See here: http://www.eia.doe.gov/steo
213 karma · joined September 12, 2007
The first such oil crisis occurred in the 1859. Before the first U.S. oil well was drilled in Pennsylvania in 1859, petroleum supplies were limited to crude oil that oozed to the surface. An 1859 advertisement for Kier’s Rock Oil advised consumers to “hurry, before this wonderful product is depleted from Nature’s laboratory.”
In 1874, the state geologist of Pennsylvania, the United States leading oil-producing state and the location of the world's first commercial oil well, estimated that only enough oil remained to keep the nation’s kerosene lamps burning for four years.
Seven such "peak oil" shortage scares occurred before 1950.
These periodic "peak oil" crises lead to short-term spikes in the spot prices for crude.
As a consequence, the capital markets flood the oil and gas business with capital to develop high-cost reserves that had been considered uneconomic. The vast inflows of capital into the Athabasca oil sands in Canada are an example of this.
If this "peak oil crisis" coincides with an era of cheap capital, the inflows of capital into industries that are perceived to be either compliments (oil sands, oil shale) and/or substitutes for crude oil (wind, solar, biofuels) can be extremely large.
Inevitably, this overallocation of capital leads to: (1) vast new discoveries of hydrocarbons, and (2) the invention of new technologies to economically develop those reserves.
Because the oil and gas industry is opaque in terms of information flows, it takes several years for news of these developments to recycle back into the capital markets.
In point of fact it was not until 2007-2008 that news began to percolate about the vast shale gas discoveries in the United States -- even though the first such monster wells had been drilled in 2000-2001.
States such as Pennsylvania, where oil and gas records are not made publicly available for a 5-year "grace" period, exacerbate this problem. In contrast, most states post updates on new oil and gas wells on a daily basis.
New investments in oil and gas technology can even turn around mature basins that had been considered to be past their peak production.
For example, according to the United States EIA (see here: http://www.eia.doe.gov/steo and here: http://www.eia.doe.gov/emeu/steo/pub/gifs/Fig12.gif), U.S. crude oil production increased this year to 5.24 million BOE (barrels of oil equivalent) per day -- the first annual increase since 1991.
The net effect is that supply vastly overshoots demand. There is a delayed recognition that the increase in the industry-average R/P ratio (the ratio of reserves-in-the-ground to production-per-year) no longer justifies continued investment.
As a result, crude oil prices crash. Those ventures into higher-cost technologies that had been launched with the presumption of hindsight that a new era of permanently higher oil prices had dawned, are deemed uneconomic. Examples include: oil sands, oil shale, photovoltaic utility-scale power plants, biofuels, wind energy.
Capital flees the market.
As the global economy continues to grow and capital remains unallocated to E&P of hydrocarbons (Exploration and production), the industry-average R/P ratio begins to slowly contract. New technologies that could be used to discover and produce untapped hydrocarbon reserves (Methane Hydrates, in the US Gulf of Mexico, for instance) remain undeveloped.
The energy industry refocuses on decreasing costs, instead of increasing supply.
After another 25 years, the cycle repeats.
(There are of-course short-term supply shocks that can occur for geopolitical reasons, such as wars, climate change legislation, nationalization of mineral rights, armed piracy on ocean shipping lanes, etc...)
In view of this history, presupposing a impeding permanent shortfall in global hydrocarbon supplies is akin to prognosticating the end-of-the road for Moore's Law and a subsequent end to the IT industry.
What happens at night?
What happens when its cloudy?
What happens during the winter-time?
Does Nanosolar’s $1 per watt investment guarantee a consistent 24/7/365 source of electricity?
Does Nanosolar’s $1 figure include the cost of installing transmission lines?
Does Nanosolar’s $1 figure include the cost laying cement for a power plant, assembling the cells into solar panels, installing the panels, and commissioning the power plant?
Does Nanosolar’s $1 figure include the cost of building base-load generating capacity to provide electricity for when the sun doesn’t shine?
Installing electrical transmission lines costs about $1 million per mile. Most PV power plants are located far away from demand centers.
This sounds like vaporware.
This is precisely the problem with the Obama administration's plan for a "green energy" future -- trying to shoehorn high-cost intermittent power sources into low-cost high-reliability applications.
Nanosolar is ignoring what solar sells are good for.
Photovolatics have traditionally enjoyed a niche market in applications where cost is not a factor, where weight is at a premium, where there are no other power sources, and where frequent fuel delivery is not an option -- orbital telecommunications satellite solar panels, remote radio transmission towers, offshore oil and gas platforms, mobile power sources for forward-deployed military units, etc...
Utility scale power generation is extremely cost-sensitive, demands high-reliability, has no weight constraints, and has no constraints on mobility and/or fuel delivery -- the exact opposite of applications in which photovolatics make sense.
Nanosolar's emphasis on cost-per-watt suggests that their target market is utility-scale power generation -- a dubious proposition at best, considering the cost and reliability problems with renewable energy sources.
Marc Andreesen has famously argued that the number one job of a startup is to achieve product-market fit.
Nanosolar, like most renewable energy companies, has a product which they are trying to force unto a market that does not want it.
That's the trouble with government subsidies -- they allow people to operate outside the constraints of reality. At taxpayer expense.
"Clean Tech" is one giant taxpayer-funded ponzi scheme.
Madoff would be proud.
and
The Big Rich: The Rise and Fall of the Greatest Texas Oil Fortunes
We are currently learning how to develop and consume natural gas, a so-called 3rd-generation hydrocarbon, with a carbon-to-hydrogen ratio of 1-to-4. Natural gas was considered a waste product well into the 20th century.
You have to take into account the fact that there are entire classes of hydrocarbons which human civilization has not yet attempted to develop.
For example, just this past week, the US DOE published an article in Science announcing the discovery of large methane hydrate deposits in the Gulf of Mexico.
With these 'unconventional' plays, the production is front-loaded. For instance, many Haynesville shale natural gas wells will produce as much gas in their first 6 months of life as they will over the next 20 years.
The same goes for the Bakken tight-oil play in Montana.
The 'rate of extraction' in unconventional oil and gas plays is extremely front-loaded. Which is why you see such large location basis price differential around these plays.
In other words, the United States is producing so much natural gas that we're running out of pipelines, storage facilities, and power plants to consume it all.
There is so much natural gas in the United States that the US should be a net energy exporter.
However, the federal government has not approved a single permit for a natgas export terminals in over 40 years.
Import terminals get approval on a regular basis, however.
Meanwhile, we're complaining about our dependence on foreign oil and subsidizing windmills.
Genius.
When laypeople who don't know the first thing about the hydrocarbons industry start talking about "peak oil", they come off sounding as stupid as when former senator Ted Stevens described the internet as a "series of tubes" that can get clogged up.
The world has sufficient hydrocarbons to last hundreds and hundreds and hundreds of years. And there is no limit to human ingenuity in inventing new technology to economically produce those resources. Any nation, company, or individual that bets on 'peak oil' is doing so on an ideological basis and is going to loose big. Having people who have never set foot on a drill rig babbling on about 'peak oil' is tantamount to someone who doesn't understand computing betting against Moore's Law.
For example: The combination of swell packers for multi-stage fracture stimulation of multi-lateral wells in tight oil and shale gas resource plays, coupled with multi-azimuth 3D seismic for detecting naturally occurring fracture networks,and microseismic for frac job design has completely revolutionized the US hydrocarbons business in the past few years. These are new technologies applied to produce oil and gas resources that used to be considered uneconomic.
Every now and then you hear some talking head warning about how Moore's Law is about to stop scaling. Meanwhile, Intel keeps adding new process technologies to their roadmap. Does the semiconductor industry have the technology in 2009 to build some of these fab's? No. Will the industry invent the technology to build that fab? Yes. It's the same thing with hydrocarbons.
BTW, a lot of the advances in semiconductor process technology are being used to discover new reserves of hydrocarbons. For example, one of the leading applications of NVIDIA's gp-gpu technology is for 3D-Seismic oil and gas exploration.
For instance, checkout some of the demos of Marti Hearst's research into faceted search at Berkeley: http://flamenco.berkeley.edu/demos.html
Be sure that you can obtain a trademark for your name from the U.S. Patent and Trademark Office (uspto.gov).
Be aware of the "gotchas" in what are considered acceptable trademarks.
For instance, under U.S. law, a "geographically (mis)-descriptive" trade name is often very difficult to trademark.
Furthermore, trademarks are often not addressed by OSI-approved open-source licenses (The GPL, for example). Therefore, obtaining a trademark for your open-source project can be a very effective way of de-comoditizing your open source project, achieving containment of forks, and building a revenue-generating business around your code base. Example: Red Hat vs Centos.
Own your namespace.
Used for identifying infill drilling locations.
Updated daily with new well locations.
Working on adding Canada, shale plays, and Gulf of Mexico offshore wells.
Using Memcached on Amazon EC2 + openlayers + Google WGS84 tiles.
"When attractive profits disappear at one stage in the value chain because a product becomes modular and commoditized, the opportunity to earn attractive profits with proprietary products will usually emerge at an adjacent stage. That is, the location in the value chain where attractive profits can be earned shifts in a predictable way over time."
Companies make attractive money when they solve the hardest problems.
Read his book, "Seeing What's Next"
Also: http://eser.org/oil-and-gas/The_law_of_conservation_of_attra...
Just because it's true that many internet businesses have become modular, commoditized, and marginally profitable, does not mean that there is a shortage of difficult and highly valuable problems to solve.
The companies the author listed are "component manufacturers". Future profits will be created by combining those components in creative ways to solve new problems.
Quoting Economist Paul Romer: “Economic growth occurs whenever people take resources and rearrange them in ways that are more valuable." see: http://eser.org/oil-and-gas/Eser_Corporation%27s_Business_Ph...
Where, NCAV (Net Current Asset Value) = Current Assets - TOTAL Liabilities.
Note that Graham calculated NCAV using total liabilities, and not just current liabilities. By using only current assets he also excluded plant and equipment, and goodwill in his calculation of NCAV. This is important, because during liquidation all creditors will demand repayment, but the valuation of plant and equipment will be impaired.
The 66% discount to NCAV provided Graham a "margin of safety".
The modern-day equivalent of NCAV is "book to tangible book value". What you want is equities that have a "book to tanglible book" ratio less than 1, a debt-to-total-equity ratio of less than 1, a price-to-earnings ratio that is competitive with peers in its sector, and a "book-to-total-free-cash-flow' ratio in the low single digits.
See ExxonMobil, for instance.
You can find all of these valuation ratios on the Reuters website.
So, the further down the list you go, the lower the rank is -- the less "similar" the links get.
We actually compute a numerical "similarity score" for each link. Perhaps we should show it?
Thanks for trying it out!
It should probably take about a week to see an improvement -- we don't want to sacrifice recall or precision to improve performance.
So, we're going to try to have our cake and eat it, too.
Based on your feedback, we've made some major changes to improve recall. Specifically, we've begun to include data from our web-crawler.
We've also started to prune many of the similarity-search results in order to improve precision.
Finally, we cleaned-up the UI to make it more clear what the website does. I think that we still have some work to do in this area, however.
Unfortunately, many of the changes we've made to the algorithm have _dramatically_ slowed down performance. Most searches now take over a minute to complete!
We're hard at work on fixing that, though. Specifically, we're playing around with implementing multi-level counting bloom filters, count-min flajolet-martin sketches, and quntile fm digests.
We should have some major performance improvements up over the next few days.
We're also looking at launching a pre-alpha of a stand-alone software package that implements the ESer algorithm so that people can run similarity-searches on their own private data sets.
Please comment with your feedback.
Thanks again!
PLSI tends to perform very well on more specific queries, such as "Paul Graham", "silicon graphics", etc...
The problem with PLSI is that it is extremely computationally expensive -- which is why most internet-scale search engines don't use it.
Our innovation was figuring out some tricks that have allowed us to improve performance dramatically. However, there is obviously still room for improvement.
Our goal is to satisfy 80% of the queries with decent results -- and to leave the other 20% (square, etc...) to someone else.
The interesting thing about PLSI is that it's able to rank documents from the text alone -- ignoring the link structure and other metadata.
Therefore, we're thinking our algorithm will make the most sense in situations where there is lots of textual data without web-like link metadata.
The two scenarios that come to mind where people need to text-mine documents outside the metadata-rich web are: (1) windows file shares on corporate intranets (2) large volumes of legal documents inside law firms
Text-mining wikipedia is a proof-of-concept at this point
I'm trying to think of a way to make the functionality of the shapes more obvious.
Currently, we're limited to running on one server. Therefore, the algorithm is restricted to running on the english Wikipedia corpus.
It appears that the "skip slope" metaphor with the shapes was a bad idea.
Each shape is a ski-slope difficulty rating symbol. So, Green -- "easy" -- will take the meaning of your query more literally. Double black diamond -- "advanced expert" -- will try to extrapolate hidden meanings in your query. It will suggest topics that are less obviously related to your query.
At this point we're really constrained by the number of cores we're running on.
Once we can get a hold of some more servers, we should be able to drastically improve the performance and prune many of the results.
We'd also like to run the algorithm on additional corpora. Specifically: (1) the US patent database (back to 1975); and (2), a collection of United States federal and state case law (the JURIS database).
Re: performance - It's mining through ~40gb of data on server with 8gb of ram. - Also, we're not using caching of search results -- it computes on-the-fly for each query. - If we can get a hold of more servers, we should be able to bring down the query time below 1 second.
Re: query "Test" - You have to search for something you're interested in.
There's a lot of room for improvement: optimizing for speed and pruning down the results are at the top of our "TODO" list.
Also, the UI is simplistic -- that's because we've been spending 99% of our time working on the algorithm in matlab.
But, we wanted to get something out -- warts and all -- to get some feedback on the general idea.
We'd value any feedback -- positive or negative.
ESER
* My web-browser of choice is Lynx :-)
Unfortunately, I'm more of a low-level kernel hacker and math geek (machine learning algorithms, cluster file systems, robotics, etc..) than I am a UI person.
Which is a _major_ problem since the first thing people see is the UI.
And since I wrote my own web server and database, it wasn't really possible to use an off-the-shelf pretty-looking CMS.
So, my current project is a web-based satistical datamining system. And the UI is ... a text box. Which means it will be more difficult for me to f-up the UI. Although, I still might manage to do that.