Abstract This paper investigates the technology and business benefits of a web-based model scheduling application, which integrates a transient model to other business applications that provide injection and demand schedules. The application provides a simple method to input complex scenarios, including compressor, regulator, and routing operations. The paper shows how the system allows non-modellers to use a complex transient model, reducing non-optimal operational decisions which could impact the wholesale natural gas price or supply to end user customers such as households or businesses. Other operational metrics are discussed. Introduction and Background Independent System Operators’ (ISOs) and Transmission System Operators’ (TSOs) use of transient pipeline models to manage nominations and allocations is seemingly an easy operational premise. The Australian Energy Market Operator (AEMO) operates the gas Declared Transmission System (DTS) which serves Victoria, a state in Australia. The DTS network consists of approximately 2,200 km of transmission pipelines with various lengths and diameters, and transports gas to a network from up to 10 different suppliers. The high pressure meshed transmission network supplies gas to 148 custody transfer points which spans the geographical extremities of the state. The DTS is becoming increasingly more complex, with changes to flow paths and dynamic demand regimes. AEMO, like other TSOs and ISOs, is utilising transient pipeline models to inform operational strategies. This paper explores the challenges facing ISOs and TSOs in the United Kingdom, The United States, and Victoria Australia. Specific reference is made to AEMO’s gas transmission network. The issues explored cover a range of subjects including financial and macro policy but all lead to the impact on a transmission network. The paper does not attempt to solve each transmission operator’s challenges in detail. However, within the context of AEMO’s operations, it attempts to identify the similarities with other TSOs and highlight how AEMO’s transient hydraulic model helps it deal with its challenges.

Abstract The purpose of a pipeline Operator Training System (OTS) is to train operators in an offline environment, while giving the look and feel of real-world operations. The problem with many OTS’s is that, while some aspects of pipeline operation are covered, it can be very challenging to simulate other parts in an effective manner. Real-world pipeline operations encompass many “moving parts” that are often ignored or highly simplified in an OTS, but the inclusion of these parts can vastly improve the training experience. The integration of these many parts poses unique challenges in the design of the pipeline simulation as well as the operation of the simulator. This paper will discuss the challenges and solutions found during the development of an OTS that integrates liquid and gas pipeline operation, pump station power plant startup, PLC control, and power distribution management models. These models were integrated in such a way as to give an operator fully comprehensive training on every aspect of the real-world system included in their operating responsibility. Introduction and Background An Operator Training System (OTS), also called an Operator Training Simulator, is an offline system that dynamically simulates real world processes. The most realistic platform of an OTS is one in which the simulation of real world processes is integrated with a stand-alone copy of the Supervisory Control and Data Acquisition (SCADA) system or Distributed Control System (DCS) that is used in the pipeline control room. This OTS platform allows for training of new operators, retraining existing operators, testing out new operating procedures, validating control logic or PLC logic prior to commissioning, etc. It can also be used for offline engineering analysis and calculations that allow for efficiency improvements or in-depth studies into how equipment modifications may affect the system. OTSs are commonly found in industrial processes such as plant or pipeline operations. Often the scope of an OTS is limited or simplified due to the complexity in modeling real world systems and the extra time and effort required to implement a full-scope simulation outweighs the added benefit derived by those using the system. On the other hand, with advances in computing and OTS conception, very complex systems can be modeled that give the look and feel of a real-world system such that operators training on them may find them difficult to distinguish from the online system, providing a seamless transition from OTS to real world operation. As with all engineering considerations, there are tradeoffs that must be balanced and compared with the end goal of the training system in mind.

Abstract Software for the simulation of the transient behavior of natural gas pipelines commercially available, however, due to their high computational demands, they do not allow real time simulations. Further, they are difficult to set up if the goal is to match measurement data from SCADA systems or compressor stations for existing pipelines. To overcome this difficulty, a state space approach is used to capture the transient behavior of the pipeline. The general approach takes a published method from the literature that derives transfer functions and state space equations from one-dimensional Navier-Stokes and extends the method to reduce uncertainty in modeling parameters. The present method is validated against results in the literature. Then, a pipeline is modeled with commercially available, well established software, and the transient behavior is simulated and the results are compared with the present method. The main contribution of the paper is the extension of the stat-space formulation to remove uncertainty in pipe-roughness assumptions through systematic estimation of friction factors. Introduction Natural Gas Pipelines are an efficient method to transport energy over large distances. The transportation of natural gas and/or blends of natural gas and hydrogen over large geographic areas requires efficient operation of compressors and other related facilities. The scheduling of flows throughout a piping network is a great challenge to control theory. Many gas pipelines are operated under unsteady operating conditions, which in turn causes significant fluctuations in the operating conditions for the compressor stations in these pipelines. These fluctuations are the result of varying demand, as well as varying gas supply. For a given pipeline segment, the gas supply pressure and flow into the pipe are subject to change as are the pressure and flow demand on the delivery side of the pipe. These conditions, as well as their timing are only predictable to a degree.

ABSTRACT LNG Terminals represent key infrastructure for gas markets in many regions. With markets shifting to a more global approach, what happens when your operational cases evolve, and the original design specifications are challenged? Or worse an operational event exposes weakness in the design? The priorities on any site continue to be around safe, profitable operation and maximising capacity/uptime. Under normal operation piping systems can withstand the resulting stresses. Events such as rapid PERC (powered emergency release coupling) closures, Emergency Shut Downs (ESDs), valve operations, and pump trips can all create transient effects. Consequences can include excessive surge pressures which in turn lead to increased pipe stresses and structural loads. An ongoing relationship with a large LNG terminal operator has driven studies into hydraulic surge in pipelines following Emergency Shut Down (ESD) events and developed this hydraulic understanding to include bend forces and resolved pipe forces which could be passed into targeted structural analysis. Over time, scenarios have become more complex including for example an increasing need to be able to re-load ships from a site originally designed as an import terminal. Alongside the technical challenge of these studies; a key factor was generating justifiable rationalisation of all permutations of operating scenarios into a manageable quantity of worst-case simulations for a multi-tank and multi-jetty site. Combined with the increasing complexity of cases we were required to develop methods to run simultaneous simulations and manage the model files and outputs in a reliable fashion. More recent work has led to feeding the force outputs into static and dynamic load analysis to understand the force and harmonic interactions with the physical structures on the site. Pressure and force results were extracted for each scenario using a high-fidelity hydraulic model and then utilized in structural analysis tools for further analysis. This paper outlines the evolution of a complex modelling problem, and the effects of working on an inherited model from a 3rd party and architecture built on scripting tools to solve problems now integrated into our modelling solution. With the concept of simultaneous modelling runs and parametric studies commonplace in today's environments, we consider the progression of this approach to meet future requirements.

ABSTRACT Upstream gas supply planning and allocation contains 3 cycles namely long term (20 years - end of life of a field) mid-term (up to 1 year) and short term (72 hours). Since the upstream assets are owned/operated by different companies under various production sharing contracts, each of the operating companies prefer to maximize their production and recover the investment costs at the earliest. A regulator acts as a custodian to ensure that all stakeholder's entitlements are protected. The custodian relies on economic and hydraulic modelling to analyse the production plateau's shared by various operating companies together with the demand profiles for viability. The commercial planning team of the custodian works closely with flow assurance engineers before confirming the production numbers as the planners are unaware of any capacity constraints in the physical network for flow. In the short term, an integrated network operator breaks the long term demand numbers and controls the network for seamless delivery of gas from upstream to LNG plants (mostly). The purpose of the paper is to highlight the challenges faced by planners and engineers during the planning cycles and to make appropriate recommendations.

ABSTRACT This paper provides an overview of Pacific Gas and Electric Company's (PG&E) In-Line Inspection (ILI) process from start to finish. PG&E's integrity management program encounters numerous operational challenges as it expands its in-line inspection program to include more challenging pipelines than previously inspected. The company has addressed these challenges by developing a rigorous hydraulic feasibility study process that evaluates risks associated with a respective ILI run before making the decision to proceed with pipeline retrofits to accommodate in-line inspection tools. Several new operating methods have been developed to increase the number of pipelines hydraulically capable of in-line inspections, while reducing risk. Two tools that PG&E has developed to analyze ILI system operations will be discussed. PG&E's Batch Analysis Tool (BAT) is used to conduct complex, multiple-scenario hydraulic analysis. Data results are then processed through an ILI BAT Results Tool, which summarizes BAT data into easily-viewed charts and tables. This allows engineers to consistently analyze and document predicted ILI run gas velocities and system response to varying operations during the inspection. Once detailed analysis is conducted, preparation for the ILI is required. This paper will discuss upgrading pipelines to accommodate inspection tools, developing detailed operating plans, directing real-time operations, and preparing to respond to operational impacts due to anomalies identified on the line. A case study of an ILI on Distribution Feeder Main (DFM) 0617-06 is presented to exemplify PG&E's ILI process from start to finish.

ABSTRACT Assessing the discharged volume during third party digging damages with efficiency and acceptable accuracy is a challenge for multiple reasons. It involves complex physics phenomena, requires taking the right assumptions and has to be perform relatively quickly as the number of cases to compute each year is important. This paper summarizes the application of a comprehensive methodology used to perform this task. The first part deals with the required field measurements needed to be obtained, the selection of an adequate physics equation as a function of the flow regime and the linkage between an analytical equation and a commercial CFD software to obtain a valid network pressure at the damage point. In the second section, a validation attempt between computed results and field measurements is made using two different sets of data. First, for some very specific incidents where the pipeline damage is close to a gate station with SCADA recording, it is possible to obtain an hourly flow profile at the break. Second, simple configurations of pipe rupture have been replicated in laboratory and tested with air. For most of the cases, the described methodology shows a good match with experimental data with typical discharge coefficient values in the range of 0.61 to 0.92. INTRODUCTION AND BACKGROUND Gaz Metro « GM » is the main natural gas distributor in the province of Quebec on the east part of Canada. The territory is connected to the TCPL Mainline (figure 1) at the very end of the transmission system. GM distributes 97% of all natural gas in Quebec (figure 2) to over 200 000 customers located in more than 300 municipalities [1]. This can be achieved by an asset of 10 000 km of underground network pipeline with more than 90% being distribution mains and services, mostly small diameter plastic pipes. Along this distribution network, digging damages by third party represent by far the primary reason for unplanned emergency response and an important part of the total non-fugitive annual gas loss. Each year, 300 to 400 rupture cases are reported and analyzed.

ABSTRACT In recent years, pipeline operators have faced reduced production environments caused by declining brownfield operations and capital constraints induced by oil prices, among other factors, which have led to pipelines operating well under their designed capacity and challenges such as congealing—the precipitation of wax solids in a crude oil pipeline. This paper discusses how models are built using scientific principles and how simulation may be used to predict where congealing is or may occur inside a pipeline. Finally, a case study from a major oil and gas company's site demonstrates how these modeling and simulation techniques may be effectively applied in the field. INTRODUCTION AND BACKGROUND Pipeline operators are currently challenged with operating pipelines safely in reduced production environments, which have been caused by declining brownfield operations, capital constraints brought on by oil prices, and the lack of drilling rigs to keep pipelines full. These present conditions result in pipelines operating well under their designed capacity and challenges such as congealing. Congealing refers to the precipitation and nucleation of wax solids in a crude oil pipeline. It is initiated by a temperature gradient between the pipe wall and the centerline flow, leading to high-yield flow stress and causing changes in flow behavior. This paper discusses the physical considerations that contribute and are necessary to detect congealing followed by a series of modeling steps to accurately simulate when and where congealing occurs in a pipeline while accounting for multiphase flow of differing compositions from multiple producers. In turn, this information can automatically be displayed as a visual pipeline profile, allowing operators to understand their entire pipeline operation from remote locations and view critical parameters and events, such as congealing, leak detection, and slugging. These modeling and congealing algorithms were implemented and validated at a major oil and gas company's site on a 150-km (~93.2 mi) commercial pipeline network used to transport roughly 50,000 BOPD (7,949 m 3 /day) from 11 gathering stations to a distribution tank farm. The main transportation pipeline was designed to transport 500,000 BOPD (79,490 m3/day). Congealing events were detected and verified by comparing the simulated and assayed pipeline data. Prediction time averaged between three and six hours in advance of the congealing event, allowing the pipeline operator take appropriate mitigation actions and reduce lost production opportunity (LPO).

Abstract In designing large-scale pipelines and facilities, a common trade-off involves cost versus risk. The conservative design margins of the past may today be the tipping point in making projects non-economic. This paper aims to identify critical factors for facilities design projects with an objective to increase the confidence in our go-to-purchase decisions. A practical decision making procedure applicable to flow assurance problems in general is presented that considers both rigorous multiphase pipeline simulation as well as facilities costs. A case study previously published in a PSIG paper is revisited to illustrate how these concepts may be applied in sizing a slug catcher. Introduction As the transport of oil and gas products in a multiphase manner is increasingly stretched over greater distances with development in more hostile environments, so too has the importance of sustaining reliable operations. The flow assurance discipline tackles these challenges using scientific methods to design reliable systems and infrastructure while identifying the inherent risks involved in production from such environments. As engineers, we formulate system designs and operating procedures to manage all risks involved. One common trade-off in this domain is cost versus risk. Overly conservative design margins may result in projects that are uneconomic. We have recently seen deep water offshore systems re-designed to be sanctionable with substantial cost reductions being achieved. During 2015, a relatively small number of major projects made Financial Investment Decision (FID) approval due to the low price of oil. Deepwater projects were hit the hardest with just a handful being given the go-ahead, the most significant being BP's West Nile Delta in Egypt and Shell's Appomattox in the deepwater Gulf of Mexico. One theme shared by all projects that did manage to achieve commercial approval was significant cost savings. For example, Shell cited an overall cost reduction of 20% for Appomattox [1], driven by design optimization and supply chain savings. BP cut less than 10% from its original budget for the Egyptian West Nile Delta project at FID [2], which seems low in comparison. But closer inspection showed that they had opted to re-phase expenditures significantly, reducing the upfront scope and cost. In addition, the project had a contracted gas price floor, thus providing some revenue protection from further market deterioration. It is estimated that Shell's Appomattox has a Net Present Value (NPV, see appendix for more details) breakeven of $50/bbl [3], which set a new benchmark for deepwater FIDs. However, it is one that still remains out of reach for most other projects. Pre-FID deepwater projects have an average NPV breakeven of $65/bbl [3]. This means significantly more cost reduction is necessary - at least another 15-20% – before the stricter investment hurdle rate is met. Current market conditions clearly drive cost-based project reviews and eventual re-design. Furthermore, the ability to optimize costs at the concept development stage of projects is now a key element of the project approval process.

Abstract Pipeline simulation tools have traditionally been used for modeling large pipeline networks; however, their quick solve times have made these tools attractive for many other applications ranging from process plant piping to valve manifolds. The governing equations and solver used by pipeline simulation tools are indeed applicable to any flow network, although many software packages offer a variety of choices that need to be properly adopted for each application. The first half of this paper will use examples to show in detail the impact of including thermal effects (adiabatic vs. full heat transfer), selecting appropriate fluid properties (single phase and simplified emulsion models), including viscosity effects on pump performance curves for a variety of systems, and model tuning and validation. Another important consideration for modeling systems ranging in size is how to represent the flow network. For example, the impact of pressure drops caused by a bend, tee or reduction is much greater on a valve manifold than on a transcontinental pipeline, thus it is important to adopt the modeling methodology to the system scale. In addition, to accurately represent a liquid system it is necessary to represent the piping from all primary flow paths; however, to achieve quick model run times piping networks often need to be simplified. The second half of this paper will compare methods for simplifying piping network ranging in size such that pressure drops of all pipes, bends, and tees are represented and discuss the effect of these methods on steady state and transient modeling. A case study will be presented to show the impact of the modeling considerations. Introduction and Background Pipeline modeling tools for predicting the performance of liquid systems are well established in the industry. With the success of these tools, they are beginning to be applied to systems not originally envisioned such as cooling loops for power generation and fuel injection manifolds. A variety of tutorials exist in the literature such as those in references [1] and [2] on what to consider when modeling traditional liquid systems. It is, however, important to address several modeling approaches and assumptions that must be adapted to the scale and type of liquid system. The purpose of this paper is to fill the void by describing key concepts to consider when modeling non-traditional systems and to demonstrate the concepts by analyzing two case studies. These concepts can be applied to any modeling tool.

Abstract In this paper, we present an integrated simulation tool for analyzing the interdependency of natural gas and electric power systems in terms of security of energy supply. In the first part, we develop mathematical models for the individual systems. In part two, we identify the interconnections between both systems and propose a method for coupling the combined simulation model. Next, we develop the algorithm for solving the combined system and integrate this algorithm into a simulation software. Finally, we demonstrate the value of the software in a case study on a real world interconnected gas and electric power system of an European region. Introduction The ongoing integration of renewable energy resources into the energy portfolio of the European Union is connected with an increased interconnection between the different critical energy infrastructures (CEI). The interdependency between natural gas and electric power systems, for instance, is expected to grow in the near future. On the electric side, the demand for flexible backup power for intermittent renewable energy sources is increasing, which can be met by gas fired power plants (GPP) connected to the gas and electric grid, while on the gas side an increased use of electric power to operate facilities in the gas system can be observed (e.g. electric driven compressors, electric power supply to LNG Terminals etc.). Moreover, the present advancement in the Power-to-Gas technology will significantly contribute to the coupling of both systems. These trends suggest the need for simulation models to examine the depth and scope of these interdependencies, how they may affect the operation of both systems and how to proactively approach the bottlenecks that may emerge. Furthermore, developing combined gas and electricity models will also facilitate the development of Risk Assessment for this type of coupled networks. In this paper, we present an integrated simulation tool for analyzing the interdependency of gas and electric power systems in terms of security of energy supply, i.e. the uninterrupted supply of energy to its customers (e.g. commercial, residential, industrial customers, public services and power generation companies) particularly in case of difficult climatic conditions and in the event of disruptions [1]. The first part of the paper, focuses on developing the mathematical models for both systems. The second part, elaborates the interconnections between both systems and derives coupling equations for the combined system, followed by a description of the algorithm for solving the resulting system of equations. Finally, the capability of the simulation tool is demonstrated by applying it to a real world instance.

Abstract As described in PSIG paper 1613, PG&E's Batch Analysis Tool (BAT) allows a planning engineer to run hundreds to thousands of simulations automatically and sequentially rather than manually, one run at a time. This functionality greatly increases efficiency and allows for thorough analyses of all potential scenarios. This paper will present an actual use case study where BAT was utilized to perform over 6,500 simulation runs to gain system intelligence, optimize operations and gain customer reliability information for a multitude of operating scenarios for 256 combinations of system operating restrictions. As the location of the San Bruno pipeline incident, PG&E's Peninsula Local Transmission (LT) System has a high level of safety focus and activity.[1] In-line inspection (ILI), strength tests, pipeline replacements and automatic and remote control valving projects result in system outages throughout the year. In addition, ILI's and strength tests can result in pressure reductions, and/or pipeline sections being isolated, which can significantly reduce capacity and the ability to meet customer demand. Customer service reliability is of particular interest for pressure reductions or operating restrictions that may occur during the high demand winter heating season. This paper will present the use of the BAT in an actual study performed on the Peninsula LT system. Five major sections of the gas system faced potential operating restrictions resulting in 256 operating restriction scenarios. Each operating restriction scenario was analyzed at various temperatures, and at various operating configurations (pressure set points, cross-tie operations, interruptible non-core customer curtailments, use of portable Compressed Natural Gas (CNG) or Liquefied Natural Gas (LNG), and modeling uncertainty). In only 59 hours the BAT technology was used to complete an extensive and complex hydraulic analysis of 6,500 runs. Performing the analyses without BAT, manually a single run at a time, would have taken weeks and only yielded a fraction of the runs and system intelligence. The expansive analysis identified the most impactful operating restrictions, the best ways to operate under the restrictions, and the time of year the system would be most at risk of not meeting demand. This paper will illustrate how the power of the technology used to rapidly perform hundreds to thousands of runs provides critical system intelligence, optimize operations to maximize capacity and improve customer service reliability and fully understand operational risks when making key decisions on proceeding with the safety work.

Abstract Midstream gathering systems present several unique pipeline simulation modeling challenges. The first, and most significant challenge, is that systems are not static. In fact, systems are constantly changing as new wells are added and depleted. One method of handling this constant change is to use geographic information systems (GIS) to build models. This requires the simulation software to be capable of importing and exporting GIS data, fix topology errors on the fly, convert 2D GIS data to 3D using digital elevation models, and display the models over geo-referenced aerial backgrounds. The second challenge is that gathering systems are often multiphase, enabling liquids and solids to collect in low spots or low velocity areas. In addition, gathering systems are often looped and interconnected. The combination of multiphase and multipath networks makes predicting flows and pressure drops difficult. In order to accurately portray how a system would react in the real world requires the simulation to be tuned often. Unfortunately, manually tuning a complex gathering system is practically unfeasible. Automatic tuning algorithms utilizing SCADA data to tune the model is likely the only reliable method to accomplish this task. This makes it possible to determine the location and severity of liquid holdup, hydrates, or salt buildup. In addition, simulation software can be used to debug new models by identifying incorrect geometry, equipment, or operational parameter model inputs. The third challenge is analyzing and understanding the simulation results. This requires the application to have both the ability to create 2D or 3D color simulation maps and graphs for visual interpretation, as well as, export the results into spreadsheets for further analysis. Introduction One of the primary purposes of computerized pipeline simulation is to assist midstream companies to troubleshoot existing systems and design modifications or new systems. The tools available to the industry today enable companies to analyze and make decisions quicker, more reliably and efficiently.

Abstract The article presents the possibility of replacing the gross calorific value measurements for the individual exit points with simulation result verified by the measurements of reference gas. The results of simulation are used for transport and balancing settlement purposes and optimization of market based system services used for ensuring integrity of system.The paper describes the work related to the research of the methodology on the artificial network in order to check the functioning of the model. Subsequently it presents the results obtained after the implementation of this methodology in the Polish gas transmission system. Admission As a result of regulations arising from the development of a competitive market for natural gas, the gas divisions of large enterprises were made. The existing large gas companies operating on the individual countries markets were divided into companies related to technical infrastructure and companies dealing with natural gas trading. The infrastructure operators are now called respectively the transmission system, distribution system and storage system operators. The principles of their functioning and relationships with traders are regulated by the European Union rules and the national ones. The developing liberalized gas market results in a rapid increase in the gas trading competition. Due to the uses of gas as an energy carrier the companies involved in gas trading are interested in providing a certain amount of energy, not the volume of gas. It causes the situation that the distribution and transmission system operators are inclined to execute the gas transmission contracts accounted in energy units. Natural gas is a raw material for the chemical industry as well as an energy carrier. Gas is transmitted from the source to the customer installation by the pipeline network. Despite the same name "natural gas", its composition and resulting from it the physical and chemical parameters are different and depend on source types they are extracted from. Until recently, the transmission and distribution systems were associated with individual source of very similar gas quality parameters. The system supplied from Siberian or Caucasian sources practically had no connections with the system supplied form the North Sea source. The significantly different gas quality system had the special installation (blending station), in which the components proportions were under the operators control. Currently as a result of the intensive development of the liberalized European gas market and transmission infrastructure, the operators face many challenges associated with increasing requirements concerning the execution and settlement of natural gas transmission services.

Abstract Due to the different geographical distribution of the natural gas sources and the consumers, the overall trend of the natural gas pipelines in China is from west to east and from north to south, and the patterns of multiple gas sources, multiple consumers, and unified network are formed, the natural gas pipelines are always in a state of high pressure and high pipe inventory. However, the complexity and importance of the large-scale pipeline network bring the centralized dispatching many new requirements, including the control of the entire pipeline network, the operating plans of every pipeline, and the fluctuation of market demands, the pipeline simulation software is often used to solve these problems. Though the application of the modern pipeline simulation system show it has a good accuracy, our study indicates some problems still exist, especially the low efficiency caused by slow computing rate, and its stability and performance cannot meet the practical needs of the large-scale pipeline network system, for it will easily go crash if the time step is longer than 6 seconds, and the complexity of the large-scale natural gas pipeline network is the main reason which cause these problems. In this paper, a new simulation engine is designed and the defects of the modern pipeline simulation software are solved, the simulation engine is based on the following two new methods, the first methods is used to improve the performance and reliability of the system, in which the stations and valve rooms are simplified based on the property of the long-distance natural gas pipeline, and the natural gas pipeline network are divided to reduce the computation scale. Moreover, the performance of the system is also enhanced by the second method, for the pipeline network models and algorithms are improved by adopting parallel computing architecture. The theoretical analysis and application indicates the computation-al scale of the new engine is 23.98% less than the pipeline simulation software in use, and the simulation time step can be increased to 5 minutes for the reliability has been significantly improved, and the computational efficiency of the new engine 2.15 times higher than the famous simulation software when it is used on a 4-core PC. The architecture design of the new simulation engine adopts MVC pattern and factory model, which bring good extendibility and high performance to itself. Additionally, a large-scale natural gas pipeline network with a total length of 9000km (5,592mi), 20 compressor stations, 200 valve rooms and 10 gas storages in China were used in the simulation.

ABSTRACT A Geographic Information System (GIS) is a system designed to capture, store, manipulate, and present all types of geographic data. Many natural gas utilities utilize GIS to store information about their gas transmission and distribution systems. Pipes, valves, regulators, compressors, etc. – facilities that are important to hydraulic modelers often have information stored in GIS that can be utilized in hydraulic models. The challenge presented is how best to get this data out of GIS and into a hydraulic model, along with the issues to be considered with this interaction. This paper will discuss the GIS data that is required to build pipeline models, the GIS data this is nice to have, and the holes typically found when utilizing GIS information. Lastly, a look at how GIS can be used in maintaining and updating the hydraulic models moving forward will be discussed. WHAT IS GIS? A Geographic Information System is a computer system that can be used to map, model, and analyze large quantities of data within a single database. GIS can be used to create maps, integrate information, and visualize scenarios and is used by a wide variety of organizations including schools, governments, and businesses. As time goes on, more and more gas companies are utilizing GIS to store their transmission and distribution assets. Finding a way to use this data efficiently for network modeling is a challenge.

ABSTRACT The Piper Alpha platform was a large, fixed structure platform located about 120 miles north east of Aberdeen in 474 ft of water. It collected oil and gas from the Piper, Claymore, and Tartan fields, separating these into streams of oil, condensate and gas. Piper Alpha, at the time, contributed about 10 per cent of the oil production from the U.K. sector of the North Sea. At 10:00 p.m. on July 6, 1988 a significant explosion and subsequent fire led to the destruction of the platform. 167 men died (62 escaped). The sequence of events leading up to the explosion and fire will be reviewed and discussed as it appertains to the pipeline network systems that the Piper Alpha platform formed an integral part of. The results of simulations of the pipeline systems will be presented and history-matched against actual data recovered during the aftermath of the disaster. Conclusions will be drawn that will point to the cause and effect of the events that took place that day. One should note that the information presented here comprised an element of expert witness testimony at the Cullen Enquiry that commenced in January 1989 and concluded with the Cullen Report published in 1990, [1]. Introduction and Background Piper Alpha, owned by Occidental Petroleum, started production in 1976 from the Piper oilfield, which was owned by the Occidental Petroleum Caledonia joint venture. It was initially constructed as an oil production platform and was later converted to facilitate gas production with a new gas recovery module added. The Piper field produced oil from 36 wells. By 1988 the platform was producing 10 per cent of the North Sea's oil and gas. Together with the Tartan and Claymore platforms, Piper Alpha was connected by a 128- mile pipeline to the Flotta oil terminal in the Orkneys - Figure 1.

ABSTRACT For Saudi Aramco, keeping the nation's oil fields in optimal condition is an operational requirement. Strategic water injection is essential for long-term, maximum oil recovery. Keeping a steady supply of treated seawater flowing into an oil field reservoir through more than 600 wells is a very challenging task. We have to maintain the water pressure, quantity and quality. If the water quality specifications are not met, then it could have a negative impact on the piping integrity and the reservoir. The use of seawater means that we are able to preserve the nation's natural water resources for use by future generations. To achieve the objective of proper reservoir support, in this presentation we will focus on utilizing a new technology in our operations, which is a great enabler of safer, more efficient, more reliable, and more profitable operations. INTRODUCTION It is a common understanding that your body needs water intake to stay fit and healthy; try going without drinking water for a while, and you'll see just why. What is less known is that the Kingdom's vast oil reservoirs also need water intake to prolong their longevity. In their own unique way, they too rely on water for optimal performance. For Saudi Aramco, keeping the nation's oil fields in optimal condition is not simply an option - it is a must. Without water injection, oil production levels cannot be maintained and could be significantly impacted and drop. Although oil production would not immediately stop without water injection, the health of the oil field would be severely affected, causing a decline in the oil it produces over time. Injected seawater replaces the oil that is extracted from the reservoir. This offsets the pressure decrease in the field that is caused by oil production. It is this decrease in pressure that affects how much oil the reservoir can produce.

ABSTRACT Centrifugal compressors are subject to transient events, such as emergency shutdowns, which can cause energetic surge events during rapid shutdown transients. Many modeling tools are used to predict the behavior of compressor systems during fast transient events. Even more, centrifugal compressor dynamic modeling is a valuable assessment tool that can help improve the design of the compressor anti-surge system to prevent harsh conditions while the unit is coasting down. Modeling of centrifugal compressor transient events requires a detailed evaluation of many system variables to obtain accurate results. Additionally, many parameters should be included and analyzed to adjust the model and obtain acceptable predictions. Those parameters can include recycle valve characteristics, the controller and actuator, suction and discharge piping volumes, aftercoolers, and operating conditions. Other parameters, such as machine coast speed and inertia and different control response times will determine if the compressor will reach its surge limit at a detrimental high head condition, avoid it or go through it at low acceptable energy conditions. Many designs use general guidelines to select and plan the compressor anti-surge system and its main components. For example, the recycle valve type, size and actuation time are key parameters during the shutdown of the compressor unit since they directly affect the amount of flow through the compressor and its reaction time. Other factors are also relevant and should be assessed in detail to assure a proper design to avoid such transient events as a sudden shutdown of a compressor from a full load or high head operating conditions resulting in damaging surge events. In order to refine the simulation approach of the transients in centrifugal compressors, SwRI has conducted an extensive assessment of the main parameters that will affect the modeling predictions. Parameters such as recycle valve size, type, actuation time, after-cooler volume, friction factors, unit speed coast down predictions, compressor map, isolation valve control, acting time, as well as placement of the discharge check valve influence the modeling predictions considerably. Therefore, parametric studies of some of those variables have helped to refine and adjust the modeling technique while improving the accuracy of the results. Moreover, computational predictions have been compared against high fidelity - high accuracy data collected in a full scale compressor system. Initial comparisons indicated reasonable results while adjustments in the technique and main assumptions improved the modeling predictions considerably. A generic methodology to improve modeling predictions and main considerations are part of the analysis. In addition, comparison of the modeling results and experimental data are presented and complemented with parametric studies of different variables. In general, this work should provide guidelines for advancing the modeling of centrifugal compressor transients as well as showing the application of a valuable tool for designing surge control systems for centrifugal compressors.

ABSTRACT Pipeline capacity determination has traditionally been carried out by applying steady state optimization techniques. However, steady state techniques are not well suited to handle situations in which the pipeline contains high flow variations or where linepack transportation / manipulation is essential to optimum throughput results. We present an implementation of a transient optimization approach to determining pipeline capacity in CenterPoint's natural gas transmission pipeline. The approach uses an optimization-based state finding technology to find the current state of the pipeline using a few hours of telemetered data, coupled with gas transient optimization to maximize the throughput of the pipeline. The current implementation of the gas transient optimizer makes use of the isothermal assumption and a single gas composition throughout the pipeline. These issues will be addressed in future implementation updates.