How AI Can Help Oil and Gas Producers Reduce Greenhouse Gas Emissions and Improve Their Business
In Canada, oil and gas production accounts for a quarter of national GHG emissions and is a significant emitter in the United States. As concerns about global warming increase, regulations are stricter, investors are more demanding and even bankers want reassurance that producers are managing their “climate risk”. Reducing greenhouse gas (GHG) emissions from oil and gas production is a smart business. Done right, reducing emissions is an important part of improved operational performance that includes higher efficiencies, lower costs, and longer well run times.
Artificial intelligence and optimization
A typical engineer supervises about 250 wells. There are only a certain number of hours in a day and who has the time to analyze all this data? Keeping production online, not optimizing it, is often the first priority. This leads to a ‘set it and forget it’ mentality and poor performance.
A Texan operator with 200 wells followed this approach, resulting in a sharp drop in operating cash. The solution was to let artificial intelligence analyze the data, which revealed that two-thirds of the rod-lifting wells were over-pumped. Automating setpoint management using artificial intelligence reduced electricity use by 11%, with GHG emissions dropping 13% to a level consistent with the sustainability goals of the ‘business.
Remote work, less emissions
During the COVID-19 pandemic, staff are able to maintain full control while working from home (very difficult with on-premise systems) as data is stored in the cloud. The data is then accessible remotely.
Cloud computing has been slowly adopted for oil and gas automation as businesses worry about security, data ownership, and loss of control over data. But the value of AI-powered optimization and maintaining continuity during difficult business disruptions has convinced leaders and owners of its value.
Reducing travel is another way to reduce emissions. AI-based automation reduces operator travel in the field.
Keeping the reconditioning rig out of the well is the first task for producers. Failures cost money. Reconditioning is expensive and the well does not produce or generate income. Predictive maintenance using artificial intelligence is an increasingly popular solution to this problem.
Using historical and current data, the software can tell when a piece of equipment is likely to fail. Repair or replacement before a failure occurs will remove the rig from the rental. The “prescriptive” analysis goes one step further by explaining why the equipment broke and where to order the replacement part.
Artificial intelligence is a question of results
Oil and gas have always been a cyclical business. Producers roam the valleys and hope to take advantage of the peaks. They can’t control the prices, but they can control the costs.
Digital technologies using artificial intelligence allow companies to analyze data to spot trends they would never have noticed before and automate processes. Experienced staff are then freed up to solve high-value problems such as reducing greenhouse gas emissions.
The company is reducing its operating costs and achieving its sustainable development goals.
Markham Hislop is a Canadian energy and climate journalist who directs video interviews with global energy experts. It also hosts the Energi Talks Podcast, writes Markham On Energy’s energy policy analysis Columns, and written on the energy future. He is frequently interviewed on Canadian radio on energy transition issues and is the “Green Switch” columnist for CBC Radio Canada.
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