Yesterday, I went to the workshop entitled, Grand challenges and research opportunities in geophysics, organized by Cengiz Esmersoy, Wafik Beydoun, Colin Sayers, and Yoram Shoham. I was curious if there'd be overlap with the Unsolved Problems Unsession we hosted in Calgary, and had reservations about it being an overly fluffy talkshop, but it was much better than I expected.
Ken Tubman, VP of Geosciences and Reservoir Engineering at ConocoPhillips, gave a splendid talk to open the session. But it was the third talk of the session, from Mark Koelmel, General Manager of Earth Sciences at Chevron, that resonated most with me. He highlighted 5 trends in applied earth science.
Data and information management
Data volumes are expanding with Moore's law. Chevron has more than 15 petabytes of data, by 2020 they will have more than 100PB. Koelmel postulated that spatial metadata and tagging will become pervasive and our data formats will have to evolve accordingly. Instead of managing ridiculously large amounts of data, a better solution may be to 'tag it and chuck it in the closet' — Google's approach to the web (and we know the company has been exploring the use of Hadoop). Beyond hardware, he stressed that new industry standards are needed now. The status quo is holding us back.
Full azimuth seismic data
Only recently have we been able to wield the computing power to deal with the kind of processes needed for full-waveform inversion. It's not only because of data volumes that new processing facilities will not be cheap — or small. He predicted processing centres that resemble small cities in terms of their power consumption. An interesting notion of energy for energy, and the reason for recent massive growth in Google's power production capability. (Renewables for power, oil for cooling... how funny would that be?)
Interpretive seismic processing and imaging
Interpretation, and processing are actually the same thing. The segmentation of seismic technology will have to be stitched back together. Imagine the interpreter working on field data, with a mixing board to produce just the right image for today's work. How will service companies (who acquire data and make images), and operators (who interpret data and make prospects) merge their efforts? We may have to consider different business relationships.
Full-cycle interpretation systems
The current state of integration is sequential at best, each node in a workflow produces static inputs for the next step, with minimal iteration in between. Each component of the sequence typically ends with 'throwing things over the wall' to the next node. With this process, the uncertainties are cumulative throughout, which is unnerving because we don't often know what the uncertainties are. Koelmel's desired future state is one of seamless geophysical processing, static model-building, and dynamic reservoir simulation. It won't reduce uncertainties altogether, but by design it will make them easier to identify and addressed.
The number of patents filed in this industry has more than tripled in the last decade. I assumed Koelmel was going to give a Big Oil lecture on secrecy and patents, touting them as a competitive advantage. He said just the opposite. He asserted that industries with excessive patenting (think technology, and Big Pharma) make innovation difficult. Chevron is no stranger to the patent processes, filing 125 patents both in 2012 and in 2011, but this is peanuts compared to Schlumberger (462 in 2012) and IBM (6457 in 2012).
The challenges geophysicists are facing are not our own. They stem from the biggest problems in the industry, which are of incredible importance to mankind. Perhaps expanding the value proposition to such heights is more essential than ever. Geophysics matters.