Integrating Decision Options and Uncertainty of Commodity Price in the Project Evaluation (36th Indonesian Petroleum Association (IPA) conference, 24 May 2012)

April 26, 2012 • Tell FriendsPrinter Friendly

The era of high uncertainty of commodity prices requires an economic reassessment of many natural resource projects.

Current conventional NPV analysis has a limitation in recognizing uncertainty during project life and some biased in its assumption, i.e.:

  1. It is assumed future cash flows to be certain to happen.
  2. Project risk does not change throughout its life
  3. It is assumed once the project is undertaken;  it will not be affected by any future managerial decision.


As shown in the above figure, the conventional NPV analysis would discount project cash flow using a constant discount rate.
The longer the project would be put into production, the higher the discounting factor would be applied to the cash flow generated from the project. This assumed cash flow uncertainty will be growing over the life of the project and would penalize long-lived projects in oil and gas industry.

The other issue in conventional NPV analysis is once an investment is made, the project will run its course without intervention (“now or never”). It’s contrary to a real situation in which a project owner has the flexibility to intervene in that project when new information becomes available in the future.

The conventional NPV appears to fail to assess the impact of uncertainty and the effect of a contingent decision when facing either adverse or favorable conditions in the future.

An attempt was made to correct the bias in conventional NPV methods in a modern valuation.

Least Squares Monte Carlo simulation (LSM) is a promising new technique in modern valuation methods for valuing assets, one that has received little or no attention in the oil and gas industry.

LSM can accommodate flexibility management in adapting and revising future decisions in response to changing circumstances such as that caused by fluctuation of oil price.

The objective of the LSM is to provide a path-wise approximation of the optimal stopping rule that maximizes the contingent claim’s value.

CASE STUDY

In this study, we investigate the possibility of extending the LSM method to value oil fields in Indonesian PSC terms. A Matlab-based program is developed for valuing the PSC block using the LSM method.

One PSC Block X is selected to carry out the reality investigation. This block was acquired in 2001 and consists of 3 fields.

Below figures shows the production forecast of the three (3) fields.

Presumably, the only source of uncertainty is the oil price (S) that will follow a mean reverting process.

Mean reverting process are naturally attractive to model crude prices since they embody the economic argument that when prices are “too high”, demand will reduce and supply will increase, producing a counter balancing effect. When Prices are “too low” the opposite will occur, again pushing price back towards some kind of long term equilibrium price.

The Ornstein Uhlenback process is widely used for modeling a mean reverting process. The process of crude price (S) is modeled as:

where

  • Wt is a Brownian-Motion, so DWt ~ N(0)
  • Lamda measures the speed of mean reversion
  • mu is the long term equilibrium price, to which the process tends to revert
  • delta is a measure of the process volatility

Based on the WTI futures prices during Jul – Dec 2001, the average of future price is at $22.91/bbl. This value would be used as a long term equilibrium price  in the mean reverting model.
Other assumptions such as the speed of mean reversion and volatility can be seen in the table below.

Assumption

Unit

Model typeCurrent Spot PriceLong term Equilibrium Price (mu)speed of mean reversion  (lamda)volatility  (delta)Simulation Run

Probabilistic

$18/bbl

$22.91/bbl

0.231

3

10,000 iteration

Above figure shows simulation result on mean reverting model of oil price with 10,000 iterations. The 80 per cent confidence range for long-term oil prices stabilizes with an upper boundary price of US$28 per bbl and a lower boundary price of US$16 per bbl.

In this study, there will be two strategic decisions that will be embedded in the LSM valuation:

  1. Operation Decision: shut down the field early if future economics is unfavorable. This applies to producing field A and B
  2. Development Decision: suspend the development of the field if future economics is unfavorable. This applies to developing field C.

According to the old PSC regulation, we can assume to carry no cost for abandonment and restoration obligations (ARO) and we can relinquish this block to the government.

LSM method will integrate the above price simulation process and dynamic optimization process into PSC calculation of Block X.

Risk free rate in the LSM valuation is assumed as 5%, benchmarked to 10 year US Government T- bonds.

Below table summarizes the forecast value from both conventional NPV and LSM for each field, based on an evaluation date of 2001 year end. The result shows LSM give a higher value for each field than conventional NPV.

 

Block X

Conventional NPV*  

($Million)

LSM Valuation

($Million)

Actual Net Cash Flow (NCF)

2001 – 2006 ($ million)

Field A

Field B

Field C

Total

15.9

7.2

9.8

32.9

19.96

11.39

14.80

46.15

Cumulative Undiscounted NCF

65.3

Present Value of NCF @ 15%

45.7

*conventional NPV use 15% discount rate and oil price of $18.0/bbl flat

 

It’s understood that conventional NPV ignored the market view about the future of oil price and the flexibility of management to anticipate the adverse oil price.

Field C is a good example for review. Since this field would be put into production in year 3 (2004), there will be a longer cash flow generated from this field. In conventional NPV technique, the value of this field would be penalized with the higher discounting factor due to longer time to generate cash flow.

In reality, after the acquisition in 2001, the block X had generated around $ 65 MM actual net cash flow from their operation up to year 2006.
Currently these fields are still in production. With a rising oil price trend from 2001 to date, we can expect more value generated from these blocks, exceeding any forecast value from conventional NPV.

Compared to the actual cash flow generated from this block, the LSM technique is more likely to reveal a true picture of the value of these fields than the conventional NPV method.

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