21–30 of 37 posts
Aren't they Big Oil's old favorite toy? In the 90s, a local university near me had a Cray XMP that was a gift from some oil company after they'd decommissioned it.
Shell Oil had a Cray 1 and an ncube when I worked there in 1989. Chevron had a Cray 1 and a raft of IBM mainframes in 1990. Chevron's DC was set up for visitors so every cluster had a sign describing the computing power for that system. Total compute power was very important because it meant they could do more analysis on seismic data to refine their oil and gas lease bids. Chevron had so much seismic data they requi…
Shell Oil had a Cray 1 and an ncube when I worked there in 1989. Chevron had a Cray 1 and a raft of IBM mainframes in 1990. Chevron's DC was set up for visitors so every cluster had a sign describing the computing power for that system. Total compute power was very important because it meant they could do more analysis on seismic data to refine their oil and gas lease bids. Chevron had so much seismic data they requi…
If you knew the effort and cost that goes into large scale near and offshore seismic and non-seismic surveys then you wouldn't think twice about putting the value of the data well above the value of the hardware. Offshore deepwater (~2500ft+) non-seismic surveys might cost 6-7 figures per day to operate, and might fill up a hard drive every 1-3 days. Depending on how many drives fit on a tape, the raw data could get…
Nun new. Supercomputing has been used in Oil & Gas exploration for decades.
Basically, I can see that they needed super computers in the 80s. But I might have assumed that their computing needs wouldn't keep scaling with supply. So that by now, just renting some GPUs from Amazon might be enough.
My (in my opinion failed) HonsBSc project was on signal analysis of GC-MS (Gas Chromatography coupled to Mass Spectrometry) signals.
If I had to do it again in 2019, then machine learning would be a much more pertinent focus. However, without the computing power of today and ubiquitous presence of programming libraries for that purpose, there are actually other ways of approaching such data (like wavelets).
Wavelet transforms were invented quite a while ago [1] but I think the seismic data analysts were some of the first to really investigate the applications of that field. The other application is for compression (and loading over an internet connection) [2].
Aren't they Big Oil's old favorite toy? In the 90s, a local university near me had a Cray XMP that was a gift from some oil company after they'd decommissioned it.
Exactly. I have been hearing about this stuff for ages. Oil companies optimized raping the land decades ago.
What kind of signal analysis do the oil companies do these days (like wavelet transforms)? My (in my opinion failed) HonsBSc project was on signal analysis of GC-MS (Gas Chromatography coupled to Mass Spectrometry) signals. If I had to do it again in 2019, then machine learning would be a much more pertinent focus. However, without the computing power of today and ubiquitous presence of programming libraries for that…
Shell Oil had a Cray 1 and an ncube when I worked there in 1989. Chevron had a Cray 1 and a raft of IBM mainframes in 1990. Chevron's DC was set up for visitors so every cluster had a sign describing the computing power for that system. Total compute power was very important because it meant they could do more analysis on seismic data to refine their oil and gas lease bids. Chevron had so much seismic data they requi…
Do you have any good resources on that Deming-style quality training?
Nun new. Supercomputing has been used in Oil & Gas exploration for decades.
Indeed, but interestingly enough the book, The Prize: The Epic Quest for Oil, Money & Power , only has 9 mentions of the word computer and zero for supercomputer . The Prize: The Epic Quest for Oil, Money & Power https://www.amazon.com/Prize-Epic-Quest-Money-Power/dp/14391...
So it's more a book to persuade (feelings) than inform (facts) - no wonder they aren't mentioned.
Know what you're reading.