Life Prediction of Crude Oil Pipeline to Mitigate Leakages: A Case Study of an NPDC Major Pipeline in OML30, Nigeria

Pipeline leak or failure is a dreaded event in the oil and gas industries. Top events such as catastrophes and multiple fatalities have occurred in the past due to pipeline leak or failure especially when loss of contents was met with fire incidents. It is therefore imperative that the causes of pipeline failure are tackled to prevent or mitigate leak incidents. This is expedient to curb the menace that goes with leak incidents, such as destruction of the environment and ecosystem; loss of assets, finance, lives and property; dangers to workers and personnel, production downtime, litigation and dent to company’s reputation. This work focuses on the investigation of the actual cause of sudden pipeline failures and frequent pipeline leaks that often result to sectional pipeline replacement before the expiration of their anticipated life cycle in OML30 oil and gas field. The pipeline material selected, the standard of the minimum wall thickness of the material, the corrosive nature of the pipeline content and the observed internal corrosion rate were probed. An analysis of the rate of thinning and diminution of the internal wall of the pipeline by monitoring the interior rate of corrosion was used to forecast the remaining life of a crude oil pipeline and predict the life expectancy of a newly replaced or installed pipeline or installed pipeline.

Performance assessment of multi-MFL inspection using feature-based POD

Oil and gas pipelines, which transport large quantities of oil products and natural gas, are subject to pipeline failures caused by corrosion. Magnetic flux leakage (MFL) is one of the most popular non-destructive testing (NDT) techniques for the detection of pipeline corrosion. Since individual MFL is insensitive to the corrosion components that are parallel with its magnetic field, two types of MFL tools with perpendicular magnetic fields are usually employed in one inspection to detect all corrosion defects. This study applies probability of detection (POD) to quantitatively assess the detection capabilities of two individual MFL tools and their combination. Due to the characteristics of MFL inspection, this study proposes the construction of the POD model as a function of two geometric features, namely the volume and the orientation, which have a significant influence on the MFL signal response. Detection results from two MFL tools are integrated using logical OR operation to study the POD of their combination. With the proposed POD model, the minimum criteria that ensure a corrosion defect will be reliably detected by MFL tools are studied in this paper. The validity of the proposed POD model is justified on the data collected from an in-service pipeline.

Failures of Pipelines

This article discusses the failure analysis of several steel transmission pipeline failures, describes the causes and characteristics of specific pipeline failure modes, and introduces pipeline failure prevention and integrity management practices and methodologies. In addition, it covers the use of transmission pipeline in North America, discusses the procedures in pipeline failure analysis investigation, and provides a brief background on the most commonly observed pipeline flaws and degradation mechanisms. A case study related to hydrogen cracking and a hard spot is also presented.

Exploring the Gains of Artificial Intelligence for Addressing the Menance of Pipeline Vandalization in Nigeria: A Review

Pipeline transport is a commonly utilised method for moving petroleum products from one location to another. It is considered as one of the safest, fastest, and most reliable options for transporting petroleum products. However, the use of pipelines for oil transport is associated with the risk of pipeline failure, a challenge caused by a range of factors including corrosion, ignition of natural gas, accidental damage during excavation work, lapses in maintenance as well as vandalization. Most prevalent in Nigeria is the menace of pipeline vandalization and oil thefts which is a critical factor responsible for most pipeline failures across the country. Varied efforts aimed at addressing the problem of vandalization and oil thefts in Nigeria have, over the years, yielded minimal benefits. Therefore, this review investigates the usefulness and suitability of artificial intelligence (AI) for securing Nigeria’s pipeline network. The review focuses on summarizing available evidence on the use of some relevant AI components such as Image Analytics, Convolutional Neural Network (CNN) as well as Edge-Based AI Solutions, for securing oil pipelines. Based on the findings of case studies and other primary research materials utilized in this review, this paper concludes that while there is need for further research on the subject, AI offers a promising and useful solution to Nigeria’s endemic challenge of pipeline vandalization and oil theft. This is as AI promotes early detection of illicit activities on pipelines and can relay signals to appropriate authorities on the need for urgent action. The use of AI in securing Nigeria’s vast pipeline network will not only minimize the economic losses caused by vandalization but will equally contribute towards mitigating the adverse environmental impact of oil pipeline vandalization in Nigeria.

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Pipeline networks have been widely utilised in the transportation of water, natural gases, oil and waste materials efficiently and safely over varying distances with minimal human intervention. In order to optimise the spatial use of the pipeline infrastructure, pipelines are either buried underground, or located in submarine environments. Due to the continuous expansion of pipeline networks in locations that are inaccessible to maintenance personnel, research efforts have been ongoing to introduce and develop reliable detection methods for pipeline failures, such as blockages, leakages, cracks, corrosion and weld defects. In this paper, a taxonomy of existing pipeline failure detection techniques and technologies was created to comparatively analyse their respective advantages, drawbacks and limitations. This effort has effectively illuminated various unaddressed research challenges that are still present among a wide array of the state-of-the-art detection methods that have been employed in various pipeline domains. These challenges include the extension of the lifetime of a pipeline network for the reduction of maintenance costs, and the prevention of disruptive pipeline failures for the minimisation of downtime. Our taxonomy of various pipeline failure detection methods is also presented in the form of a look-up table to illustrate the suitability, key aspects and data or signal processing techniques of each individual method. We have also quantitatively evaluated the industrial relevance and practicality of each of the methods in the taxonomy in terms of their respective deployability, generality and computational cost. The outcome of the evaluation made in the taxonomy will contribute to our future works involving the utilisation of sensor fusion and data-centric frameworks to develop efficient, accurate and reliable failure detection solutions.

Challenges Related to Pipeline Free Spans in Watercourse Crossings

Free span assessment in watercourse crossings for the on-shore pipeline industry has become a more and more important part of pipeline integrity practice. One reason is that it has become increasingly well known that the dominant cause of pipeline failures in watercourse crossings is fatigue failure due to vortex induced vibrations at pipeline free spans. Recognition of this is now being identified in industry recommended practices and owners are incorporating this type of assessment into their pipeline integrity management practice. On shore pipelines are not designed with an allowable free span as is the practice with off-shore pipelines, but are buried. Design codes specify minimum depths of cover when constructed and indicate that pipelines should be maintained so that no excessive loads occur. In the past the no excessive loads requirement has been interpreted that the pipeline must remained buried. As experience from the off-shore environment and increasingly from experience on-shore has shown that most exposed and/or free spans do not fail. Due to various river erosion mechanisms; scour, bank erosion or avulsion, previously buried pipelines do develop free spans. Some of the free spans fail and release products directly into the watercourse. Failures, particularly for liquid products, are very expensive due to the economic loss, repair costs and environment clean-up of the watercourse and its banks. Similarly, costs associated with pipeline replacement for free spanning pipelines or repair of pipelines that might develop free spans are relatively high. It is important to develop an understanding of the probability of the pipeline failing due to a free span, or put another way, determine which free span is a threat to integrity. This paper discusses some of the challenges with assessing free spans in watercourse crossings as part of integrity programs and highlights experiences in assessing this threat to integrity. The objective of this paper is to discuss some of the key uncertainties related to the management of the threat due to free spans. These uncertainties are due to the reliability of information about the free span, water velocity and condition of the pipelines.

Real Time Rainfall Monitoring for Pipeline Geohazards

Oil and gas pipelines are subjected to multiple types of geohazards which cause pipeline failures (loss of containment); two of the most common types occur at watercourse crossings and at landslides. At watercourse crossings, the most common geohazard which causes pipeline failures is flooding during which excessive scour may result in the exposure of the buried pipeline and if the exposure results in a free spanning pipeline, then this may fail due to fatigue caused by cyclic loading from vortex-induced vibration. Fortunately the free span length and water velocity combinations that lead to failure can be defined and can be used to identify the flood discharge that should be monitored for in order to trigger actions to manage the hazard and avoid failure. Most watercourse crossings in a pipeline network are on ungauged watercourses and necessitate the use of a proxy gauged watercourse. The “proxy” gauged watercourse is used to infer whether flooding is occurring on the ungauged crossing, and the owner can take appropriate actions. Often the proxy gauged watercourse is too far away or the watercourse may not be representative of the crossing of concern (e.g. large difference in the drainage areas). Real-time rainfall data can be used in conjunction with streamflow monitoring to determine when extreme precipitation has occurred within the ungauged watercourses catchment which may result in flooding. Where pipelines cross landslide prone areas, large scale movements can be initiated, or slow on-going movement rates increased when extreme rainfall occurs. The definition of the extreme rainfall event for slope sites is the key component of providing a suitable warning of potentially dangerous conditions; shallow slides can be caused by short term events from sub-hourly to 3 day duration precipitation events whereas large deep seated (creeping) landslides can be driven by annual and intra-annual rainfall amounts. Monitoring of real time rainfall can be used to determine when extreme rainfall occurs at a landslide site. The density of in-situ weather stations collecting real-time rainfall data prevents the application along remote sections of pipeline routes and within large sections of Canada. Gridded real time rainfall from quantitative precipitation estimations which integrate a multiple data sources including in-situ, numerical weather prediction, satellite and weather radar, can be used to overcome this problem and provide warnings when pre-determined rainfall thresholds are exceeded on a site-specific basis.

Análisis aerodinámico de un vehículo aéreo no tripulado con forma de halcón para monitoreo de fugas de hidrocarburos

The oil pipeline network requires periodic monitoring to detect pipeline damages, which may cause oil leakage with severe environmental contamination. These damages can be generated by interference from third parties such as construction works, sabotage, vandalism, excavations,and illegal oil theft. Todetect the oil pipeline damages,it canbeusedaerodynamic aerial vehicles (UAVs) with infrared cameras and image processing systems. This paperpresents the aerodynamic analysis of a UAV with a hawk shape (wingspan of 2.20 m and length of 1.49 m) for potential application in the detection of oil pipeline failures. A 1:6.5 scale prototype of the UAV is fabricated using a 3D printer. The aerodynamic coefficients of UAV are determined using computational fluiddynamic (CFD) simulations and experimental testing with a subsonic wind tunnel. In addition, the lift and drag coefficients of UAVsare obtained as a function of Reynolds number and angle of attack. Also, the air velocity profile around UAV is estimated with the CFD model. The proposed UAV could decrease the inspection costs of pipeline networks in comparison with the use of helicopters or light aircraft.