Abstract Analysing the leak detection sensitivity for a particular system, or predicting how operational transients influence it, are common challenges for leak detection professionals. An empirical approach can be followed: modeling the pipeline system, including all the inaccuracies due to the instruments and communication systems. The sensitivity can then be inferred by running specific scenarios. Designing the scenarios is not a trivial task. The system response to transients provides information about sensitivity degradation. This information is used to plot a sensitivity map, which in turn helps to understand the more favorable and less favorable sensitivities for a particular system. Colombian oil company, Ecopetrol, followed this practical procedure for a new pipeline in the commissioning phase. This allowed a pre-determined estimate of the system sensitivity and an evaluation on the operational transients involved in the leak detection tests. The present paper describes the approach which Ecopetrol followed during model construction, the design of scenarios and the results obtained. API 1149 steady state and transient predictions are also compared with the model results. A sensitivity map considering both sources of data is analyzed. Finally, the paper presents a discussion about the validity of this procedure and its generic application. Introduction Ecopetrol, the national oil and gas company in Colombia, carried out a leak detection sensitivity analysis for a pipeline prior to commissioning. The procedure included the configuration of an off-line model, the design of leak test scenarios, the addition of uncertainties to the hydraulic variables and running a leak detection system. The leak test results from the model are compared with the API 1149 steady state estimations and the sensitivity degradation due to uncertainties in system variables.

Abstract A 13.17 mile (21.20 km) long, 12" diameter black oil pipeline, owned by Hindustan Petroleum Corporation Limited (HPCL), transports Petroleum products such as Furnace Oil & Light Diesel Oil from the Trombay refinery to the Vashi terminal. The pipeline passes underneath Mumbai, one of the world's most populated cities. The operational safety, monitoring & maintenance are a concern for the pipeline operator. Operating the pipeline safely is of paramount importance to HPCL. The pipeline was constructed with the consideration of safe operation and regular maintenance regimes are in place to ensure the physical integrity. Although the pipeline integrity has a very low risk of being compromised through operational activity, there is a potential for loss of product by external interference e.g. theft/pilferage. This paper examines one such case. The pipeline was shut down and the pipeline integrity monitoring system indicated that leaks were occurring. However, due to the low pressure during the shutdown and small volume of the withdrawals, identifying the location of the theft was challenging. In an attempt to locate the theft, an analysis was made using archived data and an RTTM Leak Detection system. The background, methodology and results will be presented. Pipelines in India and Safety The most cost effective, energy efficient and environmental friendly way for transporting petroleum products in India is through the use of pipelines. With 30% lower charges than rail and 4-5 times cheaper than road transportation, pipelines are a major method of transportation for the oil industry in India. Use of pipelines has eased the overburdened rail and road infrastructure and reduced the environmental impacts intrinsic in rail and road transportation. The network of pipelines throughout India helps maintain the supply chain of crude oil, petroleum products and gas within the country and thus pipelines play an important role in balancing supply and demand across the country. With more than 8,751 miles (14,083 km) of product pipelines, 9,532 miles (15,340 km) of natural gas pipelines, 5,878 miles (9,460 km) of crude pipelines and 1,367 miles (2,200 km) of LPG pipeline the pipeline network in India is growing in parallel with its oil industry.

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.

1 ABSTRACT: Recent events have created renewed interest in deploying automatic linebreak control valves across the nation's natural gas pipeline infrastructure. However, certain pipeline configurations may not lend themselves to the installation of these devices. One such area on the Southern California Gas Company (SoCalGas) and San Diego Gas & Electric Company (SDG&E) system is the "Rainbow Corridor". The Rainbow Corridor is an area in southern Riverside County, California, where a series of three parallel pipelines of differing diameters provide the majority of gas supply to San Diego County. SoCalGas and SDG&E use transient hydraulic software to evaluate proper settings for proposed automatic linebreak control valves. During pipeline break conditions, a large pressure drop and corresponding pressure rate of change is observed at the valve location. This pressure rate of drop (ROD) is measured over a period of time and is used by the control valve to determine if a line rupture has occurred. Breaks are simulated at the furthest point from the valve on the line, or in between other control valves, in order to catch a break anywhere on the pipeline. Normal operating procedures, including operation of compressor stations, power plants, valves, etc., have the same effect on the valve, typically to a lesser extent. This unique problem is magnified by the differing pipeline diameters in the Rainbow Corridor, where a break on a large line has a drastic effect on a smaller diameter pipeline. The case study demonstrates that there are certain special circumstances where automatic linebreak control valves will be more of a hindrance than helpful, and would be better suited with remote control operation. Careful modeling of the pipeline network produced a plan which mitigated the likelihood of losing all supply to San Diego County, while improving the safety of the SoCalGas/SDG&E pipeline network.

ABSTRACT: The Vestprosess pipeline carries NGL from Kollsnes by Sture to Mongstad, all located on the west coast of Norway. The boundary conditions of a pipeline are important for optimization and future operation of the pipeline. History has shown NGL pump capacity challenges in the Vestprosess system. For this reason technical and commercial aspects that could influence the boundary conditions were studied by different projects. The scope of work in the current study was to perform detailed thermo-hydraulic simulations of the pipeline, capacity evaluations, and quality check input to and results from ongoing studies by the owners. The overall purpose of the study was to combine all results and understandings from previous and current studies in order to increase operational robustness of the Vestprosess pipeline. INTRODUCTION The study of pipeline capacity and optimization of a pipeline network require detailed thermo-hydraulic simulations. Two key elements for a hydraulic pipeline simulation are quality checked input data and the possibility to match the model to real measurements. In addition to the pipeline itself it is important to understand the boundary conditions and the processing facilities connected to the pipeline. Changes in the operating conditions of a pipeline may affect and influence the operation of the processing facilities. In 2009 the Vestprosess pipeline was undergoing several separate studies initiated by the owners. The purpose of the studies was to optimize the pipeline based on their understanding of the existing boundaries. During this work one of the options was to invest millions of USD in two new condensate pumps to meet future transportation estimates. This would have been a significant investment, and the owners were therefore interested in further analysis of the Vestprosess system. The current study was therefore initiated to ensure that all aspects were covered in terms of capacity optimizations. The different options for upgrading the capacity in Vestprosess were: Kollsens: Potensial upgrade of the condensate pumps and use of drag reducer Mongstad: Solution to improve flexibility at high rate scenario at Mongstad – Indirect feed to cavern (evaluation of pressure loss from cavern to process) – Change of diameter (8" to 12") for the pipeline going from cavern to process General: Variation in rate scenario in Vestprosess from Sture and Kollsnes The capacity study was carried out using different simulation tools. The main simulation tools were the OLGA Transient Multiphase Flow Simulator (v.5.3.2), GAP multiphase oil and gas optimiser tool and basic flow equations for pressure drop. PVT-sim (v.18) was used for fluid characterization of the OLGA PVT input file. The simulation tools were matched against pipeline measurements to ensure that the models were satisfactory. SYSTEM DESCRIPTION The Vestprosess pipeline connects the following three processing facilities: Kollsnes processing plant treats gas from the Troll, Kvitebjørn and Visund fields in the North Sea. NGL (63° API) is separated from the rich gas, and the remaining dry gas is pressurised before being transported to customers in Europe. NGL from Kollsnes may be stabilized or partly stabilized, depending on the process conditions at Kollsnes.

ABSTRACT: An existing 20″ pipeline system is being modified to operate in a batching mode to integrate the production of a new field. Two dismissible crude oils will be pumped in a specific batching scheduled to minimize the mixing volume and avoid further contamination of the highest quality oil. The fluids to be carried by the pipelines are primarily crude oils with density differences of approximately 15% and dynamic viscosity ratios up to 12.5. Both the transient response and steady-state analysis are being performed for each of the two pipelines and the entire system to determine its operating constraints and estimate the batch volume to be received at the end facility. The conducted analysis estimates the contaminated interface volume in this pipeline segment for various pipeline operating conditions. Determination of blending interface was calculated by using a pipeline simulation approach. From the pipeline modeling, it was observed that the mixing interface is slightly larger when the lighter oil batch is followed by the heavy oil. In addition, results indicated a similar mixing trending of the two fluids when the batching cycle is modified. One of the critical parameters in the calculations is the dispersion coefficient that is linear dependent of the molecular diffusion coefficient. Thus, a parametric analysis was included in the estimation of the volumes for both cases, since an exact diffusion coefficient value was not available for these types of crude oils. The pipeline modeling results provided a good estimate of the volume interface. The mixing volumes calculated by this approach are not only relevant for the operational stand point of view of the pipeline, but they are good indicators for the economic feasibility of the pipeline operation and project expansion. Thus, this study presents results from the pipeline modeling and covers the basic parameters that will affect a batching operation of two different fluids. INTRODUCTION: The oil transport system under consideration is composed of an existing 84 miles of 20″ diameter pipeline connecting Oil Center "A" (OCA) to a refinery facility. In addition, a 20″ diameter pipeline that runs from another Oil Center "B" (OCB) ties into the OCA pipeline at a node junction. Therefore, from the node junction to the refinery facility, both systems share a common 20″ pipeline that travels approximately 73 miles through a relatively downhill terrain. The two oil centers are managed by different operators, and they provide oil with different characteristics. Therefore, the operation of the system is based on a batch transport philosophy. The design batch transport system has been performed by flow rate control at oil centers and pressure control at the refinery receiving facility. However, a production increase is anticipated from OCA. Thus, the transport philosophy has been modified to adjust this increment of capacity. The proposed operating method is based on pressure control at the oil center. The targeted production will vary from 4,300 GPM to 3,700 GPM at the light crude oil center, OCA, while OCB was scheduled to maintain a constant rate of approximately 1,500 GPM.

ABSTRACT "Make everything as simple as possible, but not simpler." Who are we to argue with Einstein? In this paper we discuss a strategic approach to problem solving and its application to complex situations. The strategy is termed "problem domain reduction" and has been successfully applied to the development and testing of a simulator for modeling slack line flow for use in an on-line leak detection system. While the concept of problem domain reduction is not new, it is a powerful strategic tool in the development of reasonably complex simulators and/or systems. The strategy allows you to focus on the essential and discard the unimportant. In doing so, insight into the underlying mechanisms is revealed whilst reducing the risk of being deceived by inconsequential artefacts. In this paper we describe the problem domain reduction process; the selection of suitable test cases and tools to assist in analysis and verification within the reduced domain; the development of prototype simulators (which in itself is a problem domain reduction); the interplay between development and testing and finally the incremental development leading to a full domain solution. Although the primary focus will be on the development of a simulator capable of modeling slack line flow, we will also discuss other areas where problem domain reduction has been utilized successfully to highlight the wide application of the strategy. INTRODUCTION Firstly it is important to understand that the strategy of Problem Domain Reduction is nothing new: it is used, without reference to the name of the strategy, in many areas of application, by many people - every day. When faced with a complex problem, one's natural instinct is to simplify the problem. However, one has to avoid over-simplification as this will often lead to erroneous solutions to the problem. Formalizing the approach in the context of the development and analysis of a hydraulic simulator is beneficial, not least when one needs to provide a development plan with time scales and milestones. The first hurdle to overcome is often to justify the strategy. The strategy of Problem Domain Reduction can be broken down into a few simple steps: Comprehension : Understanding the problem Reduction : Reducing the problem domain Solution : Solving the problem in the reduced domain Testing : Testing the solution in the reduced domain Extension : Extending the solution back to the full problem domain Each of these steps may be extended to include sub-steps depending on the nature of the problem, but the core strategy remains unaltered. JUSTIFICATION The justification for using such an approach is that it provides clear and measurable steps on the development plan. Furthermore, it provides testing at the earliest opportunity in the development plan and therefore a key milestone. The frustration with this strategy is that success in testing in the reduced domain does not mean that the development is nearing completion - only that the most significant development has been successfully achieved.

ABSTRACT Energia Mayakan (Mayakan) is Mexico's first privately owned gas pipeline venture. This 432 mile 24" diameter pipeline transports natural gas from a PEMEX plant to several cyclic-load power plants in the Yucatán peninsula of Mexico. On-line leak detection, off-line predicting, and off-line training models were commissioned in the summer of 2000 and have proven successful in assisting control room operators to safely and efficiently operate this pipeline. Specific real-world experiences will be presented that demonstrate how the various simulation tools have benefited the operation. Mayakan's operators use real-time and predictor simulation models to plan compressor schedules, budget fuel usage, detect leaks, and recognize maintenance needs. The training model has been used to train and to certify all control room operators. This case history also presents lessons learned during the first year of operation, and uses of the model that had not been anticipated. INTRODUCTION Mayakan initiated commercial operation in September 1999 as the first privately owned pipeline to deliver gas to third parties in Mexico. A SCADA system was installed to monitor and control the pipeline. Computer modeling tools were configured to supplement SCADA and to provide leak detection, predictive modeling, and operator training. These tools are intended to provide support to the solo control room operator in making operational decisions and to promote safety, reliability and efficiency. This paper intends to present a description of the modeling system configuration and the benefits of using these tools in Mayakan during the first year of operation. Description of the models: Mayakan currently operates without any in-house engineering staff. Solo operators in the control room use the on-line model for linepack analysis, leak detection, SCADA instrument troubleshooting, survival time analysis, and predictive modeling analysis. They use a predictor model to make decisions regarding compressor schedules, fuel budgeting, and whether they will approve or deny customer's requests to increase their gas rates over the rates that have been previously allocated. The training model is used to educate and to certify Mayakan's staff. All three of the models are described in more detail in the sections that follow. Model Communication with SCADA All of the various models communicate with SCADA using bi-directional interfaces. SCADA data feeds the on-line leak detection model, whereas the predictor and training models can begin from either a current or saved on-line model state, or manually set conditions. All models can display their results using graphical display screens and also communicate modeling results back to SCADA. The on-line and predictor models send very few data items back to SCADA, whereas the training model, which simulates all pipeline hydraulics, sends hundreds of values to a copy of the SCADA system every few seconds. On-line and Leak Detection Model The on-line model has become an integral part of gas control. Continuous monitoring of pipeline hydraulics provides leak detection alarms, leak location calculations, and line pack calculations. The on-line model is also used to provide an evergreen starting hydraulic pipeline state for predictive modeling simulations.