|Content Type||Conference Paper|
|Title||Improvements on de Waard-Milliams Corrosion Prediction and Applications to Corrosion Management|
|Authors||Bernardus F.M. Pots, Sergio D. Kapusta and Randy C. John, Shell Global Solutions US; M.J.J. Simon Thomas and Ian J. Rippon, Shell Global Solutions International; T.S. Whitham, Shell Research Ltd.; Magdy Girgis, Shell Canada Ltd.|
|Source||CORROSION 2002, April 7 - 11, 2002 , Denver, Co|
|Copyright||2002. NACE International|
This paper describes corrosion rate prediction models for the main corrosion mechanisms of carbon steel in Exploration and Production service. The models succeed earlier work by De Waard, Milliams, and Lotz. The paper emphasizes that model accuracy is less of an issue than knowledge of the key corrosivity parameters and the quality of the corrosion control system. Models will be described for the following mechanisms: CO2 corrosion, CO2/H2S corrosion, HES corrosion, organic acid corrosion, oxygen corrosion, and microbiologically-induced corrosion. Application limits will be indicated. A good comparison with high-quality lab data is only possible for the CO2 corrosion mechanism. Computer programs will be described in which the corrosion prediction models are applied for front-end design and facility integrity management. Use of these programs during the lifetime of a facility provides a way of focusing on corrosion control issues and they are therefore essential tools for pro-active corrosion management.
The ability to confidently predict the internal corrosion of E&P carbon-steel facilities is essential for both from-end design materials engineering and for managing lifetime integrity through optimum corrosion control. While this paper will describe an improved way of CO2 corrosion rate prediction as a follow-up of the Shell De Waard-Milliams-Lotz school 1'2'3, the paper will also consider other corrosion mechanisms. These other mechanisms are: CO2/H2S corrosion, H2S corrosion, organic acid corrosion, corrosion by other acids (particularly spent stimulation acids), oxygen corrosion, and microbiologically- induced corrosion. Prediction models for these mechanisms are expected to help the corrosion risk identification and assessment processes and to find the optimal means of corrosion control and management. For example, too often corrosion inhibition is seen as the solution for avoiding further corrosion damage, but obviously one needs to understand the corrosion mechanism before defining the control means.
Another point of attention in the paper will be the link of corrosion prediction models to field application. Such a link is essential and it puts the model in the right perspective. It helps to quantify the requirements of corrosion control, such as, for example, corrosion inhibition availability, gas dehydration system availability or corrosion allowance. As such, the paper gives an overview of our latest position with regard to corrosion prediction and its application to corrosion control management.
|File Size||1802 KB||19|