Integrated environmental Monitoring (IEM) is a consortium-based project to help oil exploration companies meet operational and environmental challenges. The project monitors the health of the environment around oil & gas facilities to improve environmental management capability and operational performance specifically in challenging areas like:
- Areas covered with ice for periods of the year; ex. Chucki Alaska
- Sensitive coastal areas
- Areas with restrictions related to drilling or other types of activities parts of the year. For example, areas where spawning or breeding season of fish occurs.
IBM’s role in IEM project is to correlate environmental monitoring data and events generated from sensors and monitoring systems and deliver operational intelligence via other critical applications such as analytics and visualization portals. IBM’s Integrated Information Core (IIC) is the proposed integration framework to handle the data access and management for IEM. IIC will provide the interface to the communication infrastructure real-time data through web services or OPC. IIC uses the Reference Semantic Model (RSM) to provide the context of the integration.
IBM Advance Condition Monitoring (ACM) assets support the production, maintenance, operations, condition monitoring, measurements, data collection, diagnostics, and early warning.
IEM will monitor the health of the environment (both under and above water) around oil & gas facilities. Environmental monitoring of water, seabed and fauna is needed in order to map, and display, any changes due to oil and gas activity. The monitoring occurs in all phases of the lifetime of an oil field: 1) in the preparation phase – Before any oil & gas activity takes place, and during exploration & drilling; 2) in the production phase – when a fixed installation is in place and production commences; and 3) in the demobilization phase – after production has commenced.
The monitored entities are environmentally sensitive areas affected by exploration and drilling activities.
Sensors and Measurements:
- Physical Sensors – to measure
– Light intensity
– Currents [intensity]
– Water temperature
– Wave [Intensity/ Height]
– Wind [Speed]
- Chemical Sensors – to measure
– Salinity levels
- Biological Sensors – to measure the presence of underwater sea life line plankton, fish, or mammals
– Camera – Motion sensor and images of moving fish, mammals, etc.
– Sonar – Detects underwater objects and their motion
Situational Awareness – to understand what is happening
Sense-and-Respond – to quickly sense and respond to threats and opportunities, and
Track-and-Trace – to track and trace important items as they go through their life cycles.
A key enabler for harnessing the power of information is the Reference Semantic Model (RSM) which provides a much needed context for integration, interoperability, & analytics.
Through the RSM the framework will integrate (bring together) all types of information including not only Measurements and sensor data, but also other reference data including engineering specifications for the sensors and equipment used in IEM, and geographical data from a GIS (Geographical Information System) information source. It brings together all relevant data from various information sources in the IEM project landscape.
The framework will enable IEM to harness the power of information to greatly improve decision making – enabling the stake holders:
- To visualize & act upon critical intelligence & events for faster & smarter business decision
- To anticipate the risk requirements, and execute in advance of critical points – to mitigate and manage risk – Whether it is risk associated with Environmental health and safety, asset health, etc.
Access the following link to view the presentation on Environmental Monitoring presented at the Semantic Days conference.