When global oil prices declined dramatically in 2014 and 2015, leading energy analysts expected that oil production in the United States — consisting primarily of tight oil extracted from rock formations by means of massive hydraulic fracturing — would likewise decrease due to relatively high production costs. Despite the prospects for a negative return on investment, however, U.S. tight oil production continued almost unabated.
Perplexed by this development, a team of researchers sought to better understand the relationship between oil prices and production volumes. In particular, they aimed to pinpoint the factors that determine the breakeven points of tight oil production projects — essentially the oil price points at which revenue from sales equals the cost of production.
Though energy industry analysts have widely used breakeven costs to predict how oil producers will respond to changing market conditions and to assess the economic viability of proposed oil and gas development projects, they have routinely defined them imprecisely and inconsistently. This has resulted in predictions that have limited utility and reliability. To enable more robust predictions, the researchers — who work for Schlumberger-Doll Research, the MIT Joint Program on the Science and Policy of Global Change, the Atlantic Council, the King Abdullah Petroleum Studies and Research Center, and the Columbia University School of International and Public Affairs — have developed a systematic method to understand the costs of oil production and how they change with time and circumstances.
Applying this method, they have proposed a set of standard definitions for breakeven points at different stages of the oil production cycle. Their study appears in the journal Energy Economics.
“Instead of treating the economics of oil production as static, we realized that costs depend not only on technological change but also on supply chain optimization, the maturity of resource development, and even on the price of oil itself,” says lead author Robert L. Kleinberg, a Schlumberger Fellow based in Cambridge, Massachusetts. "Understanding the dynamic nature of the petroleum industry will help economists and policymakers more accurately predict how changes in supply and demand will affect this very important part of the world economy.”
The research team first defined three primary categories of costs that are commonly referenced in breakeven analyses: lifting, half-cycle, and full-cycle. Lifting costs are expenditures required to produce oil from existing wells. Half-cycle costs include those related to drilling activity. Full-cycle costs include all expenses related to developing a new project, including exploration, resource estimation, and lease acquisition.
The researchers next showed how internal factors, such as technological improvements in the efficiency of oil extraction, and external factors, such as the market-determined price of oil, impact these costs. They noted that as oil prices decline, the main driver of break-even economics shifts from full-cycle to half-cycle to lifting costs. As oil prices rise, they found that the reverse sequence applies.
Looking closely at internal and external factors impacting the U.S. tight oil market, the researchers determined that much of the unexpected, rapid increase in U.S. tight oil production after 2010 was due to the availability of specialized oilfield equipment built during the previous six years to exploit shale gas. They also attributed the surprisingly slow decline of U.S. tight oil supplies that occurred while oil prices fell in 2014 and 2015 to the slow decline of field-level production from tight oil wells that were beyond their more prolific first year of production.
“Oil prices have a complicated impact on the dynamics of oil production, which in turn affects oil prices,” says Sergey Paltsev, a senior research scientist at the MIT Joint Program on the Science and Policy of Global Change and MIT Energy Initiative, and a co-author of the paper. “By taking a more systematic approach to defining break-even costs than previous studies, our analysis helps to construct more robust energy scenarios, enabling more accurate modeling of how the oil market is likely to react as the world shifts to more low-carbon energy sources.”
