Workflow for analysis of compositional data in sedimentary petrology: provenance changes in sedimentary basins from spatio-temporal variation in heavy-mineral assemblages

2018 ◽  
Vol 156 (07) ◽  
pp. 1111-1130 ◽  
Author(s):  
J. VERHAEGEN ◽  
G.J. WELTJE ◽  
D. MUNSTERMAN
Keyword(s):  
Compositional Data ◽  
Principal Component ◽  
Sedimentary Basins ◽  
Heavy Mineral ◽  
Provenance Analysis ◽  
Sedimentary Petrology ◽  
Mineral Data ◽  
Spatio Temporal ◽  
Data Tables ◽  
Log Ratio

AbstractThe field of provenance analysis has seen a revival in the last decade as quantitative data-acquisition techniques continue to develop. In the 20th century, many heavy-mineral data were collected. These data were mostly used as qualitative indications for stratigraphy and provenance, and not incorporated in a quantitative provenance methodology. Even today, such data are mostly only used in classic data tables or cumulative heavy-mineral plots as a qualitative indication of variation. The main obstacle to rigorous statistical analysis is the compositional nature of these data which makes them unfit for standard multivariate statistics. To gain more information from legacy data, a straightforward workflow for quantitative analysis of compositional datasets is provided. First (1) a centred log-ratio transformation of the data is carried out to fix the constant-sum constraint and non-negativity of the compositional data. Next, (2) cluster analysis is followed by (3) principal component analysis and (4) bivariate log-ratio plots. Several (5) proxies for the effects of sorting and weathering are included to check the provenance significance of observed variations and finally a (6) spatial interpolation of a provenance proxy extracted from the dataset can be carried out. To test this methodology, available heavy-mineral data from the southern edge of the Miocene North Sea Basin are analysed. The results are compared with available information from literature and are used to gain improved insight into Miocene sediment input variations in the study area.

scholarly journals Interpretation of Sedimentary Processes Using Heavy Mineral Unconstrained Data

2018 ◽  
Author(s):  
João Cascalho
Keyword(s):  
Low Frequency ◽  
Principal Component ◽  
Heavy Mineral ◽  
Heavy Minerals ◽  
Primary Sources ◽  
Metamorphic Rocks ◽  
Mineral Occurrence ◽  
Mineral Data ◽  
Grain Sorting ◽  
Log Ratio

This work describes and interprets the presence of heavy minerals in the western Portuguese continental margin using a set of 78 bottom samples collected from 3 distinct areas of this margin: Porto, Aveiro and Nazaré canyon head areas. The main transparent heavy mineral suite (minerals with frequencies >10%), is composed by amphiboles (hornblende), mica (biotite), andalusite, tourmaline and garnet. A secondary suite (minerals with frequencies between 1 and 10%), is composed by pyroxene (enstatite, diopside and augite), staurolite, zircon and apatite. With very low frequency representing less than 1% we found rutile, olivine, kyanite, monazite, epidote, sphene, anatase, sillimanite and brookite. The main primary sources (igneous and metamorphic rocks) explain the presence of these minerals. However, the application of the principal component analysis, with a previous application of the centered log ratio transformation of the heavy mineral data, also stresses for the importance of the grain sorting as a process in controlling the heavy mineral occurrence. The importance of this process is mostly sustained by the distribution pattern of mica and of the most flattened amphibole grains in a way that these particles tend to have a hydraulic affinity to finer grained sediments.

Correspondence Analysis In Heavy Mineral Interpretation

1994 ◽  
Author(s):  
J. Tourenq ◽  
V. Rohrlich
Keyword(s):  
Principal Component Analysis ◽  
Correspondence Analysis ◽  
Principal Component ◽  
Sedimentary Basins ◽  
Component Analysis ◽  
Heavy Mineral ◽  
Heavy Minerals ◽  
Data Sets ◽  
Mineral Data ◽  
Non Parametric

Correspondence analysis, a non-parametric principal component analysis, has been used to analyze heavy mineral data so that variations between both samples and minerals can be studied simultaneously. Four data sets were selected to demonstrate the method. The first example, modern sediments from the River Nile, illustrates how correspondence analysis brings out extra details in heavy mineral associations. The other examples come from the Plio-Quaternary "Bourbonnais Formation" of the French Massif Central. The first data set demonstrates how the principal factor plane (with axes 1 and 2) highlights relationships between geographical position and the predominant heavy mineral association (metamorphic minerals and zircon), suggesting the paleogeographic source. In the second set, the factor plane of axes 1 and 3 indicates a subdivision of the metamorphic mineral assemblage, suggesting two sources of metamorphic minerals. Finally, outcrop samples were projected onto the factor plane and reveal ancient drainage systems important for the accumulation of the Bourbonnais sands. Statistical methods used in interpreting heavy minerals in sediments range from simple and classical methods, such as calculation of means and standard deviations, to the calculation of correspondences and variances. Use of multivariate methods is increasingly frequent (Maurer, 1983; Stattegger, 1986; 1987; Delaune et al., 1989; Mezzadri and Saccani, 1989) since the first studies of Imbrie and vanAndel (1964). Ordination techniques such as principal component analysis (Harman, 1961) synthesize large amounts of data and extract the most important relationships. We have chosen a non-parametric form of principal component analysis called correspondence analysis. This technique has been used in sedimentology by Chenet and Teil (1979) to investigate deep-sea samples, by Cojan and Teil (1982) and Mercier et al. (1987) to define paleoenvironments, and by Cojan and Beaudoin (1986) to show paleoecological control of deposition in French sedimentary basins. Correspondence analysis has been used successfully to interpret heavy mineral data (Tourenq et al, 1978a, 1978b; Bolin et al, 1982; Tourenq, 1986, 1989; Faulp et al, 1988; Ambroise et al, 1987). We provide examples of different situations where the method can be applied. We will not present the mathematical and statistical procedures involved in correspondence analysis, but refer readers to Benzécri et al.

Detrital zircon geochronology and heavy mineral analysis as complementary provenance tools in the presence of extensive weathering, reworking and recycling: the Neogene of the southern North Sea Basin

2021 ◽  
pp. 1-13
Author(s):  
Jasper Verhaegen ◽  
Hilmar von Eynatten ◽  
István Dunkl ◽  
Gert Jan Weltje
Keyword(s):  
North Sea ◽  
Chemical Weathering ◽  
Heavy Mineral ◽  
Mineral Analysis ◽  
Provenance Analysis ◽  
Detrital Zircon Geochronology ◽  
Southern North Sea ◽  
Variable Heavy ◽  
Mineral Data ◽  
Heavy Mineral Analysis

Abstract Heavy mineral analysis is a long-standing and valuable tool for sedimentary provenance analysis. Many studies have indicated that heavy mineral data can also be significantly affected by hydraulic sorting, weathering and reworking or recycling, leading to incomplete or erroneous provenance interpretations if they are used in isolation. By combining zircon U–Pb geochronology with heavy mineral data for the southern North Sea Basin, this study shows that the classic model of sediment mixing between a northern and a southern source throughout the Neogene is more complex. In contrast to the strongly variable heavy mineral composition, the zircon U–Pb age spectra are mostly constant for the studied samples. This provides a strong indication that most zircons had an initial similar northern source, yet the sediment has undergone intense chemical weathering on top of the Brabant Massif and Ardennes in the south. This weathered sediment was later recycled into the southern North Sea Basin through local rivers and the Meuse, leading to a weathered southern heavy mineral signature and a fresh northern heavy mineral signature, yet exhibiting a constant zircon U–Pb age signature. Thus, this study highlights the necessity of combining multiple provenance proxies to correctly account for weathering, reworking and recycling.

scholarly journals On establishing ceramic chemical groups: exploring the influence of data analysis methods and the role of the elements chosen in analysis

2013 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Kostalena Michelaki ◽  
Michael J. Hughes ◽  
Ronald G.V. Hancock
Keyword(s):  
Principal Component Analysis ◽  
Data Analysis ◽  
Compositional Data ◽  
Principal Component ◽  
Component Analysis ◽  
Data Exploration ◽  
Short Paper ◽  
Bivariate Data ◽  
Chemical Groups ◽  
Log Ratio

Since the 1970s, archaeologists have increasingly depended on archaeometric rather than strictly stylistic data to explore questions of ceramic provenance and technol- ogy, and, by extension, trade, exchange, social networks and even identity. It is accepted as obvious by some archaeometrists and statisti- cians that the results of the analyses of compo- sitional data may be dependent on the format of the data used, on the data exploration method employed and, in the case of multivari- ate analyses, even on the number of elements considered. However, this is rarely articulated clearly in publications, making it less obvious to archaeologists. In this short paper, we re- examine compositional data from a collection of bricks, tiles and ceramics from Hill Hall, near Epping in Essex, England, as a case study to show how the method of data exploration used and the number of elements considered in multivariate analyses of compositional data can affect the sorting of ceramic samples into chemical groups. We compare bivariate data splitting (BDS) with principal component analysis (PCA) and centered log ratio-principal component analysis (CLR-PCA) of different unstandardized data formats [original concen- tration data and logarithmically transformed (i.e. log10 data)], using different numbers of elements. We confirm that PCA, in its various forms, is quite sensitive to the numbers and types of elements used in data analysis.

scholarly journals Log-ratio analysis of microbiome data with many zeroes is library size dependent

2020 ◽  
Author(s):  
Dennis te Beest ◽  
Els Nijhuis ◽  
Tim Mohlmann ◽  
Caro Ter braak
Keyword(s):  
Compositional Data ◽  
Explanatory Variable ◽  
Principal Component ◽  
Real Data ◽  
Amplicon Sequencing ◽  
Sequencing Data ◽  
Library Size ◽  
Sequencing Platform ◽  
Microbiome Composition ◽  
Log Ratio

Microbiome composition data collected through amplicon sequencing are count data on taxa in which the total count per sample (the library size) is an artifact of the sequencing platform and as a result such data are compositional. To avoid library size dependency, one common way of analyzing multivariate compositional data is to perform a principal component analysis (PCA) on data transformed with the centered log-ratio, hereafter called a log-ratio PCA. Two aspects typical of amplicon sequencing data are the large differences in library size and the large number of zeroes. In this paper we show on real data and by simulation that, applied to data that combines these two aspects, log-ratio PCA is nevertheless heavily dependent on the library size. This leads to a reduction in power when testing against any explanatory variable in log-ratio redundancy analysis. If there is additionally a correlation between the library size and the explanatory variable, then the type 1 error becomes inflated. We explore putative solutions to this problem.

Sediment provenance analysis of the Permian from the Perth Basin using an automated Raman heavy mineral technique

2021 ◽  
Vol 61 (2) ◽  
pp. 688
Author(s):  
Stuart Munday ◽  
Anne Forbes ◽  
Brenton Fairey ◽  
Juliane Hennig-Breitfeld ◽  
Tim Breitfeld ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Heavy Mineral ◽  
Heavy Minerals ◽  
Sediment Provenance ◽  
Late Permian ◽  
Provenance Analysis ◽  
Spectroscopy Analysis ◽  
The North ◽  
Mineral Data ◽  
Provenance Variations

The Early Permian in the onshore Perth Basin has experienced several significant discoveries in the last 8 years. Beginning with the play-opening Waitsia discovery (AWE), this was followed more recently by the Beharra Springs Deep (Beach Energy) and West Erregulla (Strike) discoveries. In addition, Late Permian sands (Dongara and Wagina sandstones) have long been recognised as excellent reservoirs in the basin. This study attempts to better understand the provenance of the Early and Late Permian sediments using automated Raman spectroscopy as a tool to identify variations in heavy mineral assemblages. Automated Raman spectroscopy analysis of heavy minerals minimises operator bias inherent in more traditional optical heavy mineral analyses. These data are integrated with publicly available chemostratigraphy data to enable a better understanding of sediment provenance variations with stratigraphy. In addition, publicly available detrital zircon geochronological data are incorporated to help further understand sediment sources. A transect of wells is investigated, from Arrowsmith-1 in the southernmost extent to Depot Hill-1 and Mt Horner-1 in the north. While the elemental (chemostratigraphy) data suggest some changes in sediment provenance through the Permian of the Perth Basin, the Raman heavy mineral data confirm a number of sediment provenance changes both at key formational boundaries (e.g. top Kingia sandstone) and complex sediment provenance variation within reservoir sandstone units. These results are integrated to demonstrate how sediment provenance holds the key to understanding controls on variable reservoir quality as well as understanding the early infill in this basin.

scholarly journals Part–Whole Relations: New Insights about the Dynamics of Complex Geochemical Riverine Systems

Minerals ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 501
Author(s):  
Caterina Gozzi ◽  
Roberta Sauro Graziano ◽  
Antonella Buccianti
Keyword(s):  
Compositional Data ◽  
Chemical Elements ◽  
Chemical Constituents ◽  
Principal Component ◽  
Cumulative Distribution ◽  
Compositional Data Analysis ◽  
Scaling Properties ◽  
Global Biogeochemical Cycles ◽  
Riverine Systems ◽  
Log Ratio

Nature is often characterized by systems that are far from thermodynamic equilibrium, and rivers are not an exception for the Earth’s critical zone. When the chemical composition of stream waters is investigated, it emerges that riverine systems behave as complex systems. This means that the compositions have properties that depend on the integrity of the whole (i.e., the composition with all the chemical constituents), properties that arise thanks to the innumerable nonlinear interactions between the elements of the composition. The presence of interconnections indicates that the properties of the whole cannot be fully understood by examining the parts of the system in isolation. In this work, we propose investigating the complexity of riverine chemistry by using the CoDA (Compositional Data Analysis) methodology and the performance of the perturbation operator in the simplex geometry. With riverine bicarbonate considered as a key component of regional and global biogeochemical cycles and Ca2+ considered as mostly related to the weathering of carbonatic rocks, perturbations were calculated for subsequent couples of compositions after ranking the data for increasing values of the log-ratio ln(Ca2+/HCO3−). Numerical values were analyzed by using robust principal component analysis and non-parametric correlations between compositional parts (heat map) associated with distributional and multifractal methods. The results indicate that HCO3−, Ca2+, Mg2+ and Sr2+ are more resilient, thus contributing to compositional changes for all the values of ln(Ca2+/HCO3−) to a lesser degree with respect to the other chemical elements/components. Moreover, the complementary cumulative distribution function of all the sequences tracing the compositional change and the nonlinear relationship between the Q-th moment versus the scaling exponents for each of them indicate the presence of multifractal variability, thus revealing scaling properties of the fluctuations.

scholarly journals Application of Data Analytics Techniques to Establish Geometallurgical Relationships to Bond Work Index at the Paracutu Mine, Minas Gerais, Brazil

Minerals ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 302 ◽  
Author(s):  
Mahadi Bhuiyan ◽  
Kamran Esmaieli ◽  
Juan C. Ordóñez-Calderón
Keyword(s):  
Compositional Data ◽  
Principal Component ◽  
Strong Relationship ◽  
Mine Planning ◽  
Geochemical Data ◽  
Circuit Performance ◽  
Work Index ◽  
Bond Work Index ◽  
Log Ratio ◽  
Fresh Rock

Analysis of geometallurgical data is essential to building geometallurgical models that capture physical variability in the orebody and can be used for the optimization of mine planning and the prediction of milling circuit performance. However, multivariate complexity and compositional data constraints can make this analysis challenging. This study applies unsupervised and supervised learning to establish relationships between the Bond ball mill work index (BWI) and geomechanical, geophysical and geochemical variables for the Paracatu gold orebody. The regolith and fresh rock geometallurgical domains are established from two cluster sets resulting from K-means clustering of the first three principal component (PC) scores of isometric log-ratio (ilr) coordinates of geochemical data and standardized BWI, geomechanical and geophysical data. The first PC is attributed to weathering and reveals a strong relationship between BWI and rock strength and fracture intensity in the regolith. Random forest (RF) classification of BWI in the fresh rock identifies the greater importance of geochemical ilr balances relative to geomechanical and geophysical variables.

scholarly journals Multi-Proxy Provenance Analyses of the Kingriali and Datta Formations (Triassic—Jurassic Transition): Evidence for Westward Extension of the Neo-Tethys Passive Margin from the Salt Range (Pakistan)

Minerals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 573
Author(s):  
Shahid Iqbal ◽  
Michael Wagreich ◽  
Mehwish Bibi ◽  
Irfan U. Jan ◽  
Susanne Gier
Keyword(s):  
Lower Jurassic ◽  
Sediment Supply ◽  
Heavy Mineral ◽  
Passive Margin ◽  
Indian Plate ◽  
Late Triassic ◽  
Indian Shield ◽  
Margin Setting ◽  
Salt Range ◽  
Mineral Data

The Salt Range, in Pakistan, preserves an insightful sedimentary record of passive margin dynamics along the NW margin of the Indian Plate during the Mesozoic. This study develops provenance analyses of the Upper Triassic (Kingriali Formation) to Lower Jurassic (Datta Formation) siliciclastics from the Salt and Trans Indus ranges based on outcrop analysis, petrography, bulk sediment elemental geochemistry, and heavy-mineral data. The sandstones are texturally and compositionally mature quartz arenites and the conglomerates are quartz rich oligomictic conglomerates. Geochemical proxies support sediment derivation from acidic sources and deposition under a passive margin setting. The transparent heavy mineral suite consists of zircon, tourmaline, and rutile (ZTR) with minor staurolite in the Triassic strata that diminishes in the Jurassic strata. Together, these data indicate that the sediments were supplied by erosion of the older siliciclastics of the eastern Salt Range and adjoining areas of the Indian Plate. The proportion of recycled component exceeds the previous literature estimates for direct sediment derivation from the Indian Shield. A possible increase in detritus supply from the Salt Range itself indicates notably different conditions of sediment generation, during the Triassic–Jurassic transition. The present results suggest that, during the Triassic–Jurassic transition in the Salt Range, direct sediment supply from the Indian Shield was probably reduced and the Triassic and older siliciclastics were exhumed on an elevated passive margin and reworked by a locally established fluvio-deltaic system. The sediment transport had a north-northwestward trend parallel to the northwestern Tethyan margin of the Indian Plate and normal to its opening axis. During the Late Triassic, hot and arid hot-house palaeoclimate prevailed in the area that gave way to a hot and humid greenhouse palaeoclimate across the Triassic–Jurassic Boundary. Sedimentological similarity between the Salt Range succession and the Neo-Tethyan succession exposed to the east on the northern Indian passive Neo-Tethyan margin suggests a possible westward extension of this margin.

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