No abstract

The oil and gas industry is faced with uncertainty in many activities. Whereas in many of its areas, such as finance, geology and reservoirs these uncertainties are already incorporated in the modelling and studies. This is not the reality when it comes to modelling artificial lift and multiphase flow. Studies related with uncertainties in oil and gas production are limited. Therefore, this paper aims to develop a methodology to identify and quantify uncertainties, obtaining thus more accurate data to be used in production modelling. In addition, the methodology intends to evaluate oil production forecasting considering uncertainty propagation in oil flow simulation software. This study was divided in statistical analysis and production forecasting. An algorithm using R software analyzed and treated production data. It was applied statistical modelling techniques to data series. Deviations from these data were adjusted to a continuous distribution that provides the parameters to be used by Monte Carlo simulation method to generate random values to be input uncertainties of the MARLIM multiphase flow simulator. Oil flow rate, as output simulator, was adjusted to a new distribution and finally the intervals of occurrence probabilities of oil flow rate forecasts. This methodology was applied to BSW (Basic Sediments and Water) data from a representative field, showing the importance of including uncertainty analysis in order to generate greater reliability and accuracy in the production flow modeling. In conclusion, the method presented excellent results when applied to BSW.

No abstract

Cooperative vehicle platooning applications increasingly demand realistic simulation tools to ease their validation, and to bridge the gap between development and real-word deployment. However, their complexity and cost, often hinders its validation in the real-world. In this paper we propose a realistic simulation framework for vehicular platoons that integrates Gazebo with OMNeT++ over Robot Operating System (ROS) to support the simulation of realistic scenarios of autonomous vehicular platoons and their cooperative control.

No abstract