Real-Time Production Surveillance and Optimization in a Mature Subsea Asset

Topics: Intelligent fields/surveillance Subsea systems

A real-time production-surveillance and -optimization system has been developed to integrate available surveillance data with the objective of driving routine production optimization. The system aims to streamline data capture, automate data quality assurance, integrate high- and low-frequency data to extract maximum value, optimize the design and analysis of commingled well tests, and provide real-time multiphase well-rate estimates for continuous well‑performance evaluation.


The technology was piloted in an offshore field consisting of stacked deepwater channel deposits developed with five individual subsea drill centers, 15 active oil producers, one gas injector, and five water injectors. Equipment is controlled remotely, and produced ­fluids are routed to surface by two 8-in. risers from each drill center. Produced gas is treated for use as fuel gas on the surface and for gas lift by reinjecting into each production well. All wells were originally deployed with a full suite of instrumentation, as well as valve-­status sensors for each well flowline and riser. The three-phase separators on the surface use orifice plate meters for rate measurement.

The approach taken was to integrate real-time data and physical models for real-time production surveillance and optimization. The deployed system uses software that incorporates in-house-developed techniques for continuous model tuning. First, a complete integrated production model (IPM) of the production system was built, spanning reservoir inflow and wells on the one hand and flowlines, risers, and topsides on the other. The IPM is embedded in a field management software platform that houses several standard work flows as well as proprietary algorithms. Calculation results and real-time data are visualized with a visualization application.


This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 181103, “Real-Time Production Surveillance and Optimization at a Mature Subsea Asset,” by Xiang Ma, Zachary Borden, Paul Porto, Damian Burch, Nancy Huang, Paul Benkendorfer, Lynne Bouquet, Peng Xu, Cassandra Swanberg, Lynne Hoefer, Daniel F. Barber, and Tom C. Ryan, ExxonMobil, prepared for the 2016 SPE Intelligent Energy Conference and Exhibition, Aberdeen, 6–8 September. The paper has not been peer reviewed.
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Real-Time Production Surveillance and Optimization in a Mature Subsea Asset

01 March 2017

Volume: 69 | Issue: 3