Artificial Intelligence: Hype or real?

In my close door meeting with many senior executives at operators everyone asks the basic question: Is this AI a hype or real? Hence I thought of sharing some thoughts for all to ponder.

First, there is no doubt today everyone in oil and gas has woken to the fact data is an asset vs. liability, thanks to the consumerization of technology, that is first step in the right direction for sure. This innovation wave has given birth to many new potential opportunities which could have game changing impact. However only time with tell if this will be remembered in history as “AI bubble” which today keeps growing with new players popping up every quarter claiming they have magic AI to help Big Oil or burst like many past digital transformation initiatives.

The digital challenges for the E&P operator executives further multiplies as operators have to not only select between the right AI partner (some of whom can help optimize drilling, some completion, some production and some claiming all) and yet none of them talk to each other creating an ‘AI muddle” which leaves room open for again having variety of disparate data lakes for ultimately operator to connect.

The confusion just doesn’t end here, let’s not forget another key player in the eco system i.e. big 4 consultants, strategy firms and mid-market consultants who specialize in digital transition journey. They have combination of strategy framework, operational frameworks and technology frameworks to guide Big Oil through a s successful transition.

NOTE: I use the term transition not transformation, as transformation should not take 10 years, very typical in our industry.

With the noise around AI amplifying daily I wanted to share some perspectives which may help Big oil separate signal from the noise. 

Apply learnings from consumer technologies which we cannot live without today and have helped them wipe out Big oil from top 5 publicly traded companies in the world. If we focus on how they apply Machine learning (a subset of AI) we can learn a lot.

-They focused on simplifying our daily workflows as the key outcome irrespective of technology

-They focused on making us good busy from earlier bad busy

-They focused on building a growth platform, which had salient characteristics:

• It supported diverse set of participants and offer opportunities for creating value in many distinct areas?
• scale up by accommodating a large user base without adding unacceptable cost/issues?
• generated increased returns as participation grows?
• Provided incentives for participants to engage regularly and share their learnings??
• provided development leverage (investment required to build additional functionalities) and interaction leverage (effort & cost for diverse set of participants to facilitate interaction)?

clearly defined practices to guide activities of a large number of participants?

While doing this they mined not just machine data but also human generated data. I think everyone today knows machine data but let’s get on same page with what is human generated data: its videos, pictures, likes, comments we make today.

As they mined the above they started to make recommendations beyond our belief for example

How does Amazon know our buying patters and habits so accurately?

How does Siri recommend us what we may have not even thought of based on location?

Focused advertisement by google.

What many may not know earlier these companies mined only machine data but with not so accurate predictions, but as the volume of data grew coupled with human or what I call decision context grew the accuracy of predictions grew as everything thanks to their clever platform thinking forced us as consumers to share human generated data which prior to them was in disparate systems like emails, Instant messengers etc.

It baffles me when we know from our own personal experiences how accurate predictions which matter to us come from combing both human and machine generated data via these consumer platforms, why same is not being thought about today at E&P operators. Why many are laser focused on machine generated data only but letting the human generated data like picture, videos, context in email etc bite dust siting in email servers behind the firewalls. Let me show you an example of power of having them both in one platform from one of my client examples:

01  Engineer request video of next connection

02  Company man makes video and posts

03  Engineer says much better ROPs in the hotter gamma zones, try to keep DD on point-geo-steering has been pretty calm on target changes so far. After a while, engineer posts/sends to field Cross Plot saying drilling above the founder point on this run, Need to watch parameters, and requests pictures of bit when it gets to the surface.

04  Field attaches to the post pics of the BHAs

The industry must think about the bigger picture by learning and drawing parallels from consumer centric technologies to ensure AI becomes real not a hype., as ultimately if AI cannot prove to create compelling value the fault is not in AI but us.

In next blog I will write about difference between different dimensions of value which may help executives think on the bigger picture based on our learnings from the Silicon Valley.