Identification and Mitigation of a Landslide Threatening Four Operating Natural Gas Pipelines

This paper presents a case study of a landslide with the potential to affect four operating high-pressure natural gas pipelines located in the south-central US state of Mississippi. This case study follows a landslide hazard management process: beginning with landslide identification, through pipeline monitoring using strain gauges with an automated early alert system, to detection of landslide movement and its effects on the pipeline, completion of a geotechnical subsurface investigation, conceptual geotechnical mitigation planning, landslide stabilization design and construction, and stress relief excavation. Each step of the landslide hazard management process is described in this case study.

A Novel Approach for Two-Stage UAV Path Planning in Pipeline Network Inspection

Currently, unmanned aerial vehicle (UAV) provides the possibility of comprehensive coverage and multi-dimensional visualization of pipeline monitoring. Encouraged by industry policy, research on UAV path planning in pipeline network inspection has emerged. The difficulties of this issue lie in strict operational requirements, variable flight missions, as well as unified optimization for UAV deployment and real-time path planning. Meanwhile, the intricate structure and large scale of the pipeline network further complicate this issue. At present, there is still room to improve the practicality and applicability of the mathematical model and solution strategy. Aiming at this problem, this paper proposes a novel two-stage optimization approach for UAV path planning in pipeline network inspection. The first stage is conventional pre-flight planning, where the requirement for optimality is higher than calculation time. Therefore, a mixed integer linear programming (MILP) model is established and solved by the commercial solver to obtain the optimal UAV number, take-off location and detailed flight path. The second stage is re-planning during the flight, taking into account frequent pipeline accidents (e.g. leaks and cracks). In this stage, the flight path must be timely rescheduled to identify specific hazardous locations. Thus, the requirement for calculation time is higher than optimality and the genetic algorithm is used for solution to satisfy the timeliness of decision-making. Finally, the proposed method is applied to the UAV inspection of a branched oil and gas transmission pipeline network with 36 nodes and the results are analyzed in detail in terms of computational performance. In the first stage, compared to manpower inspection, the total cost and time of UAV inspection is decreased by 54% and 56% respectively. In the second stage, it takes less than 1 minute to obtain a suboptimal solution, verifying the applicability and superiority of the method.

The Use of Optimized ERW Technique to Improve Low Temperature Fracture Toughness of Welded Pipes

It is understood that the bondline microstructure of the line pipe ERW seam can be a zone of weakness in the pipe. To overcome this weakness, several research projects utilizing various line pipe steel grades and welding and heat treatment techniques have been conducted at EVRAZ NA. The overall goal of these efforts has been to understand the development of bondline microstructure during the ERW process and improve the weld seam fracture toughness for low temperature applications. These research activities included mill trials and Gleeble simulations. It was realized that a high toughness ERW weld seam is only possible through a tightly controlled combination of weld power, forging (squeeze) pressure, and welding speed. Research studies have indicated that the as-welded seam may not pass the standard ERW destructive tests if proper heat input and adequate squeeze pressure are not applied. Post weld heat treatment (normalizing) practice was also found to be a key element in the development of the appropriate bondline microstructure for higher toughness. Samples from pipes normalized using different heat treatment practices produced different bondline microstructures and hence different toughness properties. It was found through this study that a low (but still higher than the upper critical temperature Ac3) normalizing peak temperature and adequate soak time at the peak temperature result in improved Charpy toughness of ERW bondline microstructure.

Study on Intelligent Controller Design of Flow Metrological Calibration System

In recent years, China ramped up imports of natural gas to satisfy the growing demand, which has increased the number of trade meters. Natural gas flowmeters need to be calibrated regularly at calibration stations to ensure their accuracy. Nowadays, the flow metrological calibration process is done by the operator manually in China, which is easy to be affected by personnel experience and proficiency. China is vigorously developing industry 4.0 and AI(artificial intelligence) technologies. In order to improve the calibration efficiency, a design scheme of intelligent controller for flow metrological calibration system is first proposed in this paper. The intelligent controller can replace the operator for process switching and flow adjustment. First, the controller selects the standard flowmeter according to the type of the calibrated flowmeter, and switches the calibration process. To accurately control the calibration flow for 180 seconds, the controller continuously adjusts the regulating valve with a sequence of commands to the actuator. These commands are generated by intelligent algorithm which is predefined in the controller. Process switching is operated automatically according to flowmeter calibration specifications. In order to reach the required flow point quickly, the flow adjustment is divided into two steps: preliminary adjustment and precise adjustment. For preliminary adjustment, a BP neural network will be built first using the field historical data and simulation results. This neural network describes the relationship between the valve-opening scheme and the calibration flow. Therefore, it could give a calibration flow as close as possible to the expected value during calibration. For precise adjustment, an adaptive PID controller is used. It could adjust the valve opening degree automatically to make sure the flow deviation meet the calibration requirements. Since the PID controller is a self-adaptive PID controller, the process of adjustment is very quick, which can reduce the calibration time largely. After each calibration, both the original neural network and the adaptive function of the controller will be updated to achieve the self-growth. With the information of the calibrated flowmeter, the entire calibration system can run automatically. The experiment in a calibration station shows that the intelligent controller can control the deviation of the flow value within 5% during 4∼5 minutes.

Employing Space-Based Hyperspectral Imagery for Pipeline Leak Prevention, Detection and Compliance

We are now living in what has been described as the Experience Era, where lines between the digital and physical are increasingly blurred. As such, we are just beginning to see how customized access to space will improve asset stewardship in ways that are still evolving, as customization of on-orbit technology pushes the bounds of how we receive and process information. Specific to oil and gas operators, one technology being launched by microsatellite, hyperspectral imagery (HSI), is poised to enable unparalleled daily global pipeline leak prevention, detection and speciation, intrusion and change detection capabilities. This will replace conventional DOT pipeline patrol for compliance while contributing to our understanding of vapor emissions as regulated by the Environmental Protection Agency. This paper discusses both the evolving space marketplace and the state of the art for HSI, including current examples of hyperspectral findings regarding pipeline and terminal leaks. Successful deployment of HSI will drive a decrease in the number and magnitude of pipeline leaks using persistent, global, high-resolution data collection, rapid and reliable analysis, and immediate reporting of actionable information. For decades, satellite HSI technology has offered a promise of remote hydrocarbon detection and other features of interest. It is only now becoming scalable, accessible to, and cost-effective for the pipeline industry, and thus a reality for cost-effective pipeline stewardship.

Lessons Learned From Freespans at Pipeline Watercourse Crossings

Over the past 10 years inspections (site visits, boat based surveys or diver surveys) have been completed at nearly 20,000 pipeline watercourse crossings for 20 different pipeline owners. During the last 10 years there have been 721 unique locations where an exposed pipeline was found and at 213 of these locations a freespan was encountered. Only one of the freespans resulted in the failure (loss of product) of the pipeline. This record illustrates what is now become widely accepted, that pipeline exposure does not necessarily lead to pipeline failure. The record adds to this, pipeline freespan does not necessarily lead to failure. This highlights that the relevant question for “water loading caused pipeline failure” is: Does the combination of freespan length and water velocity exceed a combination that would lead to vortex induced vibration or the exceedance of the static load limit of the pipe?

Establishing a Detection Threshold for Acoustic-Based External Leak Detection Systems

A better understanding of the sensitivity threshold of external leak detection systems can assist pipeline operators in predicting detection performance for a range of possible leak scenarios, thereby helping them to make more informed decisions regarding procurement and deployment of such systems. The analysis approach described herein was developed to characterize the leak detection sensitivity of select fiber optic cable-based systems that employ Distributed Acoustic Sensing (DAS). The detection sensitivity analysis consisted of two steps. The first step involved identifying a suitable release parameter capable of providing a defensible basis for defining detection sensitivity; the second step involved the application of logistic regression analysis to characterize detection sensitivity as a function of the chosen release parameter. The detection sensitivity analysis described herein provides a means by which to quantitatively determine the leak detection sensitivity threshold for each technology and sensor deployment position evaluated in a set of full-scale tests. The chosen sensitivity threshold measure was the release parameter value associated with release events having a 90% probability of being detected. Thresholds associated with a higher probability level of 95% were also established for comparison purposes. The calculated sensitivity thresholds can be interpreted to mean that release events associated with release parameter values above the sensitivity threshold have a very high likelihood (either 90 or 95%) of being detected.

The Application of Numerical Simulation to Liquid Pipeline Leakage at LNG Terminal in China

In 2018, China’s natural gas import reached 90.39 million tons, and the liquefied natural gas (LNG) import was 53.78 million tons, accounting for 59.5% of total natural gas imports. With the construction of LNG terminals, more studies on the leakage of LNG storage and transportation facilities have emerged to prevent catastrophic consequences such as explosions and frostbite. However, most of previous researches focused on gas pipeline leakage after LNG gasification, and few of those have been done on LNG liquid pipeline leakage. In this paper, Fluent software is used to numerically simulate the process of LNG liquid pipeline leakage. After the occurrence of LNG leakage, it will suffer the process of endothermic, evaporation, and diffusion, which is considered as a two-phase diffusion process. The Euler-Lagrangian method is introduced to simulate the diffusion process of gas phase and liquid phase separately. In the simulation, the liquid phase is regarded as discrete droplets for discrete processing. The movement trajectory, heat transfer process and evaporation process of each droplet are tracked respectively. Different from the liquid phase, the gas phase is regarded as a continuous phase and the Navier-Stokes equations are adopted for calculation. Thereafter, coupling calculations of two phase are performed to determine the concentration field and temperature field of the LNG liquid pipeline leakage. As a supplement to this research, the influence of wind speed on LNG leakage and diffusion process is analysed in detail. Finally, the numerical simulation method is applied to a coastal LNG terminal in northern China to determine the distribution of natural gas concentration and temperature, as well as delimit the combustion range. The results can provide scientific reference for the delimitation of risky zones and the formulation of emergency response strategy.

Oil Temperature Prediction of Long-Distance Hot-Crude-Oil Pipeline Based on GA-BP Optimization

Due to the high pour point of the oil products transported in the long-distance high wax crude oil pipeline, in order to ensure the operation safety, it is necessary to adopt heating transmission technology, so as to ensure that the oil temperature along the pipeline is 3–5 °C higher than the pour point, that is to say, the oil temperature is the most important operation parameter of the long-distance hot oil pipeline, and the accurate prediction and control of the oil temperature is the premise of the pipeline safety optimization. Aiming at the problems of large prediction error and poor applicability of the previous theoretical formula, this paper studies the establishment of oil temperature prediction model by using data mining algorithms such as Back Propagation (BP) neural network, and improves the prediction efficiency and accuracy of the model by using Genetic Algorithm (GA) optimization. The correlation coefficient formula is used to calculate the influence coefficient of oil temperature, ground temperature, pipeline transportation and other parameters on the inlet oil temperature of the downstream station, so as to obtain the input parameters of the model. The actual production data training model is downloaded through SCADA system, and the prediction accuracy of the control model is ±0.5 °C. Compared with BP model and other theoretical formulas, the accuracy and efficiency of GA-BP oil temperature prediction model are greatly improved, and the adaptability is better. The GA-BP oil temperature prediction model trained according to the actual production data can be effectively applied to the future pipeline big data platform, which lays a theoretical foundation for the intelligent control of the pipeline.

Repair of Leaks in Thin Wall High Pressure Pipelines Using Composite Reinforcing Technologies

A study was conducted to evaluate two composite repair technologies used to reinforce severe corrosion and thru-wall leaking defects in thin-walled pipe materials; conditions where the welding of conventional Type B steel sleeves cannot be conducted. This program involved the reinforcement of simulated 85% corrosion defects in 6.625-inch × 0.157-inch, Grade X52 pipe materials subjected to cyclic pressure and burst testing. The test matrix also included repaired pipe samples with thru-wall defects that were pressurized using nitrogen gas and buried for 90 days. The program was comprehensive in that it evaluated the following elements involving a total of 81 reinforced corrosion defects. • Corrosion features with a depth of 85% of the pipe’s nominal wall thickness in thin-walled pipe material (i.e., 0.157 inches, or 4 mm). • Thru-wall defects having a diameter of 0.125 inches (3 mm). • Repairs made with leaking defects having 100 psig (690 kPa) internal pressure. • Strain gage measurement made in non-leaking 85% corrosion defects; it should be noted that the remaining “15%” ligament was 0.024 inches (0.6 mm); to the author’s knowledge, no high-pressure testing has ever been conducted on such a thin remaining wall. • Long-term 90-day test that included pressurization with nitrogen gas, followed by relatively aggressive pressure cycling up to 80% SMYS followed by burst testing. This is the first comprehensive study conducted by a major transmission pipeline operator evaluating the performance of competing composite technologies used to reinforce severe corrosion features with thru-wall defects. The reinforcement of leaks has not been accepted by regulatory bodies such as the Canadian Energy Regulator (CER), or the U.S. Pipeline and Hazardous Materials Safety Administration (PHMSA). A goal of the current study is to validate composite repair technologies as a precursor to regulatory approval. The results of this study indicate that viable composite repair technologies exist with capabilities to reinforce leaks in pipelines that experience operating conditions typical for gas transmission systems (i.e., minimal pressure cycling).