This paper presents a practical methodology for the determination of error bounds in the oil back allocation procedure and its application to decision making in the development of a giant gas condensate reservoir in the Caspian region. The case study of allocating fluid rates to individual wells has been performed by adjustment of reservoir pressure and gas-oil ratio with time using computer aided analysis.This work describes improvements in well performance modelling and outlines the effective workflow whereby well performance can be estimated at any given period. The workflow has provided a cost-effective solution that reduces uncertainties in estimating production volumes at the well level. Well models are built using production well test data. These tests are usually performed at best on an annual basis for fields with a large number of producing wells. Therefore, the well models are nearly always out of date by a matter of months or even years, and the allocation factor associated with traditional models could be over the reasonable accuracy level. In addition to traditional models well performance software models have been developed and used. By adjusting the software models for predictable changes in reservoir pressure and gas oil ratio, the oil allocation factor errors can be reduced significantly. This methodology can also be applied to historical data to improve the production assumptions used to history match the field simulation model A comparative study of the different allocation methods and its impact to allocation factor errors and to net present values has been carried out, and confirmed the importance of correct oil reconciliation at the well level. IntroductionReconciliation of fiscally measured hydrocarbon production with estimated production from the associated production wells is common practice in the oil industry, particularly in gas condensate wells. This process is known as "allocation" and is important for a number of reasons including field surveillance and volumetric input to reservoir simulators (Cramer et al., 2009). Accurate production volumes availability at the outlet of the production network and at the well level is essential to the workflows which targets the economic potential optimization of the reservoir performance (Stundner and Nunez, 2006). Correct prediction of the reservoir performance helps to support operational decisions for the field development schedule and maximize reservoir's economic value (Ibrahim, 2008). Inaccuracies in production allocation consequently decrease the prediction capability of the reservoir simulator model used in investment decision making processes such as whether or not to drill more wells.Conventional gravity based test separators are used for well-testing which can lead to errors during the measurement of multiphase fluid flow from a well (API, 2005) and also leads to errors in the allocation of the fluid at the time of the well test eg liquid carry-over can cause an erroneous increase in the GOR calculation. Measurement errors of this na...