Study On Corrosion Rate Prediction Of Casing Steel In CO Environment Of 2 / H ₂ S

With the exploration of the high acidy oil-gas field, the corrosion research of casing steel in CO2/H2S co-existing environment has become one of the hot topics in the corrosion field at present,but it is still lack of a common understanding of corrosion mechanism and rules as a result of coordination and synergic effect and many influential factors in CO2/H2S co-existing environment. The existing single corrosion rate prediction model or methods can not meet the demands, the existing corrosion protection studies are mostly based on the optimum material or indoor experimental study, which are lack of universality and can not meet the demands of acidy oil-gas field. Therefore, it is necessary to do the corrosion rate prediction research of the casing steel in CO2/H2S co-existing environment to guide the design of the corrosion life and corrosion-protection measures.Based on the literature review at home and abroad, to do the corrosion weight-loss tests on the N80casing steel in the CO2/H2S co-existing environment and build the related mathematical model of corrosion. Afterward, through mathematical algorithms to predict corrosion rates and to prove its effectiveness. Finally, do the comparative analysis of the corrosion-protection measures on prevenient research at home and abroad. Specific research contents and the results obtained are as follows.According to indoor simulation of weight-loss tests of N80casing steel in CO2/H2S co-existing environment, exploring the synergy patterns and interaction mechanism affected by many influential factors in the corrosion process under specific experiment conditions, and analysis the main reasons led to the transformation law. And using the microanalysis methods, such as scanning electron microscope(SEM), energy dispersive X-ray spectroscopy(EDS), glancing angle X-ray diffraction (XRD) to analyze the surface profile, structure and chemical character of the corrosion product film, the results show that there is no corrosion products of CO2, all the corrosion products are iron sulfides.Based on the corrosion mechanism and law, experimental analysis and experimental data to build the mathematical models in three different conditions, which means to build the mathematical model when the CO2or the H2S plays a dominant role, or under the collaborative competition relations between CO2and H2S in the corrosion process, then taking advantage of the mathematical models to draw the corrosion distribution map, which could show the transformation law of corrosion rate with the pressure of CO2and H2S clearly.To predict corrosion rate of N80casing steel by the established BP neural network model in the CO2/H2S environment, which demonstrates the model has a high forecasting precision. In order to overcome the disadvantages and play the sufficient role of the BP neural network,using the genetic algorithm to optimize the BP neural network to build the model and predict the corrosion rate again. Compared with the BP neural network prediction, the optimization of BP neural network based on genetic algorithm shows that the network training converges is more quickly, the prediction is more accurate, and the generalization ability is strengthened,which also proves the optimization of BP neural network based on genetic algorithm is a suitable tool to predict the corrosion rate of casing steel in the CO2/H2S environment.Through the analysis and summary on three kinds of corrosion-protection measures applied in the oil-gas well with CO2/H2S at home and abroad, and then compared and analyzed both the advantage and shortage, and put forward the choice of the main anti-corrosion objects and the corrosion-protection measures should be based on the CO2/H2S corrosion mechanism and law in the well conditions.