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Depositional mechanism of Fort Member Sandstone (Early-Late Bathonian), Jaisalmer Formation, Western Rajasthan: insights from granulometric analysis

Depositional mechanism of Fort Member Sandstone (Early-Late Bathonian), Jaisalmer Formation,... GEOLOGY, ECOLOGY, AND LANDSCAPES 2021, VOL. 5, NO. 2, 119–135 INWASCON https://doi.org/10.1080/24749508.2020.1833642 RESEARCH ARTICLE Depositional mechanism of Fort Member Sandstone (Early-Late Bathonian), Jaisalmer Formation, Western Rajasthan: insights from granulometric analysis a a a b a Faiz Ahmad , M. A. Quasim , A. H. M. Ahmad , S. M. Rehman and S. Asjad a b Department of Geology, Aligarh Muslim University, Aligarh, India; Department of Computer Engineering, Aligarh Muslim University, Aligarh, India ABSTRACT ARTICLE HISTORY Received 2 March 2020 Granulometric analysis is an imperative tool used to reveal the hydrodynamic conditions, mode Accepted 4 October 2020 of transportation and deposition of siliciclastic sediments. Forty-two samples of Fort Member Sandstone of the Jaisalmer Formation, Western Rajasthan were selected and studied with the KEYWORDS help of detailed granulometric analysis which include both graphical as well as mathematical Granulometric analysis; moment methods. Micro textures were recognized as chatter marks, curved and straight steps, hydrodynamic condition; grooves, upturned plates in association with V impact pits and triangular solution pits suggest- depositional environment; ing the predominance of mechanical activities over the chemical dissolution. The analysis Fort Member; Jaisalmer Formation shows the sandstone is coarse-grained, very well sorted, very fine to fine skewed and very platykurtic to platykurtic in nature. The dominance coarse grains give an indication of high energy level and almost stable as there is not much variation in the grain-size. Bivariate plots show that the sediments were deposited in beach sub-environment which was also confirmed by the linear and multigroup discriminant analysis. C-M plot shows that the sediments were transported by rolling and log-log plot also confirms the transportation by the traction processes. These features describe the sediments deposited by the fluvial process dominated by tractive current pattern in a shallow marine depositional environments. Introduction and geometry, grain-size analysis becomes an essential tool for a better understanding of the depositional Grain-size parameters are fundamental tool for identi- environment as they are mostly dependent on the syn- fying the sedimentary environments such as beach, depositional processes (Reading, 1996). dune and river and some other divisions of continental The pericratonic Jaisalmer basin situated to the west of shelf through graphic as well as mathematical moment Aravalli axis on the western part of the Indian peninsula, methods used along with other textural properties. formed the eastern most part of the Indo-Arabian Grain-size is the utmost important property of the Geological Province (Pandey & Choudhary, 2007). The sediments, affecting their entrainment, transport and basin has attracted the attention of geologists and deposition. Therefore, grain-size analysis offers signifi - palaeontologists due to its rich record of well-preserved cant evidences to the sediments provenance, transport Jurassic to Tertiary fossils. Recently, the basin has also history and depositional conditions (Ghaznavi et al., been proved its potential for oil and gas reserves and 2019; Quasim et al., 2020; Sahu, 1964; Visher, 1969). categorized category-I (producing) basin by Directorate Despite the usefulness of grain-size analysis in stu- General of Hydrocarbons (DGH). Therefore, the dies of siliciclastic sedimentary rocks, there are various research on the sedimentary features of the Jaisalmer limitations for grain-size parameters also. These limita- Formation may understand the petroleum geology char- tions include changes or subsequent modifications that acteristics and tectonic evolution history in this area. a framework particle undergoes when it is subjected to The Jurassic Jaisalmer basin is predominantly diagenesis (Ghaznavi et al., 2019; Ghosh & Chatterjee, a carbonate facies and inter-bedded with calcareous sand- 1994). Irrespective of these restrictions, parameters of stone and shale deposited under marginal marine to grain-size analysis have been used successfully in pre- occasional shelf lagoon conditions of deposition which vious studies and proved to be useful in interpreting has huge hydrocarbon generation potential and reservoir provenance, mechanism of transportation and environ- potential (Ahmad et al., 2020b; Pandey & Maurya, 2020). ment of deposition (Ahmad et al., 2017a; Cheetham Previous studies mainly focussed on the sedimentological et al., 2008; Ghaznavi et al., 2019; Kanhaiya et al., attributes like tectono-provenance (Ahmad et al., 2019), 2017; Quasim et al., 2020; Kanhaiya & Singh, 2014; diagenetic evolution (Ahmad et al., 2017b; Mahender & Weltje & Prins, 2007). In aggregation with different Banerji, 1990) and depositional environment (Ahmad sedimentological factors like structures of sedimentary et al., 2020a, 2017a; Bhat & Ahmad, 2013; Pandey et al., origin and their associations, palaeoflow, fossil content CONTACT Faiz Ahmad faizgeology@gmail.com Department of Geology, Aligarh Muslim University, Aligarh, India © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 120 F. AHMAD ET AL. 2006, 2006b) but the research on the sedimentary hydro- changing through time. The Precambrian igneous dynamic conditions of Fort Member Sandstone has not (Malani volcanics)/metamorphic rocks form the base- started yet. Sandstone grain-size characteristics are of ment for the later deposited sedimentary sequences of great significance in the analysis of sedimentary hydro- Western Rajasthan Basin, but they are exposed in only dynamic conditions (Ghaznavi et al., 2019; Ghosh & few locations around Pokhran, Jodhpur and Barmer. Chatterjee, 1994; Quasim et al., 2020). Based on the The Jaisalmer basin covers entire district of analysis of sandstone grain-size characteristics (both gra- Jaisalmer in West Rajasthan and neighbouring phical as well as mathematical moment methods) of the Kachchh basin in the south with depth of the base- Fort Member of the Jaisalmer Formation, Western ment 10,000 m near the Indo-Pak border (Figure 1 Rajasthan, the evolution history of sedimentary hydro- (a)). It is a pericratonic basin positioned at the west of dynamic conditions of the Fort Member Sandstone in the Aravalli axis on the western part of the Indian this region can be reconstructed. craton with dip direction in the north-west. It repre- sents the Tethyan margin during the Jurassic, when it was located at about 23 south of the equator. On the Geological background basis of geophysical investigations conducted by ONGC, four geostructural units are found (Figure 1 The Rajasthan shelf has been divided into four units (b)) which are Mari-Jaisalmer arch, the synclinal namely: the Jaisalmer basin, the Bikaner-Nagaur Shahgarh sub-basin, the Kishangarh sub-basin and basin, the Barmer-Sanchor basin and the Pokharan- the Miajlar sub-basin (Raghavendra Rao, 1972; Singh Nachana high but owing to continuous alteration of et al., 2005; Sinha et al., 1993). Sedimentation in the tectonic setting and palaeogeographic conditions the Jurassic Jaisalmer basin starts with widely spread extent of these basins on Rajasthan shelf kept on Figure 1. (a) Outline map of India depicting the location of the Jaisalmer basin; (b) tectonic map of the Jaisalmer basin (after Biswas, 1982; Misra et al., 1993); (c) geological map of Jaisalmer basin showing outcrop of the Jaisalmer Formation, Western Rajasthan (after Jodhawat & Kachhara, 2000). GEOLOGY, ECOLOGY, AND LANDSCAPES 121 deltaic, fluvial or lacustrine sediments in the basal Darbar and Jaithawai road. Thin-sections were prepared Lathi Formation (Srivastava, 1966) followed by mar- for these forty-two sandstone samples for their textural ginal marine sediments which in turn then followed by analysis. On an average about 200–300 grains were a series of various non-marine, marginal marine and counted in each thin section following the method of fully marine sediments. Lithostratigraphically, these Chayes (1949). Scanning Electron Microscope (SEM) deposits are classified into Jaisalmer, Baisakhi and images were used for the identification of ultra-textures Bhadasar formations (Das Gupta, 1975; Pandey, present in the quartz grains of the Fort Member. Quartz Fürsich, Sha et al., 2009; Pandey et al., 2006, 2005, grains were visually examined using JEOL JSM-5800 LV 2006b). Geologically, the Jaisalmer basin is repre- scanning electron microscope at University Sophisticated sented by a sequences of shale, siltstone, sandstone Instrument Facility (USIF), AMU, Aligarh. Phi-scale pro- and limestone. posed by Krumbein (1934), was used and the size data The depositional settings in the Jaisalmer basin fluc - were grouped in half-phi scale intervals. Cumulative fre- tuate from fluvial/lagoonal, delta front, shoreface to quency curves were plotted on a log probability scale. offshore environment with shifting water energy and Grain diameters in phi-unit that are represented by ϕ5, salinity (Ahmad et al., 2017a; Pandey et al., 2006, ϕ16, ϕ25, ϕ50, ϕ75, ϕ84 and ϕ95 percentiles were ana- 2006b). Although based on lithostratigraphic studies, lysed from the size frequency curves. Using these values it is revealed that there is cyclicity in sedimentation various statistical parameters are calculated like mean present in all the formations but it is most prominent size, standard deviation, skewness and kurtosis. These and well displayed in the Jaisalmer Formation parameters were calculated using both the graphical (JaiKrishna, 1987; Pandey & Fürsich, 1994; Pandey method as well as moment measures method. et al., 2009; Pandey et al., 2006, 2006b). According to calculations given by Krumbein and Jaisalmer Formation has been further classified Pettijohn (1938), Folk (1968, 1980), and McBride lithostratigraphically into the Hamira, Joyan, Fort, (1971), these statistical parameters have been classified. Badabag, Kuldhar and Jajiya members in increasing The mathematical method of moments used in the order (Figure 1(c)) (Das Gupta, 1975). Except for the present study was introduced by Krumbein and Phanerozoic outcrops overlying the Precambrian Pettijohn (1938). Various bivariate plots are plotted basement in the eastern and southern parts, whole of between these values to establish the interrelationships. the basin is covered by sand dunes or sands of Thar Linear Discriminate Analysis (LDA) was done to Desert. Pareek (1984) estimated the thickness of interpret the depositional sub-environment using fol- Jaisalmer Formation as 300 m. The sub-surface thick- lowing formula after Sahu (1964): ness as observed by drilling is more than 600 m (Das Y = −3.5688 Mean +3.7016 (Standard Gupta, 1975). deviation) − 2.0766 Skewness +3.1135 Kurtosis The best exposure of studied Fort Member is found This formula is used to distinguish between aeolian along the Jaisalmer fort escarpments. It is widest in north- and beach sub-environment. ern part and get narrower progressively towards south. It For beach sub-environment; Y > −2.7411 contains fine- to medium-grained sandstones, oolitic, For aeolian sub-environment; Y < −2.7411 sandy, bioturbated and fossiliferous nature of limestones, Y = 15.6534 Mean +65.7091 (Standard and cross-bedded sandy limestones (Mahender & Deviation) + 18.1071 Skewness +18.5043 Kurtosis Banerji, 1990; Pandey & Dave, 1998; Pandey et al., Y is used to delineate between beach and shallow- 2006). The sandstones are calcareous in nature and pos- marine environment. sess current bedding in upper part. The limestones are For beach sub-environment Y < 65.36 yellowish brown in colour, compact and fossiliferous. For shallow-marine sub-environment Y � 65.36 These limestones also have thin inter-beds of limestone Y = 0.2852 Mean −8.7604 (Standard that possess brachiopod and mollusca shell fragments. It Deviation) − 4.8932 Skewness +0.0428 Kurtosis contains various taxa of brachiopods, echinoids, gastro- It is used to distinguish between shallow-marine pods, corals, bryozoans and foraminifers. On the basis of and fluvial sub-environment. the stratigraphic position and inter-basinal correlation of For shallow-marine sub-environment Y > −7.4190 marker-beds (Pandey et al., 2009) the age of Fort Member For fluvial sub-environment Y < −7.4190 is interpreted as Early Bathonian to Middle/Late Y 0.7215 Mean +0.403 (Standard 4 = Bathonian. Deviation) + 6.7322 Skewness +5.2927 Kurtosis It is used to delineate between fluvial and marine turbidity sub-environment. Materials and methodology For marine turbidity sub-environment Y > 10.00 For fluvial sub-environment Y < 10.00 Three lithostratigraphic sections representing the Multigroup discriminant analysis (Sahu, 1983) was Fort Member of Jaisalmer Formation were measured carried out to differentiate between various deposi- (Figure 2). Forty-two fresh samples of sandstone were tional environments using the formula; collected from the outcrop in Near Fort scarp, Shiv Madi 122 F. AHMAD ET AL. Figure 2. Lithological succession showing the lithology of Fort Member of Jaisalmer Formation, Western Rajasthan. V 0.48048 Mean +0.06231 Standard Deviation 1996; Whalley & Krinsley, 1974). Surface textures of 1 = +0.40602 Skewness +0.44413 Kurtosis quartz sand grains have also been used to identify the V 0.24523 Mean −0.45905 Standard Deviation provenance and mode of origin of various detrital 2 = +0.15715 Skewness +0.83931 Kurtosis sediments. SEM analysis of quartz sand grains from Energy variation and fluidity factors are dependent Fort Member Sandstone has shown various surface on different processes and the depositional environ- features such as chatter marks, curved and straight ment (Sahu, 1964). steps, grooves, upturned plates in association with V impact pits and triangular solution pits. Chatter marks are series of sub-parallel indenta- Results tions which is formed when part of a grain skips across another grain (Figure 3(a)). Grooves are caused by Surface features on quartz sand grains drawing of sharp edge of a grain across another Scanning Electron Microscopy (SEM) of quartz grains (Krinsley & Margolis, 1969), they are further modified has paved way for discrimination between various by the fracture and solution activities (Figure 3(b)). sedimentary environments depending on their surface These quartz grains also show curved and straight textures (Krinsley & Donahue, 1968; Krinsley & steps in association with silica precipitation (Figure 3 Doornkamp, 2011; Krinsley & Margolis, 1969). The (c)). Small V-shaped indentations (Figure 3(d,f)) are ultra-textures provide valuable details about the dif- formed by grain to grain collision in an aqueous med- ferent processes which were operational during the ium (Krinsley & Margolis, 1969). Surfaces of the transportation and after the deposition of grains quartz grains from the Fort Member Sandstone exhibit (Krinsley & Funnell, 1965; Mahaney, 1998; Newsome silica precipitation features like irregular plates and & Ladd, 1999) and the parameters have been set to cavity filling. Furthermore, excess silica is pressed distinguish between the mechanical and chemical fea- over quartz grain surface in non-oriented patterns tures (Krinsley & Donahue, 1968; Rahman & Ahmed, (Figure 3(e)). It may be explained by the movement GEOLOGY, ECOLOGY, AND LANDSCAPES 123 Figure 3. Surface textures in quartz sand grains from Fort Member Sandstone as observed by SEM. (a) chatter Marks, (b) grooves, (c) curved and straight steps, (d) upturned plate in association with V-shaped pits, (e) silica plastering association with triangular pits and irregular plates, and (f) V-shaped pits. of grains across one another under high pressure the distribution of curves around 0.4ϕ for FS samples (Krinsley & Doornkamp, 2011). On the basis of results (Figure 4(a)) and distribution of curves around 0.35ϕ for from SEM studies it is concluded that the studied JS samples (Figure 4(b)) although few samples show samples have been deposited in shallow marine envir- different frequency curve distribution around 0.5ϕ. This onment as it is reworked by waves and tides to form indicates all of the samples are predominantly unimodal these beach sand deposits. The dominance of mechan- in nature and have sediments of pure sand type without ical activities over the chemical dissolution generally any mixing of silt particles. The unimodality is also indi- reflects medium to high energy nearshore environ- cative of more or less consistent depositional process ments. Also the roughness of surfaces and edges of during the time of sediment settling. some quartz grains in Figure 3(c,d) might reflect dif- In some of the samples (FS-11, JS 26, 27, 41, 42, 43) ferential chemical weathering that may be related to bimodality can also be seen with samples showing differences in chemical resistance within the grains peaks at around 1.4ϕ (Figure 4(b)). The bimodality is (Krinsley & Doornkamp, 2011). attributed to mixing of different size grains, variation in velocity of depositional processes and the difference in mode of transportation. Samples showing unimod- Frequency curves ality and bimodality are shown in Figure 5(a,d). Phi values are plotted against the frequency distribution Phi scales are plotted against the cumulative frequen- of each grain-size in the frequency curves. These curves cies (Figure 6), giving an idea about various modes of show modality or predominance of a particular size class. sediment transportation, deposition and their impor- These frequency curves are dominantly unimodal with tance in the genesis of sandstones. Sorting of the 124 F. AHMAD ET AL. Figure 4. Grain-size distribution curves for the Fort Member Sandstone. (a) for FS samples and (b) for JS samples. Figure 5. Four different types of textural attributes recognized based on the thin-section distribution of quartz grains (I-bimodal, II- unequal bimodal, III-unimodal unequal, and IV-unimodal equal). (a) bimodal unequal quartz grains are showing pore spaces filled by cementing materials (carbonate and iron); (b) bimodal equal quartz grains showing pore spaces filled by cementing materials (carbonate and iron); (c) unimodal unequal can be attributed to moderate to well sorting, weak alteration of unstable grains and a moderate degree of cementation and compaction. (d) unimodal equal are mainly found in well-sorted highly mature quartzarenites. Figure 6. Cumulative frequency curve showing trends of the Fort Member Sandstone. (a) for FS samples and (b) for JS samples. GEOLOGY, ECOLOGY, AND LANDSCAPES 125 samples can be obtained by the slope of middle portion (2) Graphic Mean Size (Mz)-Mean size is indicative of the curve. Poor sorting is indicated by a broad and of the average particle size. In studied samples Mz gentle gradient of the curve which also indicates low ranges from 0.04 to 0.11 with an average of 0.06 kinetic energy and velocity. A very steep slope, whereas, (Table 1). It implies that all of studied samples are is indicative of good sorting, high kinetic energy and coarse-grained sands. There is minute variability high velocity. All of the studied samples are coarse in the grain size of samples which make these grained, and based on the steepness of the gradient of samples very well sorted. the cumulative frequency curves can be regarded as very (3) Standard Deviation (σ )-It depicts the sorting or well sorted (Figure 6). uniformity of grains which in turn indicates the prevailing energy conditions at the time of trans- portation and deposition. Studied samples are Statistical parameters ranging from 0.09 to 0.24 with an average of 0.16 (Table 1) which indicate that all of the samples are Graphical method very well sorted which gives an indication of (1) Inclusive Graphic Median (ϕ )-Median smooth and constant current flow and velocity. corresponds to the 50 percentile, half of (4) Graphic Skewness (SK )-Measures the degree to the particles are coarser and the other half which a cumulative curve approach symmetry in are finer. Studied samples range from 0.12 terms of predominance of fine- or coarse – to 0.34, with an average of 0.19 (Table 1). grained fractions. The value of skewness in stu- Based on the data all of studied samples are died samples range from 0.09 to 0.42 with an coarse grained. Table 1. Statistical parameters of grain-size distribution in Fort Member Sandstone of Jaisalmer Formation, Western Rajasthan, calculated by the graphical method. Φ50, Mz, σ in phi units. Standard Verbal S. no. Median (ᶲ50) Mean size (Mz) Verbal limit deviation (σ ) limit Skewness (Sk ) Verbal limit Kurtosis (K ) Verbal imit C M 1 1 G JS-20 0.23 0.27 CS 0.21 VWS 0.29 FS 0.71 PK 995.16 852.63 JS-21 0.17 0.18 CS 0.14 VWS 0.20 FS 0.68 VPK 997.23 888.84 JS-22 0.22 0.25 CS 0.20 VWS 0.29 FS 0.68 VPK 997.23 858.57 JS-23 0.26 0.29 CS 0.22 VWS 0.24 FS 0.91 PK 997.23 835.09 JS-24 0.19 0.22 CS 0.19 VWS 0.33 VFS 0.56 VPK 999.31 876.61 JS-25 0.24 0.27 CS 0.20 VWS 0.24 FS 0.83 PK 996.54 846.75 JS-26 0.16 0.17 CS 0.14 VWS 0.22 FS 0.61 VPK 997.23 895.03 JS-27 0.27 0.31 CS 0.25 VWS 0.32 VFS 0.78 PK 996.54 829.32 JS-28 0.32 0.34 CS 0.23 VWS 0.13 FS 1.74 VLK 993.09 801.07 JS-29 0.21 0.24 CS 0.19 VWS 0.32 VFS 0.61 VPK 995.16 864.54 JS-30 0.32 0.33 CS 0.23 VWS 0.09 NSS 2.52 VLK 995.16 801.07 JS-31 0.2 0.22 CS 0.18 VWS 0.27 FS 0.66 VPK 993.78 870.55 JS-32 0.24 0.27 CS 0.21 VWS 0.29 FS 0.74 PK 997.23 846.75 JS-33 0.22 0.25 CS 0.20 VWS 0.30 FS 0.66 VPK 997.23 858.57 JS-34 0.2 0.24 CS 0.22 VWS 0.42 VFS 0.52 VPK 995.16 870.55 JS-35 0.25 0.29 CS 0.23 VWS 0.32 VFS 0.73 PK 997.23 840.90 JS-36 0.22 0.26 CS 0.20 VWS 0.33 VFS 0.62 VPK 995.16 858.57 JS-37 0.28 0.32 CS 0.24 VWS 0.27 FS 0.88 PK 995.16 823.59 JS-38 0.34 0.36 CS 0.24 VWS 0.13 FS 1.84 VLK 997.23 790.04 JS-39 0.22 0.26 CS 0.22 VWS 0.36 VFS 0.61 VPK 997.23 858.57 JS-40 0.2 0.23 CS 0.18 VWS 0.31 VFS 0.58 VPK 996.54 870.55 JS-41 0.13 0.13 CS 0.09 VWS 0.10 NSS 0.95 MK 999.31 913.83 JS-42 0.13 0.13 CS 0.09 VWS 0.10 NSS 1.00 MK 997.23 913.83 JS-43 0.12 0.13 CS 0.09 VWS 0.17 FS 0.52 VPK 997.23 920.19 JS-44 0.13 0.14 CS 0.09 VWS 0.11 FS 0.86 PK 998.61 913.83 JS-45 0.12 0.12 CS 0.09 VWS 0.09 NSS 0.99 MK 997.23 920.19 FS-1 0.13 0.14 CS 0.09 VWS 0.14 FS 0.69 VPK 993.78 913.83 FS-2 0.14 0.15 CS 0.11 VWS 0.16 FS 0.67 VPK 998.61 907.52 FS-3 0.15 0.17 CS 0.13 VWS 0.24 FS 0.53 VPK 998.61 901.25 FS-4 0.16 0.18 CS 0.13 VWS 0.23 FS 0.57 VPK 995.16 895.03 FS-5 0.14 0.15 CS 0.11 VWS 0.20 FS 0.55 VPK 999.31 907.52 FS-6 0.14 0.15 CS 0.11 VWS 0.17 FS 0.63 VPK 997.23 907.52 FS-7 0.13 0.14 CS 0.10 VWS 0.20 FS 0.50 VPK 999.31 913.83 FS-8 0.18 0.20 CS 0.16 VWS 0.29 FS 0.57 VPK 997.23 882.70 FS-9 0.15 0.17 CS 0.13 VWS 0.23 FS 0.54 VPK 999.31 901.25 FS-10 0.12 0.13 CS 0.09 VWS 0.14 FS 0.64 VPK 995.16 920.19 FS-11 0.15 0.17 CS 0.12 VWS 0.20 FS 0.60 VPK 997.23 901.25 FS-12 0.13 0.14 CS 0.10 VWS 0.16 FS 0.61 VPK 998.61 913.83 FS-13 0.14 0.15 CS 0.11 VWS 0.16 FS 0.67 VPK 997.23 907.52 FS-14 0.14 0.15 CS 0.09 VWS 0.40 VFS 0.24 VPK 999.31 907.52 FS-15 0.14 0.15 CS 0.10 VWS 0.14 FS 0.74 PK 998.61 907.52 FS-16 0.13 0.14 CS 0.10 VWS 0.19 FS 0.53 VPK 996.54 913.83 Avg. 0.19 0.21 CS 0.16 VWS 0.23 FS 0.76 PK 996.97 879.10 CS = Coarse Sand, VWS = Very Well Sorted, NSS = Near Symmetrical Skewed, FS = Fine Skewed, CSK = Coarse Skewed, VFS = Very Fine Skewed, VPK = Very Platykurtic, PK = Platykurtic, MK = Mesokurtic, LK Leptokurtic, VLK = Very Leptokurtic = 126 F. AHMAD ET AL. nd average of 0.23 (Table 1) which gives an indication (2) 2 Moment-Standard Deviation (σ )-Its value that most of the samples are fine skewed followed in studied samples range from 0.14 to 0.32 with by very fine skewed and nearly symmetrical an average of 0.24 (Table 2). It is a clear indica- skewed. tion of grains being very well sorted which is (5) Graphic Kurtosis (K )-Kurtosis is measure of also an indication of uniform energy condition peakedness in a curve. Values of Kurtosis in prevailing at the time of deposition. rd studied sample ranges from 0.24 to 2.52 with (3) 3 Moment-Skewness (SK )-The values of an average of 0.76 (Table 1). Peakedness is skewness in studied samples range from −0.09 mainly dominated by very platykurtic beha- to 2.77 with an average of 1.10 (Table 2). The viour which indicates a thinner than normal samples are dominated equally by very fine tail, followed by platykurtic, very leptokurtic skewed and fine skewed grains followed by which indicates a thicker than normal tail and near symmetrical skewed grains and coarse mesokurtic behaviour which corresponds to skewed grains. th equal thickness throughout the curve. (4) 4 Moment-Kurtosis (Kϕ)-The value of kurtosis ranges from 0.33 to 9.49 with an average of 3.38 (Table 2). Peakedness is dominated by platykur- Mathematical moment method tic behaviour with more than half of the samples st (1) 1 Moment-Mean (� x)-In studied samples the showing the same. It is then followed by meso- values of mean ranges from 0.29 to 0.6 with an kurtic and leptokurtic behaviours in equal mea- average value of 0.42 (Table 2). These values sure and very platykurtic and very leptokurtic indicate that all of studied samples are coarse behaviours. grained. Table 2. Statistical parameters of grain-size distribution in the Fort Member Sandstone of Jaisalmer Formation, Western Rajasthan, calculated by the moment method. st nd rd th Σ f(m− � xφ) Σ f(m Σ f(m 1 Verbal 2 Verbal 3 Verbal 4 Verbal 3 4 S. no. Σ fm 2 − � xφ) − � xφ) moment limit moment imit moment limit moment limit JS-20 50 7.34 0.83 1.07 0.5 CS 0.27 VWS 0.42 NSS 1.99 PK JS-21 40.44 5.33 1.02 0.47 0.4 CS 0.23 VWS 0.83 FS 1.68 VPK JS-22 48.23 7.4 1.17 1.19 0.48 CS 0.27 VWS 0.58 FS 2.18 PK JS-23 52.85 7.77 0.71 1.27 0.53 CS 0.28 VWS 0.33 NSS 2.1 PK JS-24 46.38 7.69 1.79 1.57 0.46 CS 0.28 VWS 0.84 FS 2.66 PK JS-25 49.73 6.97 0.85 1.39 0.5 CS 0.26 VWS 0.46 NSS 2.86 PK JS-26 39.94 5.86 1.71 1.1 0.4 CS 0.24 VWS 1.2 FS 3.2 MK JS-27 55.97 10.06 1.84 2.68 0.56 CS 0.32 VWS 0.58 FS 2.64 PK JS-28 57.15 7.63 0.19 1.28 0.57 CS 0.28 VWS 0.09 CSK 2.2 PK JS-29 47.87 6.98 0.89 0.93 0.48 CS 0.26 VWS 0.48 NSS 1.91 PK JS-30 56.3 6.87 0.17 0.9 0.56 CS 0.26 VWS −0.9 CSK 1.91 PK JS-31 45.5 6.57 1.2 1.24 0.45 CS 0.26 VWS 0.71 FS 2.88 PK JS-32 50.94 7.77 0.98 1.3 0.51 CS 0.28 VWS 0.45 FS 2.16 PK JS-33 49.01 7.03 0.74 0.91 0.49 CS 0.26 VWS 0.4 NSS 1.84 PK JS-34 48.65 9.11 2.45 2.31 0.48 CS 0.3 VWS 0.89 FS 2.78 PK JS-35 53.49 9.06 1.46 1.95 0.53 CS 0.3 VWS 0.54 FS 2.38 PK JS-36 49.47 7.67 1.15 0.19 0.49 CS 0.28 VWS 0.54 FS 0.33 VPK JS-37 56.14 9.22 1.17 1.99 0.56 CS 0.3 VWS 0.42 NSS 2.33 PK JS-38 59.96 8.51 0.42 1.74 0.6 CS 0.29 VWS 0.17 NSS 2.4 PK JS-39 50.65 8.67 1.68 1.85 0.5 CS 0.29 VWS 0.67 FS 2.47 PK JS-40 45.42 6.04 0.55 0.41 0.45 CS 0.24 VWS 0.37 NSS 1.14 VPK JS-41 32.1 3.04 1.09 0.48 0.32 CS 0.17 VWS 2.04 VFS 5.2 LK JS-42 32.02 3.01 1.08 0.48 0.32 CS 0.17 VWS 2.07 VFS 5.28 LK JS-43 31.13 2.69 1.01 0.45 0.31 CS 0.16 VWS 2.29 VFS 6.29 LK JS-44 31.99 3 1.08 0.48 0.31 CS 0.17 VWS 2.07 VFS 5.32 LK JS-45 29.74 2.14 0.87 0.39 0.29 CS 0.14 VWS 2.77 VFS 8.66 VLK FS-1 35.73 7.7 5.7 5.63 0.36 CS 0.27 VWS 2.67 VFS 9.49 VLK FS-2 35.27 4.08 1.2 0.52 0.35 CS 0.2 VWS 1.46 VFS 3.13 MK FS-3 40.04 6.65 2.72 2.35 0.4 CS 0.26 VWS 1.58 VFS 5.32 LK FS-4 39.84 5.62 1.49 0.89 0.39 CS 0.24 VWS 1.12 FS 2.82 PK FS-5 36.53 4.44 1.19 0.52 0.36 CS 0.21 VWS 1.28 FS 2.63 PK FS-6 35.7 3.67 1.2 0.52 0.36 CS 0.2 VWS 1.39 VFS 2.95 PK FS-7 34.43 3.96 1.36 0.69 0.34 CS 0.2 VWS 1.73 VFS 4.41 LK FS-8 43.83 4.14 1.53 1.15 0.44 CS 0.26 VWS 0.88 FS 2.55 PK FS-9 38.88 4.06 1.53 0.89 0.39 CS 0.23 VWS 1.22 FS 3.06 MK FS-10 31.08 3.31 1.26 0.72 0.31 CS 0.17 VWS 2.6 VFS 8.81 VLK FS-11 37.69 4.73 1.16 0.51 0.37 CS 0.21 VWS 1.13 FS 2.28 PK FS-12 32.86 2.86 1.13 0.5 0.33 CS 0.18 VWS 1.88 VFS 4.55 LK FS-13 35.22 5.39 1.2 0.52 0.35 CS 0.2 VWS 1.47 VFS 3.15 MK FS-14 35.49 6.73 1.2 0.52 0.35 CS 0.2 VWS 1.42 VFS 3.03 MK FS-15 34.86 3.97 1.19 0.52 0.35 CS 0.2 VWS 1.52 VFS 3.31 MK FS-16 33.93 4.2 1.18 0.51 0.34 CS 0.19 VWS 1.68 VFS 3.82 MK Avg. 42.68 5.93 1.29 1.12 0.42 CS 0.24 VWS 1.1 FS 3.38 MK GEOLOGY, ECOLOGY, AND LANDSCAPES 127 and very well sorted (Figure 7(a)). The clustering of Discussion the samples in a narrow region is indicative of very less Interrelationship of textural parameters mixing of sediments. This type of curve shows that there is minute difference between the grain sizes and To demarcate different depositional environments, hence the studied samples are very well sorted. the combination of several textural parameters in The plot between skewness and standard deviation the form of bivariant plots has been used (Friedman, (Figure 7(b)) helps to differentiate river sediments 1979). The basis behind these plots is the assump- from beach sediments (Flemming, 2007; Friedman, tion that statistical parameters reliably reflect varia- 1967; Friedman, 1961). A symmetrical curve is tions in the fluid flow mechanism of sediment obtained in two cases (1) unimodal sample with transportation and deposition (Sutherland & Lee, good sorting, or (2) equal mixtures of the two modes 1994). Various workers supposed that these plots which have the poorest possible sorting (Folk & Ward, can serve as a reliable tool for delineating processes of different environment of sedimentation (Martins, 1957). Studied samples are very well sorted and posi- tively skewed showing the unimodal behaviour. 2003; Srivastava et al., 2010, 2012; Srivastava & The trend between mean size and skewness is sinusoi- Mankar, 2009; Sutherland & Lee, 1994). The bivariate plot between mean size and standard dal (Figure 7(c)). The pure sand mode occurs by itself produces a symmetrical size curve, but addition of deviation shows the samples clustered at the centre of increasing quantities of gravel mode imparts negative the curve denoting the samples to be coarse grained Figure 7. Bivariate plots showing the placement of present samples in the model plot as proposed by Folk and Ward (1957). (a) mean grain size vs standard deviation; (b) skewness vs standard deviation, (c) mean grain size vs skewness; (d) standard deviation vs kurtosis; (e) mean grain size vs kurtosis; and (f) skewness vs kurtosis. 128 F. AHMAD ET AL. skewness. Positive skewness is shown when coarser mode better in the centre making the curve very leptokurtic of the sediment are more dominant (Folk & Ward, 1957). with K >1.0. Very platykurtic behaviour is obtained The plot shows that all of the samples are positively when two modes are present in sub-equal amount skewed, coarse-grained and the trend of the curve is (anything from 25–75% to 75–25%). Most of studied close to sinusoidal. River sands are generally positively samples are showing very platykurtic to platykurtic skewed while coarse-grained river sand can be either behaviour with three samples showing mesokurtic positively or negatively skewed (Friedman, 1961). Based and further three showing very leptokurtic with con- on this, studied samples indicate river sand and deposited stant coarse grain. It is an indication that most of in shallow marine environment. studied samples are dominated by coarse sand and in According to Folk and Ward (1957), poor sorting is case of bimodal sediments the second mode is present found in the bimodal mixtures with equal amounts of in sub-ordinate amount. the two modes, and these two will also have lowest Skewness vs kurtosis properties of samples depend on kurtosis, while, the highest kurtosis is associated with the proportions of the two modes present, generally pure the samples which have one dominant and one very sand mode gives normal curve, whereas, by addition of subordinate mode and moderate sorting. Unimodal other modes it is disturbed (Folk & Ward, 1957). Studied sediments produce normal kurtosis and very well- samples mainly fall below the shaded zone indicating the sorted samples (Folk & Ward, 1957). Studied samples dominance of very platykurtic to platykurtic grains with fall in the last category, i.e. these are unimodal, have some samples mesokurtic to very leptokurtic behaviour. normal kurtosis and are very well sorted (Figure 7(d)). All the studied samples are positively skewed giving an The plot of mean against kurtosis (Figure 7(e)) indication that sand is dominant constituent with sub- shows mixing of two or more size classes of sediment ordinate amount of silt (Figure 7(f)). which affects the sorting of central and tail part of the curve (Flemming, 2007; Molinaroli et al., 2009). Bivariate grain-size parameters According to Folk and Ward (1957), the presence of only one mode results in nearly normal curve, i.e. K Statistical parameters achieved by graphical as well as = 1.0. Addition of very small amount (3–10%) of moment methods were plotted in various bivariate another mode results in poorer sorting in the tail and diagrams, to know the environmental conditions that Figure 8. Bivariate plots of various parameters. (a) median vs standard deviation (after Moiola & Weiser, 1968; Stewart, 1958); (b) mean size vs standard deviation (after Friedman, 1961; Moiola & Weiser, 1968) and (c) skewness vs standard deviation (after Friedman, 1967). GEOLOGY, ECOLOGY, AND LANDSCAPES 129 Figure 9. Linear discriminate function analysis plot for Fort Member Sandstone. (a) Y vs Y discriminates between beach and 1 2 aeolian environment; (b) Y and Y between beach and shallow marine sub-environment; and (c) Y vs Y discriminates between 2 3 3 4 marine turbidity and fluvial environment. were present at that time. To differentiate between Linear discriminate analysis river, beach and coastal dune sub-environments, Linear discriminant function analysis is a vital tool in Friedman (1961), and Moiola and Weiser (1968), identifying the environment at the time of sediment plotted mean size versus standard deviation. The deposition. Sahu (1964) stated that there is definite bivariate is most useful in differentiating between correlation between fluctuations in energy and fluidity beach and river sands and river and coastal dune and different operating processes and environment in sands and the differentiation works well regardless of which sediments are deposited. In this study both whether quarter, half or whole phi data are used linear and multi-group discriminant function analysis (Moiola & Weiser, 1968). (Sahu, 1964, 1983) used to further distinguish deposi- Stewart (1958) distinguished between river and tional environments. wave process by plotting median grain size vs stan- Y vs Y plot by graphical method indicates that all of 1 2 dard deviation. The plots of both graphical as studied samples fall strictly in beach littoral sub- well as moment analysis indicate that all of the environment (Figure 9(a)), and by moment method, samples were deposited in beach sub-environment the samples are scattered in the fields of beach shallow (Figure 8(a)). agitated and beach littoral sub-environment with dom- Standard deviation vs mean size diagram using inance of beach shallow agitated sub- graphical method, indicates the beach sub- environment (Table 3). It is a clear indication that environment and same in the case with plot of studied samples are exclusively deposited by beach moment measures method, i.e. it also cluster in the and shallow marine processes with no indication of beach sub-environment (Figure 8(b)). aeolian processes. Standard deviation vs skewness (Friedman, 1967; The plot Y vs Y is used to differentiate between 2 3 Friedman, 1961) was plotted to distinguish beach and fluvial and shallow marine sub-environments, the river sub-environment. Graphical data show the sam- values obtained by graphical method are clustered ples to be exclusively of beach sub-environment while exclusively in fluvial beach environment, the data the moment data is showing it to be dominated by river obtained by moment analysis are quite scattered sub-environment while some of the samples also fall in (Figure 9(b)). It is dominated by shallow marine the beach sub-environment (Figure 8(c)). agitated environment with some samples falling 130 F. AHMAD ET AL. Table 3. Linear discriminate function analysis to interpret variation in energy and fluidity factors. Environmental symbols: B-beach, SM-shallow marine, F-fluvial, T-marine turbidity current. By graphical method By moment method S. no. Y1 Env. Y2 Env. Y3 Env. Y4 Env. Y1 Env. Y2 Env. Y3 Env. Y4 Env. JS-20 1.50 B 22.52 B −1.75 SM 5.81 F 3.54 B 57.05 B −2.47 SM 13.75 T JS-21 1.56 B 18.24 B −1.09 SM 4.98 F 1.75 B 55.85 B −4.34 SM 14.79 T JS-22 1.38 B 21.55 B −1.72 SM 5.62 F 3.77 B 63.15 B −3.25 SM 15.82 T JS-23 2.19 B 25.76 B −1.55 SM 6.52 F 4.04 B 58.28 B −2.06 SM 13.75 T JS-24 0.97 B 19.69 B −1.88 SM 5.27 F 4.66 B 76.78 SM −4.55 SM 20.10 T JS-25 1.94 B 23.52 B −1.46 SM 6.07 F 6.13 B 73.52 SM −2.58 SM 18.62 T JS-26 1.31 B 17.30 B −1.21 SM 4.76 F 5.50 B 90.99 SM −6.13 SM 25.33 T JS-27 1.67 B 25.86 B −2.07 SM 6.39 F 5.03 B 74.85 SM −3.46 SM 18.32 T JS-28 4.95 B 39.56 B −0.99 SM 10.17 T 4.86 B 56.41 B −0.87 SM 12.69 T JS-29 1.12 B 20.60 B −1.84 SM 5.43 F 3.18 B 55.99 B −2.72 SM 13.71 T JS-30 7.47 B 53.29 B −0.74 SM 14.05 T 6.63 B 32.25 B 4.05 SM 4.48 F JS-31 1.37 B 20.09 B −1.53 SM 5.34 F 5.69 B 77.63 SM −3.81 SM 20.37 T JS-32 1.60 B 23.08 B −1.73 SM 5.92 F 3.98 B 61.25 B −2.65 SM 14.86 T JS-33 1.33 B 21.55 B −1.78 SM 5.62 F 3.15 B 53.40 B −2.33 SM 12.81 T JS-34 0.69 B 21.30 B −2.41 SM 5.62 F 4.87 B 80.98 SM −4.89 SM 21.09 T JS-35 1.53 B 24.24 B −1.98 SM 6.11 F 4.39 B 68.03 SM −3.18 SM 16.65 T JS-36 1.13 B 21.11 B −1.90 SM 5.53 F −1.89 B 28.71 B −3.18 SM 5.77 F JS-37 2.05 B 26.51 B −1.79 SM 6.59 F 4.45 B 65.40 SM −2.58 SM 15.60 T JS-38 5.27 B 41.98 B −1.03 SM 10.73 T 5.18 B 62.41 B −1.29 SM 14.31 T JS-39 1.07 B 22.10 B −2.13 SM 5.72 F 4.40 B 71.19 SM −3.77 SM 17.98 T JS-40 1.04 B 19.54 B −1.76 SM 5.22 F 1.16 B 38.62 B −2.14 SM 8.87 F JS-41 2.64 B 20.69 B −0.51 SM 5.74 F 9.63 B 140.07 SM −9.92 F 41.50 T JS-42 2.78 B 21.44 B −0.49 SM 5.95 F 9.80 B 142.09 SM −10.06 F 42.12 T JS-43 1.13 B 13.78 B −0.87 SM 3.91 F 12.37 B 164.39 SM −11.07 F 48.94 T JS-44 2.34 B 19.07 B −0.54 SM 5.30 F 9.96 B 142.68 SM −10.07 F 42.33 T JS-45 2.78 B 20.97 B −0.43 SM 5.85 F 18.50 B 216.23 SM −13.27 F 64.70 T FS-1 1.74 B 16.49 B −0.70 SM 4.60 F 21.31 B 234.38 SM −13.19 F 68.49 T FS-2 1.62 B 16.68 B −0.83 SM 4.64 F 4.69 B 92.46 SM −7.26 SM 26.66 T FS-3 1.02 B 16.03 B −1.29 SM 4.47 F 11.11 B 137.76 SM −7.98 F 39.11 T FS-4 1.18 B 16.62 B −1.22 SM 4.60 F 4.57 B 82.35 SM −5.75 SM 22.77 T FS-5 1.19 B 15.45 B −1.06 SM 4.33 F 3.60 B 80.38 SM −6.43 SM 22.81 T FS-6 1.47 B 16.21 B −0.90 SM 4.51 F 4.29 B 88.02 SM −6.92 SM 25.25 T FS-7 1.02 B 14.31 B −1.05 SM 4.06 F 7.98 B 120.88 SM −8.53 F 35.25 T FS-8 1.07 B 18.41 B −1.59 SM 4.99 F 4.24 B 74.45 SM −4.66 SM 19.77 T FS-9 1.08 B 16.09 B −1.25 SM 4.48 F 5.03 B 88.29 SM −6.19 SM 24.71 T FS-10 1.58 B 15.55 B −0.73 SM 4.37 F 19.39 B 216.85 SM −12.51 F 64.37 T FS-11 1.32 B 16.54 B −1.09 SM 4.58 F 2.88 B 71.34 SM −5.71 SM 19.96 T FS-12 1.46 B 15.46 B −0.81 SM 4.33 F 8.02 B 125.53 SM −9.19 F 36.99 T FS-13 1.62 B 16.68 B −0.83 SM 4.64 F 4.73 B 93.01 SM −7.31 SM 26.84 T FS-14 −0.23 B 12.88 B −2.00 SM 3.97 F 4.49 B 89.89 SM −7.07 SM 25.87 T FS-15 1.90 B 17.71 B −0.73 SM 4.91 F 5.09 B 96.88 SM −7.55 F 28.02 T FS-16 1.12 B 14.53 B −0.99 SM 4.11 F 6.27 B 108.80 SM −8.28 F 31.79 T into fluvial beach and one sample is also found to shallow marine and turbidity. The plot of studied sam- fall in shallow marine beach environment (Table 3). ples concluded that all samples fall exclusively in beach Y vs Y plot shows that the most of studied sam- environment which is a reflection of deposition by the 3 4 ples fall in the turbidity current/shallow marine envir- rivers and subsequent sorting by the wave action. onment and three samples found to be in the field of fluvial/shallow marine environment by graphical C-M plot method. The moment analysis data shows a very scat- tered plot, mostly dominated by fluvial/shallow mar- Passega (1957) introduced the use of C-M plot to ine and fluvial environments and three samples have analyse the hydrodynamic forces that were opera- plotted in turbidity current/shallow marine environ- tional during the deposition of sediments. This dia- ment (Figure 9(c)). gram was plotted by the combination of coarsest grain in the sample, C (in microns) and M (Median in microns) on log probability curve. Generally the Multigroup discriminate analysis grain-size of clastic sediment defines the hydraulic Multigroup discriminant analysis has been used to dif- energy condition of the environment (Kalicki, 2000; ferentiate between various depositional environments Molinaroli et al., 2009; Le Roux & Rojas, 2007). The � � (Sahu, 1983). Eigen vectors V1 and V2 were calculated plot of studied samples on the C-M plot examined and plotted on the standard diagram of (Sahu, 1983) that the studied detritus were transported by rolling (Figure 10). Textural parameters were used to identify which is an indication of high energy conditions five depositional environments-dune, river, beach, (Figure 11). GEOLOGY, ECOLOGY, AND LANDSCAPES 131 Figure 10. Multigroup discriminant diagram after Sahu (1983) Figure 11. C-M plot to determine depositional mechanisms (after Passega, 1957). Log normal distribution curve it do not show a single line but more than one straight lines. Every segment of line depicts a different mode of Log probability curves were used to distinguish between transportation like traction bed load (> 1.0 mm), salta- the different modes of transport of sediments within tion (0.75–1.0 mm) and suspension (<0.1 mm). The a depositional medium (Visher, 1969). It is the repre- studied plot shows that the transportation of sediment sentation of cumulative grain-size distribution on by the traction processes (Figure 12). a probability plot. The importance of these data is that 132 F. AHMAD ET AL. Figure 12. Log probability curves showing the trend of various modes of transportation (after Visher, 1969). Conclusions related to differences in chemical resistance within the grains. This study once again proved the importance of grain- (2) The cumulative frequency percentage curves and size analysis of sandstone in depicting the depositional grain-size statistics of studied samples are classi- environments and processes that were functional at fied as coarse-grained and mainly have unimodal the time of the deposition and were further supported distribution with some of the samples also show- by surface textural analysis. The following conclusions ing bi-modality. The predominance of unimodal are drawn from this study- nature of sediments specifies pure sand without any mixing. The value of mean grain-size indi- (1) SEM studies indicating the grains to be depos- cates that the energy conditions of the depositing ited in shallow marine environments reworked agent was high; however, the presence of unim- by waves and tides. The dominance of mechan- odal nature of the sediments with minor bimod- ical activities over the chemical dissolution gen- ality suggests the consistent energy levels of erally reflects medium to high energy nearshore depositing medium. environments. The roughness of surfaces and (3) The average sorting of all the sandstone 0.16 edges of some quartz grains might reflect dif- represents very well-sorted grains, which are ferential chemical weathering that may be dominantly very fine to fine skewed and show GEOLOGY, ECOLOGY, AND LANDSCAPES 133 mainly very platykurtic to platykurtic beha- (western Rajasthan, India), as revealed from lithofacies and grain-size analysis. Geologica Acta, 15(3), 153–167. viour with some samples also showing meso- https://doi.org/10.1344/GeologicaActa2017.15.3.1 kurtic and leptokurtic behaviour. Bhat, G. M., & Ahmad, A. H. M. (2013). Temporal facies (4) Bivariate plots concluded that all these sediments and diagenetic evolution of the mixed siliciclastic- are deposited in beach sub-environment mainly carbonate Jajiya Member (Callovian–Oxfordian), by river processes. The linear and multigroup Jaisalmer Formation, West India. Volumina Jurassica, 11(11), 147–162. https://doi.org/10.1306/03B5A976- discriminant analyses also indicates beach envir- 16D1-11D7-8645000102C1865D. onment for deposition of these sediments. Biswas, S. K. (1982). Rift basins in western margin of India C-M plot shows the sediments to be transported and their hydrocarbon prospects with special reference to by the process of rolling and log-log plot shows the Kutch Basin. American Association of Petroleum dominance of traction processes. The sediments Geologists, 66(10), 1497–1513. https://doi.org/10.1306/ were mainly in traction and saltation before being 03B5A976-16D1-11D7-8645000102C1865D. Chayes, F. (1949). A simple point counter for thin-section deposited in a shallow marine condition. analysis. The American Mineralogist, Journal of the Mineralogical Society of America, 34(1–2), 1–11. Cheetham, M. D., Keene, A. F., Bush, R. T., Sullivan, L. A., & Acknowledgements Erskine, W. D. (2008). A comparison of grain-size analy- sis methods for sand-dominated fluvial sediments. The authors are very thankful to the Chairperson, Sedimentology, 55(6), 1905–1913. https://doi.org/10. Department of Geology (A.M.U., Aligarh) for providing 1111/j.1365-3091.2008.00972.x the necessary facilities. The authors are grateful to Ms. Das Gupta, S. K. (1975). A revision of the Mesozoic-Tertiary Sadia Khanam and Ms. Aashna Javed (Research Scholars, stratigraphy of the Jaisalmer Basin, Rajasthan. Indian Sedimentology Lab, Department of Geology, A.M.U.) for Journal of Earth Sciences, 2(1), 77–94. helping in carrying out the required calculations. Flemming, B. W. (2007). The influence of grain-size analysis methods and sediment mixing on curve shapes and tex- tural parameters: Implications for sediment trend Disclosure statement analysis. Sedimentary Geology, 202(3), 425–435. https:// doi.org/10.1016/j.sedgeo.2007.03.018 No potential conflict of interest was reported by the authors. Folk, R. L., (1968). Bimodal super mature sandstones: Product of the desert floor. In: Proceedings of the 23rd International Geological Congress, Prague, 8, 9–32 ORCID Folk, R. L. (1980). Petrology of sedimentary rocks. Hemphill publishing company. Faiz Ahmad http://orcid.org/0000-0002-2301-1760 Folk, R. L., & Ward, W. C. (1957). Brazos River bar, a study M. A. Quasim http://orcid.org/0000-0003-0081-1906 in the significance of grain size parameters. Journal of Sedimentary Research, 27(1), 3–26. https://doi.org/10. 1306/74D70646-2B21-11D7-8648000102C1865D References Friedman, G. M. (1961). Distinction between dune, beach, Ahmad, F., Ahmad, A. H. M., & Quasim, M. A. 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Depositional mechanism of Fort Member Sandstone (Early-Late Bathonian), Jaisalmer Formation, Western Rajasthan: insights from granulometric analysis

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GEOLOGY, ECOLOGY, AND LANDSCAPES 2021, VOL. 5, NO. 2, 119–135 INWASCON https://doi.org/10.1080/24749508.2020.1833642 RESEARCH ARTICLE Depositional mechanism of Fort Member Sandstone (Early-Late Bathonian), Jaisalmer Formation, Western Rajasthan: insights from granulometric analysis a a a b a Faiz Ahmad , M. A. Quasim , A. H. M. Ahmad , S. M. Rehman and S. Asjad a b Department of Geology, Aligarh Muslim University, Aligarh, India; Department of Computer Engineering, Aligarh Muslim University, Aligarh, India ABSTRACT ARTICLE HISTORY Received 2 March 2020 Granulometric analysis is an imperative tool used to reveal the hydrodynamic conditions, mode Accepted 4 October 2020 of transportation and deposition of siliciclastic sediments. Forty-two samples of Fort Member Sandstone of the Jaisalmer Formation, Western Rajasthan were selected and studied with the KEYWORDS help of detailed granulometric analysis which include both graphical as well as mathematical Granulometric analysis; moment methods. Micro textures were recognized as chatter marks, curved and straight steps, hydrodynamic condition; grooves, upturned plates in association with V impact pits and triangular solution pits suggest- depositional environment; ing the predominance of mechanical activities over the chemical dissolution. The analysis Fort Member; Jaisalmer Formation shows the sandstone is coarse-grained, very well sorted, very fine to fine skewed and very platykurtic to platykurtic in nature. The dominance coarse grains give an indication of high energy level and almost stable as there is not much variation in the grain-size. Bivariate plots show that the sediments were deposited in beach sub-environment which was also confirmed by the linear and multigroup discriminant analysis. C-M plot shows that the sediments were transported by rolling and log-log plot also confirms the transportation by the traction processes. These features describe the sediments deposited by the fluvial process dominated by tractive current pattern in a shallow marine depositional environments. Introduction and geometry, grain-size analysis becomes an essential tool for a better understanding of the depositional Grain-size parameters are fundamental tool for identi- environment as they are mostly dependent on the syn- fying the sedimentary environments such as beach, depositional processes (Reading, 1996). dune and river and some other divisions of continental The pericratonic Jaisalmer basin situated to the west of shelf through graphic as well as mathematical moment Aravalli axis on the western part of the Indian peninsula, methods used along with other textural properties. formed the eastern most part of the Indo-Arabian Grain-size is the utmost important property of the Geological Province (Pandey & Choudhary, 2007). The sediments, affecting their entrainment, transport and basin has attracted the attention of geologists and deposition. Therefore, grain-size analysis offers signifi - palaeontologists due to its rich record of well-preserved cant evidences to the sediments provenance, transport Jurassic to Tertiary fossils. Recently, the basin has also history and depositional conditions (Ghaznavi et al., been proved its potential for oil and gas reserves and 2019; Quasim et al., 2020; Sahu, 1964; Visher, 1969). categorized category-I (producing) basin by Directorate Despite the usefulness of grain-size analysis in stu- General of Hydrocarbons (DGH). Therefore, the dies of siliciclastic sedimentary rocks, there are various research on the sedimentary features of the Jaisalmer limitations for grain-size parameters also. These limita- Formation may understand the petroleum geology char- tions include changes or subsequent modifications that acteristics and tectonic evolution history in this area. a framework particle undergoes when it is subjected to The Jurassic Jaisalmer basin is predominantly diagenesis (Ghaznavi et al., 2019; Ghosh & Chatterjee, a carbonate facies and inter-bedded with calcareous sand- 1994). Irrespective of these restrictions, parameters of stone and shale deposited under marginal marine to grain-size analysis have been used successfully in pre- occasional shelf lagoon conditions of deposition which vious studies and proved to be useful in interpreting has huge hydrocarbon generation potential and reservoir provenance, mechanism of transportation and environ- potential (Ahmad et al., 2020b; Pandey & Maurya, 2020). ment of deposition (Ahmad et al., 2017a; Cheetham Previous studies mainly focussed on the sedimentological et al., 2008; Ghaznavi et al., 2019; Kanhaiya et al., attributes like tectono-provenance (Ahmad et al., 2019), 2017; Quasim et al., 2020; Kanhaiya & Singh, 2014; diagenetic evolution (Ahmad et al., 2017b; Mahender & Weltje & Prins, 2007). In aggregation with different Banerji, 1990) and depositional environment (Ahmad sedimentological factors like structures of sedimentary et al., 2020a, 2017a; Bhat & Ahmad, 2013; Pandey et al., origin and their associations, palaeoflow, fossil content CONTACT Faiz Ahmad faizgeology@gmail.com Department of Geology, Aligarh Muslim University, Aligarh, India © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society(INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 120 F. AHMAD ET AL. 2006, 2006b) but the research on the sedimentary hydro- changing through time. The Precambrian igneous dynamic conditions of Fort Member Sandstone has not (Malani volcanics)/metamorphic rocks form the base- started yet. Sandstone grain-size characteristics are of ment for the later deposited sedimentary sequences of great significance in the analysis of sedimentary hydro- Western Rajasthan Basin, but they are exposed in only dynamic conditions (Ghaznavi et al., 2019; Ghosh & few locations around Pokhran, Jodhpur and Barmer. Chatterjee, 1994; Quasim et al., 2020). Based on the The Jaisalmer basin covers entire district of analysis of sandstone grain-size characteristics (both gra- Jaisalmer in West Rajasthan and neighbouring phical as well as mathematical moment methods) of the Kachchh basin in the south with depth of the base- Fort Member of the Jaisalmer Formation, Western ment 10,000 m near the Indo-Pak border (Figure 1 Rajasthan, the evolution history of sedimentary hydro- (a)). It is a pericratonic basin positioned at the west of dynamic conditions of the Fort Member Sandstone in the Aravalli axis on the western part of the Indian this region can be reconstructed. craton with dip direction in the north-west. It repre- sents the Tethyan margin during the Jurassic, when it was located at about 23 south of the equator. On the Geological background basis of geophysical investigations conducted by ONGC, four geostructural units are found (Figure 1 The Rajasthan shelf has been divided into four units (b)) which are Mari-Jaisalmer arch, the synclinal namely: the Jaisalmer basin, the Bikaner-Nagaur Shahgarh sub-basin, the Kishangarh sub-basin and basin, the Barmer-Sanchor basin and the Pokharan- the Miajlar sub-basin (Raghavendra Rao, 1972; Singh Nachana high but owing to continuous alteration of et al., 2005; Sinha et al., 1993). Sedimentation in the tectonic setting and palaeogeographic conditions the Jurassic Jaisalmer basin starts with widely spread extent of these basins on Rajasthan shelf kept on Figure 1. (a) Outline map of India depicting the location of the Jaisalmer basin; (b) tectonic map of the Jaisalmer basin (after Biswas, 1982; Misra et al., 1993); (c) geological map of Jaisalmer basin showing outcrop of the Jaisalmer Formation, Western Rajasthan (after Jodhawat & Kachhara, 2000). GEOLOGY, ECOLOGY, AND LANDSCAPES 121 deltaic, fluvial or lacustrine sediments in the basal Darbar and Jaithawai road. Thin-sections were prepared Lathi Formation (Srivastava, 1966) followed by mar- for these forty-two sandstone samples for their textural ginal marine sediments which in turn then followed by analysis. On an average about 200–300 grains were a series of various non-marine, marginal marine and counted in each thin section following the method of fully marine sediments. Lithostratigraphically, these Chayes (1949). Scanning Electron Microscope (SEM) deposits are classified into Jaisalmer, Baisakhi and images were used for the identification of ultra-textures Bhadasar formations (Das Gupta, 1975; Pandey, present in the quartz grains of the Fort Member. Quartz Fürsich, Sha et al., 2009; Pandey et al., 2006, 2005, grains were visually examined using JEOL JSM-5800 LV 2006b). Geologically, the Jaisalmer basin is repre- scanning electron microscope at University Sophisticated sented by a sequences of shale, siltstone, sandstone Instrument Facility (USIF), AMU, Aligarh. Phi-scale pro- and limestone. posed by Krumbein (1934), was used and the size data The depositional settings in the Jaisalmer basin fluc - were grouped in half-phi scale intervals. Cumulative fre- tuate from fluvial/lagoonal, delta front, shoreface to quency curves were plotted on a log probability scale. offshore environment with shifting water energy and Grain diameters in phi-unit that are represented by ϕ5, salinity (Ahmad et al., 2017a; Pandey et al., 2006, ϕ16, ϕ25, ϕ50, ϕ75, ϕ84 and ϕ95 percentiles were ana- 2006b). Although based on lithostratigraphic studies, lysed from the size frequency curves. Using these values it is revealed that there is cyclicity in sedimentation various statistical parameters are calculated like mean present in all the formations but it is most prominent size, standard deviation, skewness and kurtosis. These and well displayed in the Jaisalmer Formation parameters were calculated using both the graphical (JaiKrishna, 1987; Pandey & Fürsich, 1994; Pandey method as well as moment measures method. et al., 2009; Pandey et al., 2006, 2006b). According to calculations given by Krumbein and Jaisalmer Formation has been further classified Pettijohn (1938), Folk (1968, 1980), and McBride lithostratigraphically into the Hamira, Joyan, Fort, (1971), these statistical parameters have been classified. Badabag, Kuldhar and Jajiya members in increasing The mathematical method of moments used in the order (Figure 1(c)) (Das Gupta, 1975). Except for the present study was introduced by Krumbein and Phanerozoic outcrops overlying the Precambrian Pettijohn (1938). Various bivariate plots are plotted basement in the eastern and southern parts, whole of between these values to establish the interrelationships. the basin is covered by sand dunes or sands of Thar Linear Discriminate Analysis (LDA) was done to Desert. Pareek (1984) estimated the thickness of interpret the depositional sub-environment using fol- Jaisalmer Formation as 300 m. The sub-surface thick- lowing formula after Sahu (1964): ness as observed by drilling is more than 600 m (Das Y = −3.5688 Mean +3.7016 (Standard Gupta, 1975). deviation) − 2.0766 Skewness +3.1135 Kurtosis The best exposure of studied Fort Member is found This formula is used to distinguish between aeolian along the Jaisalmer fort escarpments. It is widest in north- and beach sub-environment. ern part and get narrower progressively towards south. It For beach sub-environment; Y > −2.7411 contains fine- to medium-grained sandstones, oolitic, For aeolian sub-environment; Y < −2.7411 sandy, bioturbated and fossiliferous nature of limestones, Y = 15.6534 Mean +65.7091 (Standard and cross-bedded sandy limestones (Mahender & Deviation) + 18.1071 Skewness +18.5043 Kurtosis Banerji, 1990; Pandey & Dave, 1998; Pandey et al., Y is used to delineate between beach and shallow- 2006). The sandstones are calcareous in nature and pos- marine environment. sess current bedding in upper part. The limestones are For beach sub-environment Y < 65.36 yellowish brown in colour, compact and fossiliferous. For shallow-marine sub-environment Y � 65.36 These limestones also have thin inter-beds of limestone Y = 0.2852 Mean −8.7604 (Standard that possess brachiopod and mollusca shell fragments. It Deviation) − 4.8932 Skewness +0.0428 Kurtosis contains various taxa of brachiopods, echinoids, gastro- It is used to distinguish between shallow-marine pods, corals, bryozoans and foraminifers. On the basis of and fluvial sub-environment. the stratigraphic position and inter-basinal correlation of For shallow-marine sub-environment Y > −7.4190 marker-beds (Pandey et al., 2009) the age of Fort Member For fluvial sub-environment Y < −7.4190 is interpreted as Early Bathonian to Middle/Late Y 0.7215 Mean +0.403 (Standard 4 = Bathonian. Deviation) + 6.7322 Skewness +5.2927 Kurtosis It is used to delineate between fluvial and marine turbidity sub-environment. Materials and methodology For marine turbidity sub-environment Y > 10.00 For fluvial sub-environment Y < 10.00 Three lithostratigraphic sections representing the Multigroup discriminant analysis (Sahu, 1983) was Fort Member of Jaisalmer Formation were measured carried out to differentiate between various deposi- (Figure 2). Forty-two fresh samples of sandstone were tional environments using the formula; collected from the outcrop in Near Fort scarp, Shiv Madi 122 F. AHMAD ET AL. Figure 2. Lithological succession showing the lithology of Fort Member of Jaisalmer Formation, Western Rajasthan. V 0.48048 Mean +0.06231 Standard Deviation 1996; Whalley & Krinsley, 1974). Surface textures of 1 = +0.40602 Skewness +0.44413 Kurtosis quartz sand grains have also been used to identify the V 0.24523 Mean −0.45905 Standard Deviation provenance and mode of origin of various detrital 2 = +0.15715 Skewness +0.83931 Kurtosis sediments. SEM analysis of quartz sand grains from Energy variation and fluidity factors are dependent Fort Member Sandstone has shown various surface on different processes and the depositional environ- features such as chatter marks, curved and straight ment (Sahu, 1964). steps, grooves, upturned plates in association with V impact pits and triangular solution pits. Chatter marks are series of sub-parallel indenta- Results tions which is formed when part of a grain skips across another grain (Figure 3(a)). Grooves are caused by Surface features on quartz sand grains drawing of sharp edge of a grain across another Scanning Electron Microscopy (SEM) of quartz grains (Krinsley & Margolis, 1969), they are further modified has paved way for discrimination between various by the fracture and solution activities (Figure 3(b)). sedimentary environments depending on their surface These quartz grains also show curved and straight textures (Krinsley & Donahue, 1968; Krinsley & steps in association with silica precipitation (Figure 3 Doornkamp, 2011; Krinsley & Margolis, 1969). The (c)). Small V-shaped indentations (Figure 3(d,f)) are ultra-textures provide valuable details about the dif- formed by grain to grain collision in an aqueous med- ferent processes which were operational during the ium (Krinsley & Margolis, 1969). Surfaces of the transportation and after the deposition of grains quartz grains from the Fort Member Sandstone exhibit (Krinsley & Funnell, 1965; Mahaney, 1998; Newsome silica precipitation features like irregular plates and & Ladd, 1999) and the parameters have been set to cavity filling. Furthermore, excess silica is pressed distinguish between the mechanical and chemical fea- over quartz grain surface in non-oriented patterns tures (Krinsley & Donahue, 1968; Rahman & Ahmed, (Figure 3(e)). It may be explained by the movement GEOLOGY, ECOLOGY, AND LANDSCAPES 123 Figure 3. Surface textures in quartz sand grains from Fort Member Sandstone as observed by SEM. (a) chatter Marks, (b) grooves, (c) curved and straight steps, (d) upturned plate in association with V-shaped pits, (e) silica plastering association with triangular pits and irregular plates, and (f) V-shaped pits. of grains across one another under high pressure the distribution of curves around 0.4ϕ for FS samples (Krinsley & Doornkamp, 2011). On the basis of results (Figure 4(a)) and distribution of curves around 0.35ϕ for from SEM studies it is concluded that the studied JS samples (Figure 4(b)) although few samples show samples have been deposited in shallow marine envir- different frequency curve distribution around 0.5ϕ. This onment as it is reworked by waves and tides to form indicates all of the samples are predominantly unimodal these beach sand deposits. The dominance of mechan- in nature and have sediments of pure sand type without ical activities over the chemical dissolution generally any mixing of silt particles. The unimodality is also indi- reflects medium to high energy nearshore environ- cative of more or less consistent depositional process ments. Also the roughness of surfaces and edges of during the time of sediment settling. some quartz grains in Figure 3(c,d) might reflect dif- In some of the samples (FS-11, JS 26, 27, 41, 42, 43) ferential chemical weathering that may be related to bimodality can also be seen with samples showing differences in chemical resistance within the grains peaks at around 1.4ϕ (Figure 4(b)). The bimodality is (Krinsley & Doornkamp, 2011). attributed to mixing of different size grains, variation in velocity of depositional processes and the difference in mode of transportation. Samples showing unimod- Frequency curves ality and bimodality are shown in Figure 5(a,d). Phi values are plotted against the frequency distribution Phi scales are plotted against the cumulative frequen- of each grain-size in the frequency curves. These curves cies (Figure 6), giving an idea about various modes of show modality or predominance of a particular size class. sediment transportation, deposition and their impor- These frequency curves are dominantly unimodal with tance in the genesis of sandstones. Sorting of the 124 F. AHMAD ET AL. Figure 4. Grain-size distribution curves for the Fort Member Sandstone. (a) for FS samples and (b) for JS samples. Figure 5. Four different types of textural attributes recognized based on the thin-section distribution of quartz grains (I-bimodal, II- unequal bimodal, III-unimodal unequal, and IV-unimodal equal). (a) bimodal unequal quartz grains are showing pore spaces filled by cementing materials (carbonate and iron); (b) bimodal equal quartz grains showing pore spaces filled by cementing materials (carbonate and iron); (c) unimodal unequal can be attributed to moderate to well sorting, weak alteration of unstable grains and a moderate degree of cementation and compaction. (d) unimodal equal are mainly found in well-sorted highly mature quartzarenites. Figure 6. Cumulative frequency curve showing trends of the Fort Member Sandstone. (a) for FS samples and (b) for JS samples. GEOLOGY, ECOLOGY, AND LANDSCAPES 125 samples can be obtained by the slope of middle portion (2) Graphic Mean Size (Mz)-Mean size is indicative of the curve. Poor sorting is indicated by a broad and of the average particle size. In studied samples Mz gentle gradient of the curve which also indicates low ranges from 0.04 to 0.11 with an average of 0.06 kinetic energy and velocity. A very steep slope, whereas, (Table 1). It implies that all of studied samples are is indicative of good sorting, high kinetic energy and coarse-grained sands. There is minute variability high velocity. All of the studied samples are coarse in the grain size of samples which make these grained, and based on the steepness of the gradient of samples very well sorted. the cumulative frequency curves can be regarded as very (3) Standard Deviation (σ )-It depicts the sorting or well sorted (Figure 6). uniformity of grains which in turn indicates the prevailing energy conditions at the time of trans- portation and deposition. Studied samples are Statistical parameters ranging from 0.09 to 0.24 with an average of 0.16 (Table 1) which indicate that all of the samples are Graphical method very well sorted which gives an indication of (1) Inclusive Graphic Median (ϕ )-Median smooth and constant current flow and velocity. corresponds to the 50 percentile, half of (4) Graphic Skewness (SK )-Measures the degree to the particles are coarser and the other half which a cumulative curve approach symmetry in are finer. Studied samples range from 0.12 terms of predominance of fine- or coarse – to 0.34, with an average of 0.19 (Table 1). grained fractions. The value of skewness in stu- Based on the data all of studied samples are died samples range from 0.09 to 0.42 with an coarse grained. Table 1. Statistical parameters of grain-size distribution in Fort Member Sandstone of Jaisalmer Formation, Western Rajasthan, calculated by the graphical method. Φ50, Mz, σ in phi units. Standard Verbal S. no. Median (ᶲ50) Mean size (Mz) Verbal limit deviation (σ ) limit Skewness (Sk ) Verbal limit Kurtosis (K ) Verbal imit C M 1 1 G JS-20 0.23 0.27 CS 0.21 VWS 0.29 FS 0.71 PK 995.16 852.63 JS-21 0.17 0.18 CS 0.14 VWS 0.20 FS 0.68 VPK 997.23 888.84 JS-22 0.22 0.25 CS 0.20 VWS 0.29 FS 0.68 VPK 997.23 858.57 JS-23 0.26 0.29 CS 0.22 VWS 0.24 FS 0.91 PK 997.23 835.09 JS-24 0.19 0.22 CS 0.19 VWS 0.33 VFS 0.56 VPK 999.31 876.61 JS-25 0.24 0.27 CS 0.20 VWS 0.24 FS 0.83 PK 996.54 846.75 JS-26 0.16 0.17 CS 0.14 VWS 0.22 FS 0.61 VPK 997.23 895.03 JS-27 0.27 0.31 CS 0.25 VWS 0.32 VFS 0.78 PK 996.54 829.32 JS-28 0.32 0.34 CS 0.23 VWS 0.13 FS 1.74 VLK 993.09 801.07 JS-29 0.21 0.24 CS 0.19 VWS 0.32 VFS 0.61 VPK 995.16 864.54 JS-30 0.32 0.33 CS 0.23 VWS 0.09 NSS 2.52 VLK 995.16 801.07 JS-31 0.2 0.22 CS 0.18 VWS 0.27 FS 0.66 VPK 993.78 870.55 JS-32 0.24 0.27 CS 0.21 VWS 0.29 FS 0.74 PK 997.23 846.75 JS-33 0.22 0.25 CS 0.20 VWS 0.30 FS 0.66 VPK 997.23 858.57 JS-34 0.2 0.24 CS 0.22 VWS 0.42 VFS 0.52 VPK 995.16 870.55 JS-35 0.25 0.29 CS 0.23 VWS 0.32 VFS 0.73 PK 997.23 840.90 JS-36 0.22 0.26 CS 0.20 VWS 0.33 VFS 0.62 VPK 995.16 858.57 JS-37 0.28 0.32 CS 0.24 VWS 0.27 FS 0.88 PK 995.16 823.59 JS-38 0.34 0.36 CS 0.24 VWS 0.13 FS 1.84 VLK 997.23 790.04 JS-39 0.22 0.26 CS 0.22 VWS 0.36 VFS 0.61 VPK 997.23 858.57 JS-40 0.2 0.23 CS 0.18 VWS 0.31 VFS 0.58 VPK 996.54 870.55 JS-41 0.13 0.13 CS 0.09 VWS 0.10 NSS 0.95 MK 999.31 913.83 JS-42 0.13 0.13 CS 0.09 VWS 0.10 NSS 1.00 MK 997.23 913.83 JS-43 0.12 0.13 CS 0.09 VWS 0.17 FS 0.52 VPK 997.23 920.19 JS-44 0.13 0.14 CS 0.09 VWS 0.11 FS 0.86 PK 998.61 913.83 JS-45 0.12 0.12 CS 0.09 VWS 0.09 NSS 0.99 MK 997.23 920.19 FS-1 0.13 0.14 CS 0.09 VWS 0.14 FS 0.69 VPK 993.78 913.83 FS-2 0.14 0.15 CS 0.11 VWS 0.16 FS 0.67 VPK 998.61 907.52 FS-3 0.15 0.17 CS 0.13 VWS 0.24 FS 0.53 VPK 998.61 901.25 FS-4 0.16 0.18 CS 0.13 VWS 0.23 FS 0.57 VPK 995.16 895.03 FS-5 0.14 0.15 CS 0.11 VWS 0.20 FS 0.55 VPK 999.31 907.52 FS-6 0.14 0.15 CS 0.11 VWS 0.17 FS 0.63 VPK 997.23 907.52 FS-7 0.13 0.14 CS 0.10 VWS 0.20 FS 0.50 VPK 999.31 913.83 FS-8 0.18 0.20 CS 0.16 VWS 0.29 FS 0.57 VPK 997.23 882.70 FS-9 0.15 0.17 CS 0.13 VWS 0.23 FS 0.54 VPK 999.31 901.25 FS-10 0.12 0.13 CS 0.09 VWS 0.14 FS 0.64 VPK 995.16 920.19 FS-11 0.15 0.17 CS 0.12 VWS 0.20 FS 0.60 VPK 997.23 901.25 FS-12 0.13 0.14 CS 0.10 VWS 0.16 FS 0.61 VPK 998.61 913.83 FS-13 0.14 0.15 CS 0.11 VWS 0.16 FS 0.67 VPK 997.23 907.52 FS-14 0.14 0.15 CS 0.09 VWS 0.40 VFS 0.24 VPK 999.31 907.52 FS-15 0.14 0.15 CS 0.10 VWS 0.14 FS 0.74 PK 998.61 907.52 FS-16 0.13 0.14 CS 0.10 VWS 0.19 FS 0.53 VPK 996.54 913.83 Avg. 0.19 0.21 CS 0.16 VWS 0.23 FS 0.76 PK 996.97 879.10 CS = Coarse Sand, VWS = Very Well Sorted, NSS = Near Symmetrical Skewed, FS = Fine Skewed, CSK = Coarse Skewed, VFS = Very Fine Skewed, VPK = Very Platykurtic, PK = Platykurtic, MK = Mesokurtic, LK Leptokurtic, VLK = Very Leptokurtic = 126 F. AHMAD ET AL. nd average of 0.23 (Table 1) which gives an indication (2) 2 Moment-Standard Deviation (σ )-Its value that most of the samples are fine skewed followed in studied samples range from 0.14 to 0.32 with by very fine skewed and nearly symmetrical an average of 0.24 (Table 2). It is a clear indica- skewed. tion of grains being very well sorted which is (5) Graphic Kurtosis (K )-Kurtosis is measure of also an indication of uniform energy condition peakedness in a curve. Values of Kurtosis in prevailing at the time of deposition. rd studied sample ranges from 0.24 to 2.52 with (3) 3 Moment-Skewness (SK )-The values of an average of 0.76 (Table 1). Peakedness is skewness in studied samples range from −0.09 mainly dominated by very platykurtic beha- to 2.77 with an average of 1.10 (Table 2). The viour which indicates a thinner than normal samples are dominated equally by very fine tail, followed by platykurtic, very leptokurtic skewed and fine skewed grains followed by which indicates a thicker than normal tail and near symmetrical skewed grains and coarse mesokurtic behaviour which corresponds to skewed grains. th equal thickness throughout the curve. (4) 4 Moment-Kurtosis (Kϕ)-The value of kurtosis ranges from 0.33 to 9.49 with an average of 3.38 (Table 2). Peakedness is dominated by platykur- Mathematical moment method tic behaviour with more than half of the samples st (1) 1 Moment-Mean (� x)-In studied samples the showing the same. It is then followed by meso- values of mean ranges from 0.29 to 0.6 with an kurtic and leptokurtic behaviours in equal mea- average value of 0.42 (Table 2). These values sure and very platykurtic and very leptokurtic indicate that all of studied samples are coarse behaviours. grained. Table 2. Statistical parameters of grain-size distribution in the Fort Member Sandstone of Jaisalmer Formation, Western Rajasthan, calculated by the moment method. st nd rd th Σ f(m− � xφ) Σ f(m Σ f(m 1 Verbal 2 Verbal 3 Verbal 4 Verbal 3 4 S. no. Σ fm 2 − � xφ) − � xφ) moment limit moment imit moment limit moment limit JS-20 50 7.34 0.83 1.07 0.5 CS 0.27 VWS 0.42 NSS 1.99 PK JS-21 40.44 5.33 1.02 0.47 0.4 CS 0.23 VWS 0.83 FS 1.68 VPK JS-22 48.23 7.4 1.17 1.19 0.48 CS 0.27 VWS 0.58 FS 2.18 PK JS-23 52.85 7.77 0.71 1.27 0.53 CS 0.28 VWS 0.33 NSS 2.1 PK JS-24 46.38 7.69 1.79 1.57 0.46 CS 0.28 VWS 0.84 FS 2.66 PK JS-25 49.73 6.97 0.85 1.39 0.5 CS 0.26 VWS 0.46 NSS 2.86 PK JS-26 39.94 5.86 1.71 1.1 0.4 CS 0.24 VWS 1.2 FS 3.2 MK JS-27 55.97 10.06 1.84 2.68 0.56 CS 0.32 VWS 0.58 FS 2.64 PK JS-28 57.15 7.63 0.19 1.28 0.57 CS 0.28 VWS 0.09 CSK 2.2 PK JS-29 47.87 6.98 0.89 0.93 0.48 CS 0.26 VWS 0.48 NSS 1.91 PK JS-30 56.3 6.87 0.17 0.9 0.56 CS 0.26 VWS −0.9 CSK 1.91 PK JS-31 45.5 6.57 1.2 1.24 0.45 CS 0.26 VWS 0.71 FS 2.88 PK JS-32 50.94 7.77 0.98 1.3 0.51 CS 0.28 VWS 0.45 FS 2.16 PK JS-33 49.01 7.03 0.74 0.91 0.49 CS 0.26 VWS 0.4 NSS 1.84 PK JS-34 48.65 9.11 2.45 2.31 0.48 CS 0.3 VWS 0.89 FS 2.78 PK JS-35 53.49 9.06 1.46 1.95 0.53 CS 0.3 VWS 0.54 FS 2.38 PK JS-36 49.47 7.67 1.15 0.19 0.49 CS 0.28 VWS 0.54 FS 0.33 VPK JS-37 56.14 9.22 1.17 1.99 0.56 CS 0.3 VWS 0.42 NSS 2.33 PK JS-38 59.96 8.51 0.42 1.74 0.6 CS 0.29 VWS 0.17 NSS 2.4 PK JS-39 50.65 8.67 1.68 1.85 0.5 CS 0.29 VWS 0.67 FS 2.47 PK JS-40 45.42 6.04 0.55 0.41 0.45 CS 0.24 VWS 0.37 NSS 1.14 VPK JS-41 32.1 3.04 1.09 0.48 0.32 CS 0.17 VWS 2.04 VFS 5.2 LK JS-42 32.02 3.01 1.08 0.48 0.32 CS 0.17 VWS 2.07 VFS 5.28 LK JS-43 31.13 2.69 1.01 0.45 0.31 CS 0.16 VWS 2.29 VFS 6.29 LK JS-44 31.99 3 1.08 0.48 0.31 CS 0.17 VWS 2.07 VFS 5.32 LK JS-45 29.74 2.14 0.87 0.39 0.29 CS 0.14 VWS 2.77 VFS 8.66 VLK FS-1 35.73 7.7 5.7 5.63 0.36 CS 0.27 VWS 2.67 VFS 9.49 VLK FS-2 35.27 4.08 1.2 0.52 0.35 CS 0.2 VWS 1.46 VFS 3.13 MK FS-3 40.04 6.65 2.72 2.35 0.4 CS 0.26 VWS 1.58 VFS 5.32 LK FS-4 39.84 5.62 1.49 0.89 0.39 CS 0.24 VWS 1.12 FS 2.82 PK FS-5 36.53 4.44 1.19 0.52 0.36 CS 0.21 VWS 1.28 FS 2.63 PK FS-6 35.7 3.67 1.2 0.52 0.36 CS 0.2 VWS 1.39 VFS 2.95 PK FS-7 34.43 3.96 1.36 0.69 0.34 CS 0.2 VWS 1.73 VFS 4.41 LK FS-8 43.83 4.14 1.53 1.15 0.44 CS 0.26 VWS 0.88 FS 2.55 PK FS-9 38.88 4.06 1.53 0.89 0.39 CS 0.23 VWS 1.22 FS 3.06 MK FS-10 31.08 3.31 1.26 0.72 0.31 CS 0.17 VWS 2.6 VFS 8.81 VLK FS-11 37.69 4.73 1.16 0.51 0.37 CS 0.21 VWS 1.13 FS 2.28 PK FS-12 32.86 2.86 1.13 0.5 0.33 CS 0.18 VWS 1.88 VFS 4.55 LK FS-13 35.22 5.39 1.2 0.52 0.35 CS 0.2 VWS 1.47 VFS 3.15 MK FS-14 35.49 6.73 1.2 0.52 0.35 CS 0.2 VWS 1.42 VFS 3.03 MK FS-15 34.86 3.97 1.19 0.52 0.35 CS 0.2 VWS 1.52 VFS 3.31 MK FS-16 33.93 4.2 1.18 0.51 0.34 CS 0.19 VWS 1.68 VFS 3.82 MK Avg. 42.68 5.93 1.29 1.12 0.42 CS 0.24 VWS 1.1 FS 3.38 MK GEOLOGY, ECOLOGY, AND LANDSCAPES 127 and very well sorted (Figure 7(a)). The clustering of Discussion the samples in a narrow region is indicative of very less Interrelationship of textural parameters mixing of sediments. This type of curve shows that there is minute difference between the grain sizes and To demarcate different depositional environments, hence the studied samples are very well sorted. the combination of several textural parameters in The plot between skewness and standard deviation the form of bivariant plots has been used (Friedman, (Figure 7(b)) helps to differentiate river sediments 1979). The basis behind these plots is the assump- from beach sediments (Flemming, 2007; Friedman, tion that statistical parameters reliably reflect varia- 1967; Friedman, 1961). A symmetrical curve is tions in the fluid flow mechanism of sediment obtained in two cases (1) unimodal sample with transportation and deposition (Sutherland & Lee, good sorting, or (2) equal mixtures of the two modes 1994). Various workers supposed that these plots which have the poorest possible sorting (Folk & Ward, can serve as a reliable tool for delineating processes of different environment of sedimentation (Martins, 1957). Studied samples are very well sorted and posi- tively skewed showing the unimodal behaviour. 2003; Srivastava et al., 2010, 2012; Srivastava & The trend between mean size and skewness is sinusoi- Mankar, 2009; Sutherland & Lee, 1994). The bivariate plot between mean size and standard dal (Figure 7(c)). The pure sand mode occurs by itself produces a symmetrical size curve, but addition of deviation shows the samples clustered at the centre of increasing quantities of gravel mode imparts negative the curve denoting the samples to be coarse grained Figure 7. Bivariate plots showing the placement of present samples in the model plot as proposed by Folk and Ward (1957). (a) mean grain size vs standard deviation; (b) skewness vs standard deviation, (c) mean grain size vs skewness; (d) standard deviation vs kurtosis; (e) mean grain size vs kurtosis; and (f) skewness vs kurtosis. 128 F. AHMAD ET AL. skewness. Positive skewness is shown when coarser mode better in the centre making the curve very leptokurtic of the sediment are more dominant (Folk & Ward, 1957). with K >1.0. Very platykurtic behaviour is obtained The plot shows that all of the samples are positively when two modes are present in sub-equal amount skewed, coarse-grained and the trend of the curve is (anything from 25–75% to 75–25%). Most of studied close to sinusoidal. River sands are generally positively samples are showing very platykurtic to platykurtic skewed while coarse-grained river sand can be either behaviour with three samples showing mesokurtic positively or negatively skewed (Friedman, 1961). Based and further three showing very leptokurtic with con- on this, studied samples indicate river sand and deposited stant coarse grain. It is an indication that most of in shallow marine environment. studied samples are dominated by coarse sand and in According to Folk and Ward (1957), poor sorting is case of bimodal sediments the second mode is present found in the bimodal mixtures with equal amounts of in sub-ordinate amount. the two modes, and these two will also have lowest Skewness vs kurtosis properties of samples depend on kurtosis, while, the highest kurtosis is associated with the proportions of the two modes present, generally pure the samples which have one dominant and one very sand mode gives normal curve, whereas, by addition of subordinate mode and moderate sorting. Unimodal other modes it is disturbed (Folk & Ward, 1957). Studied sediments produce normal kurtosis and very well- samples mainly fall below the shaded zone indicating the sorted samples (Folk & Ward, 1957). Studied samples dominance of very platykurtic to platykurtic grains with fall in the last category, i.e. these are unimodal, have some samples mesokurtic to very leptokurtic behaviour. normal kurtosis and are very well sorted (Figure 7(d)). All the studied samples are positively skewed giving an The plot of mean against kurtosis (Figure 7(e)) indication that sand is dominant constituent with sub- shows mixing of two or more size classes of sediment ordinate amount of silt (Figure 7(f)). which affects the sorting of central and tail part of the curve (Flemming, 2007; Molinaroli et al., 2009). Bivariate grain-size parameters According to Folk and Ward (1957), the presence of only one mode results in nearly normal curve, i.e. K Statistical parameters achieved by graphical as well as = 1.0. Addition of very small amount (3–10%) of moment methods were plotted in various bivariate another mode results in poorer sorting in the tail and diagrams, to know the environmental conditions that Figure 8. Bivariate plots of various parameters. (a) median vs standard deviation (after Moiola & Weiser, 1968; Stewart, 1958); (b) mean size vs standard deviation (after Friedman, 1961; Moiola & Weiser, 1968) and (c) skewness vs standard deviation (after Friedman, 1967). GEOLOGY, ECOLOGY, AND LANDSCAPES 129 Figure 9. Linear discriminate function analysis plot for Fort Member Sandstone. (a) Y vs Y discriminates between beach and 1 2 aeolian environment; (b) Y and Y between beach and shallow marine sub-environment; and (c) Y vs Y discriminates between 2 3 3 4 marine turbidity and fluvial environment. were present at that time. To differentiate between Linear discriminate analysis river, beach and coastal dune sub-environments, Linear discriminant function analysis is a vital tool in Friedman (1961), and Moiola and Weiser (1968), identifying the environment at the time of sediment plotted mean size versus standard deviation. The deposition. Sahu (1964) stated that there is definite bivariate is most useful in differentiating between correlation between fluctuations in energy and fluidity beach and river sands and river and coastal dune and different operating processes and environment in sands and the differentiation works well regardless of which sediments are deposited. In this study both whether quarter, half or whole phi data are used linear and multi-group discriminant function analysis (Moiola & Weiser, 1968). (Sahu, 1964, 1983) used to further distinguish deposi- Stewart (1958) distinguished between river and tional environments. wave process by plotting median grain size vs stan- Y vs Y plot by graphical method indicates that all of 1 2 dard deviation. The plots of both graphical as studied samples fall strictly in beach littoral sub- well as moment analysis indicate that all of the environment (Figure 9(a)), and by moment method, samples were deposited in beach sub-environment the samples are scattered in the fields of beach shallow (Figure 8(a)). agitated and beach littoral sub-environment with dom- Standard deviation vs mean size diagram using inance of beach shallow agitated sub- graphical method, indicates the beach sub- environment (Table 3). It is a clear indication that environment and same in the case with plot of studied samples are exclusively deposited by beach moment measures method, i.e. it also cluster in the and shallow marine processes with no indication of beach sub-environment (Figure 8(b)). aeolian processes. Standard deviation vs skewness (Friedman, 1967; The plot Y vs Y is used to differentiate between 2 3 Friedman, 1961) was plotted to distinguish beach and fluvial and shallow marine sub-environments, the river sub-environment. Graphical data show the sam- values obtained by graphical method are clustered ples to be exclusively of beach sub-environment while exclusively in fluvial beach environment, the data the moment data is showing it to be dominated by river obtained by moment analysis are quite scattered sub-environment while some of the samples also fall in (Figure 9(b)). It is dominated by shallow marine the beach sub-environment (Figure 8(c)). agitated environment with some samples falling 130 F. AHMAD ET AL. Table 3. Linear discriminate function analysis to interpret variation in energy and fluidity factors. Environmental symbols: B-beach, SM-shallow marine, F-fluvial, T-marine turbidity current. By graphical method By moment method S. no. Y1 Env. Y2 Env. Y3 Env. Y4 Env. Y1 Env. Y2 Env. Y3 Env. Y4 Env. JS-20 1.50 B 22.52 B −1.75 SM 5.81 F 3.54 B 57.05 B −2.47 SM 13.75 T JS-21 1.56 B 18.24 B −1.09 SM 4.98 F 1.75 B 55.85 B −4.34 SM 14.79 T JS-22 1.38 B 21.55 B −1.72 SM 5.62 F 3.77 B 63.15 B −3.25 SM 15.82 T JS-23 2.19 B 25.76 B −1.55 SM 6.52 F 4.04 B 58.28 B −2.06 SM 13.75 T JS-24 0.97 B 19.69 B −1.88 SM 5.27 F 4.66 B 76.78 SM −4.55 SM 20.10 T JS-25 1.94 B 23.52 B −1.46 SM 6.07 F 6.13 B 73.52 SM −2.58 SM 18.62 T JS-26 1.31 B 17.30 B −1.21 SM 4.76 F 5.50 B 90.99 SM −6.13 SM 25.33 T JS-27 1.67 B 25.86 B −2.07 SM 6.39 F 5.03 B 74.85 SM −3.46 SM 18.32 T JS-28 4.95 B 39.56 B −0.99 SM 10.17 T 4.86 B 56.41 B −0.87 SM 12.69 T JS-29 1.12 B 20.60 B −1.84 SM 5.43 F 3.18 B 55.99 B −2.72 SM 13.71 T JS-30 7.47 B 53.29 B −0.74 SM 14.05 T 6.63 B 32.25 B 4.05 SM 4.48 F JS-31 1.37 B 20.09 B −1.53 SM 5.34 F 5.69 B 77.63 SM −3.81 SM 20.37 T JS-32 1.60 B 23.08 B −1.73 SM 5.92 F 3.98 B 61.25 B −2.65 SM 14.86 T JS-33 1.33 B 21.55 B −1.78 SM 5.62 F 3.15 B 53.40 B −2.33 SM 12.81 T JS-34 0.69 B 21.30 B −2.41 SM 5.62 F 4.87 B 80.98 SM −4.89 SM 21.09 T JS-35 1.53 B 24.24 B −1.98 SM 6.11 F 4.39 B 68.03 SM −3.18 SM 16.65 T JS-36 1.13 B 21.11 B −1.90 SM 5.53 F −1.89 B 28.71 B −3.18 SM 5.77 F JS-37 2.05 B 26.51 B −1.79 SM 6.59 F 4.45 B 65.40 SM −2.58 SM 15.60 T JS-38 5.27 B 41.98 B −1.03 SM 10.73 T 5.18 B 62.41 B −1.29 SM 14.31 T JS-39 1.07 B 22.10 B −2.13 SM 5.72 F 4.40 B 71.19 SM −3.77 SM 17.98 T JS-40 1.04 B 19.54 B −1.76 SM 5.22 F 1.16 B 38.62 B −2.14 SM 8.87 F JS-41 2.64 B 20.69 B −0.51 SM 5.74 F 9.63 B 140.07 SM −9.92 F 41.50 T JS-42 2.78 B 21.44 B −0.49 SM 5.95 F 9.80 B 142.09 SM −10.06 F 42.12 T JS-43 1.13 B 13.78 B −0.87 SM 3.91 F 12.37 B 164.39 SM −11.07 F 48.94 T JS-44 2.34 B 19.07 B −0.54 SM 5.30 F 9.96 B 142.68 SM −10.07 F 42.33 T JS-45 2.78 B 20.97 B −0.43 SM 5.85 F 18.50 B 216.23 SM −13.27 F 64.70 T FS-1 1.74 B 16.49 B −0.70 SM 4.60 F 21.31 B 234.38 SM −13.19 F 68.49 T FS-2 1.62 B 16.68 B −0.83 SM 4.64 F 4.69 B 92.46 SM −7.26 SM 26.66 T FS-3 1.02 B 16.03 B −1.29 SM 4.47 F 11.11 B 137.76 SM −7.98 F 39.11 T FS-4 1.18 B 16.62 B −1.22 SM 4.60 F 4.57 B 82.35 SM −5.75 SM 22.77 T FS-5 1.19 B 15.45 B −1.06 SM 4.33 F 3.60 B 80.38 SM −6.43 SM 22.81 T FS-6 1.47 B 16.21 B −0.90 SM 4.51 F 4.29 B 88.02 SM −6.92 SM 25.25 T FS-7 1.02 B 14.31 B −1.05 SM 4.06 F 7.98 B 120.88 SM −8.53 F 35.25 T FS-8 1.07 B 18.41 B −1.59 SM 4.99 F 4.24 B 74.45 SM −4.66 SM 19.77 T FS-9 1.08 B 16.09 B −1.25 SM 4.48 F 5.03 B 88.29 SM −6.19 SM 24.71 T FS-10 1.58 B 15.55 B −0.73 SM 4.37 F 19.39 B 216.85 SM −12.51 F 64.37 T FS-11 1.32 B 16.54 B −1.09 SM 4.58 F 2.88 B 71.34 SM −5.71 SM 19.96 T FS-12 1.46 B 15.46 B −0.81 SM 4.33 F 8.02 B 125.53 SM −9.19 F 36.99 T FS-13 1.62 B 16.68 B −0.83 SM 4.64 F 4.73 B 93.01 SM −7.31 SM 26.84 T FS-14 −0.23 B 12.88 B −2.00 SM 3.97 F 4.49 B 89.89 SM −7.07 SM 25.87 T FS-15 1.90 B 17.71 B −0.73 SM 4.91 F 5.09 B 96.88 SM −7.55 F 28.02 T FS-16 1.12 B 14.53 B −0.99 SM 4.11 F 6.27 B 108.80 SM −8.28 F 31.79 T into fluvial beach and one sample is also found to shallow marine and turbidity. The plot of studied sam- fall in shallow marine beach environment (Table 3). ples concluded that all samples fall exclusively in beach Y vs Y plot shows that the most of studied sam- environment which is a reflection of deposition by the 3 4 ples fall in the turbidity current/shallow marine envir- rivers and subsequent sorting by the wave action. onment and three samples found to be in the field of fluvial/shallow marine environment by graphical C-M plot method. The moment analysis data shows a very scat- tered plot, mostly dominated by fluvial/shallow mar- Passega (1957) introduced the use of C-M plot to ine and fluvial environments and three samples have analyse the hydrodynamic forces that were opera- plotted in turbidity current/shallow marine environ- tional during the deposition of sediments. This dia- ment (Figure 9(c)). gram was plotted by the combination of coarsest grain in the sample, C (in microns) and M (Median in microns) on log probability curve. Generally the Multigroup discriminate analysis grain-size of clastic sediment defines the hydraulic Multigroup discriminant analysis has been used to dif- energy condition of the environment (Kalicki, 2000; ferentiate between various depositional environments Molinaroli et al., 2009; Le Roux & Rojas, 2007). The � � (Sahu, 1983). Eigen vectors V1 and V2 were calculated plot of studied samples on the C-M plot examined and plotted on the standard diagram of (Sahu, 1983) that the studied detritus were transported by rolling (Figure 10). Textural parameters were used to identify which is an indication of high energy conditions five depositional environments-dune, river, beach, (Figure 11). GEOLOGY, ECOLOGY, AND LANDSCAPES 131 Figure 10. Multigroup discriminant diagram after Sahu (1983) Figure 11. C-M plot to determine depositional mechanisms (after Passega, 1957). Log normal distribution curve it do not show a single line but more than one straight lines. Every segment of line depicts a different mode of Log probability curves were used to distinguish between transportation like traction bed load (> 1.0 mm), salta- the different modes of transport of sediments within tion (0.75–1.0 mm) and suspension (<0.1 mm). The a depositional medium (Visher, 1969). It is the repre- studied plot shows that the transportation of sediment sentation of cumulative grain-size distribution on by the traction processes (Figure 12). a probability plot. The importance of these data is that 132 F. AHMAD ET AL. Figure 12. Log probability curves showing the trend of various modes of transportation (after Visher, 1969). Conclusions related to differences in chemical resistance within the grains. This study once again proved the importance of grain- (2) The cumulative frequency percentage curves and size analysis of sandstone in depicting the depositional grain-size statistics of studied samples are classi- environments and processes that were functional at fied as coarse-grained and mainly have unimodal the time of the deposition and were further supported distribution with some of the samples also show- by surface textural analysis. The following conclusions ing bi-modality. The predominance of unimodal are drawn from this study- nature of sediments specifies pure sand without any mixing. The value of mean grain-size indi- (1) SEM studies indicating the grains to be depos- cates that the energy conditions of the depositing ited in shallow marine environments reworked agent was high; however, the presence of unim- by waves and tides. The dominance of mechan- odal nature of the sediments with minor bimod- ical activities over the chemical dissolution gen- ality suggests the consistent energy levels of erally reflects medium to high energy nearshore depositing medium. environments. The roughness of surfaces and (3) The average sorting of all the sandstone 0.16 edges of some quartz grains might reflect dif- represents very well-sorted grains, which are ferential chemical weathering that may be dominantly very fine to fine skewed and show GEOLOGY, ECOLOGY, AND LANDSCAPES 133 mainly very platykurtic to platykurtic beha- (western Rajasthan, India), as revealed from lithofacies and grain-size analysis. Geologica Acta, 15(3), 153–167. viour with some samples also showing meso- https://doi.org/10.1344/GeologicaActa2017.15.3.1 kurtic and leptokurtic behaviour. Bhat, G. M., & Ahmad, A. H. M. (2013). Temporal facies (4) Bivariate plots concluded that all these sediments and diagenetic evolution of the mixed siliciclastic- are deposited in beach sub-environment mainly carbonate Jajiya Member (Callovian–Oxfordian), by river processes. The linear and multigroup Jaisalmer Formation, West India. Volumina Jurassica, 11(11), 147–162. https://doi.org/10.1306/03B5A976- discriminant analyses also indicates beach envir- 16D1-11D7-8645000102C1865D. onment for deposition of these sediments. Biswas, S. K. (1982). Rift basins in western margin of India C-M plot shows the sediments to be transported and their hydrocarbon prospects with special reference to by the process of rolling and log-log plot shows the Kutch Basin. American Association of Petroleum dominance of traction processes. The sediments Geologists, 66(10), 1497–1513. https://doi.org/10.1306/ were mainly in traction and saltation before being 03B5A976-16D1-11D7-8645000102C1865D. Chayes, F. (1949). A simple point counter for thin-section deposited in a shallow marine condition. analysis. The American Mineralogist, Journal of the Mineralogical Society of America, 34(1–2), 1–11. Cheetham, M. D., Keene, A. F., Bush, R. T., Sullivan, L. A., & Acknowledgements Erskine, W. D. (2008). A comparison of grain-size analy- sis methods for sand-dominated fluvial sediments. The authors are very thankful to the Chairperson, Sedimentology, 55(6), 1905–1913. https://doi.org/10. Department of Geology (A.M.U., Aligarh) for providing 1111/j.1365-3091.2008.00972.x the necessary facilities. The authors are grateful to Ms. Das Gupta, S. K. (1975). A revision of the Mesozoic-Tertiary Sadia Khanam and Ms. Aashna Javed (Research Scholars, stratigraphy of the Jaisalmer Basin, Rajasthan. Indian Sedimentology Lab, Department of Geology, A.M.U.) for Journal of Earth Sciences, 2(1), 77–94. helping in carrying out the required calculations. Flemming, B. W. (2007). 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Geology Ecology and LandscapesTaylor & Francis

Published: Apr 3, 2021

Keywords: Granulometric analysis; hydrodynamic condition; depositional environment; Fort Member; Jaisalmer Formation

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