What are the current market trends shaping the Oil and Gas space?
In the current low oil price environment, our Hess strategy is focused on preserving our balance sheet strength, preserving our core operating capabilities and preserving our long term growth options. Everything we do as a company, we make sure that it’s sustainable because we are not in it for a short term; we are in it for a long run.
What are the common business challenges the Oil and Gas sector face at this point in time? As a technology enthusiast, please opine your views on the steps organizations should take in combating those.
Is there a way that technology can basically help us, or can provide either efficiency improvements or effectiveness that we hadn't seen or focused on before because we were so busy? This is an opportunity to look at process improvements and more efficiency improvement opportunities. In particular, to improve the operations performance as well as a reduced cycle time where it’s possible. The technology can really be the enabler.
With technologies like Big Data, Cloud, RFIDs, and IoT put into use, the Oil & Gas sector is through one of the most transformative periods in its history. What are your views on how these technologies can be timed to tackle productivity concerns within this sector?
I believe this is one of the most transformational periods in history for our industry. When it comes to cloud, other innovative things and perhaps even big data, we are behind as an industry. Now is the time to not only look at it as a path forward, but to become leaders in some parts of this space.
"By using the cognitive technology and machine learning, we can focus on reducing cycle time from the inspection during the exploration stage, appraisal stage—all the way down to the development"
We are doing quite a lot of work already. We started it about two years ago on big data in our Bakken operation and now we are extending into our drilling operations and our offshore business. From system analytics to understanding what’s possible and helping us make the right decisions. These are data-driven decisions vs. perceptions or exceptions or people’s views. Actual, factual data-driven decisions.
We have been actively migrating to the cloud. We started out on cloud activities two years ago when we divested our downstream business and all of our data and programming work was done in there. Now, we are actively moving quite a lot of our applications and data to cloud services. We have quite a lot of data available. It’s our internal data, partner’s data and publicly available data. This is an opportunity that the technology can take us to the next level; agility, efficiency and cost savings in some cases.
Now on productivity, this is when RFIDs and the Internet of Things come into play. We have quite a lot of sensors in place— not everywhere—but all of our new facilities. Everything that is coming up is coming up with the sensors in place. When you have the sensors in place and you get all of this data, what are you doing with this data? What decisions will you be making? The opportunities are there to improve the up-time and reduce the non-productive time, and to reduce cycle time. This is the future. We’re working very closely with some of the suppliers, making sure that they’re getting the right data. And we really need to have suppliers working with us on our projects or in supporting our drilling and completions activities. We are identifying key data types that we need to focus on to improve our productivity.
We have a project in the Bakken called exception-based surveillance that we kicked it off about a year and a half ago. With that, not only are we changing in our Bakken operations, we are changing our organizational structure as well. A big part of our operations of the future is changing the way people work, and technology is the key enabler for that change. Exception-based surveillance is giving us the opportunity to provide services just in time and be a lot more proactive. We only go and focus on the areas that need work, vs. driving to hundreds of wells through this enormous Bakken geography–driving up to the well and saying, “Nothing needs to be done here so let me go to the next one.” In this case, you are just going to go right to where the problem is and more importantly, you are going to go there before the problem happens. That’s what the technology is able to provide.
Another technology that is emerging in the Oil &Gas space is Virtualization. Please reflect upon its features and how it helps organizations in answering productivity and maintenance challenges.
We have been virtualizing for quite a long time, for couple of reasons. It helps reduce costs but it also provides agility. And we have been virtualizing the environment, first on premises but now we are going to the cloud.
What are the major tasks for organizational CIOs at this point in time? Is there any unmet need in terms of technology that is yet to be leveraged from the vendors?
We want to, from an IT perspective, support an agile business, an efficient business and a smart business. Each one of these three areas brings in technological improvements and enabling opportunities for the business. Agility is working together with the service providers so that commodity IT is pretty much taken care of as a service. That lets us re-focus the rest of the IT organization on the areas that can provide efficiency improvements as well as delivering smart business. Efficiency improvements include exception-based surveillance and working with our Lean organization to identify opportunities to reduce waste and improve productivity through automation and improvement activities. Smart business is probably the most interesting one. That’s where big data and analytics come to play.
What is your advice for budding technologists in the Oil &Gas? How do you see the evolution few years from now with regards to disruptions and transformations within field services?
The future IT technologists are not necessarily your desktop infrastructure server experts or even networking-type expertise because all of that has become commoditized. It is your data scientists. It is people who understand the business very well and also understand the technology. It’s those who can combine these two and drive improvements for the business. If we’re talking about Watson, or focusing on cognitive computing or AI, this is where we have a huge opportunity to take the IT organization to the next level. This is where we can use big data and cognitive and machine learning to reduce cycle time.
We know that the cycle time in upstream oil and gas—from discovery to first oil in deep water is between 15 and 17 years. By using the cognitive technology and machine learning, we can focus on reducing cycle time from the inspection during the exploration stage, appraisal stage—all the way down to the development. That is where I see the future and the changes in the organization that in a way will be a little disruptive and transformative for the organization. Disruption requires a different mindset from the operations team and engineering teams and others. It requires believing that computers and data that is processed by this computer to advise you on what good looks like. In this part of the world or this particular basin, if you have this kind of conditions with this kind of features, then this is typically how you should interpret it.
You still can have a human decision. But you also have an opportunity to reduce cycle time by not doing something that perhaps has been done before and has failed or to do something that has proven to be successful. You can eliminate outliers and focus on what’s possible.