Evaluating integrity of Storage Tank Bottoms based on advanced MFL/ET scanning: Use Case in Kazakhstan

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Introduction

Aboveground storage tanks (ASTs) are indispensable in industries such as oil and gas, chemicals, and agriculture. These tanks store essential resources and play a crucial role in supporting industrial processes and economic development. However, maintaining their structural integrity, particularly the condition of their bottoms, which support the full weight of thousands of tons of stored products (e.g., oil, chemicals, water), is a significant challenge.

The tank bottom is constructed from multiple steel plates arranged in a structured layout. It consists of bottom plates and annular plates as in Figure 1, with the latter forming a reinforced ring along the perimeter. Annular plates are typically thicker than the central plates to handle increased stress near the shell-to-bottom joint.

Figure 1. Tank bottom visualization in ROSOFT for Tanks 5.1.2 software

To maintain structural integrity and prevent leaks, the plates are welded together using lap joints or butt joints. The welds follow a staggered pattern to distribute stress more evenly across the bottom. Additionally, corrosion protection measures, such as cathodic protection systems or protective coatings, are often incorporated to enhance durability and extend the service life of the tank. These design considerations ensure that the tank bottom can withstand operational loads while maintaining leak-tight performance and long-term reliability.

Corrosion, mechanical stress, and sediment accumulation contribute to material degradation, increasing the risk of leaks and failures. Such incidents can lead to catastrophic environmental contamination, safety hazards, and substantial financial losses, underscoring the importance of regular and thorough inspections. A strong reminder of the consequences of inadequate storage tank integrity management is the Norilsk disaster of May 2020. As shown on Figure 2 a fuel storage tank at a power plant collapsed, releasing over 21,000 tonnes of diesel into nearby rivers, ultimately reaching the Arctic Ocean. The incident, attributed to structural failure caused by permafrost, resulted in severe environmental damage and costly remediation efforts. The cleanup efforts were extensive, and Nornickel, the company responsible, was fined approximately $2 billion by the Russian government [1] [2]. This disaster highlighted the critical need for proactive inspection, predictive maintenance, and adaptation to evolving environmental risks to prevent similar failures.

Figure 2. Collapsed Storage Tank at Norilsk Power Plant and Aerial View of the Contaminated River

Tank Bottom Inspection

In accordance with Industrial Safety Regulation in Kazakhstan [3], storage tanks that are in operation are subject to periodic inspection and non-destructive testing to determine their actual technical condition and to assess the potential duration of their continued safe operation. Based on the inspection results, the timeline for the next scheduled inspection must be established. As per Paragraph 2 of the Rules tank inspections are categorized into full (offstream) and partial (onstream) inspections.

A partial inspection is performed without taking the tank out of service and focuses on external evaluations. It includes visual assessments, geometric checks, and localized thickness measurements to monitor structural integrity. Partial inspections are typically conducted every 5 years or in response to specific concerns, such as signs of corrosion or deformation detected during routine monitoring.

A full inspection requires the tank to be taken out of service, emptied, degassed, and cleaned to allow comprehensive access. This process includes visual inspection, geometric assessments, and NDT methods such as ultrasonic thickness measurements (UT), radiographic, and eddy-current testing to evaluate metal integrity and detect corrosion, cracks, and structural deformations. Full inspections are conducted at least once every 10 years, or more frequently based on regulatory requirements, operational history,

As part of full inspection, the Regulation on Industrial Safety Requirements for the Operation and Maintenance of Oil and Oil Product Storage Tanks [4] mandates tank bottom thickness measurements at a minimum of two points per sheet in two mutually perpendicular directions (refer to section 370). However, such spot UT measurements often fail to provide a comprehensive assessment of tank bottoms, leaving critical defects undetected. To address these limitations, advanced technologies like MFL in combination with ET have been increasingly adopted to enhance inspection accuracy and reliability. MFL technology enables a more thorough evaluation of metal loss patterns, offering valuable insights for predictive maintenance and risk mitigation. Meanwhile, ET is used to distinguish features on the internal (product side) and external (soil side) surfaces of the bottom.

Studies on MFL have demonstrated its effectiveness in detecting metal loss features like corrosion. According to the sources [5] [6] [7], MFL technology (see Figure 3) provides several advantages: it enables rapid coverage of large areas, is non-intrusive with minimal surface preparation, and is highly effective in detecting corrosion and pitting.

Figure 3. MFL Principle in Tank Bottom Inspection [8]

The benefits of comprehensive scanning of tank bottoms are well-recognized across the global oil and gas industry and are witnessing increasing demand in Kazakhstan. For instance, full MFL scanning is mandated by the corporate standard of KazTransOil [4] and is also adopted by internationally operated companies such as TCO, NCOC, and KPO, all of which align with API best practices.

Table 1. LoIE Example for Tank Bottoms

Table 1 illustrates the effectiveness of various bottom scanning methods, as outlined in the API 580 guidelines. Notably, full MFL scanning is rated as providing the highest level of effectiveness, whereas spot ultrasonic testing (UT) measurements are categorized as poorly effective.

Case Study

Scope and Data Inputs

In this study, a unique long-term MFL/ET tank bottom inspection dataset of 27 ASTs from various regions of Kazakhstan (see Figure 4) was analyzed. These tanks, primarily used for crude oil storage, have capacities ranging from 5,000 to 20,000 m³ and service lives varying from 10 to 39 years. Inspection data revealed a total of 97,467 anomalies, with 39,546 external corrosion anomalies and 57,921 internal corrosion anomalies. The depth of metal loss features ranged from 19% to 100%, highlighting the urgent need for effective monitoring and maintenance strategies. Table 2 below provides an overview of the 27 tank parameters along with the number of anomalies detected during the inspections.

Table 2. Overview of the tank parameters and anomalies

The objective of this study is to provide comprehensive analytical review of AST bottom integrity based on representative selection of MFL/ET inspection data in Kazakhstan. The study aims to:

• Assess the advantages of MFL/ET technologies over traditional inspection methods.
• Identify common trends in metal loss at AST bottoms.

Figure 4. Geographical location of the storage tanks examined in this study

Data Analysis and Interpretation (TBIT Ultra tool and ROSOFT for Tanks)

This study utilizes the results of tank bottom scanning performed with the ROSEN TBIT Ultra tool (Figure 5). First introduced to the market in 1996, this tool is known for its exceptional data reliability and consistency.

Figure 5. ROSEN Tank Bottom Inspection Tool (TBIT Ultra) [9]

The tank bottom inspection by ROSEN follows a structured approach to ensure accurate defect detection and assessment:

1. Pre-Inspection Activity – The technician assigns a numbering system to the tank bottom plates, marking them with unique reference points and a coordinate system. System setup and sensor functionality are tested before starting the inspection.
2. Tank Bottom Scanning – The process involves MFL/EC scanning with the ROSEN TBIT tool, UT for thickness verification, and visual inspection for blind zones. Safety measures, including proper ventilation and intrinsically safe equipment, are strictly followed.
3. Data Evaluation and Reporting – Initial data is reviewed in real time, followed by a more detailed offline analysis using specialized software. The final report includes MFL and UT results, defect documentation, and repair recommendations.

The ROSOFT for Tanks software was utilized to visualize inspection results, providing detailed insights into defect locations, depths, damage categorization, and repair tracking. Designed for TBIT, the software enables precise identification of tank bottom defects, accurate metal loss measurement, damage type classification, and monitoring of previously repaired areas. As shown on Figure 6 ROSOFT also offers a range of flexible visualization tools – including scan line views, wall thickness mapping, and coordinate-based displays – to support comprehensive condition assessments and effective maintenance planning.

Figure 6.  Scanned bottom of the tank in the ROSOFT software.

Key Findings

In figure 7, the analysis reveals patterns in the relationship between tank volume, service life, and anomaly density. Smaller tanks (5000 m³) exhibit a significant variation in service life, reaching over 30 years in some cases, and are often characterized by high anomaly density, which may indicate material degradation or accumulated operational stress. Tanks with a volume of 10,000 m³ have relatively low anomaly density, suggesting better structural integrity at the time of inspection. However, the overall trend indicates that anomaly density increases with service life, confirming the cumulative effects of wear and aging. Larger tanks (20,000 m³) demonstrate extended service lives, sometimes reaching up to 40 years, but also show the highest anomaly densities, emphasizing the correlation between longevity and structural degradation. These findings highlight the need for systematic monitoring and preventive measures, as an increase in operational time is accompanied by a rise in anomaly density, which may elevate the risk of failures and require additional safety measures.

Figure 7. Analysis of service life and anomaly density in storage tanks of different capacities.

The chart in the Figure 8 shows the service life and corrosion rate of tanks with capacities of 5,000 m³, 10,000 m³, and 20,000 m³. The orange bars represent service life, while the blue and purple dots indicate the average internal and external corrosion rates, respectively.

In the 5,000 m³ group, the service life ranges from 10 to 25 years, and the corrosion rate is distributed chaotically. In the 10,000 m³ category, the service life is generally lower, while the corrosion rate remains high regardless of the tank's age. The 20,000 m³ group shows a wider range of service life values, but young tanks often experience high corrosion rates.

This data supports the conclusion that tank capacity directly influences corrosion behavior and maintenance strategies. Smaller tanks, such as those with 5000 m³ capacity, experience more rapid and localized corrosion, indicating the need for frequent maintenance and more effective protective coatings. In contrast, larger tanks (10000 and 20000 m³) tend to accumulate damage more gradually over time, which makes long-term monitoring and cathodic protection systems essential. The correlation between anomaly density and the effectiveness of protective measures, particularly galvanic protection, highlights the importance of tailored maintenance strategies based on tank size and operational conditions [10] [11].

Figure 8. Service life and corrosion rate of tanks.

In addition, Figure 9 shows the average service life and anomaly density across four regions: West, South, North, and Center. Higher anomaly density, as seen in the South, may contribute to faster wear. In contrast, the North region has the longest service life and the lowest anomaly density, which may indicate better operating conditions or higher-quality materials.

Figure 9. Average service life and anomaly density by region.

In addition, Figure 11 presents a comparative analysis of tanks with and without galvanic protection, showing the number of internal anomalies and the corresponding service life. The tanks on the left side, shaded in blue, represent those without galvanic protection, while those on the right side, shaded in red, are equipped with galvanic protection.

From the visual distribution of the data, there does not appear to be a strong direct correlation between the presence of galvanic protection and the number of internal anomalies. Both groups exhibit varying levels of anomalies, and the mere presence of protection does not consistently result in lower anomaly counts across all tanks.

However, a general trend can be observed in both groups: the number of internal anomalies tends to increase with the age of the tank. Especially among tanks with galvanic protection, older tanks (with longer service life) tend to show higher anomaly counts, suggesting that time and operational wear still contribute to internal degradation, even in the presence of protective systems. In tanks without galvanic protection, the number of anomalies is already quite high across all ages, and while the relationship with age is less clearly defined, it is evident that the lack of protection contributes to consistently higher anomaly levels overall.

This indicates that while galvanic protection may mitigate corrosion or degradation to some extent, it does not eliminate the long-term effects of aging, and the accumulation of anomalies over time is still a significant factor regardless of protection status.

Figure 10. Assessment of Internal Corrosion in Tanks Based on Protection Status and Operational Time   

Conclusion

The study demonstrated the high efficiency of TBIT findings in assessing the integrity of storage tank bottoms. These techniques provided a detailed and accurate evaluation of corrosion and structural defects, surpassing the capabilities of traditional inspection methods.

The research confirmed that MFL and ET technologies enable the early detection of critical defects, allowing for timely maintenance interventions and reducing the risk of unexpected failures. The case study showed that the application of these advanced scanning methods significantly improved the accuracy of defect localization and classification. As a result, maintenance teams were able to prioritize repairs more effectively, optimizing resources and minimizing the downtime of storage facilities.

A comprehensive analysis of all factors reveals a complex interrelation between tank age, volume, geographic location, protective measures, and overall technical condition. The key takeaways can be summarized as follows:

1. The risk of damage increases by 45% with both age and volume of the tanks.
2. Coating quality and the presence of galvanic protection are critical in reducing the rate of degradation (the case study shows 32% in corrosion rate reduction).
3. Smaller tanks exhibit a high susceptibility to corrosion (25% higher than average) even at an early stage of their operational life, highlighting the need for further investigation and analysis.
4. Regional operating conditions significantly impact on the service life and structural integrity of the tanks.
5. Systematic monitoring and preventive maintenance are essential, particularly for bottom plates and tanks without protective systems.

Furthermore, the integration of TBIT data into a risk-based inspection (RBI) framework will enhance predictive maintenance strategies, making operations not only safer but also more cost-efficient. The findings also highlight the importance of continuous monitoring and data-driven decision-making in the oil and gas industry.

Overall, the study provides strong evidence that the adoption of advanced NDT techniques can significantly contribute to improving the reliability and sustainability of storage tank infrastructure. The results suggest that a wider implementation of MFL and ET technologies across the industry could lead to substantial long-term benefits, including enhanced operational efficiency and reduced environmental risks associated with tank failures.

About the authors

Daniyar Ualiyev

Author for correspondence.
Email: ualiiev03@gmail.com
ORCID iD: 0009-0001-3437-8795

Abdugaffor Mirzoev

Email: gmirzoev@rosen-group.com

References

Supplementary files