The document discusses the challenges in forecasting US shale oil production due to the industry's rapid changes and dependence on uncertain oil prices. It summarizes forecasts from major organizations that expect US shale oil production to increase by 2.2-2.3 million barrels per day in 2018-2019. However, these bullish forecasts could put downward pressure on prices, creating dynamic interactions between prices and production. Uncertainty around future prices and other changing factors like well productivity make production forecasts highly uncertain, especially at longer time horizons. Accuracy tends to decrease the further forecasts look into the future.

1. US Shale Oil Forecasts:
assumptions, uncertainty and
accuracy
Energy Initiatives Seminar (Vienna, September 18, 2018)
Salikhov Marsel (Institute for Energy and Finance, m_salihov@fief.ru)
Kurilov Viktor (Institute for Energy and Finance, v_kurilov@fief.ru)

2. «It’s hard to make predictions. Especially about the future»
2Source: EIA
 The US shale has become a major
disrupting force for global oil markets in
the last years. It will also continue
influence global markets in the future.
 From the forecasting perspective the
challenge is that the industry is relatively
new (so lack of data and short time series
with existing data) and it changes
rapidly. Factors that drive US shale are
not fixed but continue to change.
 Almost every forecaster expected that the
production will stabilize after the price
crash of 2014-15 due to financial
constraints. But the industry continued to
add production by cutting costs, improved
productivity and moving to ‘sweet spots’.
 Another reason why it is hard to predict
production is that we really cannot predict
prices. As there is uncertainty in prices
there will also be uncertainty in
production.
Forecasts of WTI oil price by EIA STEO
2
Forecasts of Lower-48 oil production by EIA STEO
mbd
$/barrel

3. 0,3
0,5
0,7
1,4 1,4
0,5 0,6
0,8
1,1
1,2
0,8 0,8
0,9
1,1
1,3
0,0
0,5
1,0
1,5
July17
Oct17
Jan18
Apr18
July18
July17
Oct17
Jan18
Apr18
July18
July17
Oct17
Jan18
Apr18
July18
EIA OPEC IEA
mbd
7,1
9,6
8,8
10,0
10,7
3,5
6,0
5,2
6,5
7,3
3
4
5
6
7
8
9
10
11
12
2013 2014 2015 2016 2017 2018
mbd
US total US shale
Almost everybody is bullish on the US shale production currently
3Source: EIA, IEA, OPEC
 1H18 the "second wave" of growth in US
shale oil finally gained momentum.
According to the first estimates, in
February-July 2018, production in the US
shale increased by 0.8 mbd y-o-y.
 In the last months almost everybody have
become bullish on the US shale. Major
international organizations (EIA, IEA and
OPEC) are now unified in their forecasts
for the shale sector and expect
production growth of 2.2-2.3 mbd in total
for 2018-2019 years.
 We’ve built a relatively simple model of
the US shale industry (6 major indicators
for 5 main US shale basins) for short-
term forecasting based on statistical
approach and individual basin attributes.
And basically we agree with such bullish
sentiment. With current oil prices
($70/barrel for WTI) we expect that that
the US production will increase 2.5-2.8
mbd in 2018-19.
US Shale Oil Production growth 2018: forecasts revision
3
US oil production actual data

4. 20
30
40
50
60
70
80
2015 2016 2017 2018 2019
$/barrel
WTI
Brent
forecast
But how it will influence prices?
4Source: EIA, IEA, OPEC
 The main consequence of such
bullishness is that the expected increase
in the US production alone can cover the
increase in global oil demand. In general
it should put downward pressure on
prices which itself is negative for the US
shale. So it’s a question of dynamic
relationship between oil prices and the
the US shale.
 Point estimates of future production and
future prices is just enough. Most sources
do not publish sensitivity estimates of US
shale production (or any other any other
parameter) to a possible price shock.
 Most forecasters do not also disclose
uncertainty of their forecasts so it’s hard
to estimate the level of confidence of the
forecast’ authors. It’s impossible to
estimate “what-if” scenarios with different
price scenarios (EIA STEO currently
expects $62/barrel for WTI for 2019
which is as assumption for the production
forecast).
EIA forecasts for oil prices
4
Global oil market supply vs demand
1,4
1,8
1,5 1,5 1,7 1,61,8
1,0
-0,3
0,8
2,0
1,4
0,7
1,9
0,7
0,1
-0,1
0,7
-0,5
0,0
0,5
1,0
1,5
2,0
2,5
3,0
3,5
2014 2015 2016 2017 2018e 2019f
mbd Other regions US produciton
Global demand

5. 2018 2019 2020
$80
+1,4 +1,5 +1,6
$70
+1,4 +1,4 +1,2
$60
+1,4 +1,2 +0,5
$50
+1,4 +0,8 -0,2
$40
+1,4 +0,3 -0,5
3
4
5
6
7
8
9
10
11
2013 2014 2015 2016 2017 2018 2019 2020 2021
$/barrel Actual $50
$60 $70
What is the influence of oil prices on shale oil production?
5Source: FIEF forecasts
 Even with oil prices going back to
$50/barrel the US shale can add about
2.2-2.3 mbd of production in 2018-2019.
But then production is expected to
decline in 2020.
 If problems with the lack of infrastructure,
personnel and equipment in the shale
industry are slowly resolved, then we can
expect a balance in the market with a
WTI price of $ 70/bbl. In this case, the
annual increase in shale production will
slow down to +0.7 mbd in 2020
(base scenario: +1,2 mbd in 2020).
If overcoming bottlenecks will take place
in the current regime, then the balancing
level of WTI prices will be closer to $ 60/
bbl.
FIEF base forecasts for shale oil production growth
5
Forecasts of the US shale production under different price scenarios

6. Uncertainty in forecasting factors: it’s dynamic picture
6
 It’s difficult to make accurate forecasts,
because of dynamic interaction of
different uncertainty factors. For example,
shale industry adjusted to oil price falling
in 2015 by increasing productivity.
Currently there’s uncertainty of how
productivity gains are left. For longer
periods (like 2-3 years) it’s a major
source for uncertainty in production
levels.
 Current Permian bottlenecks are an
additional complexity into the forecasting
process. Oil prices in the the Permian are
$14 per barrel lower than WTI because of
the lack of available pipeline capacity.
With lower oil prices Permian constraints
will be a much less important factor as
marginal producers/projects will be
delayed.
6
Oil price
Well productivity gains
(technological progress)
Drilled but UnCompleted
(DUC) wells:
increase/decrease
decisions
(business factor)
Permian basin constraints
Source: FIEF

7. How much can we trust in the forecasts?
7Source: EIA, FIEF 7
RMSE of EIA STEO and FIEF forecasts of the US shale production (in 2014-2017)
 An important factor affecting predictive accuracy
is the revision of the actual data. The revision of
the actual data explains 35-40% of the forecast
error on the horizon of one year. 15-20% of the
error is explained by price parameter (uncertainty
in oil price forecasts).
 We have to update our models and the structures
in order to keep it up to date.
 The MAE of the production forecast from the FIEF
model at the 12-month horizon is 7.1% (0.33 mbd)
which is comparable to EIA STEO forecasts. But our
model is simpler. It has lower error up to 6 months.
 The error is significantly higher at the longer
horizons. In 2015-2016 sometimes it was hard to
forecast even the direction of production changes at
15 months horizon
0,0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
mbd
STEO forecast
FIEF (STEO prices for WTI)
FIEF (actual prices for WTI)
data revision
model error
prices
uncertainty
forecasting horizon (months)

8. Questions for discussion
8
1. What are the main factors influencing the shale industry in the next 2-3
years? Are there some new not widely discussed factors?
2. Everyone is bullish on the US shale. Is there a reasonable scenario when this
this state is not realized? What can go wrong?
3. How can bullish shale oil production forecasts coincide with high oil prices
forecasts? Can we have both of them?
4. Do you evaluate shale oil production sensitivity to oil price shocks? What is
your estimate of the US shale reaction to a possible decline in oil prices?
5. Do you evaluate ex post forecast’s error when use forecasts of other sources
or your own forecasts? What are the best tools to estimate uncertainty in the
forecasts?
8