51316-7888-Modeling and Prediction of Corrosion of Steel Tubular in SAGD/CO2 Co-Injection System

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Product Number: 51316-7888-SG

ISBN: 7888 2016 CP

Author: Frank Cheng

Publication Date: 2016

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As an in-situ enhanced oil recovery (EOR) technology steam-assisted gravity drainage (SAGD) has been successfully applied for the past two decades to produce bitumen from Alberta’s large oil sands deposits. CO2 injection is presently a commonly used tertiary EOR technique for conventionl and heavy crudes not only effectively reducing the viscosity of oil but also contributing to a reduction in greenhouse gas emission. Taking advantage of SAGD and CO2 injection by combining the two processes for in situ production of bitumen is of industrial interest but so far has not been tried on commercial scale.One of the main issues identified when considering the co-injection of CO2 with steam for SAGD is the potential for accelerated corrosion of the carbon steel tubulardue to the addition of extra CO2 into the system.In this work mechanistic models were developed to understand and quantify the corrosion of the injection tubular under the SAGD/CO2 co-injection conditions by well integrating the fluid mechanics sub-model and electrochemical corrosion sub-model. A computational fluid dynamics (CFD) sub-model was developed to simulate the gas-liquid binary fluid flow in injection tubular. The flow pattern distribution of water phase and wall shear stress were determined with the considerations of the parametric effects such as temperature pressure tubular diameter CO2 content etc. The CFD sub-model provides information of the location of water accumulation for corrosion occurrence. Thermodynamic calculations were performed to determine the water chemistry. Electrochemical kinetics was calculated to predict the corrosion rate of steel under the given condition. The role of corrosion scales which may include FeCO3 or Fe3O4 or both under the high-temperature conditions was discussed and incorporated into the corrosion rate modeling. Validation of the modeling results was performed by a comparison with the published data which shows a high accuracy of the developed model.