# Beyond oil lies … more oil + price volatility

One of many best-selling books by Kenneth Deffeyes

While I was at Princeton, one of the most popular courses was geology 101 taught by Dr. Kenneth S. Deffeyes. It was a sort of “Rocks for Jocks,” but had an unusual bite since Dr. Deffeyes focussed particularly on the geology of oil. Deffeyes had an impressive understanding of oil and oil production, and one outcome of this impressive understanding was his certainty that US oil production had peaked in 1970, and that world oil was about to run out too. The prediction that US oil production had peaked was not original to him. It was called Hubbert’s peak after King Hubbert who correctly predicted (rationalized?) the date, but published it only in 1971. What Deffeyes added to Hubbard’s analysis was a simplified mathematical justification and a new prediction: that world oil production would peak in the 1980s, or 2000, and then run out fast. By 2005, the peak date was fixed to November 24, of the same year: Thanksgiving day 2005 ± 3 weeks.

As with any prediction of global doom, I was skeptical, but generally trusted the experts, and virtually every experts was on board to predict gloom in the near future. A British group, The Institute for Peak Oil picked 2007 for the oil to run out, and the several movies expanded the theme, e.g. Mad Max. I was convinced enough to direct my PhD research to nuclear fusion engineering. Fusion being presented as the essential salvation for our civilization to survive beyond 2050 years or so. I’m happy to report that the dire prediction of his mathematics did not come to pass, at least not yet. To quote Yogi Berra, “In theory, theory is just like reality.” Still I think it’s worthwhile to review the mathematical thinking for what went wrong, and see if some value might be retained from the rubble.

Deffeyes’s Maltheisan proof went like this: take a year-by year history of the rate of production, P and divide this by the amount of oil known to be recoverable in that year, Q. Plot this P/Q data against Q, and you find the data follows a reasonably straight line: P/Q = b-mQ. This occurs between 1962 and 1983, or between 1983 and 2005. Fro whichever straight line you pick, m and b are positive. Once you find values for m and b that you trust, you can rearrange the equation to read,

P = -mQ2+ bQ

You the calculate the peak of production from this as the point where dP/dQ = 0. With a little calculus you’ll see this occurs at Q = b/2m, or at P/Q = b/2. This is the half-way point on the P/Q vs Q line. If you extrapolate the line to zero production, P=0, you predict a total possible oil production, QT = b/m. According to this model this is always double the total Q discovered by the peak. In 1983, QT was calculated to be 1 trillion barrels. By May of 2005, again predicted to be a peak year, QT had grown to two trillion barrels.

I suppose Deffayes might have suspected there was a mistake somewhere in the calculation from the way that QT had doubled, but he did not. See him lecture here in May 2005; he predicts war, famine, and pestilence, with no real chance of salvation. It’s a depressing conclusion, confidently presented by someone enamored of his own theories. In retrospect, I’d say he did not realize that he was over-enamored of his own theory, and blind to the possibility that the P/Q vs Q line might curve upward, have a positive second derivative.

Aside from his theory of peak oil, Deffayes also had a theory of oil price, one that was not all that popular. It’s not presented in the youtube video, nor in his popular books, but it’s one that I still find valuable, and plausibly true. Deffeyes claimed the wildly varying prices of the time were the result of an inherent quay imbalance between a varying supply and an inelastic demand. If this was the cause, we’d expect the price jumps of oil up and down will match the way the wait line at a barber shop gets longer and shorter. Assume supply varies because discoveries came in random packets, while demand rises steadily, and it all makes sense. After each new discovery, price is seen to fall. It then rises slowly till the next discovery. At least in the short term, price is seen as a symptom of supply unpredictability rather than a useful corrective to supply needs. This view is the opposite of Adam Smith, but I think he’s not wrong, at least in the short term with a necessary commodity like oil.

Academics accepted the peak oil prediction, I suspect, in part because it supported a Marxian remedy. If oil was running out and the market was broken, then our only recourse was government management of energy production and use. By the late 70s, Jimmy Carter told us to turn our thermostats to 65. This went with price controls, gas rationing, and a 55 mph speed limit, and a strong message of population management – birth control. We were running out of energy, we were told because we had too many people and they (we) were using too much. America’s grown days were behind us, and only the best and the brightest could be trusted to manage our decline into the abyss. I half believed these scary predictions, in part because everyone did, and in part because they made my research at Princeton particularly important. The Science fiction of the day told tales of bold energy leaders, and I was ready to step up and lead, or so I thought.

By 2009 Dr. Deffayes was being regarded as chicken little as world oil production continued to expand.

I’m happy to report that none of the dire predictions of the 70’s to 90s came to pass. Some of my colleagues became world leaders, the rest because stock brokers with their own private planes and SUVs. As of my writing in 2018, world oil production has been rising, and even King Hubbert’s original prediction of US production has been overturned. Deffayes’s reputation suffered for a few years, then politicians moved on to other dire dangers that require world-class management. Among the major dangers of today, school shootings, ebola, and Al Gore’s claim that the ice caps will melt by 2014, flooding New York. Sooner or later, one of these predictions will come true, but the lesson I take is that it’s hard to predict change accurately.

Just when you thought US oil was depleted, production began rising. We now produce more than in 1970.

Much of the new oil production you’ll see on the chart above comes from tar-sands, oil the Deffeyes  considered unrecoverable, even while it was being recovered. We also  discovered new ways to extract leftover oil, and got better at using nuclear electricity and natural gas. In the long run, I expect nuclear electricity and hydrogen will replace oil. Trees have a value, as does solar. As for nuclear fusion, it has not turned out practical. See my analysis of why.

Robert Buxbaum, March 15, 2018. Happy Ides of March.

# Hydrogen powered trucks and busses

With all the attention to electric cars, I figure that we’re either at the dawn of electric propulsion vehicles or of electric propulsion vehicle hype. Elon Musk’s Tesla motor car company stock is now valued at \$59 B, more than GM or Ford despite the company having massive losses and few cars. The valuation, I suspect, has to do with the future and autonomous vehicles. There are many who expect self-driving vehicles will rule the road, but the form is uncertain. In this space, i suspect that hydrogen-battery hybrids make more sense than batteries alone, and that the first large-impact uses will be trucks and busses — vehicles that go long distance on highways.

Factory floor, hydrogen fueling station for fuel cell forklifts. This company’s fuel cells have had over 10 million refuelings so far.

Currently there are only two bands of autonomous vehicles available in the US, the Cadillac CT6, a gasoline powered car, and the Tesla. Neither work well except on highways because the number of highway problems are fewer than the number of city problems and only the CT6 allows you to take your hands off the wheel — see review here. To me, being able to take your hand off the wheel is the only real point of autonomous control, and if one can only do this only on the highway, that’s acceptable. Highway driving gets quite tiring after the first hundred miles or so, and any relief is welcome.

Tesla’s battery cars allow for some auto-driving on the highway, but you can’t take your hand off the wheel or the car stops. That battery cars compete at all for highway driving, I suspect, is only possible because the US government highly subsidizes the battery cost. Musk then hides the true cost among the corporate losses. Without this, hydrogen – fuel cell vehicles would be cheaper, I suspect, while providing better range, see my calculation here. Adding to the advantage of hydrogen over batteries, the charge time for hydrogen is much faster. Slow charge times are a real drawback for highway vehicles traveling any significant distances. While hydrogen fuel isn’t cheap — it’s becoming cheaper and is now about double the price of gasoline on a per mile basis. The advantage over gasoline is it provides pollution-free, electric propulsion, and this is well suited to driverless vehicles. Both gasoline and battery vehicles can have odd acceleration issues, e.g. when the gasoline gets wet, or the battery gets run down. And it’s not like there are no hydrogen fueling stations. Hydrogen, fuel-cell power has become a major competitor for fork-lifts, and has recently had its ten million refueling in that application. The same fueling stations that serve the larger fork-lift users could serve the self-driving truck and bus market.

For round the town use, hydrogen vehicles could still use batteries, and the combined vehicle can have very impressive performance. A Dutch company has begun to sell kits to convert Tesla model S autos to combined battery + hydrogen. With these kits, they boast a 620 mile (1000 km) range instead of the normal 240 miles. See the product here.  On the horizon, in the self-driving fuel cell market, Hyundai has debuted the “Nexo” with a range of 370 miles. Showing off the self-driving capability, Nexos were used to carry spectators between venues at the Pyongyang olympics. Japanese competitors, the Toyota Mirai (312 miles) and the Honda Clarity Fuel Cell (366 miles) can be expected to provide similar capabilities.

Cadillac CT6 with supercruise. An antonymous vehicle that you can buy today that allows you to take your hand off the wheel.

The reason I believe in hydrogen Trucks and Busses more than cars is the difficulty of refueling, Southern California has installed some 36 public hydrogen refueling stations at last count, but that’s too few for most personal car use. Other states have even fewer spots where you can drive up and get hydrogen; Michigan has only two. This does not matter for a commercial truck or bus because they go between fixed depots and these can be fitted with hydrogen dispensers as found for forklifts. It’s possible trucks can even use the same dispensers as the forklifts. If one needs a little extra range one can add a “hydrogen Jerry can” to provide an extra kg of H2 to provide 20-30 miles of emergency range. I do not see electric vehicles working as well because the charge times are so slow, the range so modest, and the electric power needs so large. To charge a 100 kWhr battery in an hour, the charge station would have to have an electric feed of 100 kW, about as much as a typical mall. With 100A, 240 V, the most you can normally get, expect a 4 1/2 hour charge.

The real benefit for hydrogen trucks and busses is autonomy. Being able to run the route without major input from a driver. So why not gasoline, as with the Cadillac? My answer is simplicity. If you want driverless simplicity, you want electric or hydrogen. And only hydrogen provides the long-range, fast fueling to make the product worthwhile.

Robert Buxbaum March 12, 2018. My company, REB Research provides hydrogen purifiers and hydrogen generators.

# Yogurt making for kids

Yogurt making is easy, and is a fun science project for kids and adults alike. It’s cheap, quick, easy, reasonably safe, and fairly useful. Like any real science, it requires mathematical thinking if you want to go anywhere really, but unlike most science, you can get somewhere even without math, and you can eat the experiments. Yogurt making has been done for centuries, and involves nothing more than adding some yogurt culture to a glass of milk and waiting. To do this the traditional way, you wait with the glass sitting outside of any refrigeration (they didn’t have refrigeration in the olden days). After a few days, you’ll have tasty yogurt. You can get taster yogurt if you add flavors. In one of my most successful attempts at flavoring, I added 1/2 ounce of “skinny syrup” (toffee flavor) to a glass of milk. The results were most satisfactory, IMHO.

My latest batch of home-made flavored yogurt, made in a warm spot behind this coffee urn.

Now to turn yogurt-making into a science project. We’ll begin with a hypothesis. I generally tell people to not start with a hypothesis, (it biases your thinking), but here I will make an exception as I have a peculiarly non-biased hypothesis to suggest. Besides, most school kids are told they need one. My hypothesis is that there must be better ways to make yogurt and worse ways. A hypothesis should be avoided if it contains any unfounded assumptions, or if it points to a particular answer — especially an answer that no one would care about.

As with all science you’ll want to take numerical data of cause and effect. I’d suggest that temperature data is worth taking. The yogurt-making bacteria is called lactose thermophillis, and this suggests that warm temperatures will be good (lact = milk in Latin, thermophilic = loving heat). Also making things interesting is the suspicion that if you make things too warm, you’ll cook your organisms and you won’t get any yogurt. I’ve had this happen, both with over-heat and under-heat. My first attempt was to grow yogurt in the refrigerator, but I got no results. I then tried the kitchen counter and got yogurt, and then I heated things a bit more by growing next to a coffee urn, and got better yogurt; yet more heat and nothing.

For a science project, you might want to make a few batches of yogurt, at least 5, and these should be made at 2-3 different temperatures. If temperature is a cause for the yogurt to come out better or worse, you’ll need to be able to measure how much “better”? You may choose to study taste, and that’s important, but it’s hard to quantify, so that should not be the whole experiment. I would begin by testing thickness, or the time to a get some fixed degree of thickness; I’d measure thickness by seeing if a small weight sinks. A penny is a cheap, small weight, and I know it sinks in milk, but not in yogurt. You’ll want to wash your penny first, or no one will eat the yogurt. I used hot water from the urn to clean and sterilize my pennies.

Another thing that is worth testing is the effect of using different milks: whole milk, 2%, 1% or skim; goat milk, or almond milk. You can also try adding stuff to it, or starting with different starter cultures, or different amounts. Keep numerical records of these choices, then keep track of how they effect how long it takes for the gel to form, and how the stuff looks or tastes to you. Before you know it, you’ll have some very good product at half the price of the stuff in the store. If you really want to move forward fast, you might apply semi-random statistics to your experimental choices. Good luck.

Robert Buxbaum, March 2, 2018. My latest observation: what happens if you leave the yogurt to mold too long? It doesn’t get moldy, perhaps the lactic acid formed kills germs (?), but the yogurt separated into curds and whey. I poured off the whey, the unappealing, bitter yellow liquid. The thick white remainder is called “Greek” yogurt. I’m not convinced this tastes better, or is healthier, BTW.