How is Artificial Intelligence Enabling Improved Decision Making for Oil and Gas Business?

Oil and Gas business, partial side effects of COVID-19, has suffered major losses this year due to drastic slowdown in the consumption. The major Oil and Gas companies including the National Oil Companies and International Oil Companies have already started implementing substantial cost-cutting plans.

The future looks dismal, but every cloud has a silver lining; the hydrocarbon prices seem to have stabilized and digital technologies have surfaced as the “knight in the shining armor”.

Every Oil and Gas company is striving hard to achieve a balance between their operations and investments by incorporating several measures, mainly by leveraging on digital technology. What are the main digital technologies that are changing the Oil and Gas market dynamics? How are they ensuring improved operational efficiency and reduction in investment at the same time?

This article will try to uncover some of the technologies and answer the pertinent questions raised above.

The technology is evolving at an unprecedented pace; almost making it impossible to catch up. Let’s start with few of the digital buzzwords:

  • Artificial Intelligence
  • Machine Learning
  • Cloud Computing

Artificial Intelligence, what is it? Is it the same as Machine Learning? A lot of us use both these terms interchangeably, but they are not the same. In fact, Machine Learning is a subset of Artificial Intelligence. How about Big Data and Cloud Computing? What is all the hype about them? I will introduce each one of them briefly before discussing their usage in the Oil and Gas business.

Let’s start with Artificial Intelligence. What is it and how is it improving the decision making within Oil and Gas business?

Artificial Intelligence

According to Google Education, Artificial Intelligence is “the general study of making intelligent machines”. What does it mean? Are the machines “stupid” and in the state of benightedness? They do not have any intelligence? or are we trying to implant brains in them? The answer is a big NO.

We have intelligent machines for example commercial flights have autopilot, weather forecast, and robots to manage the logistics to name a few. Some of them make use of Artificial Intelligence, a lot of them do not. What’s the difference? Artificial Intelligence, without any human intervention, enables the machines to think and learn. The machines without Artificial Intelligence will be programmed to carry out only a specific set of instructions. How does that help? Well, it helps to make better decisions. Just imagine, the machine itself telling you the best possible option. Wouldn’t that make your life easy?

Machine Learning

Machine Learning is a sub-set of Artificial Learning, which provides the statistical tools to explore and analyze data. It is all about “Training” and “Prediction”. So, is it a programming language?

Let’s, for the time being, assume yes. The next logical question is what is so different about it from other traditional languages. The main difference lies in the behavior i.e. the mechanism in which they work. The traditional programming languages are fed with a list of rules/instructions/data/information and they give you the results. The machine language is more about “training” your algorithm to make it learn by itself and adapt accordingly. How does it happen? Well, you need to feed a lot of examples to the algorithm.  The picture below depicts the basic difference between the traditional programming languages and Machine Learning.

Traditional language vs Machine learning
Traditional language vs Machine learning

Primarily, there are three Machine Learning types:

  • Supervised
  • Unsupervised
  • Reinforcement (Semi-Supervised)

The details are not covered in this article. I will write another article to explain the concepts later. So, please watch this space for more details.

Cloud Computing

Cloud Computing, again a new “jargon”. Does cloud have anything to do with it? Why is it called “Cloud” Computing? Are we harnessing the power of cloud? Let me try and simplify it a little bit with an example. Imagine the time when we did not have electricity or power grids. The electricity was generated using generators or the dynamos. It was a luxury to have electricity and only a few could afford, as this was expensive. Finally, the advent of power grids enabled generation of electricity at larger scale and provided access to the individual households.

Now, compare the above example with current scenario where individual users and companies have their servers and processes on premises. The companies have IT departments to maintain it. One of the main issues is the computing power, which is limited by the number of processers, hardware and other factors.

This is similar to having a generator to produce electricity: cumbersome and expensive. What if the companies do not need to maintain all the hardware and software on-premise? What if a vendor has already setup a facility like the power grid to provide the infrastructure for a nominal charge? This is what cloud computing is. A cloud is nothing but a data center that has computer system resources: storage, processes, software, and other computing capabilities already available. Cloud computing is simply allowing the user to connect to these data centers using the internet and make use of the computing power provided by them.

How are these Digital technologies enabling Oil and Gas business to make improved decisions?

Oil and Gas business is capital intensive. It requires huge upfront capital investment and the decisions have to made on estimates; pretty much everything is an estimate including capital, operating expenditure, production, and prices. The only thing, most of the time, that a company could be certain of is the participation interest. The decisions have to be made based on huge amount of data, which is evergreen and changing continuously. The market dynamics are constantly changing. The decisions can no longer be made only on the basis of experience. The oil and gas industry needed a system that can churn huge amount of data and produce a meaningful information out of it. Not only produce meaningful results but also make useful recommendations. The system should also have the cognitive abilities to predict the future. This is where these high-end digital technologies like Artificial Intelligence & Machine Learning, Cloud Computing and Big Data Analytics come into picture. Some of the major players providing digital solutions include: –

  • Microsoft
  • Google
  • Amazon
  • IBM

To conclude, the digital technologies have already started reshaping the future and they are doing it at a very fast pace. The Oil and gas industries have realized the importance of digitizing their world and have already made big investments. Oil and Gas industries are one of late adopters, but better late than never.