I just read NYTimes article about the discussion to use underground nuclear explosion to seal the oil leak in the Gulf of Mexico http://www.nytimes.com/2010/06/03/us/03nuke.html?hp. The idea may sound crazy, but experiments were conducted in 1970s in the USSR. The places are called Lira and Azgir nuclear testing sites in Western Kazakhstan, you can read more on http://www.nnc.kz/en/about/activity/radioecology.html .
Kazakhstan's National Nuclear Center continues environmental monitoring of the sites. I am not an expert in this field, but from what I understand an underground nuclear explosion creates a sealed cavity that serves as a container, which keeps natural gas and condensate form leaking into the ground. I have thought about this project when InnoCentive announced its "Emergency Response 2.0 : Solutions to Respond to Oil Spill in the Gulf of Mexico" on https://gw.innocentive.com/ar/challenge/overview/9383447 .
At that time I thought it could be nearly impossible to place a nuclear device 1 km deep into the water and further into the seabed. But I guess, some of the scientists that were involved with the project decided to give the idea a shot, literally. I knew that both underwater and underground tests were routinely done in the past (see http://alturl.com/v7x6 ), but combining two in one could be a real challenge.
I agree with NYTimes that such risky idea is cannot be seriously considered. However, as crazy as the idea sounds, the fact that it got front page coverage in NYTimes (!!!"...What about nuking the well?") suggests that both BP and the Federal government are running out of serious options. Or perhaps, public opinion is being prepared for an option that includes conventional explosion to stop the spill, which looks much more acceptable vis-a-vie a nuclear option.
Here is an abstract from the paper called Reduction of Risks from Lira Underground Nuclear Facilities at Karachaganak Oil-and-Gas Complex published by National Nuclear Center researchers in 2008:
"T. I. Ageyeva2, A. Zh. Tuleushev2 and V. V. Podenezhko2
(2) Institute of Nuclear Physics, Almaty, Kazakhstan
The theme of this article is the investigations of radioactive contamination within and around underground cavities created by underground nuclear detonations performed in connection with the operation of oil and gas condensate fields. Underground storages of gas condensate are not maintained for a long time. The results from the large-scale complex indicate the absence of a real threat from nuclear objects on the environment. However, there is a potential danger connected with possible changes in the geological environment containing the underground storages of condensates. The pressure created in the cavities is the controlling parameter of the conditions in the cavities. Laboratory investigations of a condensate from the underground cavities confirm the absence of caesium-137 and strontium-90 and the presence of tritium. The strategy of closing off the cavities with the application of filling the cavity space with loose or helium materials is designed. The basic objective of the subsequent works is to decrease the environmental risks associated with oil-and-gas operations and underground storage of condensates.
Keywords cavities - underground nuclear detonations - condensate storage - LIRA - Kazakhstan"
Source: http://www.springerlink.com/content/r3w0jgvmx87tv332/
Showing posts with label Oil spill. Show all posts
Showing posts with label Oil spill. Show all posts
Wednesday, June 2, 2010
Tuesday, June 1, 2010
Realpolitik of the Blame Game
After BP’s numerous failed attempts to stop oil contamination in the Gulf of Mexico its corporate image is in ruins. As BP’s public image reached its saturation limits for criticism, the political debate redirects public attention from the oil company to the Federal government. With the accident rolling into its sixth week, the Obama administration is forced to answer “Who is to blame?” and “What to do?” In short, political pressure and public anger demand swift satisfaction.
In this respect, Obama's decision to begin criminal investigations into the Deepwater Horizon explosion and the oil spill may give such satisfaction. Unfortunately, it is short-lived and may prove counterproductive in the long-run. Criminal inquiries into the cause of the oil spill is likely to narrow down the scope of post-mortem analysis to near physical and temporal proximity of the accident. In other words, the investigation will focus on people who made decisions as the accident emerged.
After the Exxon Valdes accident, the public was given a scapegoat, Capitan Hazelwood, who was singlehandedly blamed to cause the accident. Although, he was later cleared of the charge being drunk at the time of the accident, he had never cleared his name from the stigma of causing of the biggest oil spill in US history (until current accident). There were more systemic problems such as functional and interoperable navigation systems on board the ship and on the shore of Alaska, the culture of tolerance to safety problems among the oil executives and public official, etc. However, systemic factors tend to “spread the blame” and lack the luxury of targeted blame, thus satisfaction of punishment. Simple and straightforward causes are always easier to describe and accept. I hope to be wrong, but it is likely that we can expect several Capitan Hazelwoods from BP and its subcontractors who could be “scarified” to satisfy public outcry. However, it is unlikely that such narrow view can help us understand the complexity of the accident.
It is in our human nature to go back in time and look for a single event, which could have prevented to the catastrophe from happening. The bigger the accident, the stronger is our temptation to reverse time. Inability to reverse the situation results in anger, dissatisfaction and need for revenge. These emotions have to be channeled one way or the other. What make the case with the oil spill unique is the fact that the public is given a rare opportunity to be part of the accident as it emerges. The public feels helpless to reverse time and to contain the accident. Old and new media channels enables people to get first-hand accounts of the environmental impact on the ocean's seabed, the coast and wildlife. As the result, it is natural for people to ask who is in charge and who is to blame. If those who are in charge do not act swiftly and find those who are to blame, the public could blame those who are in charge. If those who were in charge yesterday do not blame those who are in charge today, then those who were in charge yesterday are to get blamed themselves and vice versa. The same is true with BP and its numerous subcontractors.
Unfortunately realpolitik of the blame game creates an environment in which each player is concerned with own political and legal liabilities. Criminal inquiry adds more gasoline to the flame. Starting the investigation before accident’s containment is almost like investigating causes of an air crash with airplane still in the air. Perhaps, such approach could give unique perspective, but more likely it will downgrade itself to simplified description of immediate events with operators and decision makers who were unfortunate enough to be in close proximity as the accident emerged.
In this respect, Obama's decision to begin criminal investigations into the Deepwater Horizon explosion and the oil spill may give such satisfaction. Unfortunately, it is short-lived and may prove counterproductive in the long-run. Criminal inquiries into the cause of the oil spill is likely to narrow down the scope of post-mortem analysis to near physical and temporal proximity of the accident. In other words, the investigation will focus on people who made decisions as the accident emerged.
After the Exxon Valdes accident, the public was given a scapegoat, Capitan Hazelwood, who was singlehandedly blamed to cause the accident. Although, he was later cleared of the charge being drunk at the time of the accident, he had never cleared his name from the stigma of causing of the biggest oil spill in US history (until current accident). There were more systemic problems such as functional and interoperable navigation systems on board the ship and on the shore of Alaska, the culture of tolerance to safety problems among the oil executives and public official, etc. However, systemic factors tend to “spread the blame” and lack the luxury of targeted blame, thus satisfaction of punishment. Simple and straightforward causes are always easier to describe and accept. I hope to be wrong, but it is likely that we can expect several Capitan Hazelwoods from BP and its subcontractors who could be “scarified” to satisfy public outcry. However, it is unlikely that such narrow view can help us understand the complexity of the accident.
It is in our human nature to go back in time and look for a single event, which could have prevented to the catastrophe from happening. The bigger the accident, the stronger is our temptation to reverse time. Inability to reverse the situation results in anger, dissatisfaction and need for revenge. These emotions have to be channeled one way or the other. What make the case with the oil spill unique is the fact that the public is given a rare opportunity to be part of the accident as it emerges. The public feels helpless to reverse time and to contain the accident. Old and new media channels enables people to get first-hand accounts of the environmental impact on the ocean's seabed, the coast and wildlife. As the result, it is natural for people to ask who is in charge and who is to blame. If those who are in charge do not act swiftly and find those who are to blame, the public could blame those who are in charge. If those who were in charge yesterday do not blame those who are in charge today, then those who were in charge yesterday are to get blamed themselves and vice versa. The same is true with BP and its numerous subcontractors.
Unfortunately realpolitik of the blame game creates an environment in which each player is concerned with own political and legal liabilities. Criminal inquiry adds more gasoline to the flame. Starting the investigation before accident’s containment is almost like investigating causes of an air crash with airplane still in the air. Perhaps, such approach could give unique perspective, but more likely it will downgrade itself to simplified description of immediate events with operators and decision makers who were unfortunate enough to be in close proximity as the accident emerged.
Friday, May 28, 2010
MITRE Prediction Market Pilot
Couple of days ago I’ve signed up for the MITRE Prediction Markets Pilot. Prediction market(s) is one of the most controversial and recent means of organizational tools. It is in such early development stage, that few organizations have ever made an attempt to formally integrate the method into its organizational design.
In short prediction markets create common and usually electronic platform that allow participants to put their bets on certain prediction, which has asset price and where this price is tide to the probability of this event. Most famous and successful example of prediction market is Iowa Electronic Markets, a non-profit academic exchange, which conducts US Presidential Elections prediction markets and claims to have more accurate results than the election pools.
Here are some basics: let us assume that in the Winner-Takes-All Market one-dollar value is assigned if the prediction that candidate A wins the election and zero dollars if the same candidate looses the election. The price of the contract that fluctuates between the staring point and the end-point of the bet (for example between 0.2 dollars and 0.4 dollars) means that the chances of candidate A winning the election fluctuates between 0.2 and 0.4 probability. Let us assume that the probability of the bet at a certain day is 0.33. This means that one can buy the contact for 0.33 dollar at that day and if the candidate A wins the election at some point in the future, the gain is equal to 0.77 dollar (or loose 0.33 dollar if the candidate fails).
Basic requirements for Prediction market are:
In the case of MITRE pilot, there are predictions such as “When will the oil spill in the Gulf of TX be contained (i.e. no longer allowed to contaminate the water?)”, “Will Greece default on all or part of its sovereign debt by December 31, 2011?”, “Will the iPhone be available on the Verizon Network on Oct 1, 2010?” and many more. Each player has 5,000 units of virtual currency (which for some reason are called dollars, perhaps because organizers would like to honor the currency in which the pilot is funded :) ).
In 2005 Google made an attempt to introduce prediction markets to evaluate its internal performance (such as product launch dates or quarterly figures) and assess external competitive environment (such as actions and products made by its competitors). One key distinction from the Iowa Electronic Markets and MITRE’s pilot was that Google employees/traders were trading in pseudo currency called Goobles. The authors of the project created indirect reward system, so that monetary benefits would not distort the prediction outcomes. After all, the value generated by the prediction markets was participants’ perception of future development and events. This shift in motivation made traders focus on their reputation, credibility and ability to influence the market. It is not clear if the prediction market is operational at Google these days. It seems that long-term sustainability of such initiative require strong commitment form both management and market participants. One interesting and unexpected conclusion that can be taken from Google’s initiative is the fact that prediction market can map the flow of information within particular organization. There was a study done by Google and Wharton scholars to prove this point (Using Prediction Markets to Track Information Flows: Evidence from Google, 2009). One more important detail, in Google’s case the prediction market techniques fit company’s innovative culture with its etiquette of internal communication, as well as diverse, tech-savvy and self-motivated employees.
It is too early to say, but it seems that MITRE’s pilot is also moving into the direction of using non-monetary incentives such as honor badges, surveys, rankings, etc. The main question here is whether the performance of the players will eventually be measured by virtual monetary gains or accuracy of predictions.
So what is the justification for prediction markets? I tried to dig some articles in Google Scholar. Here is a good summary of justifications that comes from Joyce E. Berg and Thomas A. Rietz; and their 2003 Prediction Markets as Decision Support Systems, Information Systems Frontiers Market paper: “(1) the markets give continuously updated dynamic forecasts; (2) through the price formation process, the markets aggregate information across traders, solving what would otherwise be complex (at best) aggregation problems; (3) markets give unbiased, relatively accurate forecasts well in advance of outcomes; (4) these forecasts can outperform existing; (5) the evidence suggests that market dynamics can overcome biases that individual traders may have, effectively eliminating them from forecasts; (6) the markets can be designed to forecast a variety of issues and provide a variety of types of information” (Joyce E. Berg, Thomas A. Rietz, 2003).
Cass R. Sunstein, Administrator of the White House Office of Information and Regulatory Affairs, former University of Chicago Law School and current Harvard Law School professor, argues that predictions market (information market) tend operate more accurately than exit pools and expert panels due to the dynamic and aggregate nature of the market. In prediction markets (information markets) participants are given the right incentives to disclose information they hold. “Groups often hold a great deal of information, and an important task is to elicit and use the information of their members… Much of the time, informational influences and social pressures lead members not to say what they know. As a consequence, groups tend to propagate and even amplify cognitive errors. They emphasize shared information at the expense of unshared information, resulting in hidden profiles… [Information] markets tend to correct rather than amplify individual error, above all because they allow shrewd investors to take advantage of the mistakes made by others. By providing economic rewards for correct individual answers, they encourage investors to disclose the information they have. As the result, they are more often more accurate than the judgment of deliberating groups”(Sunstein, 2006).
It seems that prediction markets have value, but I will have to try it on my own to be convinced. So currently I am in the "learning by doing" mode: taking careful strategies and aiming to get into upper quartile rank of market traders. I will keep readers posted on my success.
As for the trading platform of MITRE’s pilot, I should say that it is user-friendly. It has Dashboard and Stats that engage you into the trading process. It also gives you an option to ask clarifying questions and make comments before or after particular trade is made. So the system is evolving and I am interested to see where it will takes us in the end (the pilot will last for 6 months as far as I know).
You can visit the site https://mitre.inklingmarkets.com/ to be the judge.
In short prediction markets create common and usually electronic platform that allow participants to put their bets on certain prediction, which has asset price and where this price is tide to the probability of this event. Most famous and successful example of prediction market is Iowa Electronic Markets, a non-profit academic exchange, which conducts US Presidential Elections prediction markets and claims to have more accurate results than the election pools.
Here are some basics: let us assume that in the Winner-Takes-All Market one-dollar value is assigned if the prediction that candidate A wins the election and zero dollars if the same candidate looses the election. The price of the contract that fluctuates between the staring point and the end-point of the bet (for example between 0.2 dollars and 0.4 dollars) means that the chances of candidate A winning the election fluctuates between 0.2 and 0.4 probability. Let us assume that the probability of the bet at a certain day is 0.33. This means that one can buy the contact for 0.33 dollar at that day and if the candidate A wins the election at some point in the future, the gain is equal to 0.77 dollar (or loose 0.33 dollar if the candidate fails).
Basic requirements for Prediction market are:
- Clear rules. Event should have definite outcome and ending date. Preferably known market participants.
- Clear incentives (monetary or other) to make accurate predictions and bet against other participants.
- Stable market size.
- Adequate rewards for risk taking.
- Mix of participants, which includes experts and non-experts like me.
- Clearly defined, exhaustive and engaging predictions.
In the case of MITRE pilot, there are predictions such as “When will the oil spill in the Gulf of TX be contained (i.e. no longer allowed to contaminate the water?)”, “Will Greece default on all or part of its sovereign debt by December 31, 2011?”, “Will the iPhone be available on the Verizon Network on Oct 1, 2010?” and many more. Each player has 5,000 units of virtual currency (which for some reason are called dollars, perhaps because organizers would like to honor the currency in which the pilot is funded :) ).
In 2005 Google made an attempt to introduce prediction markets to evaluate its internal performance (such as product launch dates or quarterly figures) and assess external competitive environment (such as actions and products made by its competitors). One key distinction from the Iowa Electronic Markets and MITRE’s pilot was that Google employees/traders were trading in pseudo currency called Goobles. The authors of the project created indirect reward system, so that monetary benefits would not distort the prediction outcomes. After all, the value generated by the prediction markets was participants’ perception of future development and events. This shift in motivation made traders focus on their reputation, credibility and ability to influence the market. It is not clear if the prediction market is operational at Google these days. It seems that long-term sustainability of such initiative require strong commitment form both management and market participants. One interesting and unexpected conclusion that can be taken from Google’s initiative is the fact that prediction market can map the flow of information within particular organization. There was a study done by Google and Wharton scholars to prove this point (Using Prediction Markets to Track Information Flows: Evidence from Google, 2009). One more important detail, in Google’s case the prediction market techniques fit company’s innovative culture with its etiquette of internal communication, as well as diverse, tech-savvy and self-motivated employees.
It is too early to say, but it seems that MITRE’s pilot is also moving into the direction of using non-monetary incentives such as honor badges, surveys, rankings, etc. The main question here is whether the performance of the players will eventually be measured by virtual monetary gains or accuracy of predictions.
So what is the justification for prediction markets? I tried to dig some articles in Google Scholar. Here is a good summary of justifications that comes from Joyce E. Berg and Thomas A. Rietz; and their 2003 Prediction Markets as Decision Support Systems, Information Systems Frontiers Market paper: “(1) the markets give continuously updated dynamic forecasts; (2) through the price formation process, the markets aggregate information across traders, solving what would otherwise be complex (at best) aggregation problems; (3) markets give unbiased, relatively accurate forecasts well in advance of outcomes; (4) these forecasts can outperform existing; (5) the evidence suggests that market dynamics can overcome biases that individual traders may have, effectively eliminating them from forecasts; (6) the markets can be designed to forecast a variety of issues and provide a variety of types of information” (Joyce E. Berg, Thomas A. Rietz, 2003).
Cass R. Sunstein, Administrator of the White House Office of Information and Regulatory Affairs, former University of Chicago Law School and current Harvard Law School professor, argues that predictions market (information market) tend operate more accurately than exit pools and expert panels due to the dynamic and aggregate nature of the market. In prediction markets (information markets) participants are given the right incentives to disclose information they hold. “Groups often hold a great deal of information, and an important task is to elicit and use the information of their members… Much of the time, informational influences and social pressures lead members not to say what they know. As a consequence, groups tend to propagate and even amplify cognitive errors. They emphasize shared information at the expense of unshared information, resulting in hidden profiles… [Information] markets tend to correct rather than amplify individual error, above all because they allow shrewd investors to take advantage of the mistakes made by others. By providing economic rewards for correct individual answers, they encourage investors to disclose the information they have. As the result, they are more often more accurate than the judgment of deliberating groups”(Sunstein, 2006).
It seems that prediction markets have value, but I will have to try it on my own to be convinced. So currently I am in the "learning by doing" mode: taking careful strategies and aiming to get into upper quartile rank of market traders. I will keep readers posted on my success.
As for the trading platform of MITRE’s pilot, I should say that it is user-friendly. It has Dashboard and Stats that engage you into the trading process. It also gives you an option to ask clarifying questions and make comments before or after particular trade is made. So the system is evolving and I am interested to see where it will takes us in the end (the pilot will last for 6 months as far as I know).
You can visit the site https://mitre.inklingmarkets.com/ to be the judge.
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