Statistical evaluation of methods for the calculation of static formation temperatures in geothermal and oil wells using an extension of the error propagation theory

The feasibility of using the more sophisticated weighted least-squares (WLS) model, as opposed to the traditional ordinary least-squares (OLS), in linear regressions of BHT data to estimate the static formation temperatures (SFT) was investigated. The most commonly used analytical methods (line-source; spherical and radial heat flow; and cylindrical heat source) were applied. Error propagation equations were derived to calculate errors in the time function of each method. These errors were combined with the BHT measurement errors to compute weighting factors for applying the WLS. Intercept uncertainties were estimated for all regressions using sets of synthetic and actual borehole logs taken from geothermal and oil applications. SFT computed with the spherical and radial heat flow method were generally greater than those from the other two methods.     

Sixteen Statistical Tests for Outlier Detection and Rejection in Evaluation of International Geochemical Reference Materials: Example of Microgabbro PM-S

A totally objective procedure involving sixteen statistical tests (a total of thirty four single or multiple outlier versions of these tests) for outlier detection and rejection in a univariate sample is applied to a data base of sixty four elements in a recently issued international geochemical reference material (RM), a microgabbro PM-S from Scotland. This example illustrates the relative importance and usefulness of these tests in processing modern geochemical data for possible outliers and obtaining mean concentration and other statistical parameters from a final normal sample of univariate data. The final mean values are more reliable (characterized by smaller standard deviations and narrower confidence limits) than those obtained earlier using an accommodation approach (robust techniques) applied to this data base. Very high quality (certified value equivalent, cve) mean data are now obtained for eleven elements as well as high quality recommended values (rv) for thirty three elements in PM-S. Earlier work using the accommodation approach failed to establish even one cve value for any of the sixty four elements compiled here. The present procedure of outlier detection and elimination is therefore recommended in the study of RMs     

Impact of satellite soundings on the simulation of heavy rainfall associated with tropical depressions

The present study is carried out to examine the impact of temperature and humidity profiles from moderate resolution imaging spectroradiometer (MODIS) or/and atmospheric infrared sounder (AIRS) on the numerical simulation of heavy rainfall events over the India. The Pennsylvania State University–National Centre for Atmospheric Research fifth-generation mesoscale model (MM5) and its three-dimensional variational (3D-Var) assimilation technique is used for the numerical simulations. The heavy rainfall events occurred during October 26–29, 2005, and October 27–30, 2006, were chosen for the numerical simulations. The results showed that there were large differences observed in the initial meteorological fields from control experiment (CNT; without satellite data) and assimilation experiments (MODIS (assimilating MODIS data), AIRS; (assimilating AIRS data); BOTH (assimilating MODIS and AIRS data together)). The assimilation of satellite data (MODIS, AIRS, and BOTH) improved the predicted thermal and moisture structure of the atmosphere when compared to CNT. Among the experiments, the predicted track of tropical depressions from MODIS was closer to the observed track. Assimilation of MODIS data also showed positive impact on the spatial distribution and intensity of predicted rainfall associated with the depressions. The statistical skill scores obtained for different experiments showed that assimilation of satellite data (MODIS, AIRS, and BOTH) improved the rainfall prediction skill when compared to CNT. Root mean square error in quantitative rainfall prediction is less in the experiment which assimilated MODIS data when compared to other experiments.     

Numerical modelling of rheological properties of landslide debris

Debris flow has caused severe human casualties and economic losses in landslide-prone areas around the globe. A comprehensive understanding of the morphology and deposition mechanisms of debris flows is crucial to delineate the extent of a debris flow hazard. However, due to inherent complex field topography and varying compositions of the flowing debris, coupled with a lack of fundamental understanding about the factors controlling the geomaterial flow, interparticle interactions and its final settlement resulted in a limited understanding of the flow behaviour of the landslide debris. In this study, a physical model was set up in the laboratory to simulate and calibrate the debris flow using PFC, a distinct element modelling-based software. After calibration, a case study of the Varunavat landslide was taken to validate the developed numerical model. Following validation with an acceptable level of confidence, several models were generated to evaluate the effect of slope height, slope angle, slope profile, and grain size distribution of the dislodged geomaterial in the rheological properties of debris flow. Both qualitative and quantitative analysis of the landslide debris flow was performed. Finally, the utility of retaining wall and their effect on debris flow is also studied with different retaining wall positions along the slope surface.

     

Soft sediments and damage pattern: a few case studies from large Indian earthquakes vis-a-vis seismic risk evaluation

India is prone to earthquake hazard; almost 65 % area falls in high to very high seismic zones, as per the seismic zoning map of the country. The Himalaya and the Indo-Gangetic plains are particularly vulnerable to high seismic hazard. Any major earthquake in Himalaya can cause severe destruction and multiple fatalities in urban centers located in the vicinity. Seismically induced ground motion amplification and soil liquefaction are the two main factors responsible for severe damage to the structures, especially, built on soft sedimentary environment. These are essentially governed by the size of earthquake, epicentral distance and geology of the area. Besides, lithology of the strata, i.e., sediment type, grain size and their distribution, thickness, lateral discontinuity and ground water depth, play an important role in determining the nature and degree of destruction. There has been significant advancement in our understanding and assessment of these two phenomena. However, data from past earthquakes provide valuable information which help in better estimation of ground motion amplification and soil liquefaction for evaluation of seismic risk in future and planning the mitigation strategies. In this paper, we present the case studies of past three large Indian earthquakes, i.e., 1803 Uttaranchal earthquake (Mw 7.5); 1934 Bihar–Nepal earthquake (Mw 8.1) and 2001 Bhuj earthquake (Mw 7.7) and discuss the role of soft sediments particularly, alluvial deposits in relation to the damage pattern due to amplified ground motions and soil liquefaction induced by the events. The results presented in the paper are mainly focused around the sites located on the river banks and experienced major destruction during these events. It is observed that the soft sedimentary sites located even far from earthquake epicenter, with low water saturation, experienced high ground motion amplification; while the sites with high saturation level have undergone soil liquefaction. We also discuss the need of intensifying studies related to ground motion amplification and soil liquefaction in India as these are the important inputs for detailed seismic hazard estimation.     

An enhanced SMA based SCS-CN inspired model for watershed runoff prediction

Incorporation of initial soil moisture (V ₀) in the Soil Conservation Service Curve Number (SCS-CN) methodology helps to avoid the sudden jumps in Curve Number (CN) and, in turn, in computed runoff. It invoked the development of an enhanced (yet simple) Soil Moisture Accounting (SMA) procedure-based-SCS-CN inspired model, by incorporating initial moisture (V ₀). Its performance is tested using a dataset of 152 small to large watersheds of USDA (total 38,169 storm events), and compared with original SCS-CN method, Mishra and Singh (Acta Geophys Polon 50(3):457–477, 2002), Michel et al. (Water Resour Res 41(2):W02011, 2005) and Singh et al. (Water Resour Manag 29(11): 4111–4127, 2015) model using four statistical indices (RMSE, R ², PBIAS and NSE) and rank grading system (RGS). The proposed model scores highest (= 691 marks out of maximum 2280 marks) (Rank I) followed by Singh et al. (Water Resour Manag 29(11):4111–4127, 2015) model with 642 marks (Rank II), Michel et al. (Water Resour Res 41(2):W02011, 2005) model with 376 marks (Rank III) and Mishra and Singh model with 362 marks (= Rank IV). The original SCS-CN model, however, performs the poorest of all with 209 marks (Rank V).     

Uranium mineralisation associated with felsic volcanism at Mohar,Shivpuri district,Madhya Pradesh

Several small lensoidal bodies of felsic volcanics are exposed in a curvilinear pattern within the brecciated granitoids of Bundelkhand Gneissic Complex (BGC) at Mohar. Sub-surface data reveals extensive presence of these felsic volcanics below the sediment of Vindhyan Supergroup. It occurs like a sheet with thickness varying from 12 m to 134 m. Its lateral extent has been traced upto 4.8 km. Multiple flows of felsic magma are identified based on colour, granularity, cross cutting relations and cyclic distribution of multiple vesicular bands along the entire thickness of felsic magma. The felsic rock contains upto 13.21% K₂O. Chemical composition of these felsic volcanics varies across the column. Petrographically and chemically all these felsic volcanics are identified as rhyolite or rhyolite tuff.     

Tectonic inferences from the statistical treatment of the remote sensing lineament fabric data associated with the Great Boundary Fault of Rajasthan,India

A systematic statistical analysis of the lineament fabric data associated with the Great Boundary Fault of Rajasthan provides 26 axes of high density girdles. Further statistical treatment of these isolated axes following the methods of analysis of directional data indicates that the lineament can be classified into genetic categories. The result indicates that the Great Boundary Fault and the Chambal Fault are genetically related and that the majority of the lineaments are the result of the reactivation of the Great Boundary Fault under a southward directed dominant stress field.     

Eddy correlation measurements of methane flux in a northern peatland ecosystem

A pilot study to measure methane flux using eddy correlation sensors was conducted in a peatland ecosystem in north central Minnesota. A prototype tunable diode laser spectrometer system was employed to measure the fluctuations in methane concentration.The logarithmic cospectrum of methane concentration and vertical wind velocity fluctuations under moderately unstable conditions had a peak nearf = 0.10 (wheref is the nondimensional frequency) and was quite similar to the cospectra of water vapor and sensible heat. Daytime methane flux during the first two weeks of August ranged from 120 to 270 mg m^-2 day^-1. The temporal variation in methane fluxes was consistent with changes in peat temperature and water table elevation. Our results compared well with the range of values obtained in previous studies in Minnesota peatlands.These field observations demonstrate the utility of the micrometeorological eddy correlation technique for measuring surface fluxes of methane. The current state-of-the-art in tunable diode laser spectroscopy makes this approach practical for use in key ecosystems.Published as Paper No. 9556, Journal Series, Nebraska Agricultural Research Division.     

Carbon dioxide,water vapor and sensible heat fluxes over a tallgrass prairie

Fluxes of CO₂, water vapor and sensible heat were measured in a grassland ecosystem near Manhattan, Kansas, employing the eddy correlation technique. The vegetation at this site is dominated by big bluestem (Andropogon gerardii), switchgrass (Panicum virgatum), and indiangrass (Sorghastrum nutans). Diurnal patterns of the energy budget components and CO₂ fluxes are evaluated on a few selected days. Influence of high atmospheric evaporative demand and low availability of soil water are examined on (a) energy partitioning, and (b) the magnitudes and patterns of atmospheric carbon dioxide exchange.Published as Paper No. 8470, Journal Series, Nebraska Agricultural Research Division.