OTC 2016: second day
For the first time since I started attending OTC in 2001, I could park in the first row of the parking lot. I wonder why!
Couple of things grabbed my attention immediately during the session “Coping with low prices”: a more collaborative attitude between Deepwater companies to share R&D costs; “co-creation”, and despite of the low oil prices and financial straits, keeping safety first as a non-negotiable. I was happy to hear that maintaining the culture of safety is as important, or more, than fitting the financial targets. To weather this new low cycle will require a paradigm shift in the industry, one of the lecturers said.
A quick survey among the audience, somewhere between 150 and 200 people, using a remote voting keypad, gave as result that 80% expect that the oil price will be at 60 USD per barrel in 2017, 15% thought it would be $40, and 2% that it would come back at $100! That got a gasp from the audience. Another thing brought up by another lecturer is that we should be measured in our expectations of the shale oil industry come-back after the oil price rebounds. It will have been so hardly hit that it will take some time putting their balance sheets in order. Banks will be less forgiving in the next cycle.
I loved the bit of geopolitics: with the BRICS weakened, politically and economically - we are talking about Brazil, Russia, India, China and South Africa-, where would you find opportunities for growth, investment or even moving your equipment? I was surprised by the answer: Mexico, Indonesia, Nigeria and Turkey. The lecturer quickly showed us a plot of GDP for the last few quarters and looked like a very nice ascending slope to me. A wow moment. So, we have a MINT.
For my pleasure, all the lecturers agreed on a third wheel, besides safety and collaboration, and that was Big Data. They think that it will uncover avenues for reducing costs, improve efficiencies and uncover causes invisible to the human eye. A lecturer gave the example of the day and night crews at a platform: if all equal, training, resources, competencies, tools, etc., what is it that still one crew shows better performance? Data science is giving the answer. Or the other lecturer that told the story of BOPs (blow out preventer) reliability improvement and other projects where they have seen drastic reductions in downtime.