Saudi Arabian Oil Company

Tiffany Dawn McAlpin

Shannon Lee Eichmann

Sebastian Csutak

Max Deffenbaugh

David J Jacobi

Weichang Li

Peng Lu

Shuo Zhang

Dave Cantrell

Susan Agar

A method of analyzing a geologic sample includes illuminating the geologic sample with a light beam and capturing an image of the geologic sample on a hyperspectral camera as a greyscale image, R-G-B color space image, or both, thereby collecting spectra having mid-wave infrared wavelengths or ultraviolet wavelengths reflected from a surface of the geologic sample. The method further includes processing the image to transform the image from the R-G-B color space, greyscale image, or both, and analyzing the Intensity to determine mineralogy, organic content, hydrocarbon presence, or combinations thereof of the geologic sample.

Methods of geologic sample analysis

Systems, apparatuses, and computer-implemented methods are provided for the sensing and prediction of properties of source rock. Disclosed here is a method of predicting the maturity of a source rock that includes obtaining a plurality of data of a sample source rock from a plurality of data acquisition devices placed in vicinity of the sample source rock and analyzing the received data using a predictive correlation to determine maturity of the sample source rock. The predictive correlation is generated by applying a machine learning model to correlate the plurality of data acquired from a plurality of representative source rocks with a plurality of properties of the plurality of representative source rocks.

Collaborative sensing and prediction of source rock properties

Petrographic data of a carbonate reservoir in a subterranean region is received. Mud content of the carbonate reservoir is determined based on the petrographic data. A depositional porosity of the carbonate reservoir is computed based on the mud content. An amount of cementation of the carbonate reservoir is determined. A porosity loss by compaction of the carbonate reservoir is determined based on the mud content and the amount of cementation of the carbonate reservoir. A post-compaction porosity of the carbonate reservoir is computed based on the depositional porosity, the mud content, the amount of cementation, and the porosity loss by compaction.

Predicting carbonate porosity based on petrographic data

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Richmond, TX, United States of America

Tiffany Dawn McAlpin