Integration of Cluster Analysis and Rock Physics for the Identification of Potential Hydrocarbon Reservoir

Natural Resources Research - Rock physics has proven its credibility for the quantitative seismic interpretation of reservoir and reservoir characterization. In this study, we implemented K-means...     

Investigation of Arsenotrophic Microbiome in Arsenic‐Affected Bangladesh Groundwater

Arsenotrophic bacteria contribute to the nutrient cycling in arsenic (As) affected groundwater. This study employed a culture‐independent and ‐dependent investigation of arsenotrophic microbiomes in As affected groundwater samples collected from Madhabpur, Sonatengra, and Union Porishod in Singair Upazila, Manikganj, Bangladesh. Total As contents, detected by Atomic Absorption Spectrophotometry (AAS) of the samples, were 47 µg/L (Madhabpur, SNGW‐1), 53 µg/L (Sonatengra, SNGW‐2), and 12 µg/L (Union porishod, SNGW‐3), whereas the control well (SNGW‐4; depths >150 m) showed As content of 6 µg/L. Denaturing Gradient Gel Electrophoresis (DGGE) analysis of the amplified 16S rRNA gene from As‐affected groundwater samples revealed the dominance of aerobic bacteria Pseudomonas within heterogeneous bacterial populations. DGGE of heterotrophic enrichments supplemented with arsenite [As (III)] for 4 weeks showed the dominance of Chryseobacterium, Flavobacterium, and Aquabacterium, whereas the dominant genera in that of autotrophic enrichments were Aeromonas, Acinetobacter, and Pseudomonas. Cultured bacteria retrieved from both autotrophic and heterotrophic enrichments were distinguished into nine genotypes belonging to Chryseobacterium, Acinetobacter, Escherichia, Pseudomonas, Stenotrophomonas, Janibacter, Staphylococcus, and Bacillus. They exhibited varying range of As(III) tolerance from 4 to 27 mM. As(III) transformation potential was confirmed within the isolates with oxidation rate as high as 0.143 mM/h for Pseudomonas sp. Sn 28. The arsenotrophic microbiome specifies their potential role in groundwater As‐cycling and their genetic information provide the scientific basis for As‐bioremediation.     

Rock Physics Modeling and Reservoir Characterization to Estimate Hydrocarbon Zone of Cretaceous and Paleocene Strata and Subsurface Stratigraphic Correlation of Sulaiman Fold Belt to Sulaiman Depression

Doklady Earth Sciences - The research work involves rock physics modeling and reservoir characterization of Suliman fold belt to sulamain fold depression. This area is a brighter zone for...     

Reproductive biology of blood cockle <Emphasis Type="Italic">Anadara granosa</Emphasis> (Bivalvia: Arcidae) in the northern region of the Strait of Malacca

A study on the reproductive cycle of the blood cockle Anadara granosa (Bivalvia: Arcidae) was conducted at three different areas in the northern region of the Strait of Malacca. A total of 1,920 samples of adult A. granosa (38–71 mm length) were collected from June 2009 until September 2010. Qualitative techniques (gonadal microscopic fresh smear test and histology analysis) as well as quantitative techniques (analysis of condition index and gonadal index) were used to predict monthly gonadal development stages of A. granosa. The gonadal index of A. granosa from Banda Aceh (Indonesia) (r = 0.469, P > 0.05) and Pulau Pinang (Malaysia) (r = 0.123, P > 0.05) did not show any correlation to their condition index, whereas the gonadal index of A. granosa from Lhokseumawe (Indonesia) (r = 0.609, P < 0.05) showed moderate positive correlation to the condition index. During the 16 month sampling period, four reproductive cycles were observed: each from three to six months. The process of releasing gametes is termed dribble spawning, and is the same in all populations. The principle component analysis (PCA) indicated that A. granosa reproduction was affected by interaction between internal physiological factors and indigenous environmental factors. In all sampling areas, phytoplankton density played a key role in the reproductive cycle in A. granosa. Information on the reproductive biology of this species is essential for species management and to improve the sustainability practices of the fisheries industry. These findings will provide basic information on the biology of the blood cockle A. granosa for stock management in the region.     

Coseismic slip distribution of the 14 January 2021 Mamuju-Majene,Sulawesi, earthquake derived from GPS data

Natural Hazards - The 14 January 2021 Mw 6.2 Mamuju-Majene earthquake occurred in West Sulawesi, Indonesia, preceded by three earthquakes with Mw 5.7, Mw 5.2 and Mw 4.3. The fault responsible for...     

Machine learning-based thermal anomalies detection from MODIS LST associated with the Mw 7.7 Awaran,Pakistan earthquake

Natural Hazards - Satellite based thermal anomaly occurs as a substantial precursor for strong earthquakes, as the need for earthquake precursor detection has very important for impending main...     

Assessment of PM<Subscript>2.5</Subscript> chemical compositions in Delhi: primary vs secondary emissions and contribution to light extinction coefficient and visibility degradation

Haze-fog conditions over northern India are associated with visibility degradation and severe attenuation of solar radiation by airborne particles with various chemical compositions. PM_2.5 samples have been collected in Delhi, India from December 2011 to November 2012 and analyzed for carbonaceous and inorganic species. PM₁₀ measurements were made simultaneously such that PM_10–2.5 could be estimated by difference. This study analyzes the temporal variation of PM_2.5 and carbonaceous particles (CP), focusing on identification of the primary and secondary aerosol emissions, estimations of light extinction coefficient (b_ext) and the contributions by the major PM_2.5 chemical components. The annual mean concentrations of PM_2.5, organic carbon (OC), elemental carbon (EC) and PM_10–2.5 were found to be 153.6 ± 59.8, 33.5 ± 15.9, 6.9 ± 3.9 and 91.1 ± 99.9 μg m^?3, respectively. Total CP, secondary organic aerosols and major anions (e.g., SO₄ ^2? and NO₃ ^?) maximize during the post-monsoon and winter due to fossil fuel combustion and biomass burning. PM_10–2.5 is more abundant during the pre-monsoon and post-monsoon. The OC/EC varies from 2.45 to 9.26 (mean of 5.18 ± 1.47), indicating the influence of multiple combustion sources. The b_ext exhibits highest values (910 ± 280 and 1221 ± 371 Mm^?1) in post-monsoon and winter and lowest in monsoon (363 ± 110 and 457 ± 133 Mm^?1) as estimated via the original and revised IMPROVE algorithms, respectively. Organic matter (OM =1.6 × OC) accounts for ~39 % and ~48 % of the b_ext, followed by (NH₄)₂SO₄ (~21 % and ~24 %) and EC (~13 % and ~10 %), according to the original and revised algorithms, respectively. The b_ext estimates via the two IMPROVE versions are highly correlated (R² = 0.95, root mean square error = 38 % and mean bias error = 28 %) and are strongly related to visibility impairment (r = ?0.72), mostly associated with anthropogenic rather than natural PM contributions. Therefore, reduction of CP and precursor gas emissions represents an urgent opportunity for air quality improvement across Delhi.     

Subsurface Structure Analysis of the Southern North Sea

Geotectonics - The subsurface structure analysis of the Southern North Sea through the interpretation of 2D seismic data set (SNSTI-NL-87 and SNST-NL-83) is carried out. The subsurface structural...