Abstract:

The objective of this research is to econometrically detail oil supply. The working hypothesis is that the oil market has changed over time with horizontal drilling and changes in demand. The methodology to address the hypothesis will consist of applied analytics concerning data from the Energy Information Administration. This research has vast implications for the Oklahoma economy due to its close ties with the oil market. The jobs of many Oklahomans depend on the price that can be commanded by a barrel of oil.

REVIEW OF THE LITERATURE:

Short-Term Energy Outlook. EIA. April 7, 2020

Crude Oil Prices. EIA assumes that the sharp reductions in global crude oil prices, which occurred during March 2020 as a result of COVID-19, will persist through the second quarter before prices begin gradually increasing through the end of the forecast. EIA expects that considerable decreases in liquid fuel consumption will result from containment measures and economic disruptions related to COVID-19, which will affect U.S. refinery activity and, consequently, demand for crude oil. However, crude oil supply will increase in the short term as a result of agreed production cuts among OPEC+ that were suspended. EIA assumes that these two factors will keep global crude oil prices at multi-year low averages through the first half of 2020. Only gradual increases in crude oil prices are expected through all of 2020 as these factors persist, which could lead to record levels of expected global oil inventory builds in the first half of 2020.

Just like any other product, the price that can be commanded is likely to influence production. COVID-19 allows for a quasi expiriment to check this assumption.

THE ECONOMIC MODEL:

The model I will use is a simple linear model. In plain english, Oil Price ($WTI) is a function of Oil Production (Thousands of Barrels).

\(Price = f(Production)\)

The model is a simple model of correlation. In reality, Production may affect price and price may affect production. The model works well either way with a semantic switch of the axis.

THE DATA:

The data I use comes from the Energy Information Administration.

Description Release Date
Oklahoma Field Production of Crude Oil (Thousand Barrels) 1/31/2020
U.S. Weekly Product Supplied 2/20/2020
Crude Oil Production 1/31/2020
Domestic Crude Oil Purchase Prices by Area 2/3/2020
Cushing, Oklahoma Weekly Supply Estimates 2/26/2020

additionally:

Cushing OK WTI Spot Price FOB
https://www.eia.gov/dnav/pet/hist/RWTCD.htm
15:02:53 GMT-0600 (Central Standard Time)
Data Source: Thomson Reuters

Perrin, Jack. “U.S. Energy Information Administration - EIA - Independent Statistics and Analysis.” Oil Wells Drilled Horizontally Are among the Highest-Producing Wells - Today in Energy - U.S. Energy Information Administration (EIA), U.S. Energy Information Administration, 4 Nov. 2016, www.eia.gov/todayinenergy/detail.php?id=28652.

“US Oil and Gas Wells by Production Rate - U.S. Energy Information Administration (EIA).” US Oil and Gas Wells by Production Rate - U.S. Energy Information Administration (EIA), U.S. Energy Information Administration, 20 Dec. 2019, www.eia.gov/petroleum/wells/.

CORRELATION AND REGRESSION:

## 
## Call:
## lm(formula = Price ~ Production, data = orderedRecentData)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -20.8885  -3.3356  -0.2092   3.8785  14.7499 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1.004e+01  8.210e+00   1.223    0.229    
## Production  2.851e-03  5.436e-04   5.244 5.78e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7.107 on 39 degrees of freedom
## Multiple R-squared:  0.4135, Adjusted R-squared:  0.3985 
## F-statistic:  27.5 on 1 and 39 DF,  p-value: 5.783e-06

The data suggests that oil production is a significant factor of the price at a 5% level.

## 
## Call:
## lm(formula = Production ~ Price, data = orderedRecentData)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
##  -3218  -1161   -286   1122   3383 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  7320.02    1479.08   4.949 1.47e-05 ***
## Price         145.06      27.66   5.244 5.78e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1603 on 39 degrees of freedom
## Multiple R-squared:  0.4135, Adjusted R-squared:  0.3985 
## F-statistic:  27.5 on 1 and 39 DF,  p-value: 5.783e-06

The data suggests that oil price is a significant factor of the production at a 5% level.

Implications:

The current price for a barrell of oil is $12.17 (from EIA2 Cushing, OK WTI Spot Price FOB (Dollars per Barrel)).
The current Oklahoma Field Production of Crude Oil (Thousand Barrels) is 16149.

the data suggests a surplus of oil production from Oklahoma producers of \((16149 - ((12.17* 145.06) + 7320.02))* (((12.17* 145.06) + 7320.02) - ((16149-7320.02)/145.06))/2\)

or about

## [1] 31872855

31,872,855 (thousand) barrels of oil.

Conclusion:

The Price and Quantity supplied of oil has been affected by technical change. Better drilling technology has led to greater output, spurred on by higher prices. In the current market this appears to be a bane leading to a large production surplus from Oklahoma producers. Prices from the 90’s does not appear to translate to a level of Production from the 90’s. Given current market conditions and recent data I project a 31,872,855 (thousand) barrels of oil surplus. It appears price does not influence pruduction (in the short term) in relation to the historical oil market. In the long term the surplus could be worked out due to oil production being unprofitable. Market fundamentals appear to hold strong, even if the question of “when?” may be uncertain.