Testing page for app

In this paper, the authors show the limitation of CEOS for modeling reservoir behavior of liquid-phase black and volatile oil in highly undersaturated reservoirs.

In this paper, the authors present an open-source tool kit for the generation of microfabricated transparent models of porous media (micromodels) from image data sets using optically transparent 3D polymer additive manufacturing (3D printing or sintering).

In my view, we still do not possess a full understanding of oil production in unconventional fractured reservoirs. Our ability to forecast such assets remains elusive, even with copious amounts of analytics, mountains of data, and an arsenal of machine-learning tools.

Exponential thinking is called the “exponential surprise factor.” These underpinnings are observed on the tubular mechanics side also through data analytics, machine learning, artificial intelligence, and cognitive processes.

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This paper is part of an ongoing effort to minimize the likelihood of failure using data-mining and machine-learning algorithms.

This paper presents a set of equations that extends the approach of the original single-shouldered equation to account for a second shoulder, and helps to understand connection strengths better.

A new pulsed-eddy-current (PEC) electromagnetic (EM)-based tool called an enhanced pipe-thickness-detection tool (ePDT) has been introduced for the corrosion inspection of multiple pipes.

In its first 50 years, LNG has become the world’s fastest-growing gas supply source and is now part of an upheaval in the global energy market. Today, the sector stands at a crossroads, and the industry must adopt new thinking to address current and future needs of buyers, sellers, and consumers.

For this year’s feature, the selected papers provide innovative work flows that assist in determining productivity, reduce the effect of uncertainty conditions, and spark rejuvenation.