Mon Oct 13, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Newaz, Sarfaraz, Tahmid, Md Toki, Al-Aboody, Nadia, and Islam, A. B. M. Alim Al, 2023. A ubiquitous method for predicting underground petroleum deposits based on satellite data. Scientific Reports, 13:6638, doi:10.1038/s41598-023-32054-0.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2023NatSR..13.6638N,
author = {{Newaz}, Sarfaraz and {Tahmid}, Md Toki and {Al-Aboody}, Nadia and {Islam}, A.~B.~M. Alim Al},
title = "{A ubiquitous method for predicting underground petroleum deposits based on satellite data}",
journal = {Scientific Reports},
year = 2023,
month = apr,
volume = {13},
eid = {6638},
pages = {6638},
abstract = "{The method of finding new petroleum deposits beneath the earth's surface
is always challenging for having low accuracy while
simultaneously being highly expensive. As a remedy, this paper
presents a novel way to predict the locations of petroleum
deposits. Here, we focus on a region of the Middle East, Iraq to
be specific, and conduct a detailed study on predicting
locations of petroleum deposits there based on our proposed
method. To do so, we develop a new method of predicting the
location of a new petroleum deposit based on publicly available
data sensed by an open satellite named Gravity Recovery and
Climate Experiment (GRACE). Using GRACE data, we calculate the
gravity gradient tensor of the earth over the region of Iraq and
its surroundings. We use this calculated data to predict the
locations of prospective petroleum deposits over the region of
Iraq. In the process of our study for making the predictions, we
leverage machine learning, graph-based analysis, and our newly-
proposed OR-nAND method altogether. Our incremental improvement
in the proposed methodologies enables us to predict 25 out of 26
existing petroleum deposits within the area under our study.
Additionally, our method shows some prospective petroleum
deposits that need to be explored physically in the future. It
is worth mentioning that, as our study presents a generalized
approach (demonstrated through investigating multiple datasets),
we can apply it anywhere in the world beyond the area focused on
in this study as an experimental case.}",
doi = {10.1038/s41598-023-32054-0},
adsurl = {https://ui.adsabs.harvard.edu/abs/2023NatSR..13.6638N},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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