PVT Musings: Why I Started Using Python To Solve Petroleum Engineering Problems
As the oil and gas industry moves more into the machine learning space, Python-conversant petroleum domain specialists will prove to be increasingly valuable to organizations.
Artificial Intelligence Explained for Non-Computer Scientists
This article gives a succinct overview of artificial intelligence, its emerging opportunities, prospects, and challenges, and concludes with recommendations to accelerate the admission of AI into workflows.
The Nuts and Bolts of the Digital Oil Field
The term digital oil field has become a buzzword in the oil and gas industry these days, with the mention of it bringing up pictures of computers, flashy screens, and programming to mind. In reality, the concept goes beyond these.
Digitalization in the Oil and Gas industry–The Limitless Future
Digitalization is going to impact every industry in the next 5–10 years. The oil and gas industry needs a lot more data scientists today than a year ago, so a person with the right qualifications and experience is the need of the industry today.
What Will Your Job Look Like in the Future? Three Bold Predictions
The TWA HR Discussion team explores three trends that will change the way we will work in the future.
The Other Side of the Table—Are You an Engineer Who Could Thrive in Management Consulting?
Management consulting may be a rewarding career for you too. A few minutes spent reading this article may serve you well in determining whether this career option deserves your time and energy.
What's the Difference Between Data Science, Machine Learning, and Artificial Intelligence?
The data science, machine learning, and artificial intelligence fields do have a great deal of overlap, but they are not interchangeable.
The Value of Estimating—Advice for New Engineers
Value is not realized by producing precise numerical answers to a problem. Value is added by providing sound opinions and judgments about which action should be taken.
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