However interesting and generally appealing scenario thinking, as discussed in my previous article, may be, it only provides a broad, qualitative picture of the context within which one is considering a significant investment decision. But indeed, a very important picture, even with all its caveats. Yet, we need numbers when it comes to sinking capital. No decision executive will sign off on an investment proposal that only consists of a fascinating narrative. She or he will want to see some underpinning of the potential profitability and capital efficiency. And some what ifs. In other words: we need quantification, we need a cash flow outlook of some sort.
In fact, it is one of the more difficult, and therefore avoided, challenges: to combine qualitative with quantitative thinking. Many restrict themselves to one of the two worlds. Yet I believe one has to try to cross the border. Quantification alone can often not tell the story by itself, but only qualitative narratives have the danger of becoming arm-waving.
But this quantification, if done well, does not come easy. How can we put numbers on the future? One way is to assume that whatever was going on in the past will replicate itself going forward. For some variables that is quite doable. If you are investing in wind or solar energy, the wind speed patterns and annual numbers of sun hours at a particular location can reasonably be inferred from historic records, with some averaging over multiple years. However, for many variables such an approach would not be credible.
Nevertheless, this is exactly what was (and is) common across many sectors. In fact, it is well known that this practice was one of the main causes of the financial crisis in 2008. The notion of ‘risk’ was strongly related to the degree of stock volatility in prior periods. Risk models were used that were only driven by historic behaviour; there was no forward looking element (see NYT, 2009). In essence, the quantitative models made people stop thinking. For the calculation of the minimum coverage for Dutch pension funds (i.e. stretching out multiple decades) the use of the current interest rate is mandatory. Similarly for the oil and gas reserves calculations for the SEC (US Securities and Exchange Commission) it is required to use, for the purpose of asset valuation, the currentoil price for several decades of remaining production. Of course these last two examples have auditing and legal dimensions, but they do illustrate the dilemma when considering future cash flows: we know that the value that some important variable assumes today may not be representative for the future, but we (think we) have nothing else (that is auditable).
For investment decisions and strategy development we will often need both a scenario approach and quantitative analysis. It will depend on the investment project where the emphasis lies, but I would argue that for major capital decisions or strategies both should have equal weight. What we see in practice is that (if done at all) scenario work and quantitative investment evaluations are poorly linked, perhaps because these different approaches are serviced by different departments, they require different styles of working, different areas of expertise.
And of course, to come back to the earlier point, the quantification developed should use historic data as a basis, but needs also to include a forward looking, judgemental dimension. Scenario narratives and (probabilistic and judgementally forward looking) quantification should go hand in hand, in some way, for maximum understanding and clarity.
For quantitative analysis we require a choice of models and methods, fit for purpose, not too complicated, but yielding consistent results. And we need mathematics, to do things smartly, quickly and consistently. To deal with uncertainty in the numbers, we need probability theory and probability distributions. There is no way we can arrive at exact estimates of all future variables (costs, prices, schedules, sales quantities, tax rates, etc.). But what we can do is to try to estimate a range (under certain scenario assumptions).
One of the most important distributions for this purpose is the lognormal distribution. It is representative of multiplicative processes (as is the normal distribution for additive processes). This means that the product of variables with ranges of uncertainty will tend to be lognormally distributed. Examples are volumes (L*W*H) and revenues (number of units solds * price). The lognormal distribution is also used quite a bit to model share price behaviour. It has an elegant mathematical formulation and allows for modelling upsides and downsides (with a trick). A recent article I came across (Surovtsev, D. and Sungurov, A. “Vaguely Right or Precisely Wrong?”: Making Probabilistic Cost, Time and Performance Estimates for Bluefield Appraisal. SPE 181904. SPE Economics & Management Journal, July 2017.) confirms that most cost, schedule and production variables are best represented by such a distribution.
Rather than (only) relying on integrated systems and black-box like simulation software, for practitioners and analysts it may be useful to get into the guts of the lognormal distribution, understand its mathematical articulation and have some practical formulas to calculate things by hand. It gets a bit nerdy, but do check out a useful article for this purpose in our free knowledge base (in which more articles are to come).
A next blogpost will again be about global scenarios in a qualitative discussion: what can we learn from our predecessors?
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Headline crude prices for the week beginning 10 December 2018 – Brent: US$62/b; WTI: US$52/b
Headlines of the week
The Permian is in desperate need of pipelines. That much is true. There is so much shale liquids sloshing underneath the Permian formation in Texas and New Mexico, that even though it has already upended global crude market and turned the USA into the world’s largest crude producer, there is still so much of it trapped inland, unable to make the 800km journey to the Gulf Coast that would take them to the big wider world.
The stakes are high. Even though the US is poised to reach some 12 mmb/d of crude oil production next year – more than half of that coming from shale oil formations – it could be producing a lot more. This has already caused the Brent-WTI spread to widen to a constant US$10/b since mid-2018 – when the Permian’s pipeline bottlenecks first became critical – from an average of US$4/b prior to that. It is even more dramatic in the Permian itself, where crude is selling at a US$10-16/b discount to Houston WTI, with trends pointing to the spread going as wide as US$20/b soon. Estimates suggest that a record 3,722 wells were drilled in the Permian this year but never opened because the oil could not be brought to market. This is part of the reason why the US active rig count hasn’t increased as much as would have been expected when crude prices were trending towards US$80/b – there’s no point in drilling if you can’t sell.
Assistance is on the way. Between now and 2020, estimates suggest that some 2.6 mmb/d of pipeline capacity across several projects will come onstream, with an additional 1 mmb/d in the planning stages. Add this to the existing 3.1 mmb/d of takeaway capacity (and 300,000 b/d of local refining) and Permian shale oil output currently dammed away by a wall of fixed capacity could double in size when freed to make it to market.
And more pipelines keep getting announced. In the last two weeks, Jupiter Energy Group announced a 90-day open season seeking binding commitments for a planned 1 mmb/d, 1050km long Jupiter Pipeline – which could connect the Permian to all three of Texas’ deepwater ports, Houston, Corpus Christi and Brownsville. Plains All American is launching its 500,000 b/d Sunrise Pipeline, connecting the Permian to Cushing, Oklahoma. Wolf Midstream has also launched an open season, seeking interest for its 120,000 b/d Red Wolf Crude Connector branch, connecting to its existing terminal and infrastructure in Colorado City.
Current estimates suggest that Permian output numbered around 3.5 mmb/d in October. At maximum capacity, that’s still about 100,000 b/d of shale oil trapped inland. As planned pipelines come online over the next two years, that trickle could turn into a flood. Consider this. Even at the current maxing out of Permian infrastructure, the US is already on the cusp on 12 mmb/d crude production. By 2021, it could go as high as 15 mmb/d – crude prices, permitting, of course.
As recently reported in the WSJ; “For years, the companies behind the U.S. oil-and-gas boom, including Noble Energy Inc. and Whiting Petroleum Corp. have promised shareholders they have thousands of prospective wells they can drill profitably even at $40 a barrel. Some have even said they can generate returns on investment of 30%. But most shale drillers haven’t made much, if any, money at those prices. From 2012 to 2017, the 30 biggest shale producers lost more than $50 billion. Last year, when oil prices averaged about $50 a barrel, the group as a whole was barely in the black, with profits of about $1.7 billion, or roughly 1.3% of revenue, according to FactSet.”
The immense growth experienced in the Permian has consequences for the entire oil supply chain, from refining balances – shale oil is more suitable for lighter ends like gasoline, but the world is heading for a gasoline glut and is more interested in cracking gasoil for the IMO’s strict marine fuels sulphur levels coming up in 2020 – to geopolitics, by diminishing OPEC’s power and particularly Saudi Arabia’s role as a swing producer. For now, the walls keeping a Permian flood in are still standing. In two years, they won’t, with new pipeline infrastructure in place. And so the oil world has two years to prepare for the coming tsunami, but only if crude prices stay on course.
Recent Announced Permian Pipeline Projects
Headline crude prices for the week beginning 3 December 2018 – Brent: US$61/b; WTI: US$52/b
Headlines of the week