INTERNATIONAL
EIA’s Annual Energy Outlook 2019 projects growing oil, natural gas, renewables production
EIA’s Annual Energy Outlook 2019 (AEO2019), which will be released later this morning, includes projections of U.S. energy markets through 2050 based on a Reference case and six side cases that include different assumptions regarding prices, economic activity, and technology and resource estimates. AEO2019 projects continued development of U.S. shale and tight oil and natural gas resources. Natural gas and natural gas plant liquids (NGPLs) experience the highest production growth of all fossil fuels, and NGPLs account for almost one-third of cumulative U.S. liquids production through the 2050 projection period.
In the Reference case, U.S. crude oil production continues to set annual records through the mid-2020s and remains greater than 14.0 million barrels per day (b/d) through 2040. The continued development of tight oil and shale gas resources, particularly those in the East and Southwest regions, supports growth in NGPL production—which reaches 6.0 million b/d by 2030—and dry natural gas production. Dry natural gas production reaches 43.4 trillion cubic feet by 2050.
Growth in drilling in the Southwest region also drives natural gas production from tight oil formations in the Reference case. Because drilling activity in oil formations primarily depends on crude oil prices rather than natural gas prices, the increase in natural gas production from oil-directed drilling puts downward pressure on natural gas prices. Sustained low natural gas prices and declining costs of renewable power enable the shares of electricity generated by natural gas and renewables to increase. The natural gas share increases from 34% in 2018 to 39% in 2050, and the renewables share increases from 18% in 2018 to 31% in 2050.
The Reference case is not intended to be the most probable prediction of the future, but it instead forms a baseline for estimating the effects of new policy or technology changes in the future. The other six cases show the effect of changing other key model assumptions.