To rapidly move forward in the competitive upstream oil and gas sector, companies need to develop a comprehensive hybridized skill-set comprised of production processes and information technology.
While competition for natural resources is driving exploration for oil and gas to extremely remote locations, business leaders are looking for ways to improve production and yields, monitor and improve business operations, improve quality, and ensure worker and environmental safety.
These business leaders are well aware that the environment is growing increasingly unpredictable, locations more demanding, and the business challenges more convoluted.
In the Intelligent Oil Field (IOF) however, business leaders are now capable of processing mountains of information quickly and efficiently in unprecedented ways. Where decision support once may have taken days to process, it is now within hours that executives can expect to differentiate between beneficial new initiatives and dead-end projects, then deciding whether or not to give their approval.
IOF is known by many names, including “Digital Oilfield”, “Field o’ the Future”, “i-Field”, “e-Field”, “Real-time Ops”, and “Real-time Optimization”. Also well-known is how IOF can reduce the uncertainties of the looming “great crew change” and ever-increasing project complexity. IOF shows great promise for a future of higher productivity, increased recovery, lower costs and reduced health, safety and environmental exposure.
Combining People, Processes and IT
According to a Cambridge Energy Research Associates (CERA) study, the benefits of the Intelligent Oil Field can include lower operational costs, earlier and increased production, lower capital investment, increased recovery of oil and gas, and finally lower abandonment costs.
By enabling redefined and proactive asset management and using frequently captured and distributed data converted into relevant knowledge, all critical data for decision support can be evaluated and acted upon effectively in real time.
In other words, huge amounts of sensor data can be delivered to technicians who can then remotely analyze the data, convert it to accessible, meaningful knowledge and distribute it accordingly.
By using predictive analytics, companies no longer have to maintain unwieldy data stores and thereby allow raw data to remain at the source.
According to Emerson Process Management, when you have the right information delivered to the right person at the right time, you’re able to:
- Identify risky operating conditions and provide guidance on how to resolve critical safety issues;
- Provide true real-time operational data to onshore operations centers, thereby reducing the cost and risk of offshore staffing;
- Share data with subject matter experts, regardless of location;
- Enable dynamic production optimization – including model predictive control – to ensure repeatable, safe, and profitable operating strategies
- Identify changes in equipment performance to proactively resolve problems and avoid failures;
- Remotely monitor real-time asset health for predictive maintenance practices, allowing prioritization and planning of maintenance trips offshore at the best cost and schedule;
- Provide specific, targeted information to maintenance personnel on equipment problems, including which tools, parts, and work processes are required to correct problems;
- Streamline compliance documentation and reporting.
Not a Cookie-Cutter Approach
Less than 30 years ago personal computers were first introduced into the workplace. At that time, a production engineer’s only data source was located on an operator’s clipboard or in a stack of old, daily reports found in a file cabinet.
It took weeks to route an Authority for Expenditure (AFE) for any type of well or facility work. Planning, scheduling and implementing a simple work-over took weeks to months. These factors and many advancements since have set the stage for use of IOF.
Promise for the Future
Although IOF is not a cure-all, it is capable of addressing many current and future issues facing the upstream oil and gas industry. Implementation of Intelligent Oil Fields should be designed with the exact nature of the need and the status quo in mind.
In other words, there is a large probability that no two IOF programs will be identical as there are no two wells in the world that are exactly alike.