Gaining Value from Complete Automation of Progressive Cavity Pumps Well Models through Improved Optimization Processes
- Istejdad Al-Baomar (Petroleum Development Oman) | Antonio Andrade (Petroleum Development Oman) | Mohammed Al-Sawafi (Petroleum Development Oman) | Conny Velazco Quesada (Petroleum Development Oman) | Atika Al-Bimani (Petroleum Development Oman) | Issa Al-Balushi (Petroleum Development Oman) | Carlos Moreno Gomez (Petroleum Development Oman) | Salim Al-Busaidi (Petroleum Development Oman) | Mohammed Murad (Petroleum Development Oman) | Ahmed Yahyai (Petroleum Development Oman) | Majid Mahrooqi (Petroleum Development Oman) | Abdullah Riyami (Petroleum Development Oman) | Rahima Mujaini (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
- Well Models, Progressive Cavity Pump, Exception Based Surveillance, Production Optimization, Automated Well Model
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- 52 since 2007
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The objective is to increase production and run life of 1200 Progressive Cavity Pumps (PCP) wells for Petroleum Development Oman (PDO) which contributes 19% of its total production. This project also intends to improve efficiency in the management of continuously growing (100+ annually) PCP population utilizing improved surveillance and optimization techniques through automated physics-based models linked with real time data and advanced data analysis.
The primary challenge in accomplishing automated well modeling was data collection from right corporate databases with good quality. Proper workflows were designed for vendors to enter identified 42 critical data from installation/commissioning reports. Catalogs and engineering validations were prepared to ensure data consistency and highlight human errors during data-entry.
The Well Management system (WMS) was integrated with corporate databases to read required data and perform additional data quality checks/validation while building the PCP model. Furthermore, WMS was enabled to utilize measured gross, Torque, RPM and Intake pressure or fluid level to tune model automatically in real time to reflect actual well conditions.
A pilot was conducted on 14 PCP wells to establish a system that automatically generates and updates well models to provide complete accessibility of available invested resources to production engineers.8% net oil gain was identified from 50% of these wells based on optimization sensitivities.
Full Time Engineer's actual work hours reduced from 8 hours to 15 minutes for PCP optimization, hence enabled quick decisions making process. Inferred production calculation enabled engineers to monitor well performance and estimate daily production allocation between distant well tests.Simultaneously, PDO corporate database data quality issues were identified for improvements, with subsequent positive feedbacks from the automated well modeling process.
This project achieved complete standardization of PCP activities from design to commission using well-defined standard operating process and provided one version of truth to PDO engineers.Integrating physics based well model, well test information and real time data from sensors into a single platform has been able to identify hidden opportunities for production gain, perform proactive well diagnostics and increase engineers’ productive time.
Furthermore, automated well modeling has delivered benefits across multiple streams by building a platform for future data analytics projects with improved overall data quality of PDO corporate databases. Transitioning from need based well modeling using stand-alone applications and utilizing heterogeneous data from different sources to an integrated and automated Well management System has created an environment for the company to achieve their goals of accelerated net oil gain, improved run life and faster decision-making process.
|File Size||2 MB||Number of Pages||18|
ESP Surveillance & Optimization by Integrating automated Well models & measured down-hole data & ESP pump Curves at Real Time byAtika Al-Bimani, Angus Mackay, Antonio Andrade Marin, Zeyana Al-Yazidi, Waleed Al-Qarshobi, Khalfan Al-Harthy, Abdullah Al-Awaid & Harith Al-Muqbali - PDO. Mukhtar Kadir, & Nitish Kumar – Weatherford. This paper was presented at the 2015 Society of Petroleum Engineers - Gulf Coast Section Electric Submersible Pump Workshop held in The Woodlands, Texas April 24-26 2015
SPE-185135-MS: Successful Standardization and Sustainable Well Management System for ESP well Surveillance & Optimization across PDO byAtika Al-Bimani, Rahul Kulkarni, Harith Al-Muqbali, Angus Mackay, Antonio Andrade Marin, Assad Al-Busaidi, Shaymaa Touqi, Zeyana Yazeedi, Abdullah Awaid, Khalfan Harthy, Faris Kharusi – PDO & Nitish Kumar, Shyam Gupta – Weatherford. This paper was presented at the SPE Electric Submersible Pump Symposium held in The Woodlands, Texas, USA, 24–28 April 2017.