bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation on Drag Reduction Through Dimple Machining
Authors: TabkhPaz Majid , Howell Lindsay , Kockerbeck Zachary , Park Simon , Hugo Ron 
Published: November 2018

High friction between a fluid and a pipe wall results in increased pumping requirements. This friction contributes to lower production rates and reduced system capacity. Thermal heating, fluid blending, and drag reducing agents (DRA) are commonly used methods for decreasing pressure drop in pipelines. Surface patterns inscribed onto internal pipe walls have also been shown to reduce fluid friction.
In this paper, the effects of different surface patterns on the shear between a fluid and a wall are studied. Surfaces with different dimple patterns are investigated. Micro-dimpled patterns on the surface are created using an inclined, flat end micro-milling tool. The surfaces with different dimpled patterns are characterized and tested through morphological, contact angle, and viscosity measurement studies. The effects of the surface patterns are also studied through simulation. A Power Law relationship and apparent fluid viscosity is determined for the low Reynolds numbers investigated. The deepest dimpled surfaces investigated (0.2 mm dimple depth) result in a drag reduction of approximately 20% for silicone oil. Further research and application of the results to transmission pipeline systems are discussed.
Development and Execution of Consequence Assessment for Liquid Pipeline Facilities
Authors: Ferdous C. M. Refaul , Beaudin Chris , Payoe Anthony , Li Lily 
Published: November 2018

Risk assessment is an effective and commonly practiced process in industry, including oil and gas sector, as a basis for designing new pipeline terminals and stations and managing integrity of existing facilities. A holistic risk assessment method, which could be qualitative or quantitative, includes both the likelihood and consequence assessments of an undesired event. Prior to 2015, Enbridge Pipelines employed a qualitative risk assessment algorithm to assess the likelihood and consequence of a failure of liquids pipeline facilities.
Over the past decade Enbridge has identified a number of shortcomings with the qualitative approach, necessitating the development and use of Quantitative Risk Assessment (QRA) to support consistency and defensibility in risk-informed decision making. A QRA requires rigorous quantitative algorithms to measure public and environmental safety, and potential business consequences of an undesired event at a facility. While significant literature has been produced, and considerable effort has been expended to quantify the potential impacts of a flammable product release on public safety, very limited work has been done on the quantitative measurement of environment related impacts. In particular, limited research has been successful in aggregating environmental consequences, public safety and business consequences to estimate the total consequence of a liquid hydrocarbon release within a pipeline facility.
The consequence assessment of an unwanted event conducted through QRA can be combined with the associated likelihood to provide a quantitative measure of risk. This risk level may be used to support organizations in making risk informed decisions and in analyzing and treating facility risks, specifically in the:
• Identification of top risk facilities and high consequence functional areas;
• Identification of assets posing the most risk and worst case consequences;
• Understanding of system reliability risk and opportunities to optimize facility operation;
• Prioritization of facility maintenance projects in the capital and operating budget processes;
• Supporting regulatory requirements and expectations;
• Presentation of risk down to the equipment or component level; and
• Understanding of residual risk and achieved risk reduction.
This paper describes the development of a consequence model that monetizes the quantitative measure of public and environment safety, and potential business losses for a liquid product release at pipeline facilities. The proposed model characterizes the severity of impact of released product, expressed in dollars per event, as a function of system volume, proximity and category of receptors, asset location, and available controls.
Adaptive Ultrasonic Imaging of Electric Resistance Welded Pipeline Seams
Authors: Haines Harvey , Hörchens Lars , Schouten Jasper 
Published: November 2018

Imaging techniques using full matrix capture (FMC) ultrasonic NDE are well suited for in-service examination of electric resistance welded (ERW) pipe seams. We have been involved in developing an imagine technique since 2013 and presented results from Phase I at IPC in 2016 showing the system capable of detecting seam weld and SCC flaws and determining their orientation. The advantages over other methods such as phased array (PA) is the ability to image the flaw surface in addition to the flaw tip and corners where the flaw intersects the pipeline surface. This improves the ability to determine flaw orientation for discrimination of different types or crack-like features. The system produces UT images by overlaying multiple modes using reflections off the ID and OD pipe surface for ultrasonic illumination of the weld area from different directions. Using multiple modes produces a reflection off features regardless of flaw orientation from at least one of the modes. A complementary mode can then be used to size each feature by detecting the tips or ends of the feature from lower amplitude diffraction signals. Phase I used a model which assumed a cylindrical pipe shape. Real world use of this technique found limitations when pipe deviated from the assumed cylindrical shape such as severe offset plate edges, flat spots which can be the result of poor crimping adjacent the seam weld, or thickening of the seam caused by post weld heat treatment.
In Phase II a need for reduced sizing error led to improved calibration and more advanced processing. To compensate for the non-perfect nature of real pipe, a new adaptive IWEX technique was developed to improve focusing and alignment of the various modes using the actual geometry to construct better focusing laws. First the OD and ID surfaces are imaged and the resulting surfaces are used to construct focusing laws which adapt to changes in the OD and ID surfaces. Results are better aligned UT images with the ability to image complex flaws with changes in orientation, and the ability to discriminate complex flaws from multiple small flaws in the pipe. Results show improvements in pipe with the greatest improvements in pipe with the largest deviations from a cylindrical shape.
Utilizing Value Management to Increase Project Competitiveness
Authors: Tozer Michael , Tetteh-Wayoe Debra 
Published: November 2018

With the current economic pressures being faced by the oil and gas sector, organizations are increasingly required to become more competitive on their capital projects. Enbridge has implemented the practice of Value Management (VM) to help achieve the needs and expectations of stakeholders with the least possible resources.
VM is a systematic approach that is used by a multidisciplinary team to improve the value of a project (or aspects of a project) through the analysis of its functions, and is most effective when applied at the planning and development stages. A value study enables the expected performance (i.e. the desired functions) of a project to be clearly identified at the onset, and assesses a range of possible solutions/alternatives against the functions required by the owner.
While VM is commonly used in the manufacturing industry, as well as on transportation and municipal projects, few examples of its application in the oil and gas sector were found. Enbridge researched a variety of VM best practices and created a framework that compliments existing company practices.
This paper also highlights how the value methodology was recently applied to a capacity expansion project at the Front End Engineering and Design (FEED) stage. Our approach to the various elements of a value study will be discussed, including pre-workshop activities, the VM workshop, and post-workshop activities.
Enbridge has seen significant benefits from the VM studies completed on projects to-date. Given the broad applicability of the value methodology, it is believed that our approach can also be successfully applied in other areas (e.g. improving business processes).
A More Accurate and Precise Method for Large Metal Loss Corrosion Assessment
Authors: Zhang Shenwei , Yan Jason , Kariyawasam Shahani , Huang Terry , Al-Amin Mohammad 
Published: November 2018

Pipeline integrity decisions are highly sensitive to the assessment model. A less accurate and less precise model can conservatively trigger many unnecessary actions such as excavations without providing additional safety. Therefore, a more accurate and precise model will reduce excavations and provide higher assurance of safety. This is akin to using a more precise surgical tool such as a laser for cutting out a brain tumor where you can cut closer to the edge and be assured of cutting out more of the tumor (safer) and yet cut less of the surrounding brain tissue (less conservative).
This paper presents a novel model for assessing large metal-loss corrosion based on in-line inspection (ILI) or field measurement. The model described in this paper utilized an unconventional approach, namely multiple plausible profiles (P2), to idealize the shape of the corrosion, and therefore is referred to as P2 model. In contrast, all existing models use one single profile for characterizing corrosion profile, e.g. RSTRENG utilizes a single worst-case river bottom profile to characterize the shape of corrosion.
The P2 model has been initially validated using fourteen (14) full scale specimen-based hydrostatic tests on pipes containing real large corrosion features. Validation results showed that the P2 model is safe, but less conservative and more precise than RSTRENG. The magnitude of reduction in conservatism depends on the corrosion morphology. On average, the P2 model achieves 15% reduction in model bias and 44% reduction in standard deviation of model error. Further validation was provided using the testing data published by PRCI and PETROBRAS. Another set of burst tests are being conducted by TransCanada as part of the continuous validation of P2 model.
The effectiveness of the P2 model was demonstrated through two case studies (denoted by Case study 1 and 2). Case Study 1 included 170 external metal-loss corrosion features that were excavated from different pipeline sections, and have field-measurements using laser scan tool. Case Study 2 included 154 ILI-reported external metal-loss corrosion features with RSTRENG calculated rupture-pressure-ratio (RPR) of less than or equal to 1.25 (i.e. RPR ≤ 1.25); hence, these features were classified as immediate features. The Case Studies showed that the use of the P2 model resulted in 80% less number of ILI-reported features requiring immediate action (i.e., RPR ≤ 1.25) and 89% less number of excavated features requiring repair (e.g., sleeve or cut-out) compared to the respective number of features identified by RSTRENG-based assessment. The reduction in the number of features requiring excavation or repair is highly morphology-dependent with the highest reduction achievable for pipeline containing long and wide corrosion clusters (e.g., tape-coated pipeline). However, the P2 model is applicable to all clusters regardless of the number of individual corrosion anomalies associated with the cluster.
Validate Crack Assessment Models With In-Service and Hydrotest Failures
Authors: Yan Jason , Zhang Shenwei , Kariyawasam Shahani , Pino Maria , Liu Taojun 
Published: November 2018

Crack or crack-like anomaly is one of the major threats to the safety and structural integrity of oil and gas pipelines. Various assessment models have been developed and used within pipeline industry to predict the burst capacity for pipelines containing longitudinally-oriented surface cracks. These models have different level of conservatism, accuracy, and precision which significantly impacts pipeline operators’ integrity mitigation decisions such as pressure restriction, excavation, and repair, and also lead to different level of safety.
This paper compares the accuracy and precision of the most commonly used crack assessment models, i.e. Modified Ln-Sec, CorLAS, API 579 Level 2 and the recent-published PRCI MAT-8 model using in-service and hydrostatic testing failure data. A total number of 12 in-service and 63 hydrostatic test pipe ruptures due to stress corrosion cracking (SCC) with actual burst pressure, material property, and detailed crack size measurements are collected, and used to derive the probabilistic characteristics of the model errors associated with each model. Compared to the burst tests conducted in the laboratory and investigated in other previous studies, the results obtained from in-service and hydrostatic test ruptures are more representative of the real boundary conditions in pipeline operation. All the assumptions and empirical correlations associated with each model are discussed in details. The analysis result suggests that CorLAS is the most accurate model with the least uncertainty (or highest precision). Mitigation activities can be optimized without compromising safety by using the most accurate and precise model.
Accelerating Industry Performance Through Collaborative Continual Improvement
Authors: Lukaniuk Coral , Coupal Chris 
Published: November 2018

CEPA Integrity First® (Integrity First), led by the Canadian Energy Pipeline Association (CEPA) and a condition of membership, acts as a foundation for continual improvement, bringing our members together to share and implement leading practices in the areas of safety, environment and socio-economics. Integrity First includes three principles and ten priority areas (such as emergency management, pipeline integrity and water protection) where members collaborate, share leading practices and hold each other accountable.
Integrity First is a management systems approach designed by CEPA members for industry to achieve collaborative continual improvement. It supports the collective setting of priorities, plans, assessments and improvements.
While spreadsheets enabled the first rounds of assessments, CEPA required a solution that engaged multiple stakeholders over a complex timeline, coordinated activities clearly and precisely, while keeping the process transparent and efficient. The information generated is sensitive, so it must be kept secure while still being available for aggregation, reporting and reference. It needed to house communication tools so members could easily pull information and lastly, it needed to be easy to use.
In August of 2015, CEPA established a partnership with SPAN Consulting (SPAN) to address these challenges through its software as a service (SaaS) offering called Octane™.
This paper will review how CEPA designed and implemented a technical, web-based solution to enable an efficient, effective and transparent Integrity First with transformative impact. Specifically, through the use of this technology, there are now stronger communities of practice across industry with increased focus and effort on the opportunities to improve through real-time self-serve access to industry’s overall benchmarked performance, leadership and leading practices. CEPA’s commitment to enabling Integrity First is resulting in better adoption and improved performance.
A Novel Depth-First Searching Approach for Detailed Scheduling of Operations in a Multi-Product Pipeline With Multiple Pump Stations
Authors: Liao Qi , Wang Bohong , Li Zhengbing , Zhang Haoran , Liang Yongtu , Liang Jun 
Published: November 2018

Considering market’s diversified demand and transport economy, large volumes of various refined products commonly move down the pipeline in batches, which are pumped at pump stations and delivered to respective delivery stations. The integrate detailed scheduling optimization is a sophisticated problem due to the characteristics of multi-product pipelines, such as market-oriented, fluctuated demand, various processing technique and complicated hydraulic calculation during batch migration. The integrate detailed scheduling optimization has been widely studied during the last decade, however, most of them studied pipeline scheduling and pump scheduling separately. Besides, the proposed methods are mathematical models, whose computational efficiency greatly decreases in large-scale pipeline scheduling, let alone in the problems coupling with pump scheduling.
Aiming at this problem, this paper presents a novel depth-first searching approach based on flowrate ratio to deal with the detailed scheduling of operations in a multi-product pipeline with multiple pump stations. As for each single time interval, the proposed method decides an ideal flowrate ratio according to current status, then solves out the optimal flowrate that mostly conforms to the ideal ratio and satisfies all operational constraints, and finally updates information for next time interval. However, during the computational procedure, backtracking method would be adopted to modify the previous flowrate ratios and recalculate new flowrate when the actual delivered products are insufficient. Finally, a case tested on a Chinese real-world pipeline with 6 delivery stations is given to demonstrate the veracity and practicability of the proposed method. From the results, computing time of the case is within 1 minute, and the solved detailed scheduling plans can fulfill demand with stable pump operations. Besides, the proposed approach is scarcely influenced by the scale of pipeline structure and time horizon, so it is also applicable to the long-term scheduling of a pipeline with many delivery stations.
Pipeline Data Analytics: Enhanced Corrosion Growth Assessment Through Machine Learning
Authors: Smith Michael , Cronjaeger Stefan , Ershad Navid , Nickle Randy , Peussner Matthias 
Published: November 2018

Effective integrity management of a corroded pipeline requires a significant quantity of data. Common data sources include in-line inspection (ILI), process monitoring, or external surveys. The key challenge for an integrity engineer is to leverage the data to understand the level of corrosion activity along the pipeline route, and make optimal decisions on future repair, mitigation and monitoring. This practice of gaining business insights from historical datasets is often referred to as ‘data analytics’.
In this paper, a single application of data analytics is investigated — that of improving the estimation of corrosion growth rates (CGRs) from ILI data. When two or more sets of ILI data are available for the same pipeline, a process known as ‘box matching’ is typically used to estimate CGRs. Corresponding feature ‘boxes’ are linked between the two ILIs and a population of CGRs is generated based on changes in reported depth. While this is a well-established technique, there are uncertainties related to ILI sizing, detection limitations, and data censoring. Great care is required if these uncertain CGRs are used to predict future pipeline integrity.
A superior technique is ‘signal matching’, which involves the direct alignment, normalization and comparison of magnetic flux leakage (MFL) signals. This delivers CGRs with a higher accuracy than box matching. However, signal matching is not always feasible (e.g. when conducting a cross-vendor or cross-technology comparison). When box matching is the only option for a pipeline, there is great value in understanding how the box matching CGRs can be improved in order to more closely resemble those from signal matching. This limits the extent to which uncertainties are propagated into any subsequent analyses, such as repair plan generation or remaining life assessment.
Given their relative accuracy, signal matching CGRs can be utilized as a ‘ground truth’ against which box matching results can be validated. This is analogous to the ILI verification process, where in-field measurements (e.g. with laser scan) are used to validate feature depths reported by an ILI. By extension, a model to estimate CGRs following a box matching analysis can be trained with CGRs from a signal matching analysis, using supervised machine learning. The outcome is an enhanced output from box matching, which more closely resembles the true state of corrosion growth in a pipeline.
Through testing on real pipeline data, it is shown that this new technique has the potential to improve pipeline integrity management decisions and support economical, safe and compliant operation.
Using 2D and 3D Oil Spill Trajectory and Fate Models to Assess the Risk of Accidental Crude Oil Releases Along the Enbridge Line 3 Replacement Program Pipeline
Authors: Horn Matthew G. S. , Fontenault Jeremy M. 
Published: November 2018

The proposed Enbridge Line 3 Replacement Program would replace the aging pipeline from Hardisty, Alberta, Canada to Superior, Wisconsin, USA. For the Canadian route, an Ecological and Human Health Risk Assessment (EHHRA) was prepared for the National Energy Board (NEB) in Canada. In the United States, an Assessment of Accidental Releases (AAR) and the Supplemental Release Report were part of an Environmental Impact Statement (EIS) prepared for the Minnesota Public Utilities Commission (PUC) and Minnesota Department of Commerce, Energy Environmental Review and Analysis (DOC-EERA).
Computational oil spill modeling was used to assess the predicted trajectory (movement), fate (behavior and weathering), and potential effects (impacts) associated with accidental releases of crude oil along the proposed pipeline. This modeling included the 2-dimensional OILMAPLand and 3-dimensional SIMAP models. A total of 64 hypothetical release scenarios were investigated to understand the range of potential trajectories, fates, and effects that may be possible from multiple product types (Bakken, Federated Crude, and Cold Lake Winter Blend), released at any location, under varying environmental conditions.
Trajectory and fate modeling was used to predict the downstream movement and timing of oil, as well as the expected surface oil thickness, water column contamination, shoreline and sediment oiling, and proportion evaporated to the atmosphere. These results were then used to assess the potential environmental effects to demonstrate the variability of outcomes following a release under different release conditions.
In-Situ Modal Response Characterization of Pipe Structures Through Reynolds Number Variation
Authors: Chen Haobin , Hugo Ron , Park Simon 
Published: November 2018

The modal response characterization of structures is a proven and reliable technique used to monitor system behavior and change, providing information for condition assessment and damage identification. In traditional modal response characterization procedures, an external mass excitation source is used to excite the system, and this is modeled as an impact function. This provides system forcing across a broad range of frequencies. In this investigation, an in-situ method of system excitation is explored. The modal characteristics of externally-supported pipe structures are investigated by varying the flow Reynolds number (Red). Given the increase in flow turbulence with Reynolds number, hydrodynamic pressure fluctuations on the pipe wall provide a varying excitation source. This removes the requirement for an external excitation source.
A comparative analysis of data sets collected for both Acrylic and ABS pipe material show similar pressure spectra, while vibration spectra change significantly. Pressure spectra reveal a character whereby the spectral energy increases with increasing Reynolds number. A comparison of in-situ results to those obtained using traditional impact response tests show that vibration spectra collected through Reynolds number variation successfully capture the modal characteristics of the pipe-structure.