Geochemical Interpretation Research Articles

GGR Handbook of Rock and Mineral Analysis Chapter 1 (Part 2) Sampling as Part of the Measurement Process

This chapter (Sampling as Part of the Measurement Process) is a contribution to the Geostandards and Geoanalytical Research Handbook of Rock and Mineral Analysis – an online textbook that is a fully revised and updated edition of A Handbook of Silicate Rock Analysis (P. J. Potts, 1987, Blackie, Glasgow).Chapter 1 (Part 2) forms part of Section 1 of the handbook dealing with fundamentals of measurement and instrument design. The geochemical measurement process is considered to begin when the primary sample is taken from the sampling target, rather than when that sample arrives at the laboratory. This integration of sampling within the measurement procedure enables both sampling and chemical analysis to be optimised in order to achieve a measurement procedure that is fit for its intended geochemical purpose. The key metric in judging this fitness for purpose, and hence validating a measurement procedure, is the uncertainty of each measurement value. This measurement uncertainty is explained, together with methods to estimate and express it in a way that includes the contribution from sampling, with a worked example. The resultant more realistic estimates of measurement uncertainty are shown to improve the reliability of the geochemical interpretation of measurement values.

Geochemical (δ13C, δ18O, 87Sr/86Sr, REEs) characterization of travertine in Tengchong, China: Insights into travertine origin and reservoir conditions

Geochemical characterization is extensively employed in travertine research, yet few studies have explored the potential of travertine geochemistry for elucidating the subterranean details of spring systems. In this study, we systematically characterized the geochemical signatures (δ13C, δ18O, 87Sr/86Sr, REEs, Zr, Th, Sr, Mn) of travertine from six spring systems in Tengchong (SW China) and compared them with those of potential reservoir rocks, aiming to understand travertine origin and assess reservoir conditions. Our results revealed substantial variations in the δ13C and δ18O of travertine among the examined systems, but the water temperature and parent CO2 assessments suggest a hot spring thermogene origin of the travertine. The 87Sr/86Sr of the studied travertine also varies significantly among the systems and overlaps with that of potential reservoir rocks. However, only the springs systems with reservoir temperatures exceeding 150 °C are likely to have precipitated travertine with 87Sr/86Sr resembling the whole-rock 87Sr/86Sr of the reservoir rocks. REE contamination by exogenous detritus and FeMn (oxyhydr)oxides was noted, emphasizing the need for careful REE contamination evaluation in travertine research. The REE comparison reveals that the studied travertine does not fully replicate the REE signature of its potential reservoir rocks, but the REE pattern, (Eu/Eu*)SN, and (Ce/Ce*)SN characteristics of the travertine reveal informative reservoir conditions. In summary, this study shows that the geochemistry of the travertine offers valuable insights into its origin and reservoir conditions. These findings could assist in the geochemical interpretation of travertine and the exaction of hypogean reservoir conditions from travertine.

Factor analysis in residual soils of the Iberian Pyrite Belt (Spain): comparison between raw data, log-transformation data and compositional data

The Iberian Pyrite Belt (IPB) is a metallogenic province in SW Spain and Portugal hosting the largest concentration of massive sulfide deposits worldwide. Exploration campaigns in both the Spanish and Portuguese sectors of the IPB have increased recently due to the rise in metal prices. Within this framework, distinguishing geochemical features associated with natural phenomena and isolating geogenic anomalies from anthropogenic ones can pose a challenge. This contribution uses the residual soil geochemical database of the IPB (Spain) to examine numerous variables, encompassing major, minor and trace elements. Some of these variables commonly exhibit high correlations owing to consistent geochemical behaviour. However, the influence of anthropogenic factors tends to elevate data variability, occasionally masking the natural relationships that govern their distributions. We apply different treatments of data to develop factor analysis using log-transformed data, and centred log-ratio (clr) transformed data to compare and improve the geochemical interpretation of this important zone. Factor analysis has been developed with these results to compare with previously published research on factor analysis in raw data. Factor score interpolated maps were also generated using both lognormal and clr-transformed data to visualize better the distribution and the different geochemical associations in the IPB. This study shows the importance of the different data treatments and the improvement of the clr-transformed multivariate analysis to reduce the dilution or overestimation of the results of some elements that cause erroneous interpretations of the data.

Strontium isotopes and rare earth elements in terrestrial hot-spring deposits: Characterization and geothermal implications

Identifying geothermal reservoir rock types is fundamental in geothermal exploration, but the absence of active surface geothermal manifestations (especially hot springs) in blind geothermal systems makes this identification difficult. Nevertheless, blind geothermal systems may develop early-formed hot-spring deposits. As (bio-)chemical precipitate, these deposits may retain geochemical signatures of spring waters and thus provide insights into reservoir rock types. To assess their geothermal implications, the 87Sr/86Sr and rare earth elements + yttrium (REE + Y) characteristics of hot-spring deposits in two geothermal systems were investigated and compared with those of their reservoir rocks. Results showed relatively uniform 87Sr/86Sr values in hot-spring deposits within each system, but occasional 87Sr/86Sr contamination induced by exogenous detritus input was also observed. The amount of detritus input relates to the potential for interaction with surrounding soils/rocks and is thus environmentally controlled. Hot-spring deposits with high Sr concentrations showed greater 87Sr/86Sr contamination resistance than those with low Sr concentrations, revealing the influence of Sr concentration in hot-spring deposits on detrital 87Sr/86Sr contamination. The detritus input also influenced the REE + Y signatures of the hot-spring deposits, underscoring the necessity of contamination assessment before geochemical interpretation. Excluding samples with significant 87Sr/86Sr and/or REE + Y contamination, the remaining samples closely mirrored their respective reservoir rocks in terms of 87Sr/86Sr, with partial overlap in REE + Y signatures. This suggests that the 87Sr/86Sr and REE + Y characteristics of hot-spring deposits provide valuable insights into reservoir rock types. However, variations in 87Sr/86Sr or REE + Y compositions between some hot-spring deposits and corresponding reservoir rocks indicate additional influencing factors beyond reservoir rock types. Therefore, a comprehensive understanding of reservoir rock types requires integrated geochemical characterization, probably including 87Sr/86Sr, REE + Y, and other parameters. These findings underscore the potential of geochemical characterization of hot-spring deposits for identifying geothermal reservoir rock types, and this geochemical approach can complement geological and geophysical data to improve exploration efficiency, especially in blind geothermal systems.

Interpreting Mineral Deposit Genesis Classification with Decision Maps: A Case Study Using Pyrite Trace Elements

Abstract Machine learning improves geochemistry discriminant diagrams in classifying mineral deposit genetic types. However, the increasingly recognized ‘black box’ property of machine learning has been hampering the transparency of complex data analysis, leading to the challenge in deep geochemical interpretation. To address the issue, we revisited pyrite trace elements and propose to use ‘Decision Map’, a cutting-edge visualization technique for machine learning. This technique reveals mineral deposit classifications by visualizing the ‘decision boundaries’ of high-dimensional data, a concept crucial for model interpretation, active learning, and domain adaptation. In the context of geochemical data classification, it enables geologists to understand the relationship between geo-data and decision boundaries, assess prediction certainty, and observe the data distribution trends. This bridges the gap between the insightful properties of traditional discriminant diagrams and the high-dimensional efficiency of modern machine learning. Using pyrite trace element data, we construct a decision map for mineral deposit type classification, which maintains the accuracy of machine learning while adding valuable visualization insight. Additionally, we demonstrate two applications of decision maps. First, we show how decision maps can help resolve the genetic type dispute of a deposit whose data was not used in training the models. Second, we demonstrate how the decision maps can help understand the model, which further helps find indicator elements of pyrite. The recommended indicator elements by decision maps are consistent with geologists’ knowledge. This study confirms the decision map’s effectiveness in interpreting mineral genetic type classification problems. In geochemistry classification, it marks a shift from conventional machine learning to a visually insightful approach, thereby enhancing the geological understanding derived from the model. Furthermore, our work implies that decision maps could be applicable to diverse classification challenges in geosciences.

Estimation and usefulness of measurement uncertainty from sampling at different spatial scales: microns to kilometres

Uncertainty of measurement values (MU) is crucial to their reliable geochemical interpretation. MU can be estimated using the Duplicate Method, which requires the taking of a small proportion of duplicated samples, and can be applied at any spatial scale. The distance between the duplicated samples is selected to reflect the effect of analyte heterogeneity on the measurement result (i.e. estimated concentration) within each sampling target, at the particular scale of investigation. Three published case studies, at different spatial scales, are used to explain how the Duplicate Method can be applied to estimate MU. They also illustrate how MU can be used to improve geochemical interpretation and validate measurement procedures (that include sampling) by judging their fitness for purpose. At the kilometre scale, measurements from the GEMAS survey of agricultural soils across Europe are used to estimate their MU for the first time. The MU for 53 elements range from an uncertainty factor of 1.01 to over 10. The MU contributes more that 20% to the total variance for 8 of the 53 elements, showing that the measurement procedure was not fit for purpose in those cases. At the micron scale, measurements of oxygen isotopes in candidate quartz reference materials had MU that was dominated by its sampling component, caused by sometimes unacceptable heterogeneity. A third case study of Pb in soils at 12 UK sites showed that the Duplicate Method can also be used to quantify the heterogeneity (as factor 1.03 to 2.4), and that it can indicate different possible sources of an element.

Nyatygran intrusive suite, Bureya massif: Petrography, geochemistry, and age

The proposed review and analytical article provides updated information on the geology, petrography, mineralogy, and chemical composition of rocks of the Precambrian Nyatygran intrusive suite. The article provides a geochemical interpretation of the chemical and trace element compositions and presents the most actual data on the uranium-lead isotopic age of the rocks. The igneous formations of the Nyatygran gabbro-granodiorite-granite complex make up small intrusive massifs of gabbroids and granitoids, located near the ore-bearing Mel’gin trough, in the basins of the Verkhny Mel’gin, Chepkan, and Bureya rivers and their tributaries. In the gabbroids, the main rock-forming minerals are labradorite, andesine, bluish-green hornblende, and biotite. The gneissic granitoids are dominated by cataclastic quartz and feldspars (andesine, oligoclase, microcline) and contain abundant micas (biotite, sericite). The subalkaline leucogranites are dominated by oligoclase, quartz, orthoclase, and microcline; they also contain significant amounts of biotite and aegirine and rare amphibole (hornblende). The gabbro and gabbrodiorites of normal and elevated alkalinity are assigned to the high-aluminous high-magnesian rocks. The gabbroids represent I-type igneous rocks. The gneissic granitoids of normal and elevated alkalinity are predominantly high-aluminous, more ferroan than magnesian rocks, and are represented by S- and I-type granitoids. The determined isotopic ages of the Nyatygran suite formations are confined to the three main ranges: 933 ± 12–916,3 ± 7,2 Ma (1st magmatic phase: gabbro, gabbrodiorites, amphibole-biotite granites), 909,0 ± 6,6–907,3 ± 5,5 Ma (2nd phase: granodiorites and granites), and 806,8 ± 6,6–789 ± 4,0 Ma (3rd phase: biotite granites and granite-porphyry dikes). The Nyatygran suite age is established as Neoproterozoic and corresponds to the early Neoproterozoic, or Tonian (1000–720 Ma), according to the International Chronostratigraphic Scale, 2018. On the 3rd generation 1:1 000 000-scale State geological maps of the Russian Federation, it is presented as Early Proterozoic.

Geochemical proxies of the gryphon breccia of mud volcanoes in East Azerbaijan: regularities in the distribution of chemical elements and spatial characteristics of sedimentation

The paper is devoted to the study of the patterns of distribution of major oxides and trace elements in the gryphon breccia of 12 active mud volcanoes located in various oil and gas regions (Absheron, Gobustan and Lower Kura) of Azerbaijan. Interpretations of the chemical elements found in gryphon breccia samples have allowed the composition of their source rocks, sedimentation conditions, and sedimentation areas to be determined. Purpose. The main goal of the study is to conduct geochemical studies of gryphon breccias belonging to various oil and gas regions, determine spatial patterns, achieve their explanation, and at the same time determine the conditions for the deposition of mud sediments. Methods. The chemical composition of mud volcanic breccia samples was analyzed using an “S8 TIGER Series 2” spectrometer and an “Agilent 7700 Series ICP-MS” mass spectrometer. Based on the results obtained, in addition to identifying patterns in the areas, modern approaches based on geochemical interpretation were used to explain them. The results on the genesis of breccias are consistent with the results of the published literature on the development of geodynamic and paleobasin conditions in the region. Results. Samples with the lowest Si content are characteristic of the Lower Kura mud volcanoes, where the youngest (Quaternary) deposits are recorded. In samples from these mud volcanoes, relatively high contents of Mg and P are also noticeable. High contents of Ca are characteristic of volcanoes located near the Caspian Sea. These mud volcanoes are also rich in trace elements such as Li, Ga, Rb, Zr, Mo, Cs, Pr, Tl, Pb, Th, U and others, but depleted in Ni, Sr, Ba and etc. Conclusions. Plagioclase-rich source rocks and oxygen-dominated paleobasin environments played a key role in the formation of breccia deposits belonging to the mud volcanoes of Azerbaijan. Geochemical proxies make it possible to link the paleobasin conditions of the formation of the gryphon breccia of the most mud volcanoes of South and Central Gobustan with the continental setting, especially in comparison with some volcanoes of the Lower Kura, as well as Gobustan and Absheron, located on the shores of the Caspian Sea and relatively close to it. The breccias of mud volcanoes located at a relatively large distance from the modern sea boundary and in the steepest northern part of the Lower Kura are associated with marine conditions, as are breccias of mud volcanoes located in the south of this tectonic zone (subjected to intense subsidence) and at a short distance from the Caspian Sea, may be due to geological factors.

Geochemical Biodegraded Oil Classification Using a Machine Learning Approach

Chromatographic oil analysis is an important step for the identification of biodegraded petroleum via peak visualization and interpretation of phenomena that explain the oil geochemistry. However, analyses of chromatogram components by geochemists are comparative, visual, and consequently slow. This article aims to improve the chromatogram analysis process performed during geochemical interpretation by proposing the use of Convolutional Neural Networks (CNN), which are deep learning techniques widely used by big tech companies. Two hundred and twenty-one chromatographic oil images from different worldwide basins (Brazil, the USA, Portugal, Angola, and Venezuela) were used. The open-source software Orange Data Mining was used to process images by CNN. The CNN algorithm extracts, pixel by pixel, recurring features from the images through convolutional operations. Subsequently, the recurring features are grouped into common feature groups. The training result obtained an accuracy (CA) of 96.7% and an area under the ROC (Receiver Operating Characteristic) curve (AUC) of 99.7%. In turn, the test result obtained a 97.6% CA and a 99.7% AUC. This work suggests that the processing of petroleum chromatographic images through CNN can become a new tool for the study of petroleum geochemistry since the chromatograms can be loaded, read, grouped, and classified more efficiently and quickly than the evaluations applied in classical methods.

Expansion of microbial-induced carbonate factory into deeper water after the Permian-Triassic mass extinction

The extinction of most heavy calcifiers, such as corals, calcareous algae and sponges, during the Permian-Triassic mass extinction (PTME) coincides with the sudden transition from a carbonate factory dominated by metazoan productivity to one consisting of microbialites and oolites. However, the nature of deeper-water carbonate (distal inner shelf to deep shelf) during the PTME is poorly understood. Here, seven deeper-water carbonate sections from South China and South Tibet were selected to examine the earliest Triassic deeper-water carbonate factory, based on petrological observations and geochemical interpretations. The results show that the earliest Triassic deeper-water carbonates formed under anoxic conditions and reveal diverse microbial structures such as extracellular polymeric substances (EPS), cyanobacteria filaments and rod-shaped grains reminiscent of bacteria in size and shape. These observations suggest that microbial proliferation expanded to relatively deeper-water settings and contributed to the precipitation of deeper-water carbonate.

FEATURES OF FORMATION, MATERIAL COMPOSITION AND GEOLOGICAL STRUCTURE OF RARE METAL AND PEGMATITE DEPOSITS OF THE KALBA REGION ON THE EXAMPLE OF THE YUBILEINOE DEPOSIT

Link for citation: Oitseva T.A., Dyachkov B.A., Bissatova A.Ye., Orazbekova G.B., Zinyakin S.S. Features of formation, material composition and geological structure of rare metal and pegmatite deposits of the Kalba region on the example of the Yubileinoe deposit. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 7, рр. 164-176. In Rus. The relevance of the research is caused by the lack of knowledge on the behavior of rare metal in pegmatite ore formation in the Kalba region and the need to expand the rare-metal mineral resource base of the region and to establish geological and mineragenic mapping. The main aims of the research are identification of features of geotectonic development, geological structure and material composition of the rare-metal deposit Yubileynoe (Kalba region). Study area: large industrial rare metal deposit Yubileynoe and its mineral complexes. Methods: detailed geological-geochemical and mineralogical study of the region of work, use of materials from works of previous years, stock literature, as well as laboratory studies (mass spectrometric, microprobe, geochronological and other studies). The structural relationships of minerals with each other, as well as the geochemical interpretation of the results of laboratory studies, were taken into account during diagnosing mineral complexes. Results. Spatial and genetic relationship of rare-metal pegmatite deposit (Nb, Ta, Be, Cs, Li, Sn) with granites of the I phase of the Kalba complex P1 (285 Ma), is distinguished. In the location of the Yubileinoe deposit, the leading ore-controlling role is given to the system of deep latitudinal faults of ancient origin, renewed in the Hercynian cycle. A geological and genetic model of rhythmically pulsating rare-metal pegmatite formation of the Yubileinoe deposit is presented, which reflects the zonal development of mineral complexes from oligoclase-microcline (barren) to albite, greisen, spodumene-containing and pollucite-bearing (ore) with an increasing concentration of mineralization. Information was obtained on the composition of pegmatite ores with the release of typomorphic minerals (clevelandite, lepidolite, colored tourmalines, spodumene, pollucite, ixiolite, etc.) and the main geochemical elements of rare metal ore formation (Nb, Ta, Be, Cs, Li, F, P, etc.).

Full‐Waveform Tomography of the African Plate Using Dynamic Mini‐Batches

AbstractWe present a seismic model of the Africa Plate, constructed with the technique of full‐waveform inversion. The purpose of our model is to serve as a foundation for quantitative geodynamic and geochemical interpretation, earthquake‐induced ground motion predictions, and earthquake source inversion. Starting from the first‐generation Collaborative Seismic Earth Model, we invert seismograms filtered to a minimum period of 35 s and compute gradients of the misfit function with respect to the model parameters using the adjoint state method. We use dynamically changing mini‐batches of the complete data set to compute approximate gradients at each iteration. This approach has three significant advantages: (a) it reduces computational costs for model updates and the inversion, (b) it enables the use of larger datasets without increasing iteration costs, and (c) it makes it trivial to assimilate new data since we can extend the data set without changing the misfit function. We invert data from 397 unique earthquakes and 184,356 unique source‐receiver pairs. We clearly image tectonic features such as the Afar triple junction and low‐velocity zones below the Hoggar, Aïr, and Tibesti Mountains, pronounced more than in earlier works. Finally, we introduce a new strategy to assess model uncertainty. We deliberately perturb the final model, perform additional mini‐batch iterations, and compare the result with the original final model. This test uses actual seismic data instead of artificially generated synthetic data and requires no assumptions about the linearity of the inverse problem.

Restoring source rock initial quality and quantity with kinetic-based inversion - Applied to the Wolfcamp play in the Permian Delaware Basin

To calculate the volume of hydrocarbon generated from a mature source rock, it is necessary to restore the total organic carbon (TOC) and hydrogen index (HI) to their initial conditions before the hydrocarbon generation. Various methods have been proposed to restore source rock properties. Most of these methods require measured HI data and assumptions on initial HI (HIi) to calculate the transformation ratio (TR) and then restore the initial TOC (TOCi) from measured TOC data. Estimating HIi can be challenging for samples with high maturity, for cases in which immature samples and maceral data are lacking, or for heterogeneous source rocks. This study presents a workflow using a kinetic-based inversion procedure to restore the source-rock's HIi and TOCi from measured HI and TOC data. Unlike the other methods, the kinetic-based inversion method uses simulated TR derived from the basin model and independent of assumed HIi to restore the HIi and TOCi from measured HI and TOC data. Thus, a pre-defined basin model with calibrated thermal model and assigned kinetic (organofacies) for the source rock intervals is required before the kinetic-based inversion procedure is performed. The workflow is applied to the Wolfcamp Play in the Permian Delaware Basin using a proprietary dataset covering the whole basin spatially. Based on geochemical interpretation, the organofacies within the Wolfcamp interval vary from predominantly marine clastic (OF “B”) to mixed marine-terrigenous (OF “D/E”) facies. The kinetic-based inversion result shows a considerable range of restored HIi and TOCi, values indicating source rock heterogeneity of the Wolfcamp Play. Generally, Wolfcamp A and B intervals are excellent source rocks with P50 HIi of ca. 594 and 508 mgHC/gTOC and P50 TOCi of 2.84 and 2.60 wt%, respectively. Wolfcamp C and D intervals are also good-very good source rocks with relatively lower potential than Wolfcamp A and B. Despite the limitation and uncertainty as to the consequence of using TR derived from the basin model, the kinetic-based inversion procedure has the advantages of requiring no assumption for HIi and restoring the source rock according to the thermal maturity, source rock organofacies, kinetic model, and measured data, among many others. Interpreted overall kerogen type of the Wolfcamp source rock using restored HIi and TOCi supports the interpretation of predominantly marine to mixed marine-terrigenous typed organofacies source rock using other data. Preliminary calculation of the restored HIi and TOCi and the calculated volumes of hydrocarbon yield also support the massive hydrocarbon volume predicted and produced for the Wolfcamp Play in the Delaware Basin.

X-ray fluorescence scanning of soft and wet-sediment cores in terrestrial environments; A robust blind source separation approach

X-ray fluorescence (XRF) scanning of split cores using automated cores scanners is rapid but expensive and semi-quantitative method in sedimentary geochemistry. While searching for a low-cost and quantitative solution in environmental geochemistry, we investigated the application of hand-held XRF device in scanning on two siliciclastic-sediment cores from dam-reservoirs in Slovakia. The core-scan data were compared with XRF data from dry, powdered sample aliquots, grain size, water content, and magnetic susceptibility data, which were used as independent variables. The aim of the manuscript is to investigate the applicability of time-series statistical methods to reveal the physical and chemical signals from hand-held XRF scanning of wet-sediment cores. The geochemical data were processed using the centred log-ratio (clr) technique, and then by the Second-Order Blind Identification (SOBI) method, which is a subtype of robust Blind Source Separation (BSS) techniques commonly used to enhance the signal-to-noise ratio in time series analysis of data in medicine or acoustics. So far, BSS has been rarely applied in geochemistry. Raw element concentrations (ppm/wt%) of core scans and sediment powders are essentially incomparable, but their clr coefficients show statistically significant correlation for Al, P, K, Ca, Mn, Fe, Cu, As, Sr, Zr, and Pb, which reduces the difference between the two measurement methods and justifies previous attempts to calibrate the core-scanning data using log-ratio techniques. Scores of three of eight latent components (IC2, IC4, and IC7) found by SOBI in the core scan- and powder data show significant statistical correlation demonstrating the applicability of the core-scan technique. Their geochemical interpretation is based on the IC loadings by element clr, and the stratigraphic correlation with the sediment grain size and water content. These ICs explain geochemical variability due to grain-size contrast between sandy and silty layers, input of biogenic productivity-sensitive elements (Ca and P), eutrophication, and accumulation of anthropogenic elements. The robust BSS approach represents a promising method of processing of large datasets in environmental geochemistry.

Impact of natural weathering on source rocks: Organic and inorganic geochemical evidence from the Triassic Chang 7 outcrop profile in Tongchuan of the Southern Ordos Basin (China)

Exposure of buried source rocks at or near the surface causes organic matter (OM) to be subjected to loss through weathering impacts. A detailed organic and inorganic investigation of the natural weathering of the Triassic Chang 7 Yishicun Profile in Tongchuan City of the Ordos Basin revealed pronounced changes in bulk, molecular, mineral, and elemental compositions. In this study, systematic and visible variations caused by natural weathering were shown in the amount and composition of both organic (kerogen and extractable organic matter [EOM]) and inorganic matter (minerals and elements). The results indicate that natural weathering could substantially affect the characteristics of source rocks at a depth of 2 m from the surface, resulting in a 41% decrease in total organic carbon (TOC) and a 75% loss of EOM. Furthermore, changes were noted in kerogen elemental compositions, fractional compositions of EOM, and some geochemical parameters from Rock-Eval pyrolysis. The mineral and major, trace, and rare earth element (REE) compositions of the outcrop samples were also analysed and compared. The weathering of source rocks was mainly due to the influence of surface water leaching and biodegradation of the OM. This resulted in the oxidation of kerogen and the preferential depletion of low-carbon-number n-alkanes and low-molecular-weight high-water-solubility biomarkers. This has led to bias in petroleum geochemical interpretation based on these organic geochemical parameters. The major elemental composition indicated that the outcrop profile was moderately weathered. Moreover, some commonly used palaeoenvironmental geochemical proxies, including U/Th, AU, Mo, Sr/Ba, Sr/Cu, and P/Ti, display varying degrees of weathering-related alteration. However, other palaeoenvironmental proxies such as V/(V + Ni), Ni/Co, V/Cr, δU, and Ceanom experienced little variation and remained reliable for environmental interpretation. Thus, petroleum resource evaluation and sedimentary environmental analysis of source rocks based on outcrop samples should consider the effects of natural weathering.

A new version of the Langelier-Ludwig square diagram under a compositional perspective

The Langelier-Ludwig square diagram is a commonly used diagnostic tool in groundwater chemistry. Suitable groupings of cations and anions are selected and plotted as percentages of milliequivalents with the sums of the selected cations and anions plotted on the y- and x-axes, respectively. It displays relative ratios rather than absolute concentration whereby each axis ranges from 0 to 50 meq%. However, the sample space in which data are represented in a Langelier-Ludwig square diagram is indeed given by the simplex. Incorrect conclusions may be drawn when the compositional nature of compositional data is not taken into account, i.e., a change in one value in one component changes all other values due to due to the constant sum constraint of the measured chemical elements. Correlations are thus influenced by the presence of negative bias in the covariance structure and linear or nonlinear patterns on the square diagram can be misinterpreted. A new version of the Langelier-Ludwig square diagram based on a well-chosen coordinate representation of cations and anions is proposed. The advantage of the revised diagram is that all the information is contained in the log-ratios describing the intricate relationship between chemical species in aqueous solutions. It is shown that the geochemical interpretation of this new diagram – based on the relative dominance of major ions and distance from the (robust) barycenter of the data – provides a better and unbiased understanding of water-environment interactions. To further aid interpretation, (robust) tolerance ellipses show the correlation structure in the new version of the Langelier-Ludwig square diagram, and clustering algorithms can be applied to divide the data into groups beforehand. A bunch of different plotting options and interactive representations complete the implementation in free open-source software. It is recommended to replace the classic Langelier-Ludwig diagram with the new version.

Geochemical studies of the Green River Formation in the Piceance Basin, Colorado

Hierarchical cluster analysis (HCA) was applied to a geochemical dataset representing the Eocene Green River Formation in the Piceance Basin of Colorado to identify chemofacies in core and outcrop samples from the basin margin and the basin center. The input dataset consisted of inductively coupled plasma optical emission spectroscopy and mass spectrometry and total organic carbon (TOC) content analyses of 186 basin margin outcrop samples and 190 basin center core samples discussed in Part 1 of this study (this volume). TOC values and twenty-five major and trace elements were used as variables to define statistical clusters of samples for the overall dataset, for the two basin center cores, and for each separate core or outcrop dataset by HCA applying Euclidean distance and Ward’s method algorithms. For each dataset, five cluster-defined chemofacies were identified. The chemofacies for each dataset show chemical affinities with five informally defined rock types– mudstone, marlstone, carbonate-rich mudstone, siliciclastic-rich mudstone/siltstone/sandstone, and Na-rich (saline) mudstone, with each showing variations in TOC content and abundance of redox sensitive minor and trace elements. A close relationship between enrichment of redox sensitive elements, particularly As and Mo, and TOC is identified in the basin center. Whereas enrichment factors (relative to average shale) are relatively low for many Period IV (PIV) transition metals, as discussed in Part 1 of this study, their consistent coherence in enrichment or depletion in HCA-defined chemofacies demonstrates the expected relationship between redox state and organic richness. Enrichment in PIV transition metals also shows a correlation to enrichment in elements with affinity for siliciclastic sediment. Enrichment/depletion among several groups of redox indicators is not everywhere consistent, with some chemofacies showing, for example, enrichment of PIV transition metals and depletion of sulfur and arsenic. Early timing of saline conditions in the basin margin is clearly displayed in the chemofacies log display, consistent with observations based on geochemical interpretations of concentrations and elemental ratios discussed in Part 1. Overall, the chemofacies are consistent with major mineralogical units and lake history stages defined in previous work, but provide more detail on the fluctuations in lake chemistry that occurred during deposition of Green River oil shale in the Piceance Basin.

Facies variations in the Upper Jurassic source rocks of the Norwegian North Sea; from micro- to macro scale

In the northern North Sea, the Upper Jurassic Kimmeridge Clay (KC) and its equivalents in the Norwegian sector (i.e., Mandal, Tau, and Draupne) are the most prolific source rocks. These source rock units are known to record both lateral and vertical heterogeneity in organofacies with increasing terrigenous organic inputs near highs and basin flanks. Existing interpretations rely predominantly on Rock-Eval data, but only a few authors validate their geochemical interpretations with maceral assessments. In this study, Upper Jurassic source rocks from fourteen wells in the northern North Sea were analysed for both organic petrography and geochemistry. A potential correlation between the maceral compositions and Rock-Eval, total organic carbon (TOC), and stable carbon isotopes (saturate and aromatic fractions) of source rock extracts was established. This correlation suggests that carbon isotopes mirror the organofacies, and inferred redox conditions during sedimentation, described for the studied source rocks.Stable carbon isotopes of the saturate and aromatic fractions for 152 oils distributed across the Norwegian North Sea were compared to biomarker compounds sensitive to precursor organic material and oxygen abundance in the sedimentary environment. A correlation consistent with that observed between stable carbon isotopes and organofacies documented for the investigated source rocks is also observable in the oil dataset. Hence, the stable carbon isotope composition of the oils in the North Sea dataset appears to carry information related to the bulk organofacies and redox conditions prevailing during the sedimentation of their source. Oils often reflect the compositional attributes of their parental sources more efficiently than a single, or a set of rock extracts. Therefore, the stable carbon isotopes of migrated oils provide a means of inferring gross organofacies and redox conditions within different source rock kitchens in the study area.

Using community science for detailed pollution research: a case-study approach in Indianapolis, IN, USA.

Heavy metal contamination in urban environments, particularly lead (Pb) pollution, is a health hazard both to humans and ecological systems. Despite wide recognition of urban metal pollution in many cities, there is still relatively limited research regarding heavy metal distribution and transport at the household-scale between soils and indoor dusts-the most important scale for actual human interaction and exposure. Thus, using community-scientist-generated samples in Indianapolis, IN (USA), we applied bulk chemistry, Pb isotopes, and scanning electron microscopy (SEM) to illustrate how detailed analytical techniques can aid in interpretation of Pb pollution distribution at the household-scale. Our techniques provide definitive evidence for Pb paint sourcing in some homes, while others may be polluted with Pb from past industrial/vehicular sources. SEM revealed anthropogenic particles suggestive of Pb paint and the widespread occurrence of Fe-rich metal anthropogenic spherules across all homes, indicative of pollutant transport processes. The variability of Pb pollution at the household scale evident in just four homes is a testament to the heterogeneity and complexity of urban pollution. Future urban pollution research efforts would do well to utilize these more detailed analytical methods on community-sourced samples to gain better insight into where the Pb came from and how it currently exists in the environment. However, these methods should be applied after large-scale pollution screening techniques such as portable X-ray fluorescence (XRF), with more detailed analytical techniques focused on areas where bulk chemistry alone cannot pinpoint dominant pollution mechanisms and where community scientists can also give important metadata to support geochemical interpretations.

Quantitative analysis of carbazoles and hydrocarbons in condensates and oils using comprehensive GC–MS/MS and comparative GC–MS analyses

Analysis of carbazoles, nitrogen-bearing molecules found in most petroleum fluids, is often limited to GC–MS or GC × GC methods, both of which require prior sample treatment to concentrate components and minimize matrix interference. Recently, workers have introduced a novel method for analysis of carbazoles, using GC–MS/MS, without these required cleanup procedures. In this study, six thermal condensate and crude oil samples are analyzed for carbazoles and other components in their whole-petroleum and fractionated forms by both Selective Ion Monitoring (SIM) and Multiple Reaction Monitoring (MRM) methods to compare the differences. Five additional samples are then analyzed by a new hybrid MRM-SIM mode in a single run measuring over 200 components. We provide a geochemical interpretation of each sample set, based primarily on the MRM-derived carbazole abundance. In addition, we present an updated method for the analysis of carbazoles using GC–MS/MS. This study explores (1) the benefits of a hybrid MRM-SIM method for the analysis of carbazoles and other molecular markers in a single run, (2) surrogate standards to accurately quantify up to 21 species of carbazole molecules, and (3) evidence for the advantage of GC–MS/MS over previous methods for evaluations of thermal condensates and heavy crude oil. Our recommended process for the analysis of carbazole species is whole petroleum analysis using the hybrid MRM-SIM method. Even if unsuccessful with whole petroleum, the analysis of concentrated fractions analyzed on the hybrid MRM-SIM method has advantages over previous methods.