257 research outputs found

    Woodside Energy Ltd. Cossack Pioneer Facility Engineering Team

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    Cossack Pioneer is a floating production storage and offloading vessel located 112 km North West of Karratha. This report details the work performed during a 16 week internship with Woodside Energy Ltd working in the Cossack Pioneer Facility Engineering Team. This Perth based team provides engineering support to the production facility. The report incorporates a description of the facility and topsides process and discusses the systems used for process control. The earlier work performed during the internship focussed on small engineering design and control system modifications for the instrumentation and control group within the facility engineering team. Partway through the internship focus changed and the challenging role of Facility Control Engineer for Cossack Pioneer was assumed during the absence of the facility Senior Control Engineer. The report provides discussion of learning outcomes acheived and experience gained during the internship

    Detection of Solids in a Flow Stream Using Ultrasonics and Advanced Algorithms

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    Sand passing along gas production pipelines can cause major disruption to facilities and interrupt gas flow. This research focused on improving sand flow measurement in gas pipes. It provided an improved method to measure sand flow rate using commercial Acoustic Sand Detectors. Also it provided several methods to measure sand flow rate in gas pipes using ultrasonic sensors and various signal processing techniques which were more accurate than any other methods

    Modelling of an axial flow compact separator using neural network

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    A novel design axial flow cyclonic separator called I-SEP was tested with an extensive set of experiments using air-water two phase flow mixture at atmospheric pressure. These experiments provided valuable data on the separation efficiency and pressure drop under different inlet conditions. The performance parameters i.e. Gas Carry Under (GCU) and Liquid Carry Over (LCO) were found to be non-linearly related to the inlet operating conditions. However it was found that resistance on the tangential outlet of the I-SEP affects the GCU and that manipulating the pressure difference between the two outlets and the inlet of the I-SEP through manual control valves, the GCU could be controlled. The separator was also extensively tested and compared with a gravity separator, when they were placed at the exit of a riser, in severe slugging condition frequently encountered in the production pipe work from some oil fields. The tests revealed that the I-SEP has better tendency to suppress severe slugging as compared to the gravity separator. A framework for neural network based on multiple types of input was also developed to model the separation performance of the I-SEP. Mutual Information (one of the key elements of the information theory) was applied to select the appropriate candidate input variables to the neural network framework. This framework was then used to develop a neural network model based on dimensionless input parameters such as pressure coefficient. This neural network model produced satisfactory prediction on unseen experimental data. The inverse function of a trained neural network was combined with a PID controller in a closed loop to control the GCU and LCO at a given set point by predicting the manipulating variable i.e. pressure at the I-SEP outlets. This control scheme was simulated using the test data. Such controller could be used to assist the operator in maintaining and controlling the GCU or LCO at the I-SEP outlets.The work performed during this study also includes the development of a data repository system to store and query the experimental result. An internet based framework is also developed that allows remote access of the experimental data using internet or wireless mobile devices

    An assessment of subsea production systems

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    The decreasing gap between technology and the its applicability in the oil industry has led to a rapid development of deepwater resources. Beginning with larger fields where the chances of economic success are high, to marginal fields where project economics becomes a more critical parameter, the petroleum industry has come a long way. However, the ever growing water depths and harsher environments being encountered are presently posing challenges to subsea production. Being able to develop a field and then proceeding to ensure flow for the life of the field comprises many situations where the production equipment can fail and falter or through external factors, be deemed unavailable. Some of the areas where most of the current developments in subsea production are being seen are in subsea processing, flow assurance, long term well monitoring and intervention technologies areas that pose some of the biggest challenges to smooth operation in the deepwater environment. This research highlights the challenges to overcome in subsea production and well systems and details the advances in technology to mitigate those problems. The emphasis for this part of the research is on multiphase pumping, subsea processing, flow assurance, sustained casing pressure problems and well intervention. Furthermore, most operators realize a reduced ultimate recovery from subsea reservoirs owing to the higher backpressure imposed by longer flowlines and taller risers. This study investigates the reasons for this by developing a global energy balance and detailing measures to improve production rates and ultimate recoveries. The conclusions from this energy balance are validated by simulating a deepwater field under various subsea production scenarios

    Numerical prediction and mitigation of slugging problems in deepwater pipeline-riser systems

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    Slugging involves pressure and flowrate fluctuations and poses a major threat to optimising oil production from deepwater reserves. Typical production loss could be as high as 50%, affecting the ability to meet growing energy demand. This work is based on numerical simulation using OLGA (OiL and GAs) a one- dimensional and two-fluid equations based commercial tool for the simulation and analysis of a typical field case study in West Africa. Numerical model was adopted for the field case. Based on the field report, Flow Loop X1 consisted of well X1 and well X2, (where X1 is the well at the inlet and X2 is the well connected from the manifold (MF)). Slugging was experienced at Flow Loop X1 at 3000 BoPD; 4MMScf/D and 3%W/C. This study investigated the conditions causing the slugging and the liquid and gas phase behaviour at the period slugging occurred. The simulation work involved modelling the boundary conditions (heat transfer, ambient temperature, mass flowrate e.t.c). Also critical was the modelling of the piping diameter, pipe length, wall thickness and wall type material to reflect the field geometry. Work on flow regime transition chart showed that slugging became more significant from 30% water-cut, especially at the riser base for a downward inclined flow on the pipeline- riser system. Studies on diameter effect showed that increasing diameter from 8” – 32” gave rise to a drop in Usg (superficial velocity gas) and possible accumulation of liquids on the riser- base position and hence a tendency for slugging formation. Depth effect study showed that increasing depth gave rise to increasing pressure fluctuation, especially at the riser- base. Studies on the Self-Lift slug mitigation approach showed that reducing the internal diameter of the Self-lift by-pass pipe was effective in mitigating slug flow. S3 (Slug suppression system) was also investigated for deepwater scenario, with the results indicating a production benefit of 12.5%. In summary, the work done identified water-cut region where pipeline-riser systems become more susceptible to slugging. Also, two key up-coming slug mitigation strategies were studied and their performance evaluated in-view of production enhancement

    Slug flow control using topside measurements: a review

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    Slugging flow is a condition caused by a liquid obstruction at the riser base. It exhibits cyclic behaviour. The cycle consists of a protracted time of no gas production at the riser's top, followed by the arrival of a liquid slug with a length greater than the riser height, and ultimately the breakthrough of a significant gas surge. The cycle time might range from a few minutes to a few hours, depending on the system size and flow conditions. In offshore oil production, feedback control is a practical and cost-effective way to prevent slug flow. To control the flow rate or the pressure in the pipeline, adjusting the choke valve opening on the topside facility is generally utilised as the control input. From a practical standpoint, designing a control system based on topside data rather than seabed measurements is preferable. Controlling the topside pressure alone is difficult and ineffective in reality, but combining it with the flow rate results in a more reliable control solution. Measuring the flow rate of a multiphase flow, on the other hand, is difficult and expensive. All the topside measurements-based slug control techniques was critically reviewed and necessary recommendations for enhanced control performance provided. In conclusion, this review acknowledged that slugging is a well-defined flow pattern, yet despite having been studied for several decades, current slug control methods still have robustness issues. Slug flow problems are expected to become even more intense in the future as a result of longer vertical risers driven by deep-water Exploration and Production (E&P)

    MODELING OF FLOW INSTABILITY IN DEEPWATER FLOWLINES AND RISERS: A CASE STUDY OF SUBSEA OIL PRODUCTION FROM CHINGUETTI FIELD, MAURITANIA

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    Chinguetti a deepwater oil field development offshore Mauritania is experiencing a rapid decline in its production that resulted to severe flow instability or slugging in flowlines and risers of its subsea oil production system. Slugging initiates oscillations and puts field operator in a demanding situation to manage and control flow instability. It is crucial to have a model to describe flow instability issues in live field conditions. Apparently, there is no applicable model to represent flow instability in deepwater operations. Current available data that represents flow instability in flowlines and risers in live field conditions has not been published in any literature. The available data is mostly from laboratory controlled conditions or laboratory scale ideal condition. Model using laboratory conditions has limited capability that cannot be used to assess severity of slugging. A study was undertaken in which integrated production system of the Chinguetti wells, flowlines and risers were developed using the OLGA transient multi phase flow simulator. Field validation was performed by tuning the models to match field pressures and phase flowrates and instability in the systems. The impact of various changes in operating conditions on the flow instability was examined by simulating the models that included changes in well routings, gas lift injection rates and location of injection points, riser and wellhead choke openings. The severity of flow instabilities for the different operating conditions was categorized by the degree of fluctuations in liquid arrival rates and the characteristics of its liquid slugs, length and frequency. Results from field implementation of the recommended changes in operating conditions indicated improvement in flow stability and oil recovery. From the study, a methodology has been developed to assess the severity of slugging and strategies to mitigate flow stability and productivity in the flowlines and risers ofChinguetti oil production system
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