A numerical compositional one-dimensional model to predict the flow pattern and the CO2 corrosion rate of carbon and low alloyed steel tubing/casing in oil and gas production is presented. The model estimates the chemical composition of the present phases (oil/gas/water), the pH and the corrosion rate as function of depth. The effects of acid gases (CO2 and H2S) and water chemistry (Na+, K+, Ca++, Mg++, Cl-, SO4=, among others) are considered. Different flow patterns are also taken into account: bubble, slug, dispersed bubble, annular and segregated, which are determined from fluid properties and production rates of oil, gas and water.
The present tool is based on the semi empirical de Waard 95 model and a 2003 modification. For oil and vapor phases, equilibrium is considered with the Soave-Redlich-Kwong equation of state. For the water phase, the Pitzer's model is used to calculate the activity of water, and activity coefficients of cations, anions, and neutral species in the solution. To analyze flow pattern the Drift-Flux Model is used. Different modules calculate equilibrium composition, flow pattern and flow velocities. All the modules previously mentioned are coupled and require an iterative resolution at each position in the production string. The obtained outputs are temperature, pressure, flow pattern, flow velocities, gas and liquid holdup, pH, and corrosion rate.
Each of the different modules of the program were validated, however only validations of the water/gas phase equilibrium are presented in this paper. The comparison of predicted CO2 solubility in pure water, NaCl solutions and synthetic formation brine (NaCl/CaCl2 solutions) and pH show a very good fitting with experimental data. The model results for vertical/horizontal gas-oil-water well are also shown.
The Y- TubCor (YPF Tecnología Tube Corrosion) program is part of the Y-WIMS (YPF Tecnología Well Integration Management System) platform.
Corrosion has a key impact on the integrity of tube materials used in oil and gas production and transportation. The CO2 corrosion (sweet corrosion) is the most prevalent forms of attack encountered in this industry. The implication of corrosion includes its effect on capital and operational expenditures and health, safety, and the environment. This impact was the driven force for the development of Corrosion Prediction Models. The models are mainly focused on the evaluation of carbon and low alloyed steel performance. As these steels are the lower cost material alternative to be used, the models are part of the set of tools used for the material selection. Other application is to estimate the possible corrosion damage in service due to changes in environmental and/or production conditions.
