Analysis of field and ownership allocation uncertainty in complex multi-field configurations

Analysis of field and ownership allocation uncertainty in complex multi-field configurations

ABSTRACT: Current focus on cost-effective developments of new hydrocarbon fields aims at exploiting the capacity of existing production units to the maximum using a number of tie-ins to subsea developments. This results in increasingly complicated process flows, where individual multiphase streams may or may not be measured. This increased complexity makes design and analysis of allocation systems a challenging task.

Allocation principles, metering system setup, use of test separator time, ownership structure, flow rates and life time profiles are all factors which affect the field and ownership allocation uncertainty. In order to find how each field or each owner is exposed to economic risk associated with measurement and allocation uncertainty, an uncertainty analysis combined with a risk-cost-benefit analysis should be carried out. Traditionally, the analysis of such allocation systems is based on analytic calculations. These calculations increase rapidly in complexity as the process flow becomes more complicated. For systems with several tie-ins and satellites, and with a fragmented ownership, powerful numerical methods are required to perform this analysis.

This paper demonstrates the calculation of field and ownership allocation uncertainty for realistic measurement setups and allocation scenarios in a multi-field setting based on industrial projects. A flexible framework for analysis of complex multi-field configurations is used in these numerical calculations, which are based on an ISO GUM (ISO/IEC, 2008) compliant Monte Carlo technique.

Further on, it is demonstrated how different field configurations, ownership structures, allocation principles, meter uncertainties and flow rates affect the total cost and risk for each owner. This investigation includes the exposure to economic risk associated with measurement uncertainty associated with the different alternatives. We also give examples of how the lifetime cost of the metering system may vary depending on choices in allocation principle, flow rate profiles, as well as placement and calibration scheme of the individual meters. A particular focus of our work is how each owner is exposed to misallocation risk. In this context it is mandatory to take into account the correlation between the uncertainties in the field-allocated streams. Failure to include these correlations may result in erroneous estimations of each owner’s economic exposure due to misallocation, and may thus potentially result in sub-optimal field developments.

Through realistic example systems based on industry projects, it is shown how an uncertainty analysis combined with a risk analysis may provide valuable insight into the exposed economic risk for each owner due to misallocation. It is demonstrated how thorough knowledge and understanding of the allocation uncertainty is essential in order to minimize each parties’ economic exposure, especially in real-life complex allocation systems.