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

ABSTRACT Granulometric analysis is an imperative tool used to reveal the hydrodynamic conditions, mode 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 help of detailed granulometric analysis which include both graphical as well as mathematical moment methods. Micro textures were recognized as chatter marks, curved and straight steps, grooves, upturned plates in association with V impact pits and triangular solution pits suggesting the predominance of mechanical activities over the chemical dissolution. The analysis 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
Grain-size parameters are fundamental tool for identifying the sedimentary environments such as beach, dune and river and some other divisions of continental shelf through graphic as well as mathematical moment methods used along with other textural properties. Grain-size is the utmost important property of the sediments, affecting their entrainment, transport and deposition. Therefore, grain-size analysis offers significant evidences to the sediments provenance, transport history and depositional conditions (Ghaznavi et al., 2019;Quasim et al., 2020;Sahu, 1964;Visher, 1969).
Despite the usefulness of grain-size analysis in studies of siliciclastic sedimentary rocks, there are various limitations for grain-size parameters also. These limitations include changes or subsequent modifications that a framework particle undergoes when it is subjected to diagenesis (Ghaznavi et al., 2019;Ghosh & Chatterjee, 1994). Irrespective of these restrictions, parameters of grain-size analysis have been used successfully in previous studies and proved to be useful in interpreting provenance, mechanism of transportation and environment of deposition (Ahmad et al., 2017a;Cheetham et al., 2008;Ghaznavi et al., 2019;Kanhaiya et al., 2017;Quasim et al., 2020;Kanhaiya & Singh, 2014;Weltje & Prins, 2007). In aggregation with different sedimentological factors like structures of sedimentary origin and their associations, palaeoflow, fossil content and geometry, grain-size analysis becomes an essential tool for a better understanding of the depositional environment as they are mostly dependent on the syndepositional processes (Reading, 1996).
The pericratonic Jaisalmer basin situated to the west of Aravalli axis on the western part of the Indian peninsula, formed the eastern most part of the Indo-Arabian Geological Province (Pandey & Choudhary, 2007). The basin has attracted the attention of geologists and palaeontologists due to its rich record of well-preserved Jurassic to Tertiary fossils. Recently, the basin has also been proved its potential for oil and gas reserves and categorized category-I (producing) basin by Directorate General of Hydrocarbons (DGH). Therefore, the research on the sedimentary features of the Jaisalmer Formation may understand the petroleum geology characteristics and tectonic evolution history in this area.
The Jurassic Jaisalmer basin is predominantly a carbonate facies and inter-bedded with calcareous sandstone and shale deposited under marginal marine to occasional shelf lagoon conditions of deposition which has huge hydrocarbon generation potential and reservoir potential (Ahmad et al., 2020b;Pandey & Maurya, 2020). Previous studies mainly focussed on the sedimentological attributes like tectono-provenance (Ahmad et al., 2019), diagenetic evolution (Ahmad et al., 2017b;Mahender & Banerji, 1990) and depositional environment (Ahmad et al., 2020a(Ahmad et al., , 2017aBhat & Ahmad, 2013;Pandey et al., 2006Pandey et al., , 2006b but the research on the sedimentary hydrodynamic conditions of Fort Member Sandstone has not started yet. Sandstone grain-size characteristics are of great significance in the analysis of sedimentary hydrodynamic conditions (Ghaznavi et al., 2019;Ghosh & Chatterjee, 1994;Quasim et al., 2020). Based on the analysis of sandstone grain-size characteristics (both graphical as well as mathematical moment methods) of the Fort Member of the Jaisalmer Formation, Western Rajasthan, the evolution history of sedimentary hydrodynamic conditions of the Fort Member Sandstone in this region can be reconstructed.

Geological background
The Rajasthan shelf has been divided into four units namely: the Jaisalmer basin, the Bikaner-Nagaur basin, the Barmer-Sanchor basin and the Pokharan-Nachana high but owing to continuous alteration of tectonic setting and palaeogeographic conditions the extent of these basins on Rajasthan shelf kept on changing through time. The Precambrian igneous (Malani volcanics)/metamorphic rocks form the basement for the later deposited sedimentary sequences of Western Rajasthan Basin, but they are exposed in only few locations around Pokhran, Jodhpur and Barmer.
The Jaisalmer basin covers entire district of Jaisalmer in West Rajasthan and neighbouring Kachchh basin in the south with depth of the basement 10,000 m near the Indo-Pak border (Figure 1  (a)). It is a pericratonic basin positioned at the west of the Aravalli axis on the western part of the Indian craton with dip direction in the north-west. It represents the Tethyan margin during the Jurassic, when it was located at about 23 ᵒ south of the equator. On the basis of geophysical investigations conducted by ONGC, four geostructural units are found (Figure 1 (b)) which are Mari-Jaisalmer arch, the synclinal Shahgarh sub-basin, the Kishangarh sub-basin and the Miajlar sub-basin (Raghavendra Rao, 1972;Singh et al., 2005;Sinha et al., 1993). Sedimentation in the Jurassic Jaisalmer basin starts with widely spread  Biswas, 1982;Misra et al., 1993); (c) geological map of Jaisalmer basin showing outcrop of the Jaisalmer Formation, Western Rajasthan (after Jodhawat & Kachhara, 2000). deltaic, fluvial or lacustrine sediments in the basal Lathi Formation (Srivastava, 1966) followed by marginal marine sediments which in turn then followed by a series of various non-marine, marginal marine and fully marine sediments. Lithostratigraphically, these deposits are classified into Jaisalmer, Baisakhi and Bhadasar formations (Das Gupta, 1975;Pandey, Fürsich, Sha et al., 2009;Pandey et al., 2006Pandey et al., , 2005Pandey et al., , 2006b. Geologically, the Jaisalmer basin is represented by a sequences of shale, siltstone, sandstone and limestone. The depositional settings in the Jaisalmer basin fluctuate from fluvial/lagoonal, delta front, shoreface to offshore environment with shifting water energy and salinity (Ahmad et al., 2017a;Pandey et al., 2006Pandey et al., , 2006b. Although based on lithostratigraphic studies, it is revealed that there is cyclicity in sedimentation present in all the formations but it is most prominent and well displayed in the Jaisalmer Formation (JaiKrishna, 1987;Pandey & Fürsich, 1994;Pandey et al., 2009;Pandey et al., 2006Pandey et al., , 2006b. Jaisalmer Formation has been further classified lithostratigraphically into the Hamira, Joyan, Fort, Badabag, Kuldhar and Jajiya members in increasing order (Figure 1(c)) (Das Gupta, 1975). Except for the Phanerozoic outcrops overlying the Precambrian basement in the eastern and southern parts, whole of the basin is covered by sand dunes or sands of Thar Desert. Pareek (1984) estimated the thickness of Jaisalmer Formation as 300 m. The sub-surface thickness as observed by drilling is more than 600 m (Das Gupta, 1975).
The best exposure of studied Fort Member is found along the Jaisalmer fort escarpments. It is widest in northern part and get narrower progressively towards south. It contains fine-to medium-grained sandstones, oolitic, sandy, bioturbated and fossiliferous nature of limestones, and cross-bedded sandy limestones (Mahender & Banerji, 1990;Pandey & Dave, 1998;Pandey et al., 2006). The sandstones are calcareous in nature and possess current bedding in upper part. The limestones are yellowish brown in colour, compact and fossiliferous. These limestones also have thin inter-beds of limestone that possess brachiopod and mollusca shell fragments. It contains various taxa of brachiopods, echinoids, gastropods, corals, bryozoans and foraminifers. On the basis of the stratigraphic position and inter-basinal correlation of marker-beds (Pandey et al., 2009) the age of Fort Member is interpreted as Early Bathonian to Middle/Late Bathonian.

Materials and methodology
Three lithostratigraphic sections representing the Fort Member of Jaisalmer Formation were measured ( Figure 2). Forty-two fresh samples of sandstone were collected from the outcrop in Near Fort scarp, Shiv Madi Darbar and Jaithawai road. Thin-sections were prepared for these forty-two sandstone samples for their textural analysis. On an average about 200-300 grains were counted in each thin section following the method of Chayes (1949). Scanning Electron Microscope (SEM) images were used for the identification of ultra-textures present in the quartz grains of the Fort Member. Quartz grains were visually examined using JEOL JSM-5800 LV scanning electron microscope at University Sophisticated Instrument Facility (USIF), AMU, Aligarh. Phi-scale proposed by Krumbein (1934), was used and the size data were grouped in half-phi scale intervals. Cumulative frequency curves were plotted on a log probability scale. Grain diameters in phi-unit that are represented by ϕ5, ϕ16, ϕ25, ϕ50, ϕ75, ϕ84 and ϕ95 percentiles were analysed from the size frequency curves. Using these values various statistical parameters are calculated like mean size, standard deviation, skewness and kurtosis. These parameters were calculated using both the graphical method as well as moment measures method.
According to calculations given by Krumbein and Pettijohn (1938), Folk (1968, 1980), and McBride (1971, these statistical parameters have been classified. The mathematical method of moments used in the present study was introduced by Krumbein and Pettijohn (1938). Various bivariate plots are plotted between these values to establish the interrelationships.
Linear Discriminate Analysis (LDA) was done to interpret the depositional sub-environment using following formula after Sahu (1964) It is used to delineate between fluvial and marine turbidity sub-environment.
For marine turbidity sub-environment Y > 10.00 For fluvial sub-environment Y < 10.00 Multigroup discriminant analysis (Sahu, 1983) was carried out to differentiate between various depositional environments using the formula; Energy variation and fluidity factors are dependent on different processes and the depositional environment (Sahu, 1964).

Surface features on quartz sand grains
Scanning Electron Microscopy (SEM) of quartz grains has paved way for discrimination between various sedimentary environments depending on their surface textures (Krinsley & Donahue, 1968;Krinsley & Doornkamp, 2011;Krinsley & Margolis, 1969). The ultra-textures provide valuable details about the different processes which were operational during the transportation and after the deposition of grains (Krinsley & Funnell, 1965;Mahaney, 1998;Newsome & Ladd, 1999) and the parameters have been set to distinguish between the mechanical and chemical features (Krinsley & Donahue, 1968;Rahman & Ahmed, 1996;Whalley & Krinsley, 1974). Surface textures of quartz sand grains have also been used to identify the provenance and mode of origin of various detrital sediments. SEM analysis of quartz sand grains from Fort Member Sandstone has shown various surface features such as chatter marks, curved and straight steps, grooves, upturned plates in association with V impact pits and triangular solution pits.
Chatter marks are series of sub-parallel indentations which is formed when part of a grain skips across another grain (Figure 3(a)). Grooves are caused by drawing of sharp edge of a grain across another (Krinsley & Margolis, 1969), they are further modified by the fracture and solution activities (Figure 3(b)). These quartz grains also show curved and straight steps in association with silica precipitation (Figure 3 (c)). Small V-shaped indentations (Figure 3(d,f)) are formed by grain to grain collision in an aqueous medium (Krinsley & Margolis, 1969). Surfaces of the quartz grains from the Fort Member Sandstone exhibit silica precipitation features like irregular plates and cavity filling. Furthermore, excess silica is pressed over quartz grain surface in non-oriented patterns (Figure 3(e)). It may be explained by the movement of grains across one another under high pressure (Krinsley & Doornkamp, 2011). On the basis of results from SEM studies it is concluded that the studied samples have been deposited in shallow marine environment as it is reworked by waves and tides to form these beach sand deposits. The dominance of mechanical activities over the chemical dissolution generally reflects medium to high energy nearshore environments. Also the roughness of surfaces and edges of some quartz grains in Figure 3(c,d) might reflect differential chemical weathering that may be related to differences in chemical resistance within the grains (Krinsley & Doornkamp, 2011).

Frequency curves
Phi values are plotted against the frequency distribution of each grain-size in the frequency curves. These curves show modality or predominance of a particular size class. These frequency curves are dominantly unimodal with the distribution of curves around 0.4ϕ for FS samples (Figure 4(a)) and distribution of curves around 0.35ϕ for JS samples (Figure 4(b)) although few samples show different frequency curve distribution around 0.5ϕ. This indicates all of the samples are predominantly unimodal in nature and have sediments of pure sand type without any mixing of silt particles. The unimodality is also indicative of more or less consistent depositional process during the time of sediment settling.
In some of the samples JS 26,27,41,42,43) bimodality can also be seen with samples showing peaks at around 1.4ϕ (Figure 4(b)). The bimodality is attributed to mixing of different size grains, variation in velocity of depositional processes and the difference in mode of transportation. Samples showing unimodality and bimodality are shown in Figure 5(a,d).
Phi scales are plotted against the cumulative frequencies ( Figure 6), giving an idea about various modes of sediment transportation, deposition and their importance in the genesis of sandstones. Sorting of the     can be obtained by the slope of middle portion of the curve. Poor sorting is indicated by a broad and gentle gradient of the curve which also indicates low kinetic energy and velocity. A very steep slope, whereas, is indicative of good sorting, high kinetic energy and high velocity. All of the studied samples are coarse grained, and based on the steepness of the gradient of the cumulative frequency curves can be regarded as very well sorted ( Figure 6).

Graphical method
(1) Inclusive Graphic Median (ϕ 50 )-Median corresponds to the 50 percentile, half of the particles are coarser and the other half are finer. Studied samples range from 0.12 to 0.34, with an average of 0.19 (Table 1). Based on the data all of studied samples are coarse grained.
(2) Graphic Mean Size (Mz)-Mean size is indicative of the average particle size. In studied samples Mz ranges from 0.04 to 0.11 with an average of 0.06 (Table 1). It implies that all of studied samples are coarse-grained sands. There is minute variability in the grain size of samples which make these samples very well sorted. (3) Standard Deviation (σ 1 )-It depicts the sorting or uniformity of grains which in turn indicates the prevailing energy conditions at the time of transportation and deposition. Studied samples are ranging from 0.09 to 0.24 with an average of 0.16 (Table 1) which indicate that all of the samples are very well sorted which gives an indication of smooth and constant current flow and velocity. (4) Graphic Skewness (SK 1 )-Measures the degree to which a cumulative curve approach symmetry in terms of predominance of fine-or coarsegrained fractions. The value of skewness in studied samples range from 0.09 to 0.42 with an   (Table 1) which gives an indication that most of the samples are fine skewed followed by very fine skewed and nearly symmetrical skewed. (5) Graphic Kurtosis (K G )-Kurtosis is measure of peakedness in a curve. Values of Kurtosis in studied sample ranges from 0.24 to 2.52 with an average of 0.76 (Table 1). Peakedness is mainly dominated by very platykurtic behaviour which indicates a thinner than normal tail, followed by platykurtic, very leptokurtic which indicates a thicker than normal tail and mesokurtic behaviour which corresponds to equal thickness throughout the curve.

Mathematical moment method
(1) 1 st Moment-Mean (� x)-In studied samples the values of mean ranges from 0.29 to 0.6 with an average value of 0.42 (Table 2). These values indicate that all of studied samples are coarse grained.
(2) 2 nd Moment-Standard Deviation (σ ϕ )-Its value in studied samples range from 0.14 to 0.32 with an average of 0.24 (Table 2). It is a clear indication of grains being very well sorted which is also an indication of uniform energy condition prevailing at the time of deposition. (3) 3 rd Moment-Skewness (SK ϕ )-The values of skewness in studied samples range from −0.09 to 2.77 with an average of 1.10 ( Table 2). The samples are dominated equally by very fine skewed and fine skewed grains followed by near symmetrical skewed grains and coarse skewed grains. (4) 4 th 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 platykurtic behaviour with more than half of the samples showing the same. It is then followed by mesokurtic and leptokurtic behaviours in equal measure and very platykurtic and very leptokurtic behaviours.

Interrelationship of textural parameters
To demarcate different depositional environments, the combination of several textural parameters in the form of bivariant plots has been used (Friedman, 1979). The basis behind these plots is the assumption that statistical parameters reliably reflect variations in the fluid flow mechanism of sediment transportation and deposition (Sutherland & Lee, 1994). Various workers supposed that these plots can serve as a reliable tool for delineating processes of different environment of sedimentation (Martins, 2003;Srivastava et al., 2010Srivastava et al., , 2012Srivastava & Mankar, 2009;Sutherland & Lee, 1994). The bivariate plot between mean size and standard deviation shows the samples clustered at the centre of the curve denoting the samples to be coarse grained and very well sorted (Figure 7(a)). The clustering of the samples in a narrow region is indicative of very less mixing of sediments. This type of curve shows that there is minute difference between the grain sizes and hence the studied samples are very well sorted.
The plot between skewness and standard deviation (Figure 7(b)) helps to differentiate river sediments from beach sediments (Flemming, 2007;Friedman, 1967;Friedman, 1961). A symmetrical curve is obtained in two cases (1) unimodal sample with good sorting, or (2) equal mixtures of the two modes which have the poorest possible sorting (Folk & Ward, 1957). Studied samples are very well sorted and positively skewed showing the unimodal behaviour.
The trend between mean size and skewness is sinusoidal (Figure 7(c)). The pure sand mode occurs by itself produces a symmetrical size curve, but addition of increasing quantities of gravel mode imparts negative skewness. Positive skewness is shown when coarser mode of the sediment are more dominant (Folk & Ward, 1957). The plot shows that all of the samples are positively skewed, coarse-grained and the trend of the curve is close to sinusoidal. River sands are generally positively skewed while coarse-grained river sand can be either positively or negatively skewed (Friedman, 1961). Based on this, studied samples indicate river sand and deposited in shallow marine environment.
According to Folk and Ward (1957), poor sorting is found in the bimodal mixtures with equal amounts of the two modes, and these two will also have lowest kurtosis, while, the highest kurtosis is associated with the samples which have one dominant and one very subordinate mode and moderate sorting. Unimodal sediments produce normal kurtosis and very wellsorted samples (Folk & Ward, 1957). Studied samples fall in the last category, i.e. these are unimodal, have normal kurtosis and are very well sorted (Figure 7(d)).
The plot of mean against kurtosis (Figure 7(e)) shows mixing of two or more size classes of sediment which affects the sorting of central and tail part of the curve (Flemming, 2007;Molinaroli et al., 2009). According to Folk and Ward (1957), the presence of only one mode results in nearly normal curve, i.e. K G = 1.0. Addition of very small amount (3-10%) of another mode results in poorer sorting in the tail and better in the centre making the curve very leptokurtic with K G >1.0. Very platykurtic behaviour is obtained when two modes are present in sub-equal amount (anything from 25-75% to 75-25%). Most of studied samples are showing very platykurtic to platykurtic behaviour with three samples showing mesokurtic and further three showing very leptokurtic with constant coarse grain. It is an indication that most of studied samples are dominated by coarse sand and in case of bimodal sediments the second mode is present in sub-ordinate amount.
Skewness vs kurtosis properties of samples depend on the proportions of the two modes present, generally pure sand mode gives normal curve, whereas, by addition of other modes it is disturbed (Folk & Ward, 1957). Studied samples mainly fall below the shaded zone indicating the dominance of very platykurtic to platykurtic grains with some samples mesokurtic to very leptokurtic behaviour. All the studied samples are positively skewed giving an indication that sand is dominant constituent with subordinate amount of silt (Figure 7(f)).

Bivariate grain-size parameters
Statistical parameters achieved by graphical as well as moment methods were plotted in various bivariate diagrams, to know the environmental conditions that  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).
were present at that time. To differentiate between river, beach and coastal dune sub-environments, Friedman (1961), and Moiola and Weiser (1968), plotted mean size versus standard deviation. The bivariate is most useful in differentiating between beach and river sands and river and coastal dune sands and the differentiation works well regardless of whether quarter, half or whole phi data are used (Moiola & Weiser, 1968). Stewart (1958) distinguished between river and wave process by plotting median grain size vs standard deviation. The plots of both graphical as well as moment analysis indicate that all of the samples were deposited in beach sub-environment (Figure 8(a)).
Standard deviation vs mean size diagram using graphical method, indicates the beach subenvironment and same in the case with plot of moment measures method, i.e. it also cluster in the beach sub-environment (Figure 8(b)).
Standard deviation vs skewness (Friedman, 1967;Friedman, 1961) was plotted to distinguish beach and river sub-environment. Graphical data show the samples to be exclusively of beach sub-environment while the moment data is showing it to be dominated by river sub-environment while some of the samples also fall in the beach sub-environment (Figure 8(c)).

Linear discriminate analysis
Linear discriminant function analysis is a vital tool in identifying the environment at the time of sediment deposition. Sahu (1964) stated that there is definite correlation between fluctuations in energy and fluidity and different operating processes and environment in which sediments are deposited. In this study both linear and multi-group discriminant function analysis (Sahu, 1964(Sahu, , 1983 used to further distinguish depositional environments. Y 1 vs Y 2 plot by graphical method indicates that all of studied samples fall strictly in beach littoral subenvironment (Figure 9(a)), and by moment method, the samples are scattered in the fields of beach shallow agitated and beach littoral sub-environment with dominance of beach shallow agitated subenvironment (Table 3). It is a clear indication that studied samples are exclusively deposited by beach and shallow marine processes with no indication of aeolian processes.
The plot Y 2 vs Y 3 is used to differentiate between fluvial and shallow marine sub-environments, the values obtained by graphical method are clustered exclusively in fluvial beach environment, the data obtained by moment analysis are quite scattered (Figure 9(b)). It is dominated by shallow marine agitated environment with some samples falling into fluvial beach and one sample is also found to fall in shallow marine beach environment (Table 3).
Y 3 vs Y 4 plot shows that the most of studied samples fall in the turbidity current/shallow marine environment and three samples found to be in the field of fluvial/shallow marine environment by graphical method. The moment analysis data shows a very scattered plot, mostly dominated by fluvial/shallow marine and fluvial environments and three samples have plotted in turbidity current/shallow marine environment (Figure 9(c)).

Multigroup discriminate analysis
Multigroup discriminant analysis has been used to differentiate between various depositional environments (Sahu, 1983). Eigen vectors � V1 and � V2 were calculated and plotted on the standard diagram of (Sahu, 1983) ( Figure 10). Textural parameters were used to identify five depositional environments-dune, river, beach, shallow marine and turbidity. The plot of studied samples concluded that all samples fall exclusively in beach environment which is a reflection of deposition by the rivers and subsequent sorting by the wave action. Passega (1957) introduced the use of C-M plot to analyse the hydrodynamic forces that were operational during the deposition of sediments. This diagram 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 grain-size of clastic sediment defines the hydraulic energy condition of the environment (Kalicki, 2000;Molinaroli et al., 2009;Le Roux & Rojas, 2007). The plot of studied samples on the C-M plot examined that the studied detritus were transported by rolling which is an indication of high energy conditions ( Figure 11). 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.

Log normal distribution curve
Log probability curves were used to distinguish between the different modes of transport of sediments within a depositional medium (Visher, 1969). It is the representation of cumulative grain-size distribution on a probability plot. The importance of these data is that it do not show a single line but more than one straight lines. Every segment of line depicts a different mode of transportation like traction bed load (> 1.0 mm), saltation (0.75-1.0 mm) and suspension (<0.1 mm). The studied plot shows that the transportation of sediment by the traction processes ( Figure 12).

Conclusions
This study once again proved the importance of grainsize analysis of sandstone in depicting the depositional environments and processes that were functional at the time of the deposition and were further supported by surface textural analysis. The following conclusions are drawn from this study- (1) SEM studies indicating the grains to be deposited in shallow marine environments reworked by waves and tides. The dominance of mechanical activities over the chemical dissolution generally reflects medium to high energy nearshore environments. The roughness of surfaces and edges of some quartz grains might reflect differential chemical weathering that may be related to differences in chemical resistance within the grains. (2) The cumulative frequency percentage curves and grain-size statistics of studied samples are classified as coarse-grained and mainly have unimodal distribution with some of the samples also showing bi-modality. The predominance of unimodal nature of sediments specifies pure sand without any mixing. The value of mean grain-size indicates that the energy conditions of the depositing agent was high; however, the presence of unimodal nature of the sediments with minor bimodality suggests the consistent energy levels of depositing medium. (3) The average sorting of all the sandstone 0.16 represents very well-sorted grains, which are dominantly very fine to fine skewed and show mainly very platykurtic to platykurtic behaviour with some samples also showing mesokurtic and leptokurtic behaviour. (4) Bivariate plots concluded that all these sediments are deposited in beach sub-environment mainly by river processes. The linear and multigroup discriminant analyses also indicates beach environment for deposition of these sediments. C-M plot shows the sediments to be transported by the process of rolling and log-log plot shows the dominance of traction processes. The sediments were mainly in traction and saltation before being deposited in a shallow marine condition.