Hydrocarbon Production Optimization in Fields With Different Ownership and Commercial Interests
- Nils Fridthjov Haavardsson (Det Norske Veritas) | Arne Bang Huseby (University of Oslo) | Frank Børre Pedersen (Det Norske Veritas) | Steinar Lyngroth (Det Norske Veritas) | Jingzhen Xu (Det Norske Veritas) | Tore I. Aasheim (Det Norske Veritas)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- February 2010
- Document Type
- Journal Paper
- 95 - 104
- 2010. Society of Petroleum Engineers
- 4.3.4 Scale, 5.5 Reservoir Simulation, 5.5.8 History Matching, 5.2.1 Phase Behavior and PVT Measurements, 4.1.2 Separation and Treating, 7.1.5 Portfolio Analysis, Management and Optimization, 4.2 Pipelines, Flowlines and Risers, 4.1.5 Processing Equipment
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- 541 since 2007
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A main field and satellite fields consist of several separate reservoirs with gas cap and/or oil rim. A processing facility on the main field receives and processes the oil, gas, and water from all the reservoirs. This facility is typically capable of processing only a limited amount of oil, gas, and water per unit of time. In order to satisfy these processing limitations, the production needs to be choked. The available capacity is shared among several field owners with different commercial interests. In this paper, we focus on how total oil and gas production from all the fields could be optimized. The satellite-field owners negotiate processing capacities on the main-field facility. This introduces additional processing-capacity constraints (booking constraints) for the owners of the main field. If the total wealth created by all owners represents the economic interests of the community, it is of interest to investigate whether the total wealth may be increased by lifting the booking constraints. If all reservoirs may be produced more optimally by removing the booking constraints, all owners may benefit from this when appropriate commercial arrangements are in place. We will compare two production strategies. The first production strategy optimizes locally, at distinct time intervals. At given intervals, the production is prioritized so that the maximum amount of oil is produced. In the second production strategy, a fixed weight is assigned to each reservoir. The purpose of the weights is to be able to prioritize some reservoirs before others. The weights are optimized from a life-cycle perspective. As an illustration, a case study based on real data is presented. For the examples considered, it is beneficial to lift the booking constraints because all of the reservoirs combined can be produced more efficiently when this is done.
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