Machine Learning in Oil And Gas

Machine Learning and Artificial intelligence are the trends leading the oil and gas industry to an advanced level. AI and ML have diverse applications in the oil and gas industry driving it towards the optimization of production rates. Comparing how the oil and gas industry is operating now and a decade ago, infinite differences can be observed.

The modern world has been expediting advanced technologies. Some of the fields like healthcare, finance, transportation were quick in recognition of the benefits and the vast applications of AI and Machine Learning. But, the oil and gas industry wasn't that quick in advancing it towards AI and Machine Learning. Probably the huge investment required in the oil and gas industry conquered all its concentration.

Though the recognition wasn't speedy, people in the oil and gas industry are now pretty aware of its application.

Machine Learning and Artificial intelligence are the trends leading the oil and gas industry to an advanced level. AI and ML have diverse applications in the oil and gas industry driving it towards the optimization of production rates. Comparing how the oil and gas industry is operating now and a decade ago, infinite differences can be

observed. The modern world has been expediting advanced technologies. Some of the fields like healthcare, finance, transportation were quick in recognition of the benefits and the vast applications of AI and Machine Learning. But, the oil and gas industry wasn't that quick in advancing it towards AI and Machine Learning. Probably the huge investment required in the oil and gas industry conquered all its concentration.

Though the recognition wasn't speedy, people in the oil and gas industry are now pretty aware of its several other applications go application.

What is Machine Learning? What is the difference between Machine Learning & Artificial Intelligence?

Machine learning is one of the branches or subdivisions of Artificial Intelligence.

Artificial Intelligence, on its own, is a very vast topic and thus is subdivided into several categories like Machine Learning, Neural Networks, Robotics, Speech Processing, Natural Language Processing, etc.

Machine Learning is the portion of Artificial Intelligence that covers the learning of the machines on their own regardless of the labels being provided.

Related: What Is Machine Learning?

How & Where Is Machine Learning Used In The Oil & Gas Industry?

For several years, the oil and gas industry has been exploring by taking Machine Learning and Artificial Intelligence for granted. The applications of AI and Machine Learning are not only limited to the segments of the oil and gas industry but instead, tons of different software use AI and Machine Learning.

The application of Artificial Intelligence in various segments of the oil and gas industry can be elaborated as follows:

1.Upstream or E&P (Exploration and Production) sector


The E&P sector of the oil and gas industry involves the evaluation, exploration, drilling, and the extraction of crude oil and or natural gas.

Application of AI

a.A huge amount of onsite operating costs can be reduced with the use of AI. In the upstream sector, the sensors and the Internet of Things (IoT) operated with AI are widely used in controlling systems and collecting data.

b.Drilling costs can be minimized by recognizing the most reliable sites

c.Management of well reservoir facilities

d.Effectively fracking the well


2.Midstream sector


The Midstream sector of the oil and gas industry involves processing, storing, transporting, and marketing of crude oil, natural gas, and liquified natural gas.

Application of AI

a.AI engraved systems capable of forecasting and optimizing for better decision making and uplifting performances.

b.Accurate and more reliable surveying of oil and gas wells.


3. Downstream sector


The downstream sector of the oil and gas industries involves refining and processing purified crude oil and natural gas.

Application of AI

a.Streamline the refinery and petroleum transporting operations to stimulate revenue growth

b.Data modeling and the use of algorithms for managing water, residuals, and other consumables.

Besides all these applications, there are several other applications that go hand in hand with all the sectors of the oil and gas industry.

c.AI supports oil and gas companies in reducing costs and in making more reliable decisions.

d.AI helps in outlining and forecasting

e.Predictive maintenance


5 Applications of Machine Learning in Oil & Gas



Machine Learning can potentially increase the possibilities of optimizations, accurate modeling, predictive maintenance, and cost reduction in the oil and gas industries.

The enormous contribution of Machine Learning in oil and gas is the main reason why its use has been escalating.

The five different ways of how Machine Learning has impacted the oil and gas industry are described below:


5.Accurate Modelling


Accurate modeling of the underlying reservoir is very crucial in the oil and gas industry. As it is not possible to go see the reservoir ourselves, the oil and gas industry highly depends on the reservoir models. It is the only way the oil and gas companies can have the visualization of their reservoirs.

Though there are various ways data can be collected for reservoir modeling, the seismic data are more reliable and widely used.

Inputting these collected data into various AI and Machine Learning based software, oil and gas companies generate models of their reservoirs before they begin drilling.

Some of the best oil and gas simulation and modeling software are: Surfer, Aspen HYSYS, Petrel E&P Software Platform, IHS Petra, CHEMCAD, myQuorum, SeisEarth, ATMOS Simulation Suite, etc.

Related: Artificial Intelligence - The Future Ruler of The World


6.Discovering The Pinpoint For Drilling Using Machine Learning


As drilling operation is one of the most financially demanding operations in the oil and gas industry, having a better visualization of the drilling spot plays a huge role.

Machine Learning can be used to effectively reach the targeted drilling depth with more accuracy. It can highly boost drilling and exploration processes.

When drilling is done, various sets of data are collected. These data are carefully analyzed by petrophysicists before inputting them into the software.


7.Use of Machine Learning In Oil & Gas To Improve Subsurface Characterisation


Machine Learning is being used widely for determining and improving subsurface characterizations.

While using the Machine Learning based software, they not only provide us with the reservoir models and locations but also inform us about the possible characteristics of the downhole formations. This software, going through several processes, correlate, and find the potential pay zones.

In past years, correlating and finding the properties of targeted formations were very time consuming as they were all done by hand. Going through several feet of long well logs, correlating them, and then calculating or estimating the formations' properties with no doubt could have been challenging and time-consuming.

But, now using these Machine Learning and AI-based software, all those tasks are as easy as a piece of cake and can be done in just one click.

Related: Petroleum Engineering, Its Importance And Its Branches


8.Optimizing Drilling Operations


The use of Machine Learning and AI improves the operation of oil and gas companies.

As it promotes accurate decision making, it optimizes the production and drilling operations.

With the constant feeding of data, AI, and Machine learning-based software learn to function more accurately on their own and thus provide us with the best results.

But, uncertainties have been involved both ways, either we use this software or complete the task by hand. It is all about more accuracy, cost-effectiveness, and less time-consuming method.


9.Internet of Things


The oil and gas industry is a fluctuating industry based on costs and demands.

A pore system in predicting and managing the cost and demand can lead a company to a great loss. Therefore, it is extremely crucial to have the best inventory planning and optimization.

Internet of Things (IoT) helps in minimizing the risk and fluctuations in cost and planning. The effective functioning of the detectors helps in observing the overall system performance. Thus, help them in scheduling the repairs and maintenance.


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