Abstract
In general, flow measurement systems in production units only report the daily total production rates. As there is no precise control of individual production of each well, the current well flow rates and their parameters are determined when production tests are conducted. Because production tests are performed periodically (e.g., once a month), information about the wells is limited and operational decisions are made using data that are not updated. Meanwhile, well properties and parameters from the production test are typically used in multiphase flow models to forecast the expected production. However, this is done deterministically without considering the different sources of uncertainties in the production tests. This study aims to introduce uncertainties in oil flow rate forecast. To do this, it is necessary to identify and quantify uncertainties from the data obtained in the production tests, consider them in production modeling, and propagate them by using multiphase flow simulation. This study comprises two main areas: data analytics and multiphase flow simulation. In data analytics, an algorithm is developed using R to analyze and treat the data from production tests. The most significant stochastic variables are identified and data deviation is adjusted to probability distributions with their respective parameters. Random values of the selected variables are then generated using Monte Carlo and Latin Hypercube Sampling (LHS) methods. In multiphase flow simulation, these possible values are used as input. By nodal analysis, the simulator output is a set of oil flow rate values, with their interval of occurrence probabilities. The methodology is applied, using a representative Brazilian offshore field as a case study. The results show the significance of the inclusion of uncertainties to achieve greater accuracy in the multiphase flow analysis of oil production.
Highlights
Several uncertainties exist in all segments of oil and gas industries including geology, reservoir, drilling, completion, and production
Data is selected from well production tests by gathering test information and creating a dataset with measured variables that characterize the production of a well with time
Because this study focuses on the impact of uncertainty on oil flow rate response, Figure 4 was constructed with thirteen correlation matrix slices corresponding to the oil flow rate columns for each well
Summary
Several uncertainties exist in all segments of oil and gas industries including geology, reservoir, drilling, completion, and production. These uncertainties and their impacts on the segments have been studied. Few studies have been done for the production segment as the uncertainties arise from multiphase flow correlations, heat transfer into the flow, reservoir data, measurements, and data computing; which influence the production test results. The oil production measurement system usually reports only the daily total production rates. The flow rates and parameters of each well are measured only in the production test, which is done periodically (e.g., once a month). The production test data contain error sources including separator accuracy, equipment measurement, data obtained, and storage
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