摘要
Asphaltene precipitation,flocculation,and deposition can significantly reduce oil production by impacting wellbores,flowlines,and more importantly,formations’pore space around the well.Any alteration in the temperature,pressure and fluid composition can trigger asphaltene deposition.The ability to predict the occurrence and magnitude of the asphaltene deposition is a major step for flow assurance.An accurate prediction of the deposition envelope enables the operator to systematically categorize different cases based on their impact on the production.This critical knowledge can be used to predict the occurrence and magnitude of asphaltene deposition,which could potentially save the expense of installing unnecessary equipment and injecting chemical inhibitors when they are not needed.Predicting asphaltene-related flow assurance issues requires robust physically-based modeling capabilities for capturing the asphaltene’s deposition tendencies as a function of the prevailing field’s operating conditions.Although available simulators are found to be useful for predicting asphaltene’s phase behavior,precipitation tendency,and instability curves,they often overlook important physical characteristics of the asphaltenes.These properties may have a detrimental role in obtaining a realistic representation of the asphaltene deposition behavior.In this paper,the experimental and the numerical investigations are combined to present a comprehensive methodology for studying the thermodynamics of asphaltene precipitation and deposition.A wide range of pressures and CO2 concentrations are covered that are relevant to actual CO2 flooding in a Middle East oil reservoir.To do so,a series of lab experiments including routine and special PVT analyses where the Asphaltene Onset Pressure(AOP)and Saturation Pressures(Psat)were measured for different mixtures of CO2 and the reservoir oil.Maximum of 50 mol%CO2 concentration mixture was tested to measure the AOP and Psat.The amount of asphaltene precipitation was found between 0.25 and 4 wt%for the mixtures of 10e50 mol%CO2 concentration.Furthermore,detailed recommendations are presented in this paper to tune an EOS for running compositional simulations when unstable asphaltene is reported based on the lab experimental measurements.
