Digital Fields Surveillance and Prescriptive Production Enhancement Candidate - Operator Case Study
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Published:2022-10-31
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Container-title:Day 4 Thu, November 03, 2022
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Author:
Sidek Sulaiman1, Bin Ismail Muhammad Aaqil1, Nik Khansani Nik Zarina Suryana1, Shekhawat Dushyant Singh2, Vo Nghia Tri2, Fuenmayor Roberto2, Devgun Vishal2
Affiliation:
1. PETRONAS Carigali Sdn. Bhd. 2. Schlumberger
Abstract
Abstract
In this paper, the authors will discuss a systematic approach to digitalize field surveillance and identify Production Enhancement (PE) opportunities by incorporating dynamic Well Operating Envelopes (WOE). The approach considers multiple components of the producing well's technical restrictions and constraints such as reservoir management, downhole completions, tubing/piping erosion and surface production facility.
It is always a challenge to operate production wells daily as it involves multiple factors such as reservoir depletion, formation damage, and/or aging equipment. The failure of not being able to recognize and control well production behaviors may lead the producers unable to meet production targets and other severe issues like well integrity.
In the oil and gas industry, well performance management is a vital component of optimizing production systems. Hence, WOE must be accurately defined to maintain asset integrity as well as reasonable production forecasts from available resources.
The digital solutions include the development of prescriptive model-based technical workflows that employs a visualization tool to graphically represent the WOE with integrated performance dashboards to enable informed and optimal decision making. The solution leverages traditional petroleum engineering analyses and continuously enriched lookback knowledge base workflow combined with proven business logic to automatically and autonomously: Identify underperforming wells through their performance signatures.Check the quality of multi-disciplinary input data and engineering models integrated with a digital ecosystem to ensure the back-end solution engine can generate valued information for actionable recommendations.Predict potential concerns to ensure the producers are functioning in a safe and stable manner.Determine root causes and recommend appropriate remedial actions/opportunities to optimize production performance.Probabilistically quantify production gain, evaluate economic viability, and estimate the chance of success.
This method has been used in several fields and wells with various completion types and field-wide constraints, and it has proven to be flexible enough to accommodate the possible differences between well types and field peculiarities. The case study presented in this paper will demonstrate some of the benefits realized including improved reservoir management and optimization opportunities identified (i.e. flowline pressure debottlenecks, reservoir stimulation, gaslift valve change, well bean-up, behind casing opportunity, etc.). In addition, the visualization tool has been used for exception-based surveillance (EBS), which has proven to improve our response time resulting in better deferment management. Furthermore, the visualization tool has been used to carry out exception-based well surveillance that has proven to improve our response time on well deviations for better deferment management.
The collaborative approach between Operator and Solution Partner has enabled digitalization of field surveillance and PE candidate identification for an effective and efficient Reservoir, Well and Facility Management (RWFM) to protect the base production and maximize asset value within the safe limits on a day-to-day basis.
Reference5 articles.
1. Mario, C. C., Saputra, R., Saefuddin, S.. 2019. Well Opportunity Register, Define and Selection: Changing the Game in Production Optimisation Using Automation and Analytics. Paper presented at the SPE/IATMI Asia Pacific Oil and Gas Conference and Exhibition, Bali, Indonesia, 29-31 October. SPE-196326-MS. https://doi.org/10.2118/196326-MS. 2. Mario, C., Saputra, R., Saefuddin, S.. 2020. Developing a Smart Workover and Intervention Strategy, Using Automation and Advanced Data Analytics. World Oil (June): 29–32. https://www.worldoil.com/magazine/2020/june-2020/features/developing-a-smart-workover-and-intervention-strategy-using-automation-and-advanced-data-analytics. 3. Islamov, R., Motaei, E., Madon, B., Abu Bakar, K.A., Hamdan, V., and W M Zani, L (2021). Maximising Asset Value through Implementation of Dynamic Well Operating Envelop. Paper presented at the International Petroleum Technology Conference, 23 March - 1 April 2021. IPTC-21768-MS. https://doi.org/10.2523/IPTC-21768-MS. 4. Sahu, S.K., Singh, A., Balushi, M.Al, and Konwar, A. (2014). Exception-Based Surveillance - Integrating Well Models, Real Time Production Estimates and Hydrocarbon Accounting Tool in Well Operating. Paper presented at the International Petroleum Technology Conference, Kuala Lumpur, Malaysia, 10-12 December 2014. IPTC-17981-MS. https://doi.org/10.2523/IPTC-17981-MS 5. Sinha, R. R., Songchitruksa, P., Holy, R.. 2020. Well Portfolio Optimization: Rapid Screening of Production Enhancement Opportunities. Paper presented at Abu Dhabi International Petroleum Exhibition and Conference. Abu Dhabi, UAE, 9-12 November 2020. SPE-203458-MS. https://doi.org/10.2118/203458-MS.
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