The control of mineral constituents and textural characteristics on the petrophysical &amp; mechanical (PM) properties of different rocks of the Himalaya

Tandon, Ruchika Sharma; Gupta, Vikram

doi:10.1016/j.enggeo.2012.11.005

Cited by 83 publications

(20 citation statements)

References 48 publications

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“…There is no correlation between increasing P-wave velocity (V P ) and density for these intervals but a correlation between V P and SiO 2 content and V P and grain size is evident (Figure 4). Coarser grained textures and higher quartz content can be positively correlated with unconfined compressive strength (UCS) of rocks, which in turn might be correlated with P-wave velocity (Tandon and Gupta, 2013). Subsets GC, GPGC1 and GC1 show quite similar results to each other, displaying a comparatively high frequency of class changes in the upper section.…”

Section: Discussionsupporting

confidence: 66%

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

Kitzig

Kepic

Kieu

2017

Exploration Geophysics

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Abstract. New drilling, measurement-while-drilling and top-of-hole sensing technologies are being developed to overcome the challenges of exploration for new mineral deposits under deep cover. These methods will provide continuous, near-real time data collection from every drillhole in the future. Consequently, there will be a need for efficient methods of analysing and interpreting this data stream to complement the exploration strategy. We demonstrate the usefulness of cluster analysis for rapid, automated rock mass classification, and the impact of selecting different subsets of the available data on the classification results. Our study shows that only a few measurements are needed to broadly domain the intersected rock mass and highlights the importance of selecting correct input data depending on the purpose of the classification. Our analysis also indicates the potential of identifying textural and rock mechanical properties from petrophysical measurements via cluster analysis.

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Section: Discussionsupporting

confidence: 66%

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

Kitzig

Kepic

Kieu

2017

Exploration Geophysics

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“…There exists a wealth of data on the effect of extrinsic parameters on the seismic wave velocity for most of the rock types (Birch 1960;Jackson and Arculus 1984;Burke and Fountain 1990;Christensen and Mooney 1995;Parsons et al 1995;Zappone et al 2000;Kitamura et al 2003;Nishimoto et al 2005). However, study on the effect of various intrinsic parameters on seismic wave velocity is limited, particularly in the Himalaya (Gogte and Ramana 1982;Sharma et al 2011;Gupta and Sharma 2012;Tandon and Gupta 2013). This is primarily due to the mineralogical and textural heterogeneity of natural rocks which hinders the assessment of the effect of a particular parameter on the seismic wave velocity in a given rock.…”

Section: Introductionmentioning

confidence: 99%

Seismic properties of naturally deformed quartzites of the Alaknanda valley, Garhwal Himalaya, India

2015

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The present contribution summarizes the results of a study focusing on the influence of quartz microstructures on the seismic wave velocities in the quartzites of the Garhwal Himalaya. Quartzites being monomineralic were chosen for the present study so as to nullify the effect of other mineral constituents on the seismic velocity. Samples were collected from different tectonic settings of the Higher and Lesser Himalayas which are separated from one another by the major tectonic zone 'Main Central Thrust' (MCT). These are mainly Pandukeshwar quartzite, Tapovan quartzite and Berinag quartzite. The samples of Berinag quartzite were collected from near the klippen and the thrust, termed as Alaknanda Thrust. The vast differences in microstructures and associated seismic wave velocities have been noted in different quartzites. It has also been observed that quartzites of the MCT zone and Alaknanda Thrust have higher seismic velocities. This is because of their coarse-grained nature of the rocks as evidenced by the strong positive relation between seismic velocities and grain area. The coarsening is either due to the operation of grain boundary migration and grain area reduction process or high aspect ratio/shape preferred orientation. The quartzites located around Nandprayag Klippen have undergone static recrystallization and exhibit the lowest seismic wave velocities.

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“…In the research of Ghaysari et al, the prediction of production rate in diamond wire saw was investigated based on the texture characteristics of rock [10]. The relationship between the mineralogical and textural properties in quartzites, granitoids, gneisses, metabasics and dolomite rocks was studied by Tandon and Gupta [11]. The relation between the textural and mechanical properties of rock was reviewed by Ozturk and Nasuf [12].…”

Section: Introductionmentioning

confidence: 99%

Relations between Texture Coefficient and Energy Consumption of Gang Saws in Carbonate Rock Cutting Process

et al. 2018

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Texture coefficient is one of the most influential parameters in rock engineering specifications in various projects including drilling, cutting, permeability of all-section drilling devices, etc. Meanwhile, investigating and forecasting the energy consumption of saw cutters are one of the most important factors in estimating the cutting costs. The present study aims to investigate the relationship between rock texture characteristics and the amount of energy consumption of the gang saw machine in the process of cutting carbonate rocks. To evaluate the effects of texture on the rocks' engineering specifications, 14 carbonate rock samples were studied. A microscopic thin section was made from each rock specimen. Then, five digital images were taken from each section under a microscope and the values of area, environment, the largest diameter and the smallest diameter of all grains in each image were determined. Using these specifications, the coefficient of texture of all rock samples was calculated and the relationship between the texture coefficient and the rate of energy consumption of the gang saw machine was investigated for the studied samples. The study results indicated that there was a significant relation between the texture coefficient and energy consumption rate in the three groups of carbonate rocks.

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The control of mineral constituents and textural characteristics on the petrophysical & mechanical (PM) properties of different rocks of the Himalaya

Cited by 83 publications

References 48 publications

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

Seismic properties of naturally deformed quartzites of the Alaknanda valley, Garhwal Himalaya, India

Relations between Texture Coefficient and Energy Consumption of Gang Saws in Carbonate Rock Cutting Process

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