Testing page for app

A study by a real-time monitoring company showed that many coiled-tubing strings are retired with a lot of life left in them. It suggested companies could lower costs by using pipe for a longer time and could benefit from multicompany studies showing how their decisions compare to the competition.

The biennial SPE Offshore Europe conference will explore a diverse set of topics, including the application of digital technologies and preparing for a low-carbon energy future and ongoing work around standardization and decommissioning.

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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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.

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.