Evidence for microbes has been detected in extreme subsurface environments as deep as 2.5 km with temperatures as high as 90 °C, demonstrating that microbes can adapt and survive extreme environmental conditions. Deep subsurface shales are increasingly exploited for their energy applications, thus characterizing the prevalence and role of microbes in these ecosystems essential for understanding biogeochemical cycles and maximizing production from hydrocarbon-bearing formations. Here, we describe the distribution of bacterial ester-linked phospholipid fatty acids (PLFA) and diglyceride fatty acids (DGFA) in sidewall cores retrieved from three distinct geologic horizons collected to 2275 m below ground surface in a Marcellus Shale well, West Virginia, USA. We examined the abundance and variety of PLFA and DGFA prior to energy development within and above the Marcellus Shale Formation into the overlying Mahantango Formation of the Appalachian Basin. Lipid biomarkers in the cores suggest the presence of microbial communities comprising Gram (+), Gram (-) as well as stress indicative biomarkers. Microbial PLFA and DGFA degradation in the subsurface can be influenced by stressful environmental conditions associated with the subsurface. The PLFA concentration and variety were higher in the transition zone between the extremely low permeability Marcellus Shale Formation and the more permeable Mahantango Formation. In contrast to this distribution, more abundant and diverse DGFA membrane profiles were associated with the Mahantango Formation. The stress indicative biomarkers like the trans-membrane fatty acids, oxiranes, keto-, and dimethyl lipid fatty acids were present in all cores, potentially indicating that the bacterial communities had experienced physiological stress or nutrient deprivation during or after deposition. The DGFA profiles expressed more stress indicative biomarkers as opposed to the PLFA membrane profiles. These findings suggest the probable presence of indigenous microbial communities in the deep subsurface shale and also improves our understanding of microbial survival mechanisms in ancient deep subsurface environments.
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PLoS One
January 2025
Chemical & Petroleum Engineering Department, United Arab Emirates University, Al Ain, United Arab Emirates.
Oil fields located in cold environments and deep-sea locations often face challenges with paraffin wax buildup in pipelines during long-distance crude oil transportation. Various strategies have been employed to address this issue, with chemical methods being the most effective and economical. However, traditional chemical inhibitors present problems due to their high toxicity and low biodegradability, leading to increased operational costs and environmental concerns.
View Article and Find Full Text PDFOpen Res Eur
December 2024
Geosciences, Universitetet i Oslo Institutt for geofag, Oslo, Oslo, 0371, Norway.
Background: Despite extensive studies of the Mesozoic-Cenozoic magmatic history of Svalbard, little has been done on the Paleozoic magmatism due to fewer available outcrops.
Methods: 2D seismic reflection data were used to study magmatic intrusions in the subsurface of eastern Svalbard.
Results: This work presents seismic evidence for west-dipping, Middle Devonian-Mississippian sills in eastern Spitsbergen, Svalbard.
Nat Commun
January 2025
Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, USA.
The upper ocean provides thermal energy to tropical cyclones. However, the impacts of the subsurface ocean on tropical cyclogenesis have been largely overlooked. Here, we show that the subsurface variabilities associated with the variation in the 26 °C isothermal depth have pronounced impacts on tropical cyclogenesis over global oceans.
View Article and Find Full Text PDFSci Rep
January 2025
Japan Agency for Marine-Earth Science and Technology, 3173-25, Showa-machi, Kanazawa-ku, Yokohama, Kanagawa, 2360001, Japan.
Subsurface seismic velocity structure is essential for earthquake source studies, including hypocenter determination. Conventional hypocenter determination methods ignore the inherent uncertainty in seismic velocity structure models, and the impact of this oversight has not been thoroughly investigated. Here, we address this issue by employing a physics-informed deep learning (PIDL) approach that quantifies uncertainty in two-dimensional seismic velocity structure modeling and its propagation to hypocenter determination by introducing neural network ensembles trained on active seismic survey data, earthquake observation data, and the physical equation of wavefront movement.
View Article and Find Full Text PDFSci Rep
January 2025
School of Water and Environment, Chang'an University, No.126 Yanta Road, Xi'an, 710054, Shaanxi, China.
Nitrate pollution is widespread environmental concern in most shallow groundwater systems. This study conducts a comprehensive investigation of shallow groundwater, deep groundwater, and surface water in a region of the Chinese Loess Plateau. Nitrate pollution in this area is severe with more than half of the shallow groundwater samples exceeding the limit of nitrate for drinking water (50 mg/L).
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