Integrated Operations IO: Production Management System Goes Dynamic Using Online Transient Modelling

Autor: Willem Sepulveda, Azhar Ahmad, Onno van Wolfswinkel, Muzahidin Muhamed Salim, Nur Erziyati Seruji, Colinus Lajim Sayung, M Kasim M Som, M Agus Nukman M Mabror, Andreas Kimsaas, Ram Kumar, Shripad Biniwale, Jingmei Zhao, Julia Borovik, Zul Izzi B Ahmad
Rok vydání: 2016
Předmět:
Zdroj: All Days.
DOI: 10.2118/182497-ms
Popis: This paper discusses a case study of a 42-year-old mature offshore oilfield. For this field, with declining production trend and timeworn equipment and technology, understanding and analyzing the transient flow is not a well-defined process. The Integrated Operations (IO) project was kicked-off in 2012 in order to deploy an Asset Management Decision Support tool. One of the focus areas was ‘Flow Assurance Management’ to overcome challenges of well slugging, liquid surge management and to establish guidelines for Start-Up and Ramp-Up processes. Traditionally in this field, most decisions were based on steady-state well and network modelling without much emphasis on transient behavior. Moreover, lack of instrumentation and manual data processing and model updates made it difficult to estimate current reservoir/operating conditions accurately to support real-time decision making. To overcome these issues, a Dynamic Production Management System (DPMS) was designed and implemented based on a dynamic flow model describing multi-phase flow in the gas lifted wells of the field. This paper describes the system and how it aids in better understanding of flow performanxce issues, collaborative decision making, and improved communication between various operational locations and disciplines. As part of the IO project, Real-Time field measurements (pressure, temperature, flow etc.) were captured at high frequency (seconds) & validated to ensure the desired data quality. These measurements were automatically used as boundary information by the model which calculates pressure, temperature, flows and volumes in real time throughout the field. The model is used in different modes: (1) For real-time surveillance, the online model provides a series of virtual instruments at locations without actual instrumentation in the field. (2) For advance warning, a separate transient model is executed faster than real-time to predict future events for Slug/Surge Management. (3) Finally the model is also used for planning activities, such as Start-up/Ramp-up or pigging and can predict any alarming issues during these operations. Thus DPMS assists production engineers and operators to make proactive decisions for effectively managing flow assurance challenges and adds value in various areas. Surveillance: Continuous, real-time monitoring of operating conditions within the network, along with prediction of future conditions within the inlet separators.Safety (HSE): Prevention and mitigation of facility trips/shut-down due to slug and surge issues during start-up/ramp-upEfficiency: Improved utilization of engineers' time and experience with increased focus on data analysis instead of data manipulation.Production Gain: Proactive field management for improved production, rather than reactive decisions that lead to deferred production.Dynamic PMS: The system will help to fully optimize wells, networks and facilities in order to produce and operate asset to its fullest potential by minimizing unexpected downtimes It's one of the first fields in Asia to implement an integrated DPMS using the online transient model concept as a basis for effective, real-time and proactive decision support.
Databáze: OpenAIRE
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