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Authors
Elgsæter, Steinar M.; Kittilsen, Pål; Hauger, Svein Olav

Digital Object Identifier (DOI)
10.3182/20120531-2-NO-4020.00011

Page Numbers:
157-162

Index Terms
Production Optimisation: Coupling of production data and transmission systems with numerical modeling and optimization and decision support applications for the reservoir and production system; Subsea Production

Abstract
Model-based online applications such as soft-sensing, fault detection or model predictive control require representative online models. Basing models on physics has the advantage of naturally describing nonlinear processes and potentially describing a wide range of operating conditions. Implementing adaptivity is essential for online use to avoid model performance degradation over time and to compensate for model imperfection. Requirements for identifiability and observability, numerical robustness and computational speed place an upper limit on model complexity. These considerations motivate the design of balanced-complexity physical models with adaptivity for online use. Techniques used in the design of balanced complexity models are given with examples from oshore oil and gas production. Despite potential benefits, the effort required to implement balanced-complexity models,particularly at large scales, may deter their use. This paper presents a Modelica-based approach to reduce implementation effort by interfacing exported Modelica models with application code by means of a generic interface. The suggested approach is demonstrated by parameter estimation for a subsea well-manifold-pipeline system.

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