SPE 130768 Multi-Field Asset Integrated Optimization Benchmark

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Project Description

SPE 130768 Multi-Field Asset Integrated Optimization Benchmark

Silvya Dewi Rahmawati, SPE, NTNU | Curtis Hays Whitson, SPE, NTNU/PERA | Bjarne Foss, SPE, NTNU | Arif Kuntadi, SPE, NTNU

SPE EUROPEC/EAGE Annual Conference and Exhibition, Barcelona, Spain, 14–17 June 2010

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Integrated modeling of multi-field assets, from subsurface to market, is challenging due to the complexity of the problem. This paper is an extension of the SPE 121252, model based integration and optimization gas cycling benchmark [Juell, et al., 2009], extending two gas-condensate fields to two full-field multi-well models. Additionally, a full-field model is added to the Juell benchmark, introducing an oil field undergoing miscible WAG injection, where most data are taken from the SPE 5 Reservoir Simulation Comparative Project. All reservoir models are compositional, but using different EOS representations. A base case scenario is defined with fixed numbers and locations of producers and injectors.

A common field-wide surface processing facility is modeled with emphasis on water handling, NGL extraction, sales-gas spec, and gas reinjection. The surface process model interacts with the three reservoir models through two main mechanisms – (1) water- and gas-handling constraints, and (2) distribution of available produced gas for reinjection into the three reservoirs.

The field asset model provides long-term production forecasts of gas, oil, and NGL revenue. Cost functions are introduced for all major control variables (number of wells, surface facility selection and operating conditions, injection gas composition). Net present value is used as the target objective function.

This paper will evaluate optimal production strategies for the base case benchmark problem, using several key control variables and field operational constraints. Optimization performance will be tested with a few solver algorithms. The benchmark will be provided to the industry through application data files, network infrastructure, and results from our integrated optimization model.

Copyright 2010, Society of Petroleum Engineers