Angus Mackay, Antonio Andrade Marin, Zeyana Al-Yazidi, Waleed Al-Qarshobi, Khalfan Al-Harthy, Abdullah Al-Awaid & Harith Al-Muqbali - PDO. Mukhtar Kadiri, & Nitish Kumar - Weatherford before SPE ESP Workshop, The Woodlands, Texas April 2016
A web-enabled, integrated surveillance: optimization & control tool, LOWIS system: Pilot Case History in ESP oil fields in Petroleum Development Oman (PDO) by Atika Al-Bimani, Salim Al-Busaidi, Waleed Al-Qarshoobi and Saud Al-Nabi - PDO; Mukhtar Kadiri - Weatherford. Presented before SPE ATW in Egypt 2010 & Middle East Artificial Lift Forum (MEALF) in Bahrain 2011