Recently, in the oil and gas extraction and transportation field, much attention has been paid both to increase efficiency and to reduce the environmental impact of the extraction techniques that, by now, consists mainly on Enhanced Oil Recovery processes based on gas or water injection into the reservoirs. Thus, compressor trains are a crucial part of the overall plant, and they require precise performance estimation during the whole oilfield lifespan, when production rates and compression demands significantly change. For this reason, in compression plant design and in-service behavior prediction, modular simulation codes turns out to be the best choice respect to tools for specific plant configuration, since they provide flexibility without losing accuracy. In this paper, a new modular tool for compression plant simulation is described; it is based on a wide database of centrifugal compressors and a library of elementary components that can be freely assembled to build any plant's configuration, regardless of its layout. The code's numerical solver is the implementation of a trust-region Gauss-Newton method, called TRESNEI, which possess a larger convergence region than standard Newton methods. The performance of the code has been tested on two compression train arrangements with both series and parallel-mounted compressors; comparison with the solution of the test cases obtained with a dedicated pre-existing in-house code, shows a good matching between the results. Computational speed and robustness of the new code is also shown.
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