OK, captainflame and Finn47, "best-guessing" (not second-guessing) the seabed location of the AF447 hull is a PROCESS based on probabilities and a pot full of known and inferred datapoints. Debris locations and "Ultimo Reporte" are datapoints in that pot... Perhaps I should have said "best-guessing from the known and estimated flight path of the A/C and the location of found debris;" all are datapoints. Sorry for the confusion. Likely at play here is Bayesian search theory.
The most interesting search in similar circumstance to AF447 was conducted in 1968, for the nuclear submarine USS SCORPION, where Dr. John Craven, the Chief Scientist of the U.S. Navy’s Special Projects Division, successfully used Bayes’ Theorem of subjective probability to ultimately locate the wreck far from where many thought it should be found. The pot of data available in the AF447 case is eerily familiar:
"On May 27, 1968 USS SCORPION was reported missing with ninety-nine men on board. Nobody had any idea where SCORPION was or what had happened to her. All they knew was that the 3,500 ton nuclear attack submarine was due back in Norfolk, VA and had failed to arrive... The site of the first explosion – codenamed Point Oscar - marked where the search would begin. The water at Point Oscar was 2 miles deep. The SCORPION would have stopped imploding about 7,000 feet before she hit bottom, cutting off the acoustic trail. Depending on how fast she had been traveling, and in what direction, and depending on the force of the implosion and the position of her stern planes as she fell, she could have been thrown miles further... [Craven] asked a group of submarine and salvage experts to bet on the probability of each of the different scenarios being considered to explain SCORPION's loss. Once the bets were completed Craven sat down to draw a probability map... Years later mathematicians would write a book based on their work with Craven entitled "Theory of Optimal Search," the U.S. Coast Guard would adopt the method for search and rescue, and the Navy would use Craven’s interpretation of Bayes’ Theorem to locate sunken ordnance in the Suez Canal." (A good read at
http://en.wikipedia.org/wiki/USS_Scorpion_(SSN-589))
This PPRuNe thread has been helpful, I should think, in providing expert data points and scenarios. As I said in my last post, likely thousands of expert hours have been invested in answering the best-place-to-search question. Certainly a lot of assets have been deployed to search "somewhere."
"Bayesian search theory is the application of Bayesian statistics to the search for lost objects. It has been used several times to find lost sea vessels, for example the USS SCORPION. The usual procedure is as follows:
1. Formulate a number of hypotheses about what happened to the vessel.
2. Corresponding to each hypothesis construct a probability distribution for the location of the vessel.
3. Construct a probability distribution for actually finding an object in location X if it really is in location X. In an ocean search, this is usually a function of water depth — in shallow water your chances of finding an object are good if you are looking in the right place. In deep water your chances are reduced.
4. Combine the above information coherently to produce an overall probability distribution. (Usually this simply means multiplying the two distributions together.) This gives the probability of finding the vessel by looking in location X, for all possible locations X. (This is like a contour map of probability.)
5. Construct a search path which starts at the point of highest probability and 'scans' over high probability areas, then intermediate probabilities, then the low probability areas.
6. Revise all the probabilities continuously as you search, i.e. if you have searched location X then the probability that the vessel is there is greatly reduced (though not usually zero) and the probabilities of all other locations must be increased. The revision process is done using Bayes' theorem."
Bayesian search theory - Wikipedia, the free encyclopedia