google oil business

Clive Humby, UK Mathematician and architect of Tesco’s Clubcard is considered the first person who said: “Data is the new oil” in 2006. And I think that the tech giants like Google, Microsoft, and Amazon take this quote very seriously as they invest heavily in the oil business in recent years and so after “Cloud Wars” these companies are now involved in the Oil Race.

Background

America’s first oil well was drilled in 1859 by Edward Drake in Pennsylvania. And with the passage of time, the consumption and demand for oil increased tremendously. So, there was always a danger that America will run out of the oil but somehow it goes on.

Edwin Drake Oil Well 1959

In 1909 there was an estimate that the US oil will run out in 1937, but in 1937 a new estimation was proposed that US oil will disappear in 1952 but it didn’t disappear and such estimation goes on till today.

But the question is how those estimations were wrong? The answer to this question is technology. As we know that with the passing time the drills, pumps, and techniques of oil extraction evolved i.e. Seismic Scans, LIDAR, Hydraulic Fracturing, etc. But those estimations didn’t count that factor that’s why those estimates were proved wrong by the time.

So, technology is the part where these big tech companies come in. These companies by using machine learning algorithms can help to find a better location for drilling and after that to optimize the extraction of oil.

In 1989 a Dutch geologist mapped the rock layers using seismic scans. IBM researchers use this seismic scans data to train their machine learning algorithm and after almost 10 minutes of training, it can name the rock layer with accuracy nearly as a human expert.

Similarly, Georgia Tech discovers a location for oil using geological data of that place, fed into machine learning algorithms.

According to the Zion report, the global AI in the oil and gas market was 1.75 billion USD in 2018 and is expected to reach around 4.01 billion USD by 2025.

Google

Google energy centers get 34% of energy through renewable resources in 2012 but by 2017 this percentage increases to 100%. They also lower their total usage of energy by using Machine Learning.

So, now Google wants to use the same Machine Learning in oil discovery and extraction. And for this they last year, hired Darryl Willis, a 25-year veteran of BP (British Petroleum) as the VP for Google oil, gas, and energy division. The goal of this division is to provide a solution to oil and gas companies using Google cloud and Machine Learning.

Moreover, Google signs a deal with Total (a well-known big oil company) to develop a solution of subsurface data analysis for oil and gas exploration and production.

But Google is in a lot of pressure as according to The Guardian report Google has made contributions to some notorious climate deniers in Washington despite its insistence that it supports political action on the climate.

So, we can say Google may disagree with these companies in climate policies but the profit benefit is the key factor that sticking these companies together.

Microsoft

Microsoft is a big tech company that is famous for providing industrial solutions using machine learning and cloud computing nowadays.

Microsoft is also working on the utilization of artificial intelligence and machine learning in advance climate research to deal with current environmental problems. And this past year it became the first tech giant to join the Climate Leadership Council. So, it may create difficulties for Microsoft to step in the oil business but their goal is to make this industry safer and efficient that actually seems to better the climate changes caused by this industry. They also hired Darryl Willis away from Google.

Schneider Electric, a 30 years global partner of Microsoft in providing tech solutions for industries is now out to solve the challenges of the oil and gas industry. The company has pushed edge solutions into new, predictive realms with the help of Azure Machine Learning and Azure IoT Edge.

“Traditionally, machine learning is something that has only run in the cloud, but for many IoT scenarios that isn’t good enough.… Now we have the flexibility to run it in the cloud or at the edge—wherever we need it to be.”

Matt Boujonnier: Analytics Application Architect
Schneider Electric

Microsoft not only working on the oil discovery and extraction but collaborated with Sopris and Trenegy to also provide management and optimization services like streamline operations, connected field services, predictive analytics, optimize utilization, lower DSO and leveraging data analytics. As a whole Microsoft provides these oil companies a digital transformation by using Azure cloud, AI and IoT that make these companies cost-efficient, costumer friendly and more profitable by enhancing performance.

Microsoft Dynamics AX (now Dynamics 365 for Finance & Operations) is the program under which all such services are provided and is collaborated with big companies like Hitachi, British Petroleum, Rockwell Automation, Exxon Mobil and Chevron.

Amazon

Amazon, like other tech giants, is providing AWS Machine Learning and big data tools to quickly and easily extract powerful insight structured and unstructured seismic scans data. It also focusses on accelerating digital transformation, unleash innovation to optimize production and profitability, and improve cost and operational efficiency.

Amazon is currently providing services to Shell, BP, Hess, GE Oil & Gas, Willbros and Seaoil.

But like Google, Amazon also faces criticism on collaboration with oil companies. According to The Washington Post report Amazon had threatened to fire two employees who had voiced environmental criticism against their employer.

Conclusion

The Collaboration of technology with oil & gas companies is not that bad as it sounds. It will make this industry more efficient, profitable, productive and most importantly a bit safer.

But on the other hand, this can result in drastic climate and environmental change if there are no appropriate policies and measures to control it.

For now, I can only say, we just have to wait to see what it will bring to us in the future.

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