Stanford study finds energy requirements of super-giant oilfields can significantly increase over time

Stanford study finds energy requirements of super-giant oilfields can significantly increase over time

17 July 2017

A new study finds that as some of the world’s largest oilfields age, the energy required to keep them operating can rise dramatically even as the amount of petroleum they produce drops. Failing to take the changing energy requirements of oilfields into account can cause oilfield managers or policymakers to underestimate the true climate impacts, Stanford scientists warn.

Mohammad Masnadi and Adam Brandt used decades-long time-series data from twenty-five globally significant oil fields (>1 billion barrels ultimate recovery) to model greenhouse gas (GHG) emissions from oil production as a function of time.Depletion requires increased energy expenditures in drilling, oil recovery, and oil processing. They found that volumetric oil production declines with depletion, but that this depletion is accompanied by significant growth—in some cases more than tenfold—in per-MJ GHG emissions.

Using probabilistic simulation, they derived a relationship for estimating GHG increases over time, showing an expected doubling in average emissions over 25 years. The new findings, published in the journal Nature Climate Change, have implications for long-term emissions and climate modeling, as well as climate policy.

Current climate and energy system models typically don’t explore the impacts of oil reservoir depletion in any detail. As oilfields run low, emissions per unit of oil increase. This should be accounted for in future modeling efforts.

—Adam Brandt

BRANDT
Time-series trends in normalized upstream GHG intensities of twenty-five global oil fields (offshore and onshore) with dfferent extraction practices (water injection/flooding, gas injection/flooding/lifting, or steam flooding) over the course of production in the period of 1949–2015. a, Heavy oils. b, Medium oils. c, Light oils. Filled and hollow markers represent offshore and onshore fields, respectively. Masnadi & Brandt (2017). Click to enlarge.

Conventional greenhouse gas estimates calculate emissions through a kind of economic reverse engineering, whereby an economic index is used to convert the monetary value of an oilfield’s final products—whether it be processed oil, natural gas or petroleum-based products—into greenhouse gas emissions. This top-down approach for converting economic values into environmental and energetic costs misses a lot of underlying information, Masnadi said.

Further, many studies look at data from only a single point in time, and as a result capture only a snapshot of an oilfield’s greenhouse gas emissions. But the Stanford scientists argue that in order to paint the most accurate picture of an oilfield’s true climate impacts—and also have the best chance of reducing those impacts—it’s necessary to assess the energy costs associated with every stage of the petroleum production process, and to do so for the oilfield’s entire lifetime.

Developed in Brandt’s lab at Stanford, a software tool called the Oil Production Greenhouse gas Emissions Estimator (OPGEE) is designed to do just that. For any given oilfield, OPGEE performs a lifecycle assessment, analyzing each phase of the oil production process—extraction, refinement and transportation. It then uses computer models to calculate how much energy is consumed during each step. From this, scientists can calculate how much greenhouse gas each oilfield emits.

This bottom-up type of analysis hasn’t been done before because it’s difficult. For this study, we needed over 50 different pieces of data for each oilfield for each year. When you’re trying to analyze an oilfield across decades, that’s a lot of data.

—Mohammad Masnadi

Most oil companies are reluctant to release this type of temporal data about their oilfields. The Stanford researchers developed two workarounds to this problem. First, they gathered data from places where transparency laws require oil production data be made publicly available. These included Canada, Norway and the UK, and the state of California in the US. Secondly, the pair conducted a deep data mine of the scientific literature to seek out clues about oilfield production levels in published studies.

One way to reduce the increase in emissions is through tougher government regulations that force companies to reduce their greenhouse gas emissions or risk having to lower production. This has been shown to work at two Canadian offshore fields, Hibernia and Terra Nova, where regulations have sharply lowered greenhouse gas emissions by limiting oil production in fields where gas is wasted through flaring and venting.

Better regulation is certainly part of the answer, but a more progressive solution is to encourage energy companies to draw the energy they need to operate their aging oilfields from renewable sources such as solar, wind or geothermal.

—Mohammad Masnadi

Masnadi cites the example of the California-based company GlassPoint Solar, which uses solar-powered steam generators to reduce the gas consumption and carbon emissions of its oilfields by up to 80%.

Done right, such solutions could end up being a win-win for industry and the environment, the Stanford scientists said, by helping oil companies drive down energy costs while simultaneously reducing their climate impacts.

The OPGEE tool Brandt’s team developed has already been adopted by the California Air Resources Board to help reduce greenhouse gas emissions from transport fuels, but Brandt thinks it could also prove useful to industry.

Funding for the study was provided by the Natural Sciences and Engineering Research Council of Canada and Ford Motor Co.

Resources

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