core analysis

This article explains what deep learning is and how it works and presents an example use case from the energy industry.

This paper presents agile technologies that integrate data management, data-quality assessment, and predictive machine learning to maximize asset value using underused legacy core data.

Researchers from Skoltech have trained a neural network to recognize rock samples in core box images efficiently. The process has sped up analysis by up to 20 times and made it possible to automate the description of rock samples.

This paper introduces a new core-analysis work flow for determining resistivity index (RI), formation factor (FF), and other petrophysical properties directly from an as-received (AR) set of core samples.

The evaluation of complex carbonate reservoirs is a challenging task, and a detailed understanding of reservoir heterogeneity is still lacking. In this study, the effect of static rock type and sample size was investigated on special-core-analysis laboratory (SCAL) data derived from capillary pressure and resistivity-index experiments at reservoir temperature and net …

The variable data quality of core analysis, the sensitivity of results to different test methods, poor reporting standards, and the reluctance of some vendors to share experience and expertise have contributed to basic mistakes and poor data quality.