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241.
Prabal Shankar Das Rima Chatterjee Sumangal Dasgupta Ranajit Das Debjani Bakshi Mukesh Gupta 《Geophysical Prospecting》2019,67(1):150-166
Sands belonging to Kamalapuram Formation of Paleocene-Eocene age are deposited in Cauvery basin as incised valley fill during a regressive cycle. Here we attempt to quantify the influence of diagenesis on pore-filling materials using rock physics template constrained by geohistory modelling. Primarily, porosity–velocity and acoustic impedance – the ratio of P-wave and S-wave velocity (VP/Vs) cross-plots are used as rock physics templates. Rock physics template has efficiently quantified pore-filling materials namely; contact cement and non-contact cement. The estimated contact cement and non-contact cement are correlated with conventional petrophysical logs within the selected depth interval. Further, this correlation is used to interpret the composition of pore-filling materials. Shallower depth intervals (I and II) exhibit moderate non-contact cement (4–5%) and insignificant contact cement (1–2% approx.) depositions. However, deeper interval (III) records a significant amount of pore-filling materials amounting average of 12% non-contact cement and 4% contact cement. Pore-filling materials demonstrate a positive correlation with the depth of burial. The fluid response is substantially affected by the degree of diagenesis, composition and spatial distribution of pore-filling materials. Shallower depth intervals (1770–1786 m and 1858–1878 m) are relatively more sensitive to fluid changes as it is affected by insignificant contact cement. The depth interval 1770–1786 m shows class II (oil) and class III (gas) amplitude variation with offset anomalies. The sand occurring in depth interval 1858–1878 m demonstrates class IIP (oil) and II (gas) anomaly. The deeper interval (2118–2170 m) is comparatively stiffer and demonstrates class I amplitude variation with offset (oil and gas sand) anomaly. 相似文献
242.
Saha Debasree Chatterjee Debashis Chakravarty Sanchita Roychowdhury Tarit 《Natural Resources Research》2019,28(4):1505-1520
Natural Resources Research - The bituminous-to-sub-bituminous quality feed coals of thermal power plants contain several environmental-concern trace elements (As, Se, Ni, Cr, Zn, Pb, Cu, Cd, Co and... 相似文献
243.
244.
We investigated the scenario of time-dependent diffusive interaction between dark matter and dark energy and showed that such a model can be accommodated within the observations of luminosity distanceredshift data in Supernova la(SN la)observations.We obtain constraints on different relevant parameters of this model from the observational data.We consider a homogeneous scalar field(t)driven by a k-essence Lagrangian of the form L=V(φ)F(X)with constant potential V(φ)=V,to describe the dynamics of dark energy in this model.Using the temporal behaviour of the FRW scale factor,the equation of state and total energy density of the dark fluid,extracted from the analysis of SN la(JLA)data,we have obtained the time-dependence of the k-essence scalar field and also reconstructed the form of the function F(X)in the k-essence Lagrangian. 相似文献
245.
246.
Investigations related to scientific deep drilling to study reservoir-triggered earthquakes at Koyna,India 总被引:1,自引:0,他引:1
Harsh Gupta N. Purnachandra Rao Sukanta Roy Kusumita Arora V. M. Tiwari Prasanta K. Patro H. V. S. Satyanarayana D. Shashidhar K. Mallika Vyasulu V. Akkiraju Deepjyoti Goswami Digant Vyas G. Ravi K. N. S. S. S. Srinivas M. Srihari S. Mishra C. P. Dubey D. Ch. V. Raju Ujjal Borah K. Chinna Reddy Narendra Babu Sunil Rohilla Upasana Dhar Mrinal Sen Y. J. Bhaskar Rao B. K. Bansal Shailesh Nayak 《International Journal of Earth Sciences》2015,104(6):1511-1522
247.
Swastika Chatterjee Sirshendu Bhattacharyya Surajit Sengupta Tanusri Saha-Dasgupta 《Physics and Chemistry of Minerals》2011,38(4):259-265
We report studies based on a combination of ab initio electronic structure and Monte Carlo (MC) technique on the problem of
cation partitioning among inequivalent octahedral sites, M1 and M2 in mixed olivines containing Mg2+ and Fe2+ ions. Our MC scheme uses interactions derived out of ab initio, density functional calculations carried out on measured crystal
structure data. Our results show that there is no reversal of the preference of Fe for M1 over M2 as a function of temperature.
Our findings do not agree with the experimental findings of Redfern et al. (Phys Chem Miner 27:630–637, 2000), but are in agreement with those of Heinemann et al. (Eur J Mineral 18:673–689, 2006) and Morozov et al. (Eur J Mineral 17:495–500, 2005). 相似文献
248.
Ecological consideration of trace element contamination in sediment cores from Sundarban wetland,India 总被引:2,自引:1,他引:1
E. V. Silva Filho M. P. Jonathan M. Chatterjee S. K. Sarkar S. M. Sella A. Bhattacharya K. K. Satpathy 《Environmental Earth Sciences》2011,63(6):1213-1225
This article reports on the concentration of selected trace elements (Mn, Zn, Cr, Cu, Ba, As, B, V, and Hg) and major elements
(Fe and Al) from the intertidal sediment cores from Sundarban wetland, India. This is a typical meso-macrotidal estuarine
area affected by domestic and industrial activities located upstream. The overall concentrations range is low to moderate,
indicating the environmental conditions in the outfall zone (grain size, hydrodynamic regime, and confinement), which favors
the in situ accumulation of pollutants. The extent of contamination from trace elements in Sundarban core sediments is evaluated
through a two-pronged approach: (i) by determining the metal enrichment in the sediments through the calculation of Pollution
Load Index (PLI), Enrichment Factor (EF) and Index of Geoaccumulation (I
geo), and (ii) by defining a potential level of biological risk by the use of quality criteria such as Threshold Effect Level
(TEL) and Effects Range-Low (ERL) benchmarks. On the basis of the calculated indices, sediments are particularly enriched
with Cr, Cu, B, V, and As. Those enrichments seem to be due to the fine granulometry of the regions with Fe and Mn oxi-hydroxides
being the main metal carriers. Trace Elements input to the Sundarban wetland need to be kept under strict control in future
specially with reference to As since, according to TEL and ERL benchmarks, it already appears to be associated with a potential
biological risk. 相似文献
249.
Resource estimation of a placer deposit is always a difficult and challenging job because of high variability in the deposit.
The complexity of resource estimation increases when drill-hole data are sparse. Since sparsely sampled placer deposits produce
high-nugget variograms, a traditional geostatistical technique like ordinary kriging sometimes fails to produce satisfactory
results. In this article, a machine learning algorithm—the support vector machine (SVM)—is applied to the estimation of a
platinum placer deposit. A combination of different neighborhood samples is selected for the input space of the SVM model.
The trade-off parameter of the SVM and the bandwidth of the kernel function are selected by genetic algorithm learning, and
the algorithm is tested on a testing data set. Results show that if eight neighborhood samples and their distances and angles
from the estimated point are considered as the input space for the SVM model, the developed model performs better than other
configurations. The proposed input space-configured SVM model is compared with ordinary kriging and the traditional SVM model
(location as input) for resource estimation. Comparative results reveal that the proposed input space-configured SVM model
outperforms the other two models. 相似文献
250.
Suspended sediment yield modeling in Mahanadi River,India by multi-objective optimization hybridizing artificial intelligence algorithms 总被引:2,自引:1,他引:1
River sediment produced through weathering is one of the principal landscape modification processes on earth.Rivers are an integral part of the hydrologic cycle and are the major geologic agents that erode the continents and transport water and sediments to the oceans.Estimation of suspended sediment yield is always a key parameter for planning and management of any river system.It is always challenging to model sediment yield using traditional mathematical models because they are incapable of handling the complex non-linearity and non-stationarity.The suspended sediment modeling of the river depends on the number of factors such as rock type,relief,rainfall,temperature,water discharge and catchment area.In this study,we proposed a hybrid genetic algorithm-based multi-objective optimization with artificial neural network(GA-MOO-ANN)with automated parameter tuning model using these factors to estimate the suspended sediment yield in the entire Mahanadi River basin.The model was validated by comparing statistically with other models,and it appeared that the GA-MOO-ANN model has the lowest root mean squared error(0.009)and highest coefficient of correlation(0.885)values among all comparative models(traditional neural network,multiple linear regression,and sediment rating curve)for all stations.It was also observed that the proposed model is the least biased(0.001)model.Thus,the proposed GA-MOOANN is the most capable model,compared to other studied models,for estimating the suspended sediment yield in the entire Mahanadi river basin,India.The results also suggested that the proposed GA-MOO-ANN model is unable to estimate suspended sediment yield satisfactorily at gauge stations having very small catchment areas whereas performing satisfactorily on locations having moderate to the large catchment area.The models provide the best result at Tikarapara,the gauge station location in the extreme downstream,having the largest catchment area. 相似文献