Optimizing CAPEX and OPEX for High CO2 and H2S Field by Using Mechanistic Corrosion Modelling Approach
Abstract The gas contaminants especially CO2 and H2S from the well is a major threat to oil and gas production facilities and pipeline. Developing this type of reservoir cost enormous CAPEX and OPEX due the need for expensive materials or the need of continuous chemical injection. This paper outlines the opportunity of cost optimization for future field development and operational through mechanistic corrosion modelling approach. This method was embedded to an in-house corrosion prediction model that was first developed by collaboration with Ohio University in 2008 with capability to predict corrosion rate for partial pressure more than 20bar of CO2 and up to 1bar of H2S. The model validation was performed based on actual field production operated at 55°C and 22 bar of CO2 partial pressure followed the methodology as outlined in NACE paper C2012-0001449. Upon successful validation, the model has been deployed to assist an Operator of an offshore pipeline in Southeast Asia, operating at 97°C and 17 bar of CO2 partial pressure, to ascertain the risk due to CO2 corrosion and review the original pipeline design adequacy. Subsequently, the model has been utilized for an Operator of onshore facilities in Middle East to address specific issue encountered during the final stage of development for one of the wellpad in which the wells are expected to experience increase of H2S from 100ppm in original design to more than 1000ppm during actual production. This process changes raised a serious concern on the integrity of the materials as potential corrosion issue and the need for corrosion mitigation such as H2S Scavenger injection was not originally considered during early stage of engineering. The corrosion rate from the model has been validated against the intelligent pigging (IP) data and proven to be able to predict corrosion rate with +20% accuracy and more than 99% confidence level for CO2 partial pressure up to 25 bar with the presence of H2S. Based on deployment and utilization of the model, the high confidence in the model ability to accurately predict the corrosion rate will lead to potential CAPEX and OPEX optimization for the field development and during operational stage.