Publications

Partial Routing Allocation for Gas Production Optimization Based on Genetic Integer/ Routing Optimiser in the Tunu Field, East Kalimantan, Indonesia

Proceedings Title : Proc. Indon. Petrol. Assoc., 41st Ann. Conv., 2017

Tunu is a giant gas field located in the Mahakam River Delta of East Kalimantan, Indonesia. The field extends almost 80 km from north to south, covering almost 400 km2. Currently this field is contributing 40% of TOTAL E&P Indonesie Production from 1200 well line up in 41 Platform (PTF). The reservoirs are characterized as multilayered with perforated producing zones ranging from (MD) 700 m to 5100 m. Predicting pressure drop in pipeline networks is essential for production, forecasting, modeling and cost optimization. There are many factors affecting the complexity of the pressure drop calculation, such as fluids properties, pipe configurations, deviation of well and flow rate of fluids. However, some empiricisms are involved in order to overcome the complexity of the problem. GAP (General Application Package) was designed to eliminate artificial boundary conditions in reservoir, well and surface network models, through the creation of integrated models using PETEX tools. It is able to consider the multiphase network response of multiple wells producing into a common production system, where the response of one well can affect production of another (i.e. back pressure response). GIRO (Genetic Integer/ Routing Optimizer) was specialized in cases where wells/ manifolds routing opportunities exist. Most of the optimization problems involving routing opportunities will also contain continuous variables as multiple constraints. Considering that constraints have a non-linear response and that the imposed constraints make the problems non-convex, it will deal with Mixed Integer Non-Convex Non-Linear Optimization Problem (MINLP), with the platform provided by Resolve-IPM Module. This paper discusses matching the surface/routing configuration, PTF’s fluid properties (gas rate, pressure, temperature, API, CGR, WGR) between actual condition and the GAP model. After validating the model, this paper suggests the application of RESOLVE-IPM as a GIRO/MINLP platform to determine best partial routing allocation to optimize the gas production in the Tunu Field. Keyword: MINLP, GIRO, GAP, Resolve, routing, optimization.

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