Development of an Operations Surveillance System that Relies on a Dynamic Simulation Model
It has been recognized for several years that the upstream oil and gas 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 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 to prevent incidents.
The system developed for Pioneer Resources enabled users to monitor the performance of equipment and minimize 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, with the corresponding sub-sea transportation pipelines with heat transfer considerations and considering multi-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 modeled 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 is collected.
The model was calibrated to historical data including oil Production changes due to step-change in bottomhole pressures.
