Gupta, M K (Oil and Natural Gas Corporation Ltd.) | Sukanandan, J N (Oil and Natural Gas Corporation Ltd.) | Singh, V K (Oil and Natural Gas Corporation Ltd.) | Bansal, R (Oil and Natural Gas Corporation Ltd.) | Pawar, A S (Oil and Natural Gas Corporation Ltd.) | Deuri, Budhin (Oil and Natural Gas Corporation Ltd.)
This paper discusses a case study of one of the onshore field of ONGC where while processing well fluid, frequent surge has been observed leading to shutdown of the SDVs creating severe operational problems and loss of production. It was imperative to find out the problematic wells/lines located in clusters which contribute for surge formation and mitigation approach with minimum modifications.
A transient complex network of sixty five wells flowing with a different lift mode such as intermittent gas lift, continuous gas lift etc were developed in a dynamic multiphase flow simulator OLGA. Time cycle of each well were introduced for intermittent lift wells. Simulation study reveals pulsating transient trends of liquid flow, pressure which was matched with the real time data of the plant and hence confirms the accuracy of the model. After verifying the results, different scenarios were created to determine the causes of surge formation. After finding the cause, a low cost approach was considered for surge mitigations.
An integrated rigorous simulation was carried out in OLGA, by feeding more than 12,000 data points to obtain model match. Several scenarios were also created such as optimization of lift gas quantity, optimization of elevation and size. Trend obtained after each scenario was pulsating behaviour and it matched with the real time data appearing in the SCADA system of the field. After rigorous simulation with each scenario, it was established that the cause of surge forming wells/pipelines. Once the root cause of surge has been confirmed then quantum of liquid generated due to surge was determined. Adequacy checks of the existing separators were carried out to estimate the handling capacity of the existing separators at prevalent operating condition. After adequacy check it was found that existing separators cannot handle the surge generated in that time interval leading to cross the high-high safety level, resulting closure of shut down valve (SDV). After establishment of root cause of the surge, a low cost solution with small modification in pipelines and control system/valves was adopted to arrest the surges. It was first of its kind simulation carried out for a huge network of wells/ pipelines by feeding more than 12,000 data to analyze the surge formation cause and capture its dynamism owing to wide array of suspected causes. This will help to address the challenges of efficiently reviewing the entire pipeline network while designing new well pad/GGS and will also help to arrest surge by adopting a low cost solution wherever such situation arises.
Integrated and automated integrity management is essential for Arctic and cold region pipeline failure prevention, predictive maintenance, and life extension because the consequence of a failure will be disastrous both environmentally and economically. Without managing integrity, the condition of pipeline would continue to deteriorate until found unfit for service or premature failure. Real-time Condition Monitoring (CM) is a sensor- based monitoring technique aimed at enhancing the productivity of pipeline operation. The main intent of condition monitoring is to assess operating conditions and performance, improve performance, aid maintenance, extend life, and inform operator if the integrity is compromised. Other purpose of monitoring is to provide warning when something is starting to go wrong, and provide instantaneous information when things have gone wrong. This paper presents a recently developed concept and methodology for Arctic pipeline integrity management using Inspection, Maintenance and Repair (IMR) strategy using real-time CM data by probabilistic risk assessment. The probabilistic risk assessment is performed by combining advanced probabilistic analysis with computation. In this paper, the joint probability of failure arising from potential pipeline defects (e.g. corrosion, cracking, and strain) and likely operational deviations (e.g. pressure, temperature, and vibration) is computed real-time using the CM data to predict a condition-based IMR strategy. Having such a model would enable rapid decision-making regarding pipeline failure prevention, predictive maintenance and life extension.
Unbonded flexible risers are a critical part of offshore field architecture bringing oil and gas from seabed to platforms on the surface. A failure in operation will result in stop of production and hence a significant loss of revenue. Risers are subject to a number of loading issues including internal and external pressure, vessel motions and current and wave actions. As a result, risers, endure significant strain levels which can impact on their integrity and functionality.
The recent implementation of fiber optic monitoring embedded in flexible risers, is an important step towards turning risers into inspectable structures. The embedded monitoring systems ensure the asset can operate safely at its optimum level for the maximum period of time. The combined use of optical point sensors and fully distributed sensors allow various events to be monitored. This includes breach of outer sheath, condensate build up, polymer temperature, pipe temperature during shut in, fatigue and wire break.
The traditional industry method for combating these issues has been extensive onshore testing on small sections of the riser allowing the operator to build up a bank of fatigue and reliability data which is used to statistically forecast the strains and stresses the riser will encounter. This data takes into account expected changes throughout the lifecycle of the riser, such as material degradation and environmental issues including storms and hurricanes. The main inspection method in operation to back this up has been expensive inspection campaigns by diver or ROV focusing on external damage.
New advances in optical technology and riser manufacturing techniques mean that a suite of real-time monitoring can provide a far more accurate picture of a riser's condition during operation. This improves decision making by allowing structural and temperature issues to be detected at the earliest possible stage and rectified in the most efficient manner, ensuring risers satisfy safety and regulatory requirements and help maximize oilfield productivity. The enabled condition dependent maintenance of risers will reduce the need for expensive ROV operations for inspection.
Real time riser monitoring is set to play an increasingly important role as the operators start to insist on the adoption of this technology in the risers delivered to them. As oil production reaches into deeper and deeper water depths, the real time understanding of the integrity of the risers will become paramount.
This paper details the advances that have been made in optical monitoring and visualization techniques and their application within the intelligent riser.