We will describe an in-house developed software application that uses DNV’s Solver and Python programming language to proactively perform various parametric hydraulic studies. We will discuss the deep system intelligence gained from the comprehensive data provided by thousands of hydraulic results along with multiple study types performed and the highly valued, practical business benefits obtained. We will also discuss the application’s potential use for retiring gas facilities as demand drops due to building electrification.

In this study, machine learning (ML) algorithms are utilized to predict the minimum flow rates required to transport sand particles successfully in intermittent and stratified gas-liquid flow regimes in pipelines. The models predict the value of critical velocities in pipes via ML using accessible parameters as inputs, namely, sand concentration, pipe diameter, pipe inclination, liquid and gas properties, particle size and density. The predictive abilities of the models are further validated by comparing their performance with well-established mechanistic models based on empirical correlations. The results indicate that the proposed method gives comparable or even higher scores by contrast to correlations and mechanistic models for multiphase flow, while it is significantly faster and could be easily employed for industrial applications.

The paper will primarily focus on taking field data from a Solar customer across a segment of their pipeline to see how transients play out in data, at various sampling rates: 10 sec, 1 min, 10 min, etc. We will use the most interesting transients in the data as examples in the paper. We will then setup the transients in the modeling framework we presented last year and compare results. We believe that getting actual, high fidelity field data out into the public domain will greatly benefit modelers and operators alike.

Erosion damage caused by solid particles in multiphase flows can affect the operation and integrity of fluid transport pipeline systems. Amongst available approaches for predicting erosion, mechanistic models provide reliable predictions under various conditions with a low calculation time. The purpose of this study is to develop a novel mechanistic model for predicting erosion in multiphase flows which is based on the trajectory of particles and the characteristics of various upward vertical flow regimes. Computational models are used to construct a trajectory-based model in a three-dimensional domain of the elbow geometry which describes the flow around the particles. Flow regimes such as bubbly flow, churn flow, annular flow, and mist flow are characterized and applied to the trajectory-based model. The validity of the proposed model is examined using a large number of experimental erosion data from previous studies and comparing with the available mechanistic models from the literature suggests that the new model can provide more accurate predictions for gas-dominated flow and high liquid rate conditions.

This paper presents approaches for calculating leak rates through a pipe hole/crack of various sizes and shapes. Also, methods are presented for estimation of the total released volume during the time that the pipeline was leaking. The presentation will discuss the methodologies including hydraulic simulations used for leak rate and released volume calculations. The effect of pipe operating pressure on the pipe crack opening area will be discussed.

This paper discusses the use of the shear stress-based analysis approach to predict the DRA degradation performance in real operational scenarios for different fluid properties (viscosity, density, wax and other impurity contents), pipeline characteristics (diameter and length) and flow rates. The maximum drag reduction empirical formula based on Virk’s asymptote theory is generated as preliminary drag reduction potential assessment. Some rules of thumb formulas are provided for drag reduction gain and loss calculations as practical references. When the shear stress acting at the pipe wall exceeds a specific threshold, the DRA behavior is depicted as the pseudo steady-state condition, in which the time variable will be introduced to define a kind of dynamic drag reduction phenomenon. The presentation will discuss this DRA performance prediction method, rationale and key findings.

Field experience shows that the estimated DRA dosage can be underestimated, and predicted DRA performance does not always match actual field performance. This paper presents two DRA application cases in refined product pipelines, in which the actual DRA performance achieved was lower than predicted. The causes for deviation were studied, and mitigations for meeting the target flowrates were proposed.

Pipelines that have intermittent flow, can often be a difficult for a Leak Detection System (LDS) to manage reliably without causing issues with sensitivity. The LDS’s for these pipelines often require significant effort to tune and re-tune. The writers of this paper developed a highly reliable and robust LDS that automatically adapts to changes in pipeline operations. The model uses a simplified linepack model using a LaGrangian frame of reference to track the fluid elements along the pipeline. In addition a simplified Newtonian cooling heat transfer model was developed. This Newtonian cooling model continuously adapts, using feedback from temperature data and slack estimates from previous pipeline start-ups. The LDS is currently in use on one pipeline, and the result is a very sensitive system, where the cause of all false alarms to date have been identified and removed.

This paper deals with natural gas odorization for leak detection tasks in gas networks. The presentation will discuss the development of a machine learning model for monitoring the odorization system at a city gate station in Italy.

Energy transition is required to meet the world’s climate change goals. Early pro-active consideration and out of the box thinking are needed to successfully navigate to the energy transition future. Natural gas utilities and pipeline companies have infrastructure well positioned to adapt. This paper will discuss learnings and challenges facility planning engineers should consider when modelling hydrogen, renewable natural gas, building electrification, advanced metering, banning or restricting natural gas usage, forecasting and integrated resource planning.

To improve project economic viability of an electrolyzer at a utility-scale solar farm, Low Carbon Fuel Standard pathways by means of utilizing the natural gas system in California is proposed and evaluated. This paper contextualizes the carbon footprint of these novel pathways featuring hydrogen injection compared to producing hydrogen via steam methane reformation.

This paper discusses the intrinsic leakage reduction that can be achieved by regulating the outlet pressure of a City Gate Station. The presentation will discuss the theoretical approach used to estimate the amount of avoidable leakage in a medium pressure distribution network located in Italy.

In the context of carbon reduction efforts, discussions evolve around hydrogen compression, as well as compression requirements related to CO2 capture, transportation and sequestration. The study includes realistic descriptions of the necessary compressor designs for the compression of CO2 from the capture point to the pressures needed for transport. The compression of Hydrogen, either as pure Hydrogen, or as Hydrogen-Natural gas mixture, as well as considerations on transporting the gas in pipelines are studied and presented.

The paper will review natural gas system decarbonization proposals and efforts in California. An overview of various gas decarbonization approaches including hydrogen, renewable natural gas, and building electrification will be provided. The remainder of the paper will discuss building electrification to reduce or eliminate gas use and the expected impacts on gas throughput, revenue, and gas rates. The need to retire portions of the gas system to reduce costs and manage gas rates will be discussed. The paper will conclude with a review of the complex hydraulic analyses needed to identify gas system retirement and the potential use of parametric studies to perform the analyses.

This paper will discuss the thermodynamic and mass flow changes that can occur with blending in hydrogen and how that affects pulsation frequencies, amplitudes, and pulsation control systems. Pulsations can negatively affect many areas of pipeline operation including compressors stations, metering areas, and piping hubs, and it is important to ensure that sufficient pulsation control or avoidance occurs when creating operational modifications. The theory behind pulsation control systems and vortex-shedding will be discussed in this presentation with case study examples used for illustrative purposes.

This paper identifies the challenges in the automation of process flows in pipeline scheduling. Besides highlighting that a hybrid tool with built in strategies together with manual intervention alone can help in addressing the requirements, the paper also confronts the solution providers towards advancement of features for ease of use and effectives in scheduling pipeline activities.

The complex operations of large water pipeline networks and their tanks present a good opportunity for numerical optimization. While during normal usage these networks can be expected to more or less follow a daily cycle, an optimizer is helpful when planning maintenance, when dealing with equipment failures or supply interruptions, and in planning extensions to the pipeline network. This paper presents a complete end-to-end optimization approach which solves for tank levels, pump and regulator valve setpoints, ressures and flow rates to meet the demand schedules while obeying all operational constraints and minimizing the total power and maintenance costs. This optimizer uses multiple stages to solve different parts of the problem, applying a combination of nonlinear programming, dynamic programming, simulated annealing, and a transient hydraulic model, while taking advantage of the unique problem simplifications possible in a water network. We present the algorithm and some example scenarios, as well as some of the challenges that arose during the testing and commissioning process on a real pipeline.

Fast turnaround on individual gas or liquid simulations can be crucial to support time critical operational or planning decisions, but complex transient simulations of large systems can be slow. Standard techniques for speeding up transient simulations via parallel computation generally require expensive low-level software rewrites. We present an a parallel method that can be applied with little-to-no modification of existing software, and present both liquid and gas pipeline examples. The method is applicable both to desktop and cloud machines, and scales to arbitrarily large pipelines.