Abstract
Because of hydrocarbon oil reservoirs aging and oil production declining, and due to continuous change of oil characteristics and deterioration of production flowlines and shipping pipelines, oil congealing is becoming an increasingly major challenge in maintaining continuous production for both light and heavy oil operations. Thousands of oil barrels are lost on daily basis across the oil industry due to oil congealing indicating that there is a significant gap in industry knowledge to understand the real root causes and how to address or mitigate them.
Hydrocarbon oil has a very complex liquid characteristic specially when is comingled with other crude oils (with different properties), and other deposits which are produced from reservoir and/or formed during production and/or transportation. The oil flow regime could yet be even more complex with varying weather conditions. With aging-reservoirs’ temperature and flowrate declining, and, increasing asset integrity issues minimizing the pressure envelop of production and transportation pipelines, maintaining a healthy flow is becoming a major challenge specially during low temperature and rainy seasons. Such conditions reduce the oil temperature and thus viscosity, and if the condition persists, then cause the development and formation of oily wax and subsequently oil congealing.
It is thus critical to significantly improve the knowledge of (mixed) oil characteristics and properties and their rheology behavior with varying temperatures, pressures and flowrates by performing complex and non-linear modelling and simulation to better predict their flow regime, and address and prevent any issues ahead of the time using appropriate preventing measures in the form of mechanical, thermal and chemical solutions.
PT. Chevron Pacific Indonesia has made a major step change and development in the industry, and significantly progressed to mitigate oil congealing in her light oil operations by developing a comprehensive real-time and integrated prediction and prevention tool to help eliminate or minimize lost production due to oil congealing. The development included two stages: oil rheology and non- Newtonian modeling, and prediction algorithm and digital tool development. In this paper the sequence of both stages is presented, and the results are discussed in detail.
Stage 1 development process was implemented using comprehensive laboratory and field tests of various oils/oil mixtures for different shear rates and temperatures, categorization of 19 different oils/oil mixtures with wide-varying wax appearance temperatures and the development of oil rheology models and simulations. The pipeline network which included 11 gathering stations with feeder lines from 6" to 12" and the main 30" shipping line extending about 80 km, indicated the complexity of the assessment requiring significant simplification. The results were comprehensively checked against norm trends and tested using several commercial modelling and simulation tools. Significant iterations were applied, and non-Newtonian models were built to finally converge to meaningful data and in the development of a visual basic algorithm representing the oil and oil mixture for the logic sequence.
Stage 2 development process was implemented by thorough running of visual basic tool for various temperatures followed by comprehensively and iteratively checking the outputs against collected historical event data until the data converged with an acceptable bias. The inclusive algorithms were developed in two stages to include a wide-ranging prediction tool for various production scenarios, development of a significant library for thousands of varying temperature, pressure and flowrate scenarios and the associated prevention and combating solutions. It was then linked through a sequence of intelligent logics to an operations intelligence software and an existing Human-Machine-Interface to minimize human interface and maximize digital innovation in prediction and subsequent prevention actions. The tool included real time "Day 0" data as well as predicted pressures and temperatures for the following 8 days based on a paid weather service data which were also calculated based on crude oil travelling time. This tool, which was developed in 2018 as part of a critical digital flow assurance project, has been put in operation mode for some time and has already made considerable contribution to the operation to prevent oil congealing and lost production, and, also helped build substantial confidence that oil congealing could be mitigated entirely
