Abstract
A modelling effort was made to try to predict the life of downhole tubes or casings, synthetically considering the effect of service influencing factors on corrosion rate. Based on the discussed corrosion mechanism and corrosion processes of downhole tubes, a mathematic model was established. For downhole tubes, the influencing factors are environmental parameters and stress, which vary with service duration. Stress and the environmental parameters including water content, partial pressure of H2S and CO2, pH value, total pressure and temperature, were considered to be time-dependent. Based on the model, life-span of an L80 downhole tube in oilfield Halfaya, an oilfield in Iraq, was predicted. The results show that life-span of the L80 downhole tube in Halfaya is 247 months (approximately 20 years) under initial stress of 0.1 yield strength and 641 months (approximately 53 years) under no initial stress, which indicates that an initial stress of 0.1 yield strength will reduce the life-span by more than half.
Highlights
IntroductionFailure of the downhole tube and casing is a problem constantly disturbing oil production
Failure of the downhole tube and casing is a problem constantly disturbing oil production.Once the tube or casing, especially the tube, is corroded to perforation or cracking, the oil well may face production suspension or may even be discarded
It can be known that life-span of the L80 downhole tube in Halfaya is
Summary
Failure of the downhole tube and casing is a problem constantly disturbing oil production. The data mining models do not care about the mechanism and processes of corrosion They are mainly based on statistics from vast amounts of field data; for example, Hu et al [4] proposed a cross-scale life-time prediction model for oil tubes mainly based on statistical theory and used Monte-Carlo method as Materials 2016, 9, 741; doi:10.3390/ma9090741 www.mdpi.com/journal/materials. Developed a residual life prediction model based on elastic-plastic fracture mechanics He took the combined effects of internal pressure and axial force into consideration as the main influences, but ignored their variation with service time in his model. It is not easy to establish a model combining corrosion data and corrosion mechanism, especially when the effect of time and other influencing factors are taken into consideration Development of such model requires a combination of scientific understanding of corrosion processes and sound approaches to mathematical modelling [13]. Two criteria for failure judgment, the thickness criterion and the strength criterion, aiming at the failure caused by wall thickness thinning and strength loss, respectively, have been proposed
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