Natural gas processing

Development of an Operations Surveillance System that relies on a dynamic simulation model

It has been recognized for a number of years that the Oil & Gas upstream sector offers interesting business opportunities related to process simulation and optimization tools used as engines for decision making in both design and operations. Operators face the continuous challenge of increasing production and reducing operational costs, while meeting goals for financial revenue, cash flow and profitability. Dynamic decision making is a core competency to optimize the company’s assets, the volume of available data gathered via automated systems (SCADA, DCS, downhole measurements, etc.) is very large and needs to be processed into useful information to support better decisions; all within the time constraints imposed by the situation. Detecting and resolving operational problems quickly can save hundreds of thousands of dollars every day.

The main objective of an Operations Surveillance System (OSS) is to provide an online dynamic simulation model of the asset in order to calculate instant well production rates and compare model results with measured values in real time.  A model-based pipeline surveillance system is a crucial tool for assisting operators in understanding the asset's behaviour and in making better operational decisions. 

The OSS leads to more accurate estimates for well production rates, and more importantly, such values become available in nearly-real-time, with the associated extra benefits of helping detect operational issues (e.g. well production issues, pipeline integrity) that may not be visible with just measured information. In today’s heavily regulated environmental compliance requirements, having a tool like OSS providing extra information (in addition to the measured one) has proven beneficial in order to prevent incidents.

The system developed for Pioneer Resources enabled users to monitor the performance of equipment and minimize the downtime. Similarly the tool provided decision support to switch to various production modes of operation such as artificial lift. Furthermore, the calculation of instant well production was useful to detect problems such as improper valve alignment.


Oooguruk Production Facilities

The dynamic simulation model included 15 wells operating in free flowing, ESP (electrical submersible pump) or shut-in modes together with the corresponding sub-sea transportation pipelines with heat transfer considerations and considering muti-phase flow (oil, water, gas). Process Ecology applied in-house tools to characterize the oil and match fluid characteristics as determined by reservoir simulation. Note that the model was built such that every well is allowed to have a different oil characteristic representing various regions and layers of the reservoir. The ESP scenario was modelled using a multi- stage pump with manufacturer pump curves. The boundary of the system included a man made gravel island where the production of all the wells are collected.



The model was calibrated to historical data including oil Production changes due to step-change in bottomhole pressures.