R-Squared Energy Blog

Pure Energy

A Year Without a Car

On March 1, 2008 I sold my Nissan Micra in Aberdeen, Scotland and hopped a plane to Amsterdam to take up a new position. I have not owned a car since that time. A while back someone asked what that experience has been like, and suggested I write a story on it. So here it is.

While in Europe

It is really a tale of two continents. In large parts of Europe, one can get along reasonably well without a car. In the past year, I have worked at my company’s Accoya factory in the Netherlands most of the time. I fly in to Amsterdam, and there is a train station right in the airport. I catch a direct, 1 hour and 15 minute train to the Arnhem Central Train Station. From there, it’s a 15-minute cab ride to my apartment. (If you want to argue that my international flights more than offset any fuel savings from biking to work, you won’t get any argument from me. But in this economy, you do what you have to).

I secured an apartment that is only about half a mile from work, and I adopted the common Dutch habit of riding my bike to work. I certainly don’t feel safe all of the time with cars whizzing past me, and at times it has been an inconvenience, but the vast majority of the time the bike suits me just fine.

As for the inconvenience, if I want to go out to eat, I am around a mile from the nearest restaurant. When visitors come over to the factory to visit, I often find myself riding the bike in the dark, to a restaurant that may be 3 miles from my apartment. That may seem like a piece of cake, but I have done it in the snow, in freezing rain, and with a fierce wind in my face. It would certainly be more convenient to hop in a car and go.

The worst inconvenience to date was when I had a bad cold, and my secretary made me a doctor’s appointment on short notice. I hopped on my bike and rode a mile and a half in a freezing downpour. I could have probably bothered someone to take me, but I really try to be as low-maintenance as possible.

I do have other options, and I utilize them. There is a bus stop near my apartment, and I use it quite a lot. During the day the bus comes frequently, but later in the evening it only runs once an hour, and then stops altogether at about 10 p.m. (Incidentally, I learned one night while waiting for a bus at 10 that’s when the prostitutes come out and take over the bus stops).

For trips of intermediate length, a cab is another option I utilize from time to time. When I fly home, I have to catch a train at 6 a.m. That’s always a cab ride to the station. If I want to travel to another major European city, the train connections are superb. However, if you want to venture out into the countryside, it may be more difficult. My son wants me to take him to Normandy this summer, and that’s almost impossible to do without a car because the major points of interest are scattered over several miles, and there aren’t easy train connections to my knowledge. So this summer I expect to rent a car in Europe for the first time.

Meanwhile, Back in Texas

But as I said, it is a tale of two continents. When I fly back to Texas, it is hard to do without a car. I fly into the airport, and the first thing I have to do is catch a cab for the 35-mile drive to my house.

I bought a house 25 miles from my Dallas office, because 1). I hate cities, so I chose a house in the country; 2). I knew I wasn’t going to have to spend that much time in the office. 3). Because the housing bubble was imploding, I got a builder’s foreclosure for about half the appraised price. If I had to make that commute every day, I would have sucked it up and bought a house closer to the office, preferably close to some kind of public transportation. From where I live, public transportation isn’t an option, so I rent a compact car when I have to be in the office, or borrow my wife’s car if the kids are out of school.

How long can I keep this up? To be honest, I never thought I could keep it up for over a year. My initial assignment involved several straight months in the Netherlands, and I thought I would have to buy a car when I returned. But every time I do a cost benefit analysis, I can never justify it when I only need it one or two weeks a month. I have no registration fees or maintenance to pay, and I don’t have to keep insurance on it, because my insurance company covers me for a car rental at no extra cost. In the past six months, I have spent a total of $825 on car rentals. I don’t think a car purchase makes economic sense until I find myself spending 3-4 times this amount over a six month period. Given my current work arrangements, that is unlikely to happen any time soon.

Besides, I like the idea of living without a car. I will continue to put it off as long as possible, even if it occasionally means riding my bike to the doctor in the freezing rain.

Footnote

On an unrelated footnote, the 2009 EIA Energy Conference takes place on April 7th and 8th. The conference is free, so feel free to drop by if you are in the area. There are a number of topics that look interesting, including the following two plenary talks:

Energy and the Macroeconomy – William D. Nordhaus, Sterling Professor of Economics, Yale University

Energy in a Carbon-Constrained World – John W. Rowe, Chairman and Chief Executive Officer, Exelon Corporation

There are also a number of panel sessions, including:

The Future for Transport Demand

What’s Ahead for Natural Gas Markets?

Meeting the Growing Demand for Liquids

Financial Markets and Short-Term Energy Prices

Investing in Oil and Natural Gas – Opportunities and Barriers

I have been asked to participate on the panel Energy and the Media. The other panelists are Steven Mufson from the Washington Post and Eric Pooley from Harvard University (who was also former managing editor at Fortune). Mufson is the main energy reporter for the Post, and I think he does a good job of reporting the important stories. I have read a lot of his work, and have spoken to him on at least one occasion. Then there’s me, the energy blogger. Please humor me and let’s not play the game “Which One is not Like the Others?” 🙂

Here’s where I could use some assistance. I have a general idea of the themes I would like to explore. Namely, I want to discuss the amount of energy misinformation, which I think stems from some reporters really not having the background to know when they are being misled. We as a nation have a low energy IQ, and that creeps into many of the stories in the media. The TDP fiasco is a perfect example. Had the reporters dug a bit more and been more critical, it would have been another possibly interesting next generation fuel experiment, instead of something that ultimately had a lot of taxpayer money thrown at it.

But what else? What other themes should be examined on a panel entitled Energy and the Media?

March 16, 2009 Posted by | cars, DOE, EIA, Energy Information Administration, mass transit, Netherlands, texas | 83 Comments

EPA Denies Ethanol Waiver

No big surprise here, and I have been advising people that there was very little chance that the EPA would grant the waiver, but they have officially denied the ethanol waiver request from the state of Texas:

EPA denies Texas governor’s ethanol waiver request

EPA Administrator Stephen Johnson, during a conference call with reporters, said the agency’s assessment looked at the livestock issue and found feed prices have increased because of biofuel production. “However, is that the result of the (Renewable Fuels Standard) mandate? Our conclusion is no,” Johnson said. “And second, are those price increases meeting the statutory requirement of severe harm to the economy? And our conclusion is no.”

Environmental groups, concerned about how biofuels affect climate, water quality and biodiversity, also supported the waiver. Sandra Schubert, spokeswoman for the Environmental Working Group, said the denial is shortsighted and that the country should be focused on viable clean energy solutions. “Instead, the misguided corn ethanol mandate is forcing farmers to plow up marginal land and wildlife habitat, while increasing global warming and dumping toxic fertilizers and pesticides into our precious water sources,” she said in a statement.

On Capitol Hill, the decision drew mixed reaction. Members of the Texas congressional delegation, U.S. Rep. Joe Barton and Sen. Kay Bailey Hutchison, who has filed legislation that would freeze future ethanol production at this year’s level, criticized the agency’s decision.

“I am disappointed that the EPA missed this opportunity to provide relief for American consumers who are dealing with skyrocketing food prices due to the unintended consequences of the continued escalation of the ethanol mandate,” Hutchison said in a statement.

U.S. Sen. Chuck Grassley of Iowa, also a Republican, called the decision a “victory,” saying it will allow farmers to “continue to plan for and meet the fuel and food needs of the future.”

Given the Bush administration’s infatuation with ethanol, I thought the chances of the waiver being granted were very slim.

August 8, 2008 Posted by | EPA, ethanol, ethanol mandate, texas | 20 Comments

When Will Saudi Arabian Oil Production Peak?

The eventual decline of oil production in Saudi Arabia will likely have a profound impact on all of our lives. This event will result in energy shortages around the world, and depleting oil supplies will be bid up to higher and higher levels. Poor countries will no longer be able to compete, and they will be the first casualties of oil depletion. The richer countries will bid against each other for the remaining supplies, and if the depletion rate is high enough we will be in for some very tough times. The Saudis say they have plenty of oil. However, there are a lot of skeptics.

So, I am very interested in understanding what’s going on inside Saudi Arabia. One thing is certain: Over the past year their oil production has declined. I think up until now the reasons they have given for reducing oil production – which they say is entirely voluntary – have been consistent with what the market was calling for. So, I believe that their decline over the past year has been voluntary.

Other researchers disagree. Books have been written calling into question the claims of Saudi reserves. Matt Simmon’s book Twilight in the Desert was devoted to this subject. Many people have come up with models for attempting to predict the demise of Saudi oil production. This essay, also posted to The Oil Drum, takes a close look at one popular model that is often used as evidence pointing to an imminent peak for Saudi, as well as world oil production.

In Part I, I take a look at the model by feeding it historical Texas oil production data and observing the predictions. In Part II, I will feed it historical Saudi oil production data and observe the results.

Part I – Texas Myths

Like Cindy Crawford, I have done quite a bit of modeling in my career. However, mine has been in front of a computer. There are various types of models. They can be empirical, such that you curve fit data without having a clear explanation of the underlying mechanisms. Or they can be theoretical, in which the system is modeled according to the governing scientific principles and mathematical equations.

However, one thing is critical to keep in mind. If you are going to use the model for forecasting, the model must be tested. Testing the model is called “validation”, or sometimes “back-casting.” This involves feeding the model real data, and observing how well the predictions match up with the observations. If the predictions match up on a consistent basis, and any large variations are explainable, you have the makings of a predictive model. If you have not validated your model, or if you have attempted to validate it and found that the predictions were inconsistent, the model should be used with caution (if at all). In this essay I have done some back-casts on the Hubbert Linearization (HL) model and attempted to use it to make predictions using historical data.

The background of the technique is outside the scope of this essay, but Stuart Staniford has provided details here. The HL model is a hybrid model with empirical parts and theoretical parts. Jumping past the differential equations involved, a basic explanation of the modeling technique is as follows: If one plots the cumulative oil production of a region (Q), versus the yearly production (P) divided by the cumulative production (P/Q), a plot can be made to extrapolate and find the ultimate recoverable reserves (URR) for the region (Qt). You can see a number of HL examples in Stuart’s essays When Does Hubbert Linearization Work? and Extrapolating World Production.

Qt and Peak Production

I am unaware of a case in which a country has completely run out of recoverable oil and had Qt verified by the HL method. However, there are plenty of examples in which a region’s production profile follows the expected path determined by the HL. There are also many examples showing that a region’s production peaked at very close to 50% of Qt. Quoting from an article by oil geologist Jeffrey Brown and “Khebab”:

With time, a HL data set starts to show a linear progression, and one can extrapolate the data down to where P is effectively zero, which gives one Qt, or ultimate recoverable reserves for the region. Based on the assumption that production tends to peak at about 50% of Qt, one can generate a predicted production profile for the region. The Lower 48 peaked at 48.5% of Qt.

Some areas have tended to peak at a higher % Qt than others. It is commonly claimed that Texas production, for example, peaked in 1972 at 57% of Qt (the reason for the qualifier will become apparent later in the essay). The fact that Texas peaked later than most regions is sometimes explained by the fact that prior to 1972 Texas was the swing producer, and production was regulated. This situation is similar to that of Saudi Arabia, so Texas is often used as an analog for predicting Saudi Arabia’s peak. So far, so good. But the astute reader may wonder “Can the value of Qt change significantly over time?” If the answer is “yes”, then the inevitable follow-up is “Then how can I be confident in using the HL to predict a peak?” I will attempt to answer these key questions by looking at the evolution of the HL for Texas over time.

Evolution of the Texas HL

I have retrieved historical Texas oil production records and modeled a series of HLs at various time periods. According to a 1956 Hubbert paper, (1) Texas had extracted approximately 4 billion barrels of oil prior to 1935. Beginning in 1935, we have annual production statistics that take us through the end of 2006. (2) Therefore, we can construct a series of HL curves. To avoid any bias on my part, I had Excel extrapolate the line and make the forecast once there was a relatively smooth trend. Let’s take a snapshot from 1960:


Figure 1. HL of Texas Oil Production Using Data Available in 1960.

As you can see, we have a nice trend. In fact, the latest 10 points are reminiscent of today’s HL of Saudi Arabia. The points have settled down and are staying pretty close to the line. So, what could we say in 1960? Qt as determined in 1960 from the intercept above is 42.5 billion barrels (Gbl). Texas crossed 50% of Qt in 1957, and by 1960 was at 56% of Qt – almost the same value as today. Surely peak was imminent. In fact, if you look at the data, Texas clearly peaked in 1956 at 1.079 MM bbl/day. By 1960, Texas was down to 892,000 bbl/day. It had undergone an annual decline of 5.5% for 4 years, and was well past 50% of Qt.

In 1960, we could have said “Texas oil production peaked in 1956, as predicted by the HL method.” But as we know, that’s not at all what happened. That would have been forecasting the peak 16 years too early. So let’s fast-forward to 1970:

Figure 2. HL of Texas Oil Production Using Data Available in 1970.

Well, that’s not very helpful. Our Texas HL in 1970 is much more muddled than in 1960. The 1956 record was broken in 1968 – twelve years after the 1960 analysis indicated a peak. We are starting to see some points rise above the line and extend Qt out further than was implied in 1960. The trend line that Excel drew is now forecasting 46.25 Gbl as our URR. That puts production in 1970 at 73% of Qt. The last 14 years had been spent well above 50% of Qt. But, the last 4 points – starting in 1967 – seem to indicate that Qt may end up being even further out than we thought. Now remember, it’s 1970. What exactly about this curve would indicate that we are 2 years from peaking?

Let’s jump forward now to 1980:


Figure 3. HL of Texas Oil Production Using Data Available in 1980.

Qt continues to grow. Excel is now forecasting Qt at 55.5 Gbl. The trend toward a higher URR is evident. The last few points imply that the forecast will grow to 57 Gbl. If so, our 1980 HL would put Texas’ 1972 peak at 63% of Qt. So, not only do we see Qt growing with time, we see that the % of Qt when the 1972 peak occurred is getting smaller. So, can we forecast the 1972 peak by 1980? No. We have already seen a case where the 1956 production record wasn’t broken for 12 years. The % Qt during that time was well over 50%. The % Qt in 1970 had climbed to 73%. Yet that still didn’t enable us to call peak. On what basis could we have done so in 1980? We have now gone through 24 years in which we could say “peak might be here.” To suggest that we could have made any other forecast at that time is wishful thinking.

So let’s skip to present day – end of 2006:

Figure 4. HL of Texas Oil Production Using Data Available in 2006.

Qt is now at 62 Gbl, but look at those last few points. They are once again pointing to a higher Qt. Some time in the 1980’s, as production continued to fall, we could have finally said “1972 was the peak.” But the % of Qt for the 1972 peak is still a moving target. Today, the 1972 peak clocks in at 58.3% of Qt – not far from the value in 1960. In 1980 it was 63% of Qt, and in 1970 it was 73% of Qt. Therefore, claims of “no examples of large producing regions showing sustained, steady increases in production past the 60% of Qt mark” are clearly wrong. Texas showed steady production increases past the 60% mark of Qt, because it reached that level in the early 1960’s. Texas even showed production increases past 70% Qt, as it reached 73% two years prior to the production peak.

Implications for Saudi

So, is Saudi like Texas in 1956, or is Saudi like Texas in 1972? Or is it like neither? The HL can’t tell us that. This essay should make clear that confidently predicting a Saudi peak on the basis of the Texas HL is nothing more than an exercise in faith-based forecasting. The only reason that the Texas HL looks as it does is because we have decades of data points following the Texas peak. But what is missed is that the HL has changed greatly from the time Texas actually peaked. So the Texas HL at its peak looked nothing like the Saudi HL of today.

It is invalid to use three decades of hindsight for refining the Texas forecast, because we clearly don’t have the same option with Saudi Arabia. Yet some argue that the Saudi peak can be forecast with confidence using the knowledge obtained from the case of Texas – a region in which the uncertainty of the method spanned almost 3 decades.

So, the HL has shown that it is good at forecasting the past, but can be very unreliable for predicting the future. In Part II, we will examine the evolution of the Saudi HL over time.

Notes

For those who may be unfamiliar with my position, this argument in no way diminishes my belief that we need to take action right now concerning oil depletion. I am merely evaluating one of the tools that is used to forecast peak, and trying to determine whether that tool can give us any precision on forecasting a peak in Saudi Arabia. My conclusion is that it can’t, but we will look at the specific case of Saudi Arabia in Part II.

I believe that by summer (barring recession) we should know one way or another, because the market looks to be undersupplied at the moment. I think Saudi will be called upon to open the taps by summer. If they can’t, look out.

References

1. Hubbert, M. King. Nuclear Energy and the Fossil Fuels. Paper presented at an American Petroleum Institute meeting in San Antonio, Texas. March 7-9, 1956 p. 10.

2. Oil Production and Well Counts in Texas 1935-2005, Railroad Commission of Texas, Accessed March 2007

March 14, 2007 Posted by | hubbert linearization, hubbert peak, Peak Oil, Saudi Arabia, texas | 9 Comments

When Will Saudi Arabian Oil Production Peak?

The eventual decline of oil production in Saudi Arabia will likely have a profound impact on all of our lives. This event will result in energy shortages around the world, and depleting oil supplies will be bid up to higher and higher levels. Poor countries will no longer be able to compete, and they will be the first casualties of oil depletion. The richer countries will bid against each other for the remaining supplies, and if the depletion rate is high enough we will be in for some very tough times. The Saudis say they have plenty of oil. However, there are a lot of skeptics.

So, I am very interested in understanding what’s going on inside Saudi Arabia. One thing is certain: Over the past year their oil production has declined. I think up until now the reasons they have given for reducing oil production – which they say is entirely voluntary – have been consistent with what the market was calling for. So, I believe that their decline over the past year has been voluntary.

Other researchers disagree. Books have been written calling into question the claims of Saudi reserves. Matt Simmon’s book Twilight in the Desert was devoted to this subject. Many people have come up with models for attempting to predict the demise of Saudi oil production. This essay, also posted to The Oil Drum, takes a close look at one popular model that is often used as evidence pointing to an imminent peak for Saudi, as well as world oil production.

In Part I, I take a look at the model by feeding it historical Texas oil production data and observing the predictions. In Part II, I will feed it historical Saudi oil production data and observe the results.

Part I – Texas Myths

Like Cindy Crawford, I have done quite a bit of modeling in my career. However, mine has been in front of a computer. There are various types of models. They can be empirical, such that you curve fit data without having a clear explanation of the underlying mechanisms. Or they can be theoretical, in which the system is modeled according to the governing scientific principles and mathematical equations.

However, one thing is critical to keep in mind. If you are going to use the model for forecasting, the model must be tested. Testing the model is called “validation”, or sometimes “back-casting.” This involves feeding the model real data, and observing how well the predictions match up with the observations. If the predictions match up on a consistent basis, and any large variations are explainable, you have the makings of a predictive model. If you have not validated your model, or if you have attempted to validate it and found that the predictions were inconsistent, the model should be used with caution (if at all). In this essay I have done some back-casts on the Hubbert Linearization (HL) model and attempted to use it to make predictions using historical data.

The background of the technique is outside the scope of this essay, but Stuart Staniford has provided details here. The HL model is a hybrid model with empirical parts and theoretical parts. Jumping past the differential equations involved, a basic explanation of the modeling technique is as follows: If one plots the cumulative oil production of a region (Q), versus the yearly production (P) divided by the cumulative production (P/Q), a plot can be made to extrapolate and find the ultimate recoverable reserves (URR) for the region (Qt). You can see a number of HL examples in Stuart’s essays When Does Hubbert Linearization Work? and Extrapolating World Production.

Qt and Peak Production

I am unaware of a case in which a country has completely run out of recoverable oil and had Qt verified by the HL method. However, there are plenty of examples in which a region’s production profile follows the expected path determined by the HL. There are also many examples showing that a region’s production peaked at very close to 50% of Qt. Quoting from an article by oil geologist Jeffrey Brown and “Khebab”:

With time, a HL data set starts to show a linear progression, and one can extrapolate the data down to where P is effectively zero, which gives one Qt, or ultimate recoverable reserves for the region. Based on the assumption that production tends to peak at about 50% of Qt, one can generate a predicted production profile for the region. The Lower 48 peaked at 48.5% of Qt.

Some areas have tended to peak at a higher % Qt than others. It is commonly claimed that Texas production, for example, peaked in 1972 at 57% of Qt (the reason for the qualifier will become apparent later in the essay). The fact that Texas peaked later than most regions is sometimes explained by the fact that prior to 1972 Texas was the swing producer, and production was regulated. This situation is similar to that of Saudi Arabia, so Texas is often used as an analog for predicting Saudi Arabia’s peak. So far, so good. But the astute reader may wonder “Can the value of Qt change significantly over time?” If the answer is “yes”, then the inevitable follow-up is “Then how can I be confident in using the HL to predict a peak?” I will attempt to answer these key questions by looking at the evolution of the HL for Texas over time.

Evolution of the Texas HL

I have retrieved historical Texas oil production records and modeled a series of HLs at various time periods. According to a 1956 Hubbert paper, (1) Texas had extracted approximately 4 billion barrels of oil prior to 1935. Beginning in 1935, we have annual production statistics that take us through the end of 2006. (2) Therefore, we can construct a series of HL curves. To avoid any bias on my part, I had Excel extrapolate the line and make the forecast once there was a relatively smooth trend. Let’s take a snapshot from 1960:


Figure 1. HL of Texas Oil Production Using Data Available in 1960.

As you can see, we have a nice trend. In fact, the latest 10 points are reminiscent of today’s HL of Saudi Arabia. The points have settled down and are staying pretty close to the line. So, what could we say in 1960? Qt as determined in 1960 from the intercept above is 42.5 billion barrels (Gbl). Texas crossed 50% of Qt in 1957, and by 1960 was at 56% of Qt – almost the same value as today. Surely peak was imminent. In fact, if you look at the data, Texas clearly peaked in 1956 at 1.079 MM bbl/day. By 1960, Texas was down to 892,000 bbl/day. It had undergone an annual decline of 5.5% for 4 years, and was well past 50% of Qt.

In 1960, we could have said “Texas oil production peaked in 1956, as predicted by the HL method.” But as we know, that’s not at all what happened. That would have been forecasting the peak 16 years too early. So let’s fast-forward to 1970:

Figure 2. HL of Texas Oil Production Using Data Available in 1970.

Well, that’s not very helpful. Our Texas HL in 1970 is much more muddled than in 1960. The 1956 record was broken in 1968 – twelve years after the 1960 analysis indicated a peak. We are starting to see some points rise above the line and extend Qt out further than was implied in 1960. The trend line that Excel drew is now forecasting 46.25 Gbl as our URR. That puts production in 1970 at 73% of Qt. The last 14 years had been spent well above 50% of Qt. But, the last 4 points – starting in 1967 – seem to indicate that Qt may end up being even further out than we thought. Now remember, it’s 1970. What exactly about this curve would indicate that we are 2 years from peaking?

Let’s jump forward now to 1980:


Figure 3. HL of Texas Oil Production Using Data Available in 1980.

Qt continues to grow. Excel is now forecasting Qt at 55.5 Gbl. The trend toward a higher URR is evident. The last few points imply that the forecast will grow to 57 Gbl. If so, our 1980 HL would put Texas’ 1972 peak at 63% of Qt. So, not only do we see Qt growing with time, we see that the % of Qt when the 1972 peak occurred is getting smaller. So, can we forecast the 1972 peak by 1980? No. We have already seen a case where the 1956 production record wasn’t broken for 12 years. The % Qt during that time was well over 50%. The % Qt in 1970 had climbed to 73%. Yet that still didn’t enable us to call peak. On what basis could we have done so in 1980? We have now gone through 24 years in which we could say “peak might be here.” To suggest that we could have made any other forecast at that time is wishful thinking.

So let’s skip to present day – end of 2006:

Figure 4. HL of Texas Oil Production Using Data Available in 2006.

Qt is now at 62 Gbl, but look at those last few points. They are once again pointing to a higher Qt. Some time in the 1980’s, as production continued to fall, we could have finally said “1972 was the peak.” But the % of Qt for the 1972 peak is still a moving target. Today, the 1972 peak clocks in at 58.3% of Qt – not far from the value in 1960. In 1980 it was 63% of Qt, and in 1970 it was 73% of Qt. Therefore, claims of “no examples of large producing regions showing sustained, steady increases in production past the 60% of Qt mark” are clearly wrong. Texas showed steady production increases past the 60% mark of Qt, because it reached that level in the early 1960’s. Texas even showed production increases past 70% Qt, as it reached 73% two years prior to the production peak.

Implications for Saudi

So, is Saudi like Texas in 1956, or is Saudi like Texas in 1972? Or is it like neither? The HL can’t tell us that. This essay should make clear that confidently predicting a Saudi peak on the basis of the Texas HL is nothing more than an exercise in faith-based forecasting. The only reason that the Texas HL looks as it does is because we have decades of data points following the Texas peak. But what is missed is that the HL has changed greatly from the time Texas actually peaked. So the Texas HL at its peak looked nothing like the Saudi HL of today.

It is invalid to use three decades of hindsight for refining the Texas forecast, because we clearly don’t have the same option with Saudi Arabia. Yet some argue that the Saudi peak can be forecast with confidence using the knowledge obtained from the case of Texas – a region in which the uncertainty of the method spanned almost 3 decades.

So, the HL has shown that it is good at forecasting the past, but can be very unreliable for predicting the future. In Part II, we will examine the evolution of the Saudi HL over time.

Notes

For those who may be unfamiliar with my position, this argument in no way diminishes my belief that we need to take action right now concerning oil depletion. I am merely evaluating one of the tools that is used to forecast peak, and trying to determine whether that tool can give us any precision on forecasting a peak in Saudi Arabia. My conclusion is that it can’t, but we will look at the specific case of Saudi Arabia in Part II.

I believe that by summer (barring recession) we should know one way or another, because the market looks to be undersupplied at the moment. I think Saudi will be called upon to open the taps by summer. If they can’t, look out.

References

1. Hubbert, M. King. Nuclear Energy and the Fossil Fuels. Paper presented at an American Petroleum Institute meeting in San Antonio, Texas. March 7-9, 1956 p. 10.

2. Oil Production and Well Counts in Texas 1935-2005, Railroad Commission of Texas, Accessed March 2007

March 14, 2007 Posted by | hubbert linearization, hubbert peak, Peak Oil, Saudi Arabia, texas | Comments Off on When Will Saudi Arabian Oil Production Peak?

When Will Saudi Arabian Oil Production Peak?

The eventual decline of oil production in Saudi Arabia will likely have a profound impact on all of our lives. This event will result in energy shortages around the world, and depleting oil supplies will be bid up to higher and higher levels. Poor countries will no longer be able to compete, and they will be the first casualties of oil depletion. The richer countries will bid against each other for the remaining supplies, and if the depletion rate is high enough we will be in for some very tough times. The Saudis say they have plenty of oil. However, there are a lot of skeptics.

So, I am very interested in understanding what’s going on inside Saudi Arabia. One thing is certain: Over the past year their oil production has declined. I think up until now the reasons they have given for reducing oil production – which they say is entirely voluntary – have been consistent with what the market was calling for. So, I believe that their decline over the past year has been voluntary.

Other researchers disagree. Books have been written calling into question the claims of Saudi reserves. Matt Simmon’s book Twilight in the Desert was devoted to this subject. Many people have come up with models for attempting to predict the demise of Saudi oil production. This essay, also posted to The Oil Drum, takes a close look at one popular model that is often used as evidence pointing to an imminent peak for Saudi, as well as world oil production.

In Part I, I take a look at the model by feeding it historical Texas oil production data and observing the predictions. In Part II, I will feed it historical Saudi oil production data and observe the results.

Part I – Texas Myths

Like Cindy Crawford, I have done quite a bit of modeling in my career. However, mine has been in front of a computer. There are various types of models. They can be empirical, such that you curve fit data without having a clear explanation of the underlying mechanisms. Or they can be theoretical, in which the system is modeled according to the governing scientific principles and mathematical equations.

However, one thing is critical to keep in mind. If you are going to use the model for forecasting, the model must be tested. Testing the model is called “validation”, or sometimes “back-casting.” This involves feeding the model real data, and observing how well the predictions match up with the observations. If the predictions match up on a consistent basis, and any large variations are explainable, you have the makings of a predictive model. If you have not validated your model, or if you have attempted to validate it and found that the predictions were inconsistent, the model should be used with caution (if at all). In this essay I have done some back-casts on the Hubbert Linearization (HL) model and attempted to use it to make predictions using historical data.

The background of the technique is outside the scope of this essay, but Stuart Staniford has provided details here. The HL model is a hybrid model with empirical parts and theoretical parts. Jumping past the differential equations involved, a basic explanation of the modeling technique is as follows: If one plots the cumulative oil production of a region (Q), versus the yearly production (P) divided by the cumulative production (P/Q), a plot can be made to extrapolate and find the ultimate recoverable reserves (URR) for the region (Qt). You can see a number of HL examples in Stuart’s essays When Does Hubbert Linearization Work? and Extrapolating World Production.

Qt and Peak Production

I am unaware of a case in which a country has completely run out of recoverable oil and had Qt verified by the HL method. However, there are plenty of examples in which a region’s production profile follows the expected path determined by the HL. There are also many examples showing that a region’s production peaked at very close to 50% of Qt. Quoting from an article by oil geologist Jeffrey Brown and “Khebab”:

With time, a HL data set starts to show a linear progression, and one can extrapolate the data down to where P is effectively zero, which gives one Qt, or ultimate recoverable reserves for the region. Based on the assumption that production tends to peak at about 50% of Qt, one can generate a predicted production profile for the region. The Lower 48 peaked at 48.5% of Qt.

Some areas have tended to peak at a higher % Qt than others. It is commonly claimed that Texas production, for example, peaked in 1972 at 57% of Qt (the reason for the qualifier will become apparent later in the essay). The fact that Texas peaked later than most regions is sometimes explained by the fact that prior to 1972 Texas was the swing producer, and production was regulated. This situation is similar to that of Saudi Arabia, so Texas is often used as an analog for predicting Saudi Arabia’s peak. So far, so good. But the astute reader may wonder “Can the value of Qt change significantly over time?” If the answer is “yes”, then the inevitable follow-up is “Then how can I be confident in using the HL to predict a peak?” I will attempt to answer these key questions by looking at the evolution of the HL for Texas over time.

Evolution of the Texas HL

I have retrieved historical Texas oil production records and modeled a series of HLs at various time periods. According to a 1956 Hubbert paper, (1) Texas had extracted approximately 4 billion barrels of oil prior to 1935. Beginning in 1935, we have annual production statistics that take us through the end of 2006. (2) Therefore, we can construct a series of HL curves. To avoid any bias on my part, I had Excel extrapolate the line and make the forecast once there was a relatively smooth trend. Let’s take a snapshot from 1960:


Figure 1. HL of Texas Oil Production Using Data Available in 1960.

As you can see, we have a nice trend. In fact, the latest 10 points are reminiscent of today’s HL of Saudi Arabia. The points have settled down and are staying pretty close to the line. So, what could we say in 1960? Qt as determined in 1960 from the intercept above is 42.5 billion barrels (Gbl). Texas crossed 50% of Qt in 1957, and by 1960 was at 56% of Qt – almost the same value as today. Surely peak was imminent. In fact, if you look at the data, Texas clearly peaked in 1956 at 1.079 MM bbl/day. By 1960, Texas was down to 892,000 bbl/day. It had undergone an annual decline of 5.5% for 4 years, and was well past 50% of Qt.

In 1960, we could have said “Texas oil production peaked in 1956, as predicted by the HL method.” But as we know, that’s not at all what happened. That would have been forecasting the peak 16 years too early. So let’s fast-forward to 1970:

Figure 2. HL of Texas Oil Production Using Data Available in 1970.

Well, that’s not very helpful. Our Texas HL in 1970 is much more muddled than in 1960. The 1956 record was broken in 1968 – twelve years after the 1960 analysis indicated a peak. We are starting to see some points rise above the line and extend Qt out further than was implied in 1960. The trend line that Excel drew is now forecasting 46.25 Gbl as our URR. That puts production in 1970 at 73% of Qt. The last 14 years had been spent well above 50% of Qt. But, the last 4 points – starting in 1967 – seem to indicate that Qt may end up being even further out than we thought. Now remember, it’s 1970. What exactly about this curve would indicate that we are 2 years from peaking?

Let’s jump forward now to 1980:


Figure 3. HL of Texas Oil Production Using Data Available in 1980.

Qt continues to grow. Excel is now forecasting Qt at 55.5 Gbl. The trend toward a higher URR is evident. The last few points imply that the forecast will grow to 57 Gbl. If so, our 1980 HL would put Texas’ 1972 peak at 63% of Qt. So, not only do we see Qt growing with time, we see that the % of Qt when the 1972 peak occurred is getting smaller. So, can we forecast the 1972 peak by 1980? No. We have already seen a case where the 1956 production record wasn’t broken for 12 years. The % Qt during that time was well over 50%. The % Qt in 1970 had climbed to 73%. Yet that still didn’t enable us to call peak. On what basis could we have done so in 1980? We have now gone through 24 years in which we could say “peak might be here.” To suggest that we could have made any other forecast at that time is wishful thinking.

So let’s skip to present day – end of 2006:

Figure 4. HL of Texas Oil Production Using Data Available in 2006.

Qt is now at 62 Gbl, but look at those last few points. They are once again pointing to a higher Qt. Some time in the 1980’s, as production continued to fall, we could have finally said “1972 was the peak.” But the % of Qt for the 1972 peak is still a moving target. Today, the 1972 peak clocks in at 58.3% of Qt – not far from the value in 1960. In 1980 it was 63% of Qt, and in 1970 it was 73% of Qt. Therefore, claims of “no examples of large producing regions showing sustained, steady increases in production past the 60% of Qt mark” are clearly wrong. Texas showed steady production increases past the 60% mark of Qt, because it reached that level in the early 1960’s. Texas even showed production increases past 70% Qt, as it reached 73% two years prior to the production peak.

Implications for Saudi

So, is Saudi like Texas in 1956, or is Saudi like Texas in 1972? Or is it like neither? The HL can’t tell us that. This essay should make clear that confidently predicting a Saudi peak on the basis of the Texas HL is nothing more than an exercise in faith-based forecasting. The only reason that the Texas HL looks as it does is because we have decades of data points following the Texas peak. But what is missed is that the HL has changed greatly from the time Texas actually peaked. So the Texas HL at its peak looked nothing like the Saudi HL of today.

It is invalid to use three decades of hindsight for refining the Texas forecast, because we clearly don’t have the same option with Saudi Arabia. Yet some argue that the Saudi peak can be forecast with confidence using the knowledge obtained from the case of Texas – a region in which the uncertainty of the method spanned almost 3 decades.

So, the HL has shown that it is good at forecasting the past, but can be very unreliable for predicting the future. In Part II, we will examine the evolution of the Saudi HL over time.

Notes

For those who may be unfamiliar with my position, this argument in no way diminishes my belief that we need to take action right now concerning oil depletion. I am merely evaluating one of the tools that is used to forecast peak, and trying to determine whether that tool can give us any precision on forecasting a peak in Saudi Arabia. My conclusion is that it can’t, but we will look at the specific case of Saudi Arabia in Part II.

I believe that by summer (barring recession) we should know one way or another, because the market looks to be undersupplied at the moment. I think Saudi will be called upon to open the taps by summer. If they can’t, look out.

References

1. Hubbert, M. King. Nuclear Energy and the Fossil Fuels. Paper presented at an American Petroleum Institute meeting in San Antonio, Texas. March 7-9, 1956 p. 10.

2. Oil Production and Well Counts in Texas 1935-2005, Railroad Commission of Texas, Accessed March 2007

March 14, 2007 Posted by | hubbert linearization, hubbert peak, Peak Oil, Saudi Arabia, texas | 4 Comments