Introduction
Corrosion represents one of the main challenges for the oil industry, as it affects the integrity of pipelines, equipment, and production systems. This problem is exacerbated by extreme operating conditions, such as high pressures, temperatures, and the presence of corrosive fluids such as carbon dioxide (CO₂), hydrogen sulfide (H₂S) and water with chlorides. Under this context, NODAL Analysis, emerges as a simulation tool that allows predicting the performance of production wells, as well as corrosion problems in the components associated with these systems.
Traditionally, corrosion control has relied on inspection and preventive maintenance techniques. However, these strategies are reactive and lack the predictive capability to anticipate problems. In this context, the use of simulation tools such as NODAL Analysis offers an advanced and predictive approach to identify conditions that favor corrosion and optimize mitigation strategies.
The Nodal Wear Model (NWM) constitutes an applicable study tool to analyze the differential corrosion processes in the Peirce-Smith converter (PSC), used in the metallurgical industry, particularly in copper production. The purpose is to achieve significant improvements in the life and productivity of the various coating alternatives that could be used1.
In the oil and gas industry, corrosion of equipment and metallic structures represents a problem that affects safety, production and the environment. This article discusses an advanced methodology known as nodal analysis used to predict corrosion in production facilities, optimizing systems and reducing risks.
What is NODAL Analysis?
NODAL analysis, known as Nodal Wear Model (NWM), is a simulation algorithm used to analyze hydrocarbon production systems in order to optimize the efficiency of these systems in the oil industry2. This approach divides the system into several analysis points (“nodes”), where variables such as pressure, flow and temperature are evaluated. The objective is to determine the optimal balance between fluid inflow and outflow at each node, allowing:
- Optimize operating conditions.
- Predict corrosion failure scenarios.
- Design more efficient systems for hydrocarbon transport.
By using this tool it is possible to model two-phase flow in pipelines, which occurs when two phases (liquid and gas) coexist within the same transport system. This phenomenon is common in oil production, where natural gas and liquid hydrocarbons flow simultaneously through pipelines. Two-phase flow models analyze flow patterns such as:
- Stratified flow: Separate phases with gas above the liquid.
- Annular flow: A film of liquid surrounds the gas.
- Bubbly flow: Gas droplets dispersed in the liquid.
These flow patterns influence the formation of corrosion cells and the distribution of corrosion inhibitors, making them critical for the control of asset integrity. The application of MDN requires a deep and detailed knowledge of the system, it is a fundamental working tool for the study of corrosion processes in an indirect way. Although it is not directly used to prevent corrosion, it can help identify operating conditions (such as flow rates or pressure) that could contribute to corrosion mechanisms, which would allow adjusting parameters to mitigate them.
Nodal analysis and its role in corrosion prediction in two-phase flows
This analysis method, widely used in the oil and gas industry, is generally used in the simulation of production wells to optimize performance and also provides valuable information on operating conditions that may influence corrosion of production components.
In two-phase flow systems (liquid and gas), variations in pressure, velocity and flow regime create conditions that can accelerate corrosion. For example, a turbulent flow regime or stratified flow can promote the formation of localized corrosion at specific points in the system, such as in areas where liquid accumulates or at the interfaces between the liquid and gas phases.
Applications of Nodal Analysis for corrosion control
The prediction of pressures and flow regimes is one of the most important aspects obtained through simulation, because through these data at the bottom of the well, it is possible to determine the pressures of the fluids at the surface; and to identify low pressure zones where water or condensates accumulate, conditions that favor corrosion.
Nodal analysis also allows the impact of different system components such as piping, valves, compressors and separators to be assessed. With this information, adjustments can be made to minimize operational risks and prevent premature material wear. For example, controlling flow velocity helps to avoid regimes that accelerate component deterioration due to corrosion.
Simulations can predict areas where high flow velocities or water accumulations create significant risks, such as erosion and localized corrosion, and provide information on the distribution of corrosion inhibitors, ensuring their effectiveness in the most vulnerable areas.
Data for two-phase flow simulation and modeling
To perform an efficient nodal analysis, specific data is essential. This includes fluid properties, such as chemical composition (CO₂, H₂S, water), density, viscosity and surface tension. Also, it is essential to know the geometry of the system, considering the diameter, length, and configuration of the pipes, as well as the operating conditions, such as key pressures and temperatures. Flow velocity must also be measured to evaluate potential corrosion patterns and impacts.
Integrating these data into nodal analysis and two-phase flow modeling provides accurate results for corrosion control. This approach identifies material loss rates under different flow conditions and fluid composition, locates critical areas where factors such as water accumulation or turbulence aggravate damage, and facilitates the design of mitigation strategies. This includes optimization of inhibitor injection systems or the use of internal coatings.
Successful cases of corrosion prediction in oil structures using Nodal Analysis
1. Nodal analysis on offshore platforms
On offshore platforms, such as those of ExxonMobil, nodal analysis has been implemented to predict corrosion at the most critical points of gas transport pipelines. This analysis uses simulation models to identify nodes with high corrosion rates in pipelines, considering variables such as temperature, pressure, and salinity of the environment.
Nodal analysis helps predict potential failure points before they occur, allowing preventive maintenance strategies to be implemented. By predicting where corrosion will develop, platforms can prioritize interventions in the most vulnerable areas.
Numerical fact: Studies show that the implementation of nodal analysis has reduced corrosion incidents on offshore platforms by 25%, resulting in savings of approximately $50 million annually in repair and replacement costs.
2. Nodal analysis in pipelines
At Chevron, nodal analysis is used to monitor pipelines that pass through areas with high variability in corrosion conditions, such as changes in the pH and temperature of the transported fluid. Analysis nodes are placed at critical points where higher corrosion rates are expected to occur, allowing for adjustments in cathodic protection and predictive maintenance.
Nodal analysis enables a predictive maintenance approach, which optimizes resources and reduces the risk of pipeline failures, ensuring continuous and safe operation. It can be integrated with intelligent sensors that provide real-time data to adjust protection strategies.
Numerical fact: In pipeline projects, nodal analysis has been shown to reduce corrosion failures by up to 40%, significantly reducing operating costs.
3. Integration of Nodal Analysis with ultrasonic inspection
In an oil field in Saudi Arabia, the combination of nodal analysis with ultrasonic inspection has improved the prediction of corrosion in crude oil transport pipelines. Nodes predict critical areas, and ultrasound is used to check pipe wall thickness in real time.
By combining nodal analysis with advanced inspection technologies, such as ultrasound, corrosion prediction and monitoring is optimized. This allows for more effective intervention in the most susceptible areas, minimizing operational risks.
Numerical fact: Studies at Chevron and Shell have shown that the combined use of nodal analysis and ultrasound has increased the accuracy of corrosion predictions by up to 30%, resulting in a 20% reduction in unplanned repairs.
4. Corrosion prediction in refineries
At the Texas refinery, nodal analysis is used to model corrosion in Fluid Catalytic Cracking (FCC) units. Nodes help identify points where high acid concentrations can cause significant damage. Predictions are validated by in-line corrosion sensors, facilitating real-time intervention.
This approach improves the refinery’s ability to anticipate problems and properly plan maintenance interventions without the need for invasive inspections. It also optimizes equipment durability, avoiding unexpected shutdowns.
Fact: In refineries that implement this system, equipment life has increased by 15%, with a decrease in corrosion-related operating costs of more than 10% annually.
5. Nodal analysis in oil well corrosion management
In the oil field in Venezuela, nodal analysis was used to predict corrosion in deep wells, where temperature and pressure are critical factors. The node system provided an accurate prediction of the location of corrosion, allowing well protection strategies to be adjusted and specific chemicals to be applied to inhibit corrosion.
Nodal analysis is key to efficient corrosion monitoring in high-pressure and high-temperature environments, allowing more accurate management of well conditions and avoiding catastrophic failures.
Numerical fact: Nodal analysis has reduced the frequency of failed oil well perforations by 30%, which has increased oil production by 10% in fields with high corrosion rates.
Conclusions
The application of simulation methods such as Nodal Analysis allows to indirectly evaluate the impact of corrosion on critical components of production wells. By identifying flow and wear patterns in multiphase systems, this approach contributes to predict corrosion in equipment and improve the operational performance of production wells in the oil industry.
Despite advances in simulation techniques, the application of Nodal Analysis in corrosion prediction remains an area with little documentation and research. This gap limits the potential of these tools to address complex challenges, highlighting the need for further development and validation in diverse industrial environments.
The use of Nodal Analysis in modeling two-phase flow in piping networks to predict wear and corrosion mechanisms offers a predictive approach that strengthens equipment integrity management. By anticipating areas of increased susceptibility, these tools reduce the likelihood of unexpected failures, improving safety and operational efficiency in industrial systems subject to corrosion.
References
- Luis F Verdeja, et al; “Nodal Wear Model in the corrosion Peirce – Smith copper converter”; March 2004, Boletin de la Sociedad Espanola de Ceramica y Vidrio 43(2):203-205.
- Robinson S Salazar R, et al; “ Decision making using an algorithm to analyze hydrocarbon production systems”; / Earth Sciences Bulletin (40), pp. 75-83. July, 2016.
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