Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-17T21:47:38.529Z Has data issue: false hasContentIssue false

Geochemical characteristic of the Lutetian black shale (Bayburt, NE-Turkey): amount, nature, origin of organic matter and palaeo-environment conditions

Published online by Cambridge University Press:  22 October 2024

Çiğdem Saydam Eker*
Affiliation:
Department of Geological Engineering, Faculty of Natural Sciences and Engineering, Gümüşhane University, Gümüşhane, Turkey
*
Corresponding author: Ç. Saydam Eker; Email: csaydam@gumushane.edu.tr
Rights & Permissions [Opens in a new window]

Abstract

To define the amount, thermal maturity and type of organic matter (OM), a comprehensive analysis of major and trace elements, organic carbon isotope and organic geochemistry was conducted on Lutetian black shales found in the Everek (Bayburt) region of northeastern Turkey. Total organic carbon (TOC) levels in the shale samples range from 0.62% to 6.75%, and type II–III to type III kerogen is generated, displaying a combination of high terrigenous and low marine OM. The δ13C values (ranging from –28.22‰ to –28.23‰), aromatic hydrocarbon compounds (methyl phenanthrene, dibenzothiophene, tri-aromatic and monoaromatic steroids), saturated hydrocarbon compounds (sterane and terpane), acyclic isoprenoids, n-alkane distribution (n-C13–n-C36) and inorganic geochemical characterization support that the black shales were deposited in a terrestrial-marine transition environment and had a high proportion of terrestrial OM with small amounts of marine OM preserved in relatively arid to hot climate and oxic to suboxic conditions. The analysis of biomarker thermal maturity markers, Tmax (ranging from 449–458 oC) and estimated vitrinite reflectance (varying from 0.92 to 1.08%) values suggest that the black shales have reached the oil window. As a result, black shales are thought to contain low to high amounts of TOC, have a mixed kerogen type, reach a high thermal maturity level and produce little hydrocarbons.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press

1. Introduction

Black shales are typically thin laminated dark-coloured sedimentary rocks with fine-grained particles (Wignall, Reference Wignall1994; Eric et al. Reference Eric, Adama, Etutu, Kwankam, Betrant and Esue2023). The origin, palaeo-climatic conditions, palaeo-depositional environment, palaeo-salinity and palaeo-redox conditions may all be inferred from the geochemical composition of shales (McLennan et al. Reference Mclennan, Hemming, Mcdaniel, Hanson, Johnson and Basu1993, Tanaka et al. Reference Tanaka, Akagawa, Yamamoto, Tani, Kawabe and Kawai2007; Liang et al. Reference Liang, Wu, Jiang, Cao and Song2018; Li et al. Reference Li, Wu, Xia, You, Zhang and Lu2020; Wu et al. Reference Wu, Zhao, Wang, Pu, Lash, Han, Zhang and Feng2021)

Everyone agrees that the world’s petroleum supply will ultimately run out of resources. It makes sense for the government and energy sectors to rekindle their interest in oil shale as a viable alternative supply of oil or a complement to fuel (Cirilli et al. Reference Cirilli, panfili, Buratti and Frixa2018; Spina et al. Reference Spina, Vecoli, Riboulleau, Clayton, Cirilli, Di Michele, Marcogiuseppe, Rettori, Sassi, Servais and Riquier2018 Ilevbare & Adeleye, Reference Ilevbare and Adeleye2023). Because they have the potential to be sources and reservoirs of hydrocarbon accumulation, black shale sedimentary rocks – also known as organic-rich mudstone and shale – are of enormous interest to people all over the world (Jarvie et al. Reference Jarvie, Hill, Ruble and Pollastro2007; Spina et al. Reference Spina, Cirilli, Sorci, Schito, Clayton, Corrado, Fernandes, Galasso, Montesi, Pereira, Rashidi and Rettori2021). Nonetheless, because of rising energy demands, both marine and continental black shales have drawn more interest from conventional and unconventional petroleum resource developers. It is well known that most black shale deposits were primarily deposited in anoxic bottom-water environments in marine and continental sedimentary basins and that they contain significant levels of organic matter (OM) – more than 1 weight per cent (Hakimi et al. Reference Hakimi, Abdullah and Shalaby2011; Makeen et al. Reference Makeen, Hakimi and Abdullah2015; Hatem et al. Reference Hatem, Abdullah, Hakimi and Mustapha2016; Ahmed et al. Reference Ahmed, Jahandad, Hakimi, Gharib, Mehmood, Kahal and Lashin2022).

However, many variables, including continental weathering, biological productivity, clay mineralogy, sedimentation rates, sea level change, water column oxygen levels and depositional environment, severely restrict the accumulating of OM in shale (e.g. Li et al. Reference Li, HE and Yang2008; Zonneveld et al. Reference Zonneveld, Versteegh, Kasten, Eglinton, Emeis, Huguet, Koch, De Lange, De Leeuw, Middelburg, Mollenhauer, Prahl, Rethemeyer and Wakeham2010; Bechtel et al. Reference Bechtel, Jia, Strobl, Sachsenhofer, Liu, Gratzer and Püttmann2012; Shu et al. 2013; He et al. Reference He, Ding, Jiang, Jiu, Li and Sun2017; Zhang et al. Reference Zhang, Wang, Wang, Bjerrum, Hammarlund, Haxen, Wen, Ye and Canfield2019). Prior studies have exhibited that the primary causes of OM enrichment are the productivity of organisms as well as the preservation and resolution of OM (Calvert & Pedersen, Reference Calvert and Pedersen1993; Bordenave et al. Reference Bordenave, Espitalié, Leplat, Oudin, Vandenbroucke and Bordenave1993; Carroll & Bohacs, Reference Carroll and Bohacs1999). OM preservation is significantly influenced by redox conditions. Furthermore, there might be fluctuating restrictions on OM enrichments due to the terrigenous input and sedimentation rate. Some of the sources of Al and Ti are heavy minerals and aluminosilicate minerals. It is proposed that both components serve as reliable stand-ins for detrital inflow (Murphy et al. Reference Murphy, Sageman, Hollander and Lyons2000). In addition, primary productivity is increased in warm, humid climates that support biological growth (Meng et al. Reference Meng, Liu, Bruch, Liu and Hu2012; He et al. Reference He, Ding, Jiang, Jiu, Li and Sun2017; Li et al. 2019). This means that there is a definite relationship between climate and productivity.

Sediments provide good information on the palaeo-climate and palaeo-environment after several representatives, including elemental, isotopic and molecular organic geochemical ones, are investigated. These biomarkers are frequently employed in the reconstruction of palaeo-environmental conditions (Meyers & Ishiwatari, Reference Meyers and ishiwatari1993; Meyers, Reference Meyers2003; Xie et al. Reference Xie, Guo, Huang, Chen, Wang and Farrimond2004; Zhou et al. Reference zhou, Xie, Meyers and Zheng2005; Ortiz et al. 2010 & Reference Ortiz, Torres, Delgado, Valle, Soler, Araujo, Rivas, Julià, Sanchez-Palencia and Vega-Panizo2021; Koralay Reference Koralay2021). N-alkanes are widely used for this purpose because the origin of n-alkanes in the lithological record can be inferred from their distribution, e.g. primary sources of short-chain n-alkanes (C17 and C19) are cyanobacteria and algae (Cranwell et al. Reference Cranwell, Eglinton and Robinson1987). Terrestrial plants have n-alkanes in their leaf wax that are richer in C27 to C31, while aquatic macrophytes have homologues of C23 and C25 predominating (Eglinton & Hamilton Reference Eglinton and Hamilton1967; Ortiz et al. Reference Ortiz, Torres, Delgado, Valle, Soler, Araujo, Rivas, Julià, Sanchez-Palencia and Vega-Panizo2021). The δ13C composition of certain chemicals has been utilized for palaeo-environmental interpretations. The δ13C composition of individual n-alkanes provides more specific information on past variations in C3 and C4 plant abundance than the δ13C of bulk OM. It has been utilized to deduce source inputs and biochemical pathways (Street-Perrot et al. Reference Street-Perrott, Huang, Perrott, Eglinton, Barker, Ben Khelifa, Harkness and Olago1997; Ficken et al. Reference Ficken, Street-Perrott, Perrott, Swain, Olago and Eglinton1998; Huang et al. Reference Huang, Dupont, Sarnthein, Hayes and Eglinton2000; Sinninghe Damste et al. Reference Sinninghe Damste, Verschuren, Ossebaar, Blokker, Van Houten, Van Der Meer, Plessen and Schouten2011; Sun et al. Reference Sun, Xie, Shi, Zhang, Lin, Shang, Wang, Li, Liu and Chu2013).

The Lutetian sedimentary sequence outcropping in the Everek area (Bayburt) contains black shale layers in places. Since it is thought that these black shale levels may be rich in OM, it was found worth investigating. Eocene aged marl/shale outcropping around Çalıdere, approximately 20 km away from the Everek region, was previously examined to feature the OM and sedimentation environment and to evaluate its hydrocarbon production potential (Saydam Eker, Reference Saydam Eker2022). With the previous study, approximate information was obtained about the type, amount and degree of maturation of OM in marl/shale. However, questions about productivity, the relationship between productivity and OM, the relationship between the palaeo-environment and its conditions and OM, the factors causing high Tmax and the basin model have not been answered due to the lack of aromatic biomarkers and major and trace element analyses.

The main purpose of this study is to define the amount of OM contained in black shales, kerogen type, maturation level of OM, source of OM and affecting factors based on organic geochemical analysis (Rock-Eval/TOC, stable carbon isotope, gas chromatography (GC), GC-mass spectrometry (GC-MS)). In addition, palaeo-climate, palaeo-productivity, palaeo-redox and palaeo-salinity conditions and therefore palaeo-depositional environment and conditions were interpreted based on inorganic (whole-rock trace and major elements analysis) and organic geochemical data of the black shales.

2. Geological setting

The Bayburt area is in the Eastern Pontides orogenic band of the Alpine–Himalaya fold system in northeastern Anatolia. The Carboniferous aged Pulur Metamorphic Massif, which comprises migmatite, amphibolite, gneiss, phyllite, marble, meta-chert and metavolcanic, is the oldest geological block in the Bayburt region. Upper Carboniferous–Permian rocks consist of the Carboniferous Cebre Rhyolite including high K calc-alkaline rhyolites and detrital rocks containing conglomerate, mature sandstone, limestone and shale (Topuz et al. Reference Topuz, Altherr, Kalt, Satir, Werner and Schwarz2004; Eyüboğlu et al. Reference Eyuboğlu, Dudas, Thorkelson, Zhu, Liu and Chatterjee2017; Dokuz et al. Reference Dokuz, Külekçi, Aydinçakir, Kandemir, Alçiçek, Pecha and Sünnetçi2017). The Early Jurassic unit thickness varies between 1500 and 1800 m and consists of an alternation of conglomerate, sandstone, siltstone, marl, shale and tuffite. This alternation is accompanied by bands and lenses of red-coloured fossiliferous limestone, coal and acidic-basic rocks, dykes and sills. This sequence is unconformably layered above these basement rocks (Saydam Eker et al. Reference Saydam Eker, Sipahi and AKPINAR2015; Saydam Eker et al. Reference Saydam Eker, Akpinar and Sipahi2016a). The Late Jurassic to Early Cretaceous aged limestone, which is separated into three units in the research region, is unconformably layered above these strata. Unit I is primarily made up of thick to medium-bedded grey and beige-coloured sandstone, gravel stone and sandy limestone; Unit II is made up of thick-bedded grey and beige-coloured oolitic, wackestone, packstone and grainstone and Unit III is mostly made up of thin-bedded yellow-coloured dolomite. Reefal limestones conformably overlie earlier limestone units, whereas the Upper Cretaceous series conformably overlies the carbonate rocks. Late Cretaceous rocks show great diversity lithological and have been examined under four different units. Unit I consists of an alternation of brown, yellowish sandstone, red pelagic limestone, mudstone and claystone. Unit II consists of andesite, basalt, andesitic-basaltic, tuff and tuffite. Unit III is a mélange and contains sandstone, marl, radiolarite, chert, serpentinite, gabbro, basalt and limestone blocks. Unit IV is a white, grey-coloured reef limestone and contains abundant coral (Keskin et al. Reference Keskin, Korkmaz, Gedik, Ateş, Gök, Küçümen and Erkal1990). Unit IV is overlain unconformably by the Pleistocene sedimentary rock, which is made up of marl, sandstone, sandy limestone and grey-coloured, thin, medium-layer pelagic limestone. Keskin et al. (Reference Keskin, Korkmaz, Gedik, Ateş, Gök, Küçümen and Erkal1990) divided Eocene rocks into four formations named Sığırcı Formation (thickness varies between 275 and 470), Sırataşlar Formation (thickness about 750 m), Yazyurdu Formation (thickness varies between 250 and 300) and Rize Pluton (thickness varies between 800 and 1000). Sığırcı Formasyonu (the subject of this study) begins with basement conglomerate. Lutetian sedimentary rocks are classified as turbidite units, consisting of grey, brown and greyish-green thin- to thick-layered, fine- to medium-grained sandstones intercalated with marls and shales that are grey and dark grey in hue (Saydam Eker, Reference Saydam Eker2012). There is also an upper interval of coal-containing claystone in some places (Saydam Eker et al. Reference Saydam Eker, Akpinar, Sipahi and Yapici2016b). Sırataşlar Formasyonu consists of grey, beige, yellow, dirty yellow, light green, coloured, medium-thick layered, limestone, sandstone, occasionally marl and sandy limestone levels. Yazyurdu Formasyonu is characteristic of volcano-clastic rocks composed of andesitic-basaltic rock, marl, sandstone and tuff. Rize Pluton generally consists of volcanic and plutonic rocks. The basaltic to andesitic rocks have an affinity for calc-alkaline to tholeiitic rocks, whilst the intrusive rocks are composed of granodiorite, tonalite and diorite. (Kaygusuz & Öztürk, Reference Kaygusuz and Öztürk2015; Eyuboğlu et al. Reference Eyuboğlu, Dudas, Thorkelson, Zhu, Liu and Chatterjee2017; Gücer, Reference Gücer2021; Kaygusuz et al. Reference Kaygusuz, Yücel, Aydinçakir, Gücer and Ruffet2022). Eocene rocks unconformably overlie Miocene rocks, which include limestone, marl, conglomerate, siltstone, sandstone and gypsum. Travertine is formed when carbonic acid-rich water percolates from rocks in limestone. The alluvium is from rounded and subrounded gravel, clay, silt and sand, mainly derived from non-altered sources and not chemically mature (Saydam Eker & Demirkol Kiliç, Reference Saydam Eker and Demirkol, Kiliç2018; Reference Saydam Eker and Demirkol, Kiliç2024), the older rocks are covered unconformably by Quaternary units (Figs. 1a, b, 2a).

Figure 1. (a) Simplified geological map of the eastern Pontides (after Güven, Reference Güven1993) and location map of the study area. (b) Geological map of the study area (after Musaoğlu, Reference Musaoğlu1987).

Figure 2. (a) Stratigraphic section of Eocene rocks, (b) measured stratigraphic sections of Lütetian detrital rocks, (c) and (d) photographs of black shale and (e) photograph of plant fragments.

3. Samples and methods

During the field study, a stratigraphic section was measured (Measured stratigraphic section= MSS) from Everek (about 40o7′59″ north and 40o22′59″east), where the Lutetian black shales are best exposed. The Everek measured stratigraphic section starts with sandstones at the base and contains alternations of sandstone, marl and shale upwards (Fig. 2a). For geochemical analysis, 10 samples were collected from black shales (Fig. 2b). Whole-rock trace, major elements and Rock-Eval/TOC analyses were applied to 10 shale samples. Based on the results of the Rock-Eval/TOC analyses, stable carbon isotope (δ13C), GC–MS of aromatic and saturated biomarkers and GC analyses were also applied to two shale samples (E-15 and E-16, Fig. 2c, b).

3.a. Inorganic geochemistry analysis

At Vancouver, Canada’s commercial Acme Analytical Laboratories Ltd. (now Bureau Veritas Minerals), major and trace elements were identified on ten shale samples. 0.2 g of sediment fused with 1.5 g of LiBO2 and dissolved in 100 ml of 5% HNO3 were used to evaluate the major and trace element compositions using inductively coupled plasma mass spectrometry (ICP-MS) and ICP optical emission spectrometry. Dried samples were heated to 1,000 °C for 15 minutes to calculate loss on ignition. For trace elements, the detection limits ranged from 0.1 ppm to 10 ppm. Calibration and verification standards together with reagent blanks was added to the sample sequences. In-house certification of STD SO-18 was performed against 38 certified reference materials, which included CANMET SY-4 as well as established external standards USGS AGV-1, G-2, GSP-2 and W-2. The analytical precision exceeds 4%.

Since chemical weathering is closely related to palaeo-climate, chemical index alteration (CIA) was used. Nesbitt & Young (Reference Nesbitt and Young1982) first proposed CIA, which is widely used to investigate the palaeo-climate (Feng et al. Reference Feng, Chu, Zhang and Zhang2003; Yadav & Rajamani, Reference Yadav and Rajamani2004; Goldberg & Humayun, Reference Goldberg and Humayun2010; Wang et al. Reference Wang, Fu, Feng, Song, Wang, Chen and Zeng2017; Xu & Shao, Reference Xu and Shao2018; Liang et al. Reference Liang, Xu, Xu, Yu, Liang and Wang2020; Saydam Eker & Arı, Reference Saydam Eker and Ari2020). The CIA is calculated using the following formula:

(1) $${\rm{CIA}} = {\rm{mole }}\left[ {{\rm{A}}{{\rm{l}}_{\rm{2}}}{{\rm{O}}_{\rm{3}}}{\rm{/}}\left( {{\rm{A}}{{\rm{l}}_{\rm{2}}}{{\rm{O}}_{\rm{3}}} + {\rm{CaO}} + {\rm{N}}{{\rm{a}}_{\rm{2}}}{\rm{O}} + {{\rm{K}}_{\rm{2}}}{\rm{O}}} \right)} \right] \times 100$$
(2) $${\rm{CaO*}} = {\rm{mole}}\ {\rm{CaO\ mole\ }}{{\rm{P}}_{\rm{2}}}{{\rm{O}}_{\rm{5}}} \times {\rm{10/5}}$$

Where CaO* indicates the sum of CaO in silicates.

Furthermore, the distribution and content of a few main and trace elements in sedimentary strata may reveal palaeo-climatic changes (Hu et al. Reference Hu, Li, Song, Wang and Shen2017). Some research effectively used the C-value as a proxy for climate change (e.g. Zhao et al. Reference Zhao, Zhao, Wang, Liao and Liu2007; Fu et al. Reference Fu, Wang, Chen, Feng, Wang, Song and Zeng2016; Wang et al. Reference Wang, Fu, Feng, Song, Wang, Chen and Zeng2017)

The C-value is calculated by the following formula:

(3) $$\small{\eqalign{& {\rm{C - value}} =\cr & {\Sigma ( {{\rm{Fe}} + {\rm{Mn}} + {\rm{Cr}} + {\rm{Ni}} + {\rm{V}} + {\rm{Co}}} )}{/} \Sigma ( {{\rm{Ca}} + {\rm{Mg}} + {\rm{Na}} + {\rm{K}} + {\rm{Sr}} + {\rm{Ba}}})}}$$

3.b. Stable carbon isotope analysis

Two samples of black shale (E-15 and E-16 samples containing the highest TOC) underwent stable carbon isotope analysis (δ13C). A system called Elementary Vario Pyro Cube Isoprime Vision Elemental Analyzer– Isotope Ratio Mass Spectrometry (EA-IRMS) was used to perform this analytical technique. Calibration was performed using Sorghum Flour, EMA-PI and NB-22-approved reference materials. The isotope data for nitrogen, carbon and sulphur are provided by Vienna Canyon Diablo Troilite VCDT, Vienna Pee Dee Belemnite (VPDB) and AIR. Every sample undergoes at least two analyses. The Turkish Petroleum Corporation’s Oil and Organic Geochemistry Laboratory (TPAO, Ankara) performed the analyses.

3.c. Organic geochemistry analysis

Rock-Eval 6 equipment fitted with a TOC module has been used for Rock-Eval pyrolysis/TOC analysis of shale materials. The samples were heated at a rate of 25 °C per minute from 300 °C (hold time: 3 min) to 650 °C. For oxidation, the crushed sediment was heated at a rate of 25 °C per minute from 400 °C (hold time 3 min) to 850 °C (hold time 5 min). Two samples (E-15 and E-16) were subjected to a 40-hour Soxhlet extraction process using dichloromethane (CH2Cl2) to yield extracts. An Agilent 6850 gas chromatograph fitted with a flame photometric detector and flame ionization detector was used to examine the entire extract. Helium was used as the carrier gas for a fused capillary column (100m, 0.25 mm i.d.) coated with cross-linked dimethylpolysiloxane (JandW, 0.50 ⁰m film thickness) used for separation. The oven’s temperature was set to rise at a rate of 4 oC per minute from 40 oC (hold time: 8 min) to 270 oC (hold time: 60 min). Using liquid chromatography, the extract samples were divided into fractions containing Nitrogen, Sulfur, Oxygen (NSO) compounds, aromatic hydrocarbons and saturated hydrocarbons. To elute the fractions, N-hexane, toluene and methanol were utilized, in that order. The two samples (E-15 and E-16) with the highest extract were subjected to GC-MS studies. Shale extracts’ saturated fractions were used for the GC-MS analyses. An Agilent 5975C quadrupole mass spectrometer was connected to an automated liquid sampler (7683 B) and a gas chromatograph (7890 A). An HP-1MS fused silica capillary column measuring 60 m in length, 0.25 mm in diameter and 0.25 µm in film thickness was fitted with the gas chromatograph. The carrier gas in this case was helium. Programming for the oven temperature included a range of 50 oC (hold time 10 min), 200 oC (hold time 15 min), 250 oC (hold time 24 min) and 280 oC (hold time 24 min) at 2 oC/min. At last, the oven was raised to 290 oC (hold time: 40 min) at a rate of 1 oC per minute. At a source temperature of 300 oC and an ionization energy of 70 eV, the mass spectrometer was run in the EI mode. Biomarker contents are at m/z 191 for tri-, tetra- and pentacyclic triterpenes, at m/z 217 for steranes and rearranged steranes, at m/z 253 for monoaromatic steranes, m/z 231 for tri-aromatic steranes, phenanthrene, and methyl-phenanthrene at 178 and 192, dibenzothiophene (DBT) and methyl- DBT at m/z 184 and 198 determined using the record and ion fragmentogram definitions are given in SI table. Elution order matching and retention time were used to identify compounds. The Turkish Petroleum Corporation’s Oil and Organic Geochemistry Laboratory (TPAO, Ankara) performed the analyses.

Additionally, vitrinite reflectance (Ro %) values were calculated based on Tmax (Jarvie et al. Reference Jarvie, Claxton, Henk and Breyer2001). The Ro % is calculated using the following formula:

(4) $${\rm{Ro}}\% = \left( {0.018\times{{\rm{T}}_{{\rm{max}}}}} \right)-7.16$$

4. Results

4.a. Lithology

In this investigation, the shale samples were collected from the Lutetian age sequence from the Everek area. Here the sequence starts with sandstones at the base and keeps going with sandstone, marl and shales. The layer thickness of sandstones generally varies between 10 and 100 cm. The layer thicknesses of marl and shales are quite variable and marl layers vary between 4 cm and 50 cm, and shale layers vary between 2 cm and 30 cm. The total thickness of the sequence is 380 m. It starts with brown-grey, thick-layered sandstone (about 1 m thick) and continues for 20 metres (Fig. 2a, b). Throughout to the top, the section is formed of thin-thick-bedded brown-grey sandstone, thick-medium-bedded green-grey marl and medium, thin-bedded grey-dark grey-black shale (Fig. 2c, d). Therefore, while sandstone dominates in the lower parts of the stratigraphic section, shale and marl become dominant towards the top. The shales show a dark grey to black colour, especially in the central parts of the sequence, and are usually laminated. Intra-layer sedimentary structures (lamination and gradation), and sub-layer sedimentary structures (flute, load and rill marks) have been detected in the section and many remarkably well-preserved plant fragments (Fig. 2e). These sedimentary structures are the primary indicators of sequences transported and deposited by turbidity currents. It is possible to classify these turbidity currents into two groups: a) hyperpycnal turbidites and low-density turbidites (Gani, Reference Gani2004; Mutti et al. Reference Mutti, Bernoulli and Lucchi2009; Yang et al. Reference Yang, Cao and Wang2015; Zhang et al. Reference Zhang, Meng, Misch, Sachsenhofer, Liu, Hu and Shen2021). Hyperpycnal turbidity currents are high-density flows that carry high concentrations of sediment particles; they are observed at the bottom of the section. Because coarse-grained and thick-layered sandstones are more dominant in the lower part of the section than in the upper part, an upward-fining grain sequence is observed above the higher energy deposits; this corresponds to the energy attenuation zone with limited erosion capacity. Moderate, low-density flows have a low erosional capacity and mostly form fining-upward sequences, as observed at the top and medium of the section, respectively. These flows can erode, and ripples are produced by bedload reworking and low-amplitude bed waves. In this study, low-density turbidites contain higher amounts of TOC than hyperpycnal turbidites.

4.b. Major and trace elements

Trace and major element concentrations of the studied black shale are listed in Table 1. Trace and major elements protect a wealth of palaeo-redox and palaeo-climate knowledge beneficial to the reconstruction of the early diagenetic history and depositional environment of fine-grained detrital rocks (Wu et al. Reference Wu, Zhao, Wang, Pu, Lash, Han, Zhang and Feng2021; Li et al. Reference Li, Wu, Xia, You, Zhang and Lu2020; Lin et al. Reference Lin, Zhan, Zou, Cai, Liang and Shi2019; Zhang et al. Reference Zhang, Liu, Liang, Wang, Bai, Yang, Liu, Huang and Guan2018).

Table 1. Concentrations of elements in the analyzed groups of black shale

SiO2 and Al2O3 contents of the black shale range from 48.83 to 53.30 wt% (mean 51.36 wt%) and 14.73 to 17.52 wt% (mean 15.90 wt%), respectively. Fe2O3 content of the samples is extremely similar to one another and varies between 8.09 and 8.51 wt% (mean 8.29 wt%). MgO, CaO and K2O contents of the samples range from 4.36 to 5.45 wt% (mean 4.90 wt%), 2.09 to 5.26 wt% (mean 4.01 wt%) and 1.87 to 2.87 wt% (mean 2.48 wt%), respectively. Other major element oxides such as TiO2, Na2O, MnO, P2O5 and Cr2O3 have low contents, those of Na2O and TiO2 are higher than 1 wt%, and others are less than 1 wt% (Table 1). The mean concentrations of the chosen trace element in the samples indicate the following trends Ba (306ppm) > V (191ppm) > Ni (175ppm) > Sr(151ppm) > Cu (62.8ppm) > Co (36.5 ppm) > Th (28.0 ppm) > Zn (22.2 ppm) > U (1.93 ppm) > Mo (0.33 ppm) > Cd(0.20 ppm) (Table 1).

The ratios of Th/U, C-values and CIA values used as palaeo-climate indicators vary from 3.63 to 4.76, 0.64 to 1.12 and 42 to 62 (Table 2), respectively. The ratios of Cu/Zn, Ni/Co and V/(V+Ni) used as palaeo-redox indicators range from 2.10 to 2.48, 4.14 to 5.42 and 0.51 to 0.56, (Table 2), respectively. The ratios of Sr/Ba and TS/TOC used as palaeo-salinity indicators vary from 0.35–0.65 to 0.07–0.49 (Table 2), respectively. The ratios of Ni/Al, Cu/Al and Zn/Al utilized as palaeo-productivity indicators are between 0.019 and 0.022, 0.006 and 0.007 and 0.002–0.003, respectively. The ratio Ti/Al is used as a detrital input indicator and ranges from 0.07 to 0.13 (Table 2). However, it is known that the trace and major elements in the sediments originate from hydrothermal, authigenic, clastic, hydrogenous and biogenic, origins in mixed proportions (Dymond, Reference Dymond, Kulm, Dymond, Dasch, Hussong and Roderick1981; Brumsack, Reference Brumsack2006; Xu et al. Reference Xu, Hannah, Bingen, Georgiev and Stein2012; Tripathy et al. Reference Tripathy, Singh and Ramaswamy2014; Liang et al. Reference Liang, Xu, Xu, Yu, Liang and Wang2020). When the element is authigenic, it can be used to investigate palaeo-productivity, palaeo-redox and palaeo-salinity conditions (Tribovillard et al. Reference Tribovillard, Algeo, Lyons and Riboulleau2006).

Table 2. Concentrations of elemental ratios in the analyzed groups of black shale

4.c. δ 13 Corg isotopes

Because this parameter is used by plant communities for photosynthesis, stable carbon isotopic parameters (δ13C) are used to identify the source of the OM (aquatic vegetation, dissolved OM, particulate OM, algae, microbes and terrestrial vascular plants). (Whiticar, Reference Whiticar1996; Lamb et al. Reference Lamb, Wilson and Leng2006; Samanta et al. Reference Samanta, Bera, Ghosh, Bera, Filley, Pande, Rathore, Rai and Sarkar2013; Kumar et al. Reference Kumar, Ghosh, Tiwari, Varma, Mathews and Chetia2021).

The bulk fraction of δ13Corg isotope content of the samples is close to each other, measured as −28.23 for E-15 and −28.22 for E-16 (Table 4).

Table 3. Rock-Eval and carbon isotope analysis results and calculated parameters

Table 4. The parameters were calculated from gas chromatograms (GC) for selected shale samples

CPI = 2 × Σ tek n-C23–29/(Σ çift n-C22–28 + Σ çift n-C24–30);

OEP = (n-C21 + 6 × n-C23 + n-C25)/(4 × nC22 + 4 × n-C24); WI =Σ n-C21-31/Σ n-C15-20;

TAR = (n-C27 + n-C29 + n-C31)/(n-C15 + n-C17 + n-C19);

Pr = Pristane; Ph = Phytane.

4.d. Bulk organic geochemical characteristics

4.d.1. TS, TOC and Rock-Eval pyrolysis

The consequences of the Rock-Eval pyrolysis, TOC analysis and TS values are given in Table 3. TS values of the studied shale samples vary between 0.05 and 0.83% (mean of 0.30%). The TOC abundance of shale samples from Everek varies considerably, ranging from 0.62 to 6.54 % (mean 1.57 %), and the S1+S2 values range from 0.44 to 13.12 mg/g (mean 2.21 mg/g). The HI indicates a narrow variation in the shale samples, varying from 73 to 192 mgHC/g TOC (mean 93 mgHC/g TOC). The highest TOC, HI and S1+S2 values are observed in the middle part of the section (E-15 sample). In addition, HI, S1+S2 values show a linear relationship with TOC (Fig. 3). Tmax and Ro values of the samples are high, ranging from 449oC to 458oC (mean 455oC), and 0.91 and 1.08, respectively. Tmax is similar throughout the section, and unlike TOC, S1+S2 and HI, the lowest value was measured in the E-15 sample (Fig. 3). The production index (PI) and bitumen index of the samples range from,0.03 to 0.09 (mean = 0.07) and 0.03 – 0.13 (mean = 0.08), respectively.

Figure 3. Organic geochemical proxy profiles of the black shale samples.

4.d.2. n-alkanes and isoprenoids

For sample E-15, n-alkanes in the range n-C13–n-C36 are characterized by monomodal distributions, with the maximum peak appearing at n-C25 (Fig. 4a), while for E-16, n-alkanes are characterized by monomodal distributions in the range n-C15–n-C34 and the maximum peak also appears at n-C25 (Fig. 4b).

Figure 4. Gas chromatograms of saturated hydrocarbons of two representative black shale samples.

Because they capture the redox conditions during sedimentation and diagenesis as well as the palaeo-environmental conditions of the source rocks, phytane (Ph) and pristane (Pr) are often regarded as the most significant acyclic isoprenoid hydrocarbons (Didyk et al. Reference Didyk, Simoneit and Brassell1978; Chandra et al. Reference Chandra, Mishra, Samanta, Gupta and Mehrotra1994). In both samples, Pr and Ph are the acyclic isoprenoids record, with Pr being very dominant over Ph (Fig. 4a, b). Therefore, Pr/Ph ratios are calculated as 7.48 for E-15 and 5.86 for E-16 (Table 4). Pr/n-C17 ratios are calculated as 2.35 and 4.03 for E-15 and E-16, respectively, and Ph/n-C18 ratios are calculated as 0.32 and 0.41 for E-15 and E-16, respectively. The carbon preference index (CPI, Peters & Moldowan, Reference Peters and Moldowan1993) and odd-to-even predominance (OEP, Scalan & Smith, Reference Scalan and Smith1970) values are calculated as 1.11 and 1.03 for E-15, respectively, and 1.07 and 1.02 for E-16, respectively (Table 4). Terrigenous/aquatic ratio (TAR; Bourbonniere & Meyers, Reference Bourbonniere and Meyers1996) values are higher than 1 and are calculated as 1.42 for E-15 and 1.74 for E-16. The n-C17/n-C27 ratio represents the marine/aquatic input and is calculated as 0.62 and 0.49 for E-15 and E-16, respectively. The WI values, indicating the contribution of terrestrial plants to the OM (Waxiness index, Peters et al. Reference Peters, Walters and Moldowan2005), are calculated as 2.61 and 3.07 for E-15 and E-16, respectively (Table 4).

4.d.3. Terpanes and steranes

Hopanes (pentacyclic terpane), C24 Tet (tetracyclic terpane) and C19-C26 Tri (Tricyclic Terpane) are observed in E-15 and E-16 samples (Fig. 5a, b). The ratios of C19/C23 Tri, C24/C23 Tri, C26/C25 Tri of the E-15 sample are higher than the E-16 sample. The ratios of C19/C23 Tri, C24/C23 Tri and C26/C25 Tri are calculated as 1.02, 0.87 and 1.10 and 0.37, 0.55 and 0.87 for E-15 and E-16 samples, respectively (Table 4). The C24Tet/(C24Tet+ C23Tri) ratios of the analyzed samples were close to each other and were calculated as 0.41 and 0.34 for E-15 and E-16, respectively. C29H/(C29H+C29M), C30H/(C30H+C30M) and Ts/(Ts+Tm) ratios are widely used as thermal maturity parameters (Seifert & Moldowan, Reference Seifert and Moldowan1978; George et al. Reference George, Ruble, Dutkiewicz and Eadington2001). The ratios C29H/(C29H+C29M), C30H/(C30H+C30M)and Ts/(Ts+Tm) are calculated as 0.87, 0.87 and 0.23 for E-15, respectively, and 0.91, 0.88 and 0.30 for E-16, respectively. The Gammacerane/H30 ratio is utilized to appraise the salinity of the sedimentation environment and the ratios of the Gammacerane/H30 of the analyzed samples are highly low and varying from 0.02 to 0.03 for E-15 and E-16, respectively. C3122S/22(S+R) ratios are calculated as 0.59 for E-15 and E-16 samples. C3222S/22(S+R) ratios for E-15 and E-16 are calculated as 0.58 and 0.60, respectively. While the homohopane index (HHI) was calculated as 0.03 for both samples, the C35/C34 ratio was calculated as 0.62 for E-15 and 0.47 for E-16 (Table 4).

Figure 5. The m/z 191 mass fragmentograms (on top) and m/z 217 mas fragmentograms (below) saturated hydrocarbon fractions of two representative black shale samples.

The sterane distributions are indicated in Fig. 5 c, d; their concentrations are lower than hopanes with the sterane/hopane ratio calculated as 0.32 for E-15 and 0.20 for E-16 (Table 4). C27Dia(Dia+Regular) sterane ratios are calculated as 0.40 for E-15 and 0.70 for E-16. The ααα20Rsteranes are characterized by lower proportions of C27 (20 % for E-15 and 20 % for E-16) compared to C28 (20 % for E-15 and 24 % for E-16), and C29 (60 % for E-15 and 56 % for E-16). The equilibrium point of the C29 ββ/(ββ + αα) ratio varies between 0.67 and 0.71 (Seifert & Moldowan Reference Seifert and Moldowan1986). The calculated C29 ββ/(ββ + αα) ratios of E-15 and E-16 samples are 0.61 and 0.55, respectively.

4.d.4. Aromatic hydrocarbons

In the m/z 192 and 178 mass chromatograms of the E-15 and E-16 samples, phenanthrene (P) constitutes the dominant peak, and methyl phenanthrene abundances are approximately similar (Fig. 6a, b). While DBT has the highest abundance in the m/z 184-198 mass chromatograms of both samples, methyl dibenzothiophenes (MDBTs) show approximately similar distribution (Fig. 6c, d). In the m/z 231 mass chromatogram of both samples, the highest value belonged to the C28 tri-aromatic steroid, while the lowest value was recorded in the C27 tri-aromatic steroid (Fig. 6 e, f). The TAI/(TAI+TAII) ratio was calculated as 0.78 for the E-15 sample and 0.80 for the E-16 sample (Table 5). In the m/z 253 mass chromatogram of both samples, while C29 monoaromatic steroid has the highest value, the lowest value belongs to C27 monoaromatic steroid (Fig. 6g, h). The order is monoaromatic steroid C29 > C28 > C27 (57 %, 27 %, 16 % in the E-15 and 48 %, 26 %, 26 % in the E-16) and the C29/C27 ratio is calculated as 3.59 for E-15 and 1.89 for E-16 (Table 4). The MAI/(MAI+MAII) ratio is not very high and is calculated as 0.25 for E-15 and 0.21 for E-16 (Table 4).

Figure 6. The m/z 178-192, m/z 184-198, m/z 231 and m/z 253 ion fragmentograms aromatic hydrocarbon fractions of two representative black shale samples.

Table 5. Selected saturated and aromatic biomarker parameters for the selected black shale samples

Tri = tricyclic terpanes. Tet = tetracyclic terpanes. H = hopane. M= Moretan. HHI = homohopane index ((HHI. C35/ΣC31-35 22S and 22R homohopanes; Peters and Cassa, Reference Peters, Cassa, Magoon and Dow1994)). Steranes/hopanes = C27-C29 regular steranes/C29-C35 17α-hopanes. Dia: diasteranes; Reg: regular steranes; Ts: 17α- 22.29.30-trsinorhopane; Tm: 18α-22.29.30-trisnorhopane, MPI= (2MP+3MP)/(1MP+9MP), TAI/(TAI+TAII)= (C20+C21)/(C20+C21+C26+C27+C28), MA(I)/(MAI+MAII)= (C21+C22)/(C21+C22+C27+C28+C29).

5. Discussion

5.a. Nature of organic matter and deposition environment

To define the OM type of black shale samples, the S2/S3 ratios (hydrocarbon type index) and hydrogen index (HI) values obtained from TOC and pyrolysis analysis results were used. The HI vs Tmax diagram developed by Lafargue et al. (Reference Lafargue, Marquis and Pillot1998) is widely used to determine the kerogen type. Kerogen type, which is commonly classified under three groups (Type I, II and III), provides very important information about the source from which OM is derived. Type III kerogen is primarily composed of terrestrial plants, Type I kerogen is derived dominantly from alginite and Type II kerogen has a mixed source of marine organisms and higher terrestrial plant debris (Zhou et al. Reference Zhou, Sun, Yang, Zhang, Wang, Gao, Zhang, Wang, Liu, Shao and Lu2023).

In the HI vs Tmax diagram, 7 samples of black shale were in the Type II–III kerogen and oil-gas-prone region, while three samples of shale were in the Type II kerogen and oil-prone region (Fig 7a). S2/S3 ratios of the analyzed samples are widely distributed and vary between 1.28 and 62.45 (Table 3). According to the classifications of Clementz et al. (Reference Clementz, Demaison and Daly1979) and Peters & Cassa (Reference Peters, Cassa, Magoon and Dow1994), the kerogen content of these samples changes between Type III and Type I/Type II, Type III and Type I, respectively. Based on this, we can talk about mixed OM, with OM predominantly coming from terrestrial plants. Additionally, the high value of the correlation coefficient and the linear distribution of the samples in the S1 vs S2 graph (r = 0.96, Fig 7b) indicate that a single source is dominant for OM. However, only terrestrial OM is characterized by relatively higher S3 values and lower S2/S3. The samples in the TOC-S2/S3 diagram show linear spread in a narrow range (ratios (r = 0.78, Fig 7c) (Mallick et al. Reference Mallick, Banerjee, Hassan, Kumar, Babu, Krishna and Kumar2022), confirming that a single source is dominant. The fact that the S2/S3 ratios of all the samples are >1 (1.28 – 62.45) suggests mixed type OM. This shows the limited contribution of marine OM, as well as the intense OM input coming from land during the deposition of shales, which is supported by C isotope values as explained below.

Figure 7 (a) The plot of Tmax vs. HI indicates kerogen types for the black shale samples (Lafargue et al. Reference Lafargue, Marquis and Pillot1998), (b) the plot of S1 vs. S2 and (c) TOC vs. S2/S3 for the black shale samples.

OM obtained from terrestrial vascular C3 plants has δ13C isotope values ranging from −22 to −33, whereas the δ13C isotope values of C3 aquatic plants vary between −13 and −27‰ (Whiticar, Reference Whiticar1996). δ13C isotope values of bacteria in coastal and open sea environments vary between −12 and −27‰ depending on their source (Coffin et al. Reference Coffin, Fry, Peterson and Wright1989). The analyzed samples’ δ13C isotope levels are in the range of values seen in OM obtained from terrestrial vascular C3 plants. In this context, the OM contained in the studied shales is thought to be predominantly of terrestrial origin.

Gas chromatograms of selected samples have low to high-weight n-alkanes and the n-alkanes distribution varies between n-C13-n-C36 for E-15 and n-C15-n-C34 for E-16. This distribution reflects a mixture of algae/bacteria (Hunt, Reference Hunt1996) and terrestrial plants (Eglinton & Hamilton, Reference Eglinton and Hamilton1967; Killops & Killops, Reference Killops and Killops2005; Saydam Eker, Reference Saydam Eker2013; Qiao et al. Reference Qiao, Baniasad, Zieger, Zhang, Luo and Littke2021). The high n-C17/n-C27 ratio reflects the dominance of marine OM over terrestrial OM. In this study, the n-C17/n-C27 ratios are < 1 (vary between 0.62 and 0.49) indicating OM of terrestrial is more predominant. TAR values of the samples are >1, supporting that terrestrial OM is more dominant than marine OM. These values mentioned above reflect the existence of both marine and terrestrial OM in the depositional environment. However, in the Pr/n-C17 vs. Ph/n-C18 graph, which is widely used to interpret the origin of OM and the depositional environment, the samples fell into the terrestrial OM area. This can be explained by the high amount of pristane due to the oxic-suboxic environment (Fig. 8).

Figure 8. The plot of Pr/n-C17 vs. Ph/n-C18 of the black shale samples (Shanmugam, Reference Shanmugam1985).

The primary sources of the biomarker compounds sterane and hopane, respectively, are bacteria and plants/algae (Rohmer & Outrissan Reference Rohmer and OURISSON1976). While high amounts of C19 and C20 TT indicate terrestrial OM (Peters et al. Reference Peters, Walters and Moldowan2005), the dominance of C23 TT exhibits a reducing marine carbonate environment and marine OM input (Waples & Machihara, Reference Waples and Machihara1991; Tao et al. Reference Tao, Wang, Du, Liu and Chen2015; Qiao et al. Reference Qiao, Baniasad, Zieger, Zhang, Luo and Littke2021). While the E-15 sample’s C19/C23 TT ratio is calculated as >1, indicating the dominance of terrestrial OM, the E-16 sample’s C19/C23 TT ratio is calculated as <1, indicating the dominance of marine OM (Table 4). For this reason, it can be said that there is both marine and terrestrial OM in the depositional environment. The high C24Tet/(C24Tet+C23TT) ratio indicates that OM includes a mixture of aquatic algal-bacterial and terrestrial OM (Alexander et al. Reference Alexander, Kagi and Sheppard1983; Connan et al. Reference Connan, Bourouller, Dessort and Albrechht1986; Peters et al. Reference Peters, Walters and Moldowan2005). The C24Tet/(C24Tet+C23TT) ratio of the analyzed black shale samples is not very low and varies between 0.34 and 0.41 (Table 4), confirming the dominance of terrestrial OM as well as the presence of aquatic algae and bacteria. While C29 steranes derive from continental higher plants, C27 steranes are generally of algal origin (Huang & Meinschein, Reference Huang and Meinschein1979; Moldowan et al. Reference Moldowan, Sundararaman and Schoell1986; Volkman, Reference Volkman2003;). In the studied samples, in order C29ααα20R>C28ααα20R>C27ααα20R is observed (Table 4). In this context, the dominance of C29ααα20R steranes over C28ααα20R and C27ααα20R steranes in the black shale samples indicates the dominance of terrestrial OM (Fig. 9).

Figure 9. The ternary diagram indicating the distribution of C27, C28, C29 ααα 20R steranes (modified from Huang and Meinschein, Reference Huang and Meinschein1979, after Qiao et al. Reference Qiao, Baniasad, Zieger, Zhang, Luo and Littke2021).

Although some phytoplankton and microalgae produce the aromatic component C29 sterol, the major origin of this sterol is terrestrial plants (Volkman et al. Reference Volkman, Barrett and Blackburn1999; Volkman, Reference Volkman2003; Kostova et al. Reference Kostova, Zdravkov, Bechtel, Botoucharov, Grob, Dochev and Apostolova2022;). C28 sterols are highly high in microalgae of marine (Barrett et al. 1995; Volkman et al. 1998; Volkman, Reference Volkman2003), while C27 sterols are typically derived from marine phytoplankton (Brassell & Eglinton, Reference Brassell and Eglinton1981; Volkman, 1986). Therefore, the C29/C27 sterol ratio is accustomed to determining the proportion of terrestrial/phytoplankton OM in the environment. C29/C27 sterol < 1 indicates that phytoplankton/algal input is more dominant in the sedimentation environment. The C29/C27 ratio of the studied black shale samples is > 1, indicating the dominance of terrestrial OM in the depositional environment. However, C29 sterols are represented by stigmastanol (a chemical compound found in many plants) rather than sitosterol (one of the phytosterols whose chemical structure is like cholesterol), which means that plenty of even-numbered n-alkanes are observed over low-weight n-alkanes in anaerobic environments (Welte & Ebhardt, Reference Welte and Ebhardt1968; Welte &Waples, Reference Welte and Waples1973). In this context, it should be kept in mind that a high C29/C27 ratio indicates not only the dominance of terrestrial plants but also the presence of aquatic plants, especially in anoxic environments. In the study, it is thought that the depositional environment was oxic-suboxic and the high C29/C27 ratio represents terrestrial OM, and the order C29MA>C28MA>C27MA also supports this.

5.b. Palaeo-climate

Th/U ratios and C-values are widely used to interpret palaeo-climatic conditions. Cao et al. (Reference Cao, Wu, Chen, Hu, Bian, Wang and Zhang2012) suggested that Mn, Fe, Cr, Co, Ni and V are relatively enriched under humid conditions. Contrarily, Ca, Mg, K, Na, Sr and Ba are relatively enriched under arid conditions. Warm, humid climates are indicated by Th/U ratios less than 4, whereas hot, dry climates are indicated by higher values (Xu et al. Reference Xu, Liu, Bechtel, Meng, Sun, Jia, Cheng and Song2015; Zhang et al. Reference Zhang, Meng, Misch, Sachsenhofer, Liu, Hu and Shen2021). Low CIA values (70–50) show weak chemical weathering under arid climates, medium CIA values (80–70) reflect moderate chemical weathering under humid and warm climates and high CIA values (100–80) indicate hard chemical weathering under humid and hot climates (Yan et al. Reference Yan, Chen, Wang and Wang2010).

In this study, while the C-values are low (mean of 0.88), the Th/U ratios are generally higher than 4 (mean of 4.14), indicating that the palaeo-climate was arid and hot. The low CIA values of the studied samples indicate that chemical weathering is weak, and the region has an arid and hot climate. The highest CIA value was calculated in sample E-26 (at the top of the MSS), and the lowest CIA value was calculated in E-16 (in the middle of the MSS) (Table 2, Fig. 10).

Figure 10 (a), (b). Inorganic geochemical and proxy profiles of the black shale samples.

5.c. Palaeo-productivity and detrital influx

Although some researchers (Goldberg & Arrhenius, Reference Goldberg and Arrhenius1958; Dehairs et al. Reference Dehairs, Chesselet and Jedwab1980; Dymond et al. Reference Dymond, Suess and Lyle1992; McManus et al. 1999; Cardinal et al. Reference Cardinal, Savoye, Trull, Andre, Kopczynska and Dehairs2005) have noted a clear relationship between Ba and OM abundance, the biogenic contraption of Ba is thought to be some contentious (Liang et al. Reference Liang, Xu, Xu, Yu, Liang and Wang2020). In this study, the negative relationship between Ba and TOC and the lack of any correlation with Al made the source of the Ba uncertain, therefore, the Ba was not used as a productivity proxy. The elements Cu, Ni and Zn in sediments react with OM (which is usually present in living things) to form complexes that eventually lead them to precipitate at the bottom of the water (Martin and Knauer, Reference Martin and Knauer1973; Piper and Perkins, Reference Piper and Perkins2004). Therefore, Zn, Cu and Ni were considered proxy productivity indicators due to their micronutrient behaviour (Brumsack, Reference Brumsack2006). During deposition, element ratios like Zn/Al, Ni/Al and Cu/Al are commonly employed to assess the palaeo-productivity of source rocks. Increased Ni/Al, Zn/Al and Cu/Al ratios signify higher palaeo-productivity (Algeo and Maynard, Reference Algeo and Maynard2004; Schoepfer et al. Reference Schoepfer, Shen, Wei, Tyson, Ingall and Algeo2015; Shen et al. Reference Shen, Schoepfer, Feng, Zhou, Yu, Song, Wei and Algeo2015)

In this study, Cu/Al, Ni/Al and Zn/Al are quite low, indicating that the productivity is not high. It is known that an arid climate decreases primary productivity, whereas a humid and warm climate increases primary productivity (Meng et al. Reference Meng, Liu, Bruch, Liu and Hu2012). This means that there is a definite relationship between climate and productivity. During the deposition of the shale, arid and hot climatic conditions existed in the study area, resulting in low productivity.

It is thought that Ti and Al serve as proxies for the input of detrital material (Hatch & Leventhal, Reference Hatch and Leventhal1992; Canfield, Reference Canfield1994; Algeo & Maynard, Reference Algeo and Maynard2004; Wu et al. Reference Wu, Zhao, Wang, Pu, Lash, Han, Zhang and Feng2021). Al is mainly found in aluminosilicate minerals such as feldspar and clay (Rimmer, Reference Rimmer2004), while titanium often exists in heavy minerals and clays (Kidder et al. Reference Kidder, Xa, Erwin and Xa2001). As a result, the Ti/Al ratio indicates the energy of sediment deposition, and Ti and Al abundances aid in identifying the provenance of sediment (Murphy et al. Reference Murphy, Sageman, Hollander and Lyons2000; Liang et al. Reference Liang, Wu, Jiang, Cao and Song2018; Wu et al. Reference Wu, Zhao, Wang, Pu, Lash, Han, Zhang and Feng2021).

The Ti/Al ratio of the samples varies between 0.07 and 0.13, and the mean is calculated as 0.08 (Table 2). This value is considered moderate and indicates a medium-energy flow of clastic sediment, representing moderate terrestrial detrital input during this period. Consequently, the OM enrichment was not significantly affected by the dilution of OM caused by detritus sediment influx, as shown by the low correlation relationship between TOC and Ti/Al (r = 0.227).

5.d. Palaeo-redox condition

Redox conditions play a significant role in the preservation of OM in the sedimentation environment. The accumulations of some trace elements (e.g. V, U, Cr, Cu, Ni, Zn and Co) express the palaeo-redox conditions (McKay et al. Reference Mckay, Pedersen and Mucci2007). Cu/Zn, Ni/Co and V/V+Ni ratios are commonly used to interpret palaeo-redox conditions. In a sedimentary environment, the Ni/Co ratios above 5 show suboxic and anoxic conditions, while the Cu/Zn values below 5 show oxic conditions (Jones and Manning, Reference Jones and Manning1994; Liang et al. Reference Liang, Xu, Xu, Yu, Liang and Wang2020). In this study, the Ni/Co ratios of six samples are above 5, the others are below 5, while the Cu/Zn ratios of all samples are below 5 with an average of 2.29, indicating oxic to dysoxic and oxic conditions (Table 2, Fig. 10). Redox conditions classed as euxinic, suboxic to anoxic, dysoxic and oxic are shown by V/(V + Ni) ratios of >0.82, >0.60 to ≤0.82, >0.46 to ≤0.60 and ≤0.46, respectively (Hatch & Leventhal, Reference Hatch and Leventhal1992; Jones & Manning, Reference Jones and Manning1994). V/(V+Ni) ratios of black shale samples are above 0.46 and below 0.60 (mean of 0.52), indicating dysoxic conditions. This determination is also supported by the TS vs V/(V+Ni) diagram. In the diagram, all the samples are in suboxic conditions and a mixture of marine-terrestrial areas (Fig.11).

Figure 11. Cross-plot of sulphur (TS) and V/(V+Ni) ratio, indicating highly marine reducing environmental conditions black shale samples (Bechtel et al. Reference Bechtel, Gratzer and Sachsenhofer2001).

In addition, Pr/Ph ratios were used to interpret redox conditions in this study. Phytane (Ph) and pristane (Pr) are considered the foremost significant isoprenoid compounds of hydrocarbons in that they indicate the palaeo-environmental conditions of the source rocks and reflect the redox conditions during diagenesis and sedimentation. (Powell & McKirdy, Reference Powell and Mckirdy1973; Didyk et al. Reference Didyk, Simoneit and Brassell1978; Chandra et al. Reference Chandra, Mishra, Samanta, Gupta and Mehrotra1994; Hakimi and Abdullah, 2014). A high Pr/Ph ratio indicates that the deposition environment is oxic throughout the sedimentation of OM (Mello & Maxwell, Reference Mello, Maxwell and Katz1990; Philp, Reference Philp, Scot and Fleet1994; Huang et al. Reference Huang, Larter and Love2003; Saydam Eker et al, Reference Saydam Eker, Akpinar, Sipahi and Yapici2016b). Peters & Moldowan (Reference Peters and Moldowan1993) stated that Pr/Ph ratio <0.5 reflects a strongly anoxic environment, 0.5<Pr/Ph<1 exhibits an anoxic environment (aquatic), 1<Pr/Ph<2 reflects a weakly oxic-weakly anoxic aquatic environment and Pr/Ph>2 shows an oxic environment. The Pr/Ph ratios of the analyzed black shales are much higher than 2 (Table 4), indicating an oxic condition. A high C35 homohopane value is one of the most important indicators of evaporitic and anoxic environments (Boon et al. Reference Boon, Hine, Burlingame, Bjoray, Albrecht and Cornford1983; Connan et al. Reference Connan, Bourouller, Dessort and Albrechht1986), so the C35/C34 homohopane ratio is accustomed to interpreting the redox conditions of depositional environments, and low ratios (< 1) show oxic-dysoxic conditions for the source rock (Curiale et al. Reference Curiale, Cameron and Davis1985). The C35/C34 HH ratios were calculated as < 1 for the analyzed samples, indicating that the depositional environment was oxic-dysoxic. In addition, low HHI values indicate oxic and/or sulphate-poor, as well as clastic depositional environments (Köster et al. Reference Köster, Van Kaam-Peters, Koopmans, De Leeuw and Damsté1997; Peters et al. Reference Peters, Walters and Moldowan2005). The HHI value of samples E-15 and E-16 was calculated as 0.03, which is low and supports that the deposition environment was oxic and/or sulphate-poor.

5.e. Palaeo-salinity

Various parameters (Sr/Ba and TS/TOC ratios) were used to interpret the palaeo-salinity conditions of the depositional environment (e.g. Deng & Qian, Reference Deng and Qian1993; Wei & Algeo, Reference Wei and Algeo2020; Zhang et al. Reference Zhang, Meng, Misch, Sachsenhofer, Liu, Hu and Shen2021). S is preserved in the sediment through evaporation, microbial sulphate and thermochemical sulphate reduction (Trundinger et al. Reference Trudinger, Chambers and Smith1985; Sim et al. Reference Sim, Bosak and Ono2011), thus providing information about the salinity of the environment. TS/TOC is less than 0.1 in freshwater and greater than 0.1 in marine and brackish facies. Whereas Sr/Ba is >0.5 in marine facies, it is <0.2 in freshwater and 0.2–0.5 in brackish (Wei & Algeo, Reference Wei and Algeo2020). In analyzed shale, the Sr/Ba ratios vary from 0.35 to 0.65 (Table 2, Fig. 10), indicating brackish and marine facies and this finding is also supported by the TS/TOC ratio. TS/TOC ratios vary from 0.07 to 0.49, indicating freshwater and brackish and marine facies and deposition environments.

Gammacerane obtained from biomarker analysis also provides useful information about the palaeo-deposition environment. Gammacerane is generally abundant in high-salt marine environments. In addition, the high gammacerane/C30hopane ratio indicates marine depositional environments with high salinity associated with evaporite and carbonate deposition (Peters & Moldowan; 1991). In this study, the gammacerane/C30hopane ratios are low, varying between 0.02 and 0.03, indicating a moderate salinity environment.

5.f. Thermal maturity of organic matter

The characteristics that are most frequently utilized in thermal maturity studies include the colour change of the palynomorph, vitrinite reflectance and Tmax, which is obtained by programmed temperature pyrolysis (e.g. Hartkopf-Fröder et al. Reference Hartkopf-Fröder, Königshof, Littke and schwarzbauer2015; Sorci et al. Reference Sorci, Cirilli, Clayton, Corrado, Hints, Goodhue, Schito and Spina2020; Spina et al. Reference Spina, Cirilli, Sorci, Schito, Clayton, Corrado, Fernandes, Galasso, Montesi, Pereira, Rashidi and Rettori2021; Buratti et al. Reference Buratti, De Luca, Garuti, Sorci, Spina and Clayton2024). In the present study, to determine the OM’s thermal maturity, Tmax and vitrinite reflectance (Ro%) values calculated based on Tmax (Jarvie et al. Reference Jarvie, Claxton, Henk and Breyer2001), aliphatic and aromatic components are used. Aliphatic maturity parameters contain the ββ/(ββ + αα) sterane (reaching an equilibrium value is 0.70), 20S/(20R + 20S) homohopane (value of achieving equilibrium for C29 is 0.55) (Seifert & Moldowan, Reference Seifert and Moldowan1986), and 22S/(22R + 22S) homohopane (C32), and their ratios increase as maturity increases. Likewise, the 22S/(22R + 22S) homohopane ratios are quite reliable in indicating the thermally early mature to immature range (value ranges from 0.55 to 0.60, Waples & Machihara, Reference Waples and Machihara1991; Peters et al. Reference Peters, Walters and Moldowan2005). In aromatic components, methyl-DBT ratio and methyl-phenanthrene index (MPI) (MDR = 4MDBT/1MDBT) (Radke & Willsch, Reference Radke and Willsch1994) are used as maturity parameters and these rates increase as maturity increases. Additionally, Radke (Reference Radke1987) divided source rock maturity into three groups according to MPI-3 value; MPI-3 > 1 mature, MPI-3 = 0.80–1 medium mature and MPI-3< 0.80 immature.

The Tmax value of the studied shale samples was measured as > 435 oC and the Ro values were calculated as > 0.70, therefore, the samples of black shale are thermally mature according to the classifications of Mukhopadhyay et al. (Reference Mukhopadhyay, Wade and Kruge1995), Espitalié et al. (Reference Espitalié, Laporte, Madec, Marquis, Leplat, Paulet and Boutefeu1977) and Peters and Cassa (Reference Peters, Cassa, Magoon and Dow1994) (Schito et al. Reference Schito, Corrado, Trolese, Aldega, Caricchi, Cirilli and Valentim2017; Riboulleau et al. Reference Riboulleau, Spina, Vecoli, Riquier, Quijada, Tribovillard and Averbuch2018). The Tmax–PI diagram (Lafargue et al. (Reference Lafargue, Marquis and Pillot1998) also supports this; in this graph, all the black shale samples are clustered in the mature area (Fig 12). In the ββ/(ββ + αα) C29 sterane and ααα20S/(20S+20R) C29 sterane and C32 homohopane 22S/(22S + 22R) and C31 homohopane 22S/(22S+22R) diagrams, samples E-15 and E-16 have reached the equilibrium value and are therefore thermally mature (Fig. 13a, b). In addition, in the diagram of 20S/(20S+20R) C29 sterane and C32 22S/(22S + 22R) homohopane, both samples were collected with peak oil window maturity area (Fig. 13c). However, MPI-3 values of E-15 and E-16 samples were calculated as 4.85 and 4.18, respectively, and MDR ratios were calculated as 0.96 and 0.92, indicating medium thermal maturity. In short, various aromatic indicators exhibit slight differences, but all values (Tmax, Ro %, aliphatic indicators) indicate oil window maturity.

Figure 12. The plot of Tmax vs. PI shows hydrocarbon potential for the black shale samples.

Figure 13. The plots of biomarker parameters sensitive to the thermal maturity of the two black shale samples a) (a) C29 ααα 20S/(20S + 20R) vs. C29 ββ/(ββ + αα), (b) C31 homohopan S/(S+R) vs. C32 homohopan S/(S+R), (George et al. Reference George, Ruble, Dutkiewicz and Eadington2001), c)20S(20S+20R) C29 sterane vs. C32 22S(22S+22R) homohopane (modified from Peters and Cassa, Reference Peters, Cassa, Magoon and Dow1994, from Hakimi & Abdullah, 2014).

The studied black shales are Lutetian in age and no younger formations were deposited on them in the study area. Therefore, such a high level of thermal maturation cannot be explained by the burial history. It is known that there were volcanic activities near the study area, contemporary with sedimentation during the Eocene (Keskin et al. Reference Keskin, Korkmaz, Gedik, Ateş, Gök, Küçümen and Erkal1990). These volcanic (andesitic, basaltic and pyroclastic rocks) and intrusive rocks (granodiorite, diorite and tonalite) (Kaygusuz & Öztürk, Reference Kaygusuz and Öztürk2015; Eyuboğlu et al. Reference Eyuboğlu, Dudas, Thorkelson, Zhu, Liu and Chatterjee2017; Gücer, Reference Gücer2021) are thought to help increase the temperature of the basin where the black shales were deposited and cause the thermal maturation of the OM.

5.g. Source rocks characteristics and hydrocarbon production potential

Regarding low to moderate HI values and TOC contents, the samples can be featured as fair oil source rocks (Fig. 14a). Potential production (PP = S1 + S2) < 2 mg/HC rock value indicates that the rocks do not have source rock potential, 2-6 mg/HC rock value indicates that the rocks have moderate source rock and hydrocarbon production potential and > 6 mg/HC rock value indicates that the rocks have good source rock and hydrocarbon production potential (Tissot & Welte, Reference Tissot and Welte1984). The PP value of one (E-15) of the shale samples is >6 mg/HC rock, the PP value of two (E-16 and E-20) of them varies between 2 and 6 mg/HC rock and the PP value of the others is <2 mg/HC rock. Therefore, the studied shale samples vary from poor to very good source rock, and Figure 14b supports this.

Figure 14. The plots of (a) TOC vs. HI (Zhang et al., Reference Zhang, Meng, Misch, Sachsenhofer, Liu, Hu and Shen2021) and (b) TOC vs S1+S2 (Kostova et al. Reference Kostova, Zdravkov, Bechtel, Botoucharov, Grob, Dochev and Apostolova2022) show source rock characteristics for the black shale samples.

All the studied samples in the Tmax and PI diagram (Lafargue et al. Reference Lafargue, Marquis and Pillot1998) are in the “well-drained source rock” area (Fig. 12). Hunt (1995) stated that 1% TOC is required for oil production and 0.5% TOC for gas production. TOC values of the samples examined show a very strong positive correlation with RC values (r = 0.99, Fig. 15a), and RC values of 3 samples (E-15, 16 and 20) are > 1%, indicating a few generative potentials left. Furthermore, given the positive relationship between TOC and PC values (r = 0.98, Fig. 15b), thermal maturity and mixed kerogen type (mostly terrestrial and marine), some samples with high TOC content may release little hydrocarbons (English et al. Reference English, Fowler, Johnston, Mihalynuk and Wight2004; Mallick et al. Reference Mallick, Banerjee, Hassan, Kumar, Babu, Krishna and Kumar2022).

Figure 15. The plots of (a) TOC vs. RC and (b) TOC vs. PC show hydrocarbon potential for the black shale samples.

In summary, it is observed that primary productivity is generally low in the basin (except in some places) and, accordingly, the amount of OM is not very high. It appears that palaeo-conditions were not suitable for OM accumulation at the top and bottom of the sequence. Conversely, OM-rich shales were deposited in the middle part of the sequence, particularly between 150th and 280th metres. This can be explained by the variability of sea water level, OM productivity, palaeo-salinity, palaeo-redox, palaeo-climatic conditions and terrigenous material input in the basin. However, the palaeo-productivity, palaeo-climate conditions and terrigenous material input amounts of the samples taken from the bottom, middle and top parts of the section are generally similar (Table 2, Fig. 10a). The palaeo-redox and palaeo-salinity conditions of the middle part of the section differ slightly from the bottom and top parts and are relatively higher (Fig. 10b). Therefore, it may be said that the OM enrichments in the Lutetian shales were controlled by palaeo-redox and palaeo-salinity conditions. In other words, the fact that the samples in the middle part of the section are rich in OM can depend on the rise in sea level, low-density flows and the provision of a stratified water column. Due to the stratified water column, anoxic conditions may have been temporarily provided, albeit slightly, and OM may have been preserved. Therefore, it is thought that the sea level can be divided into three stages during the deposition of Lutetian clastic rocks. In the I. stage, the sea level is low, there is terrigenous debris matter and low productivity (Fig. 16a). In stage II, the sea level is relatively high, the terrestrial debris material is lower than in stage I and the productivity is higher than in stage I (Fig 16b). Stage III is like stage I, with low sea level, high terrestrial debris material input and low productivity (Fig 16c). However, during the Lutetian, climatic conditions were hot and dry, and chemical weathering was low.

Figure 16. Schematic figure showing the organic matter accumulation and sedimentation model of Lutetian clastic rocks, (a) stage I, (b) stage II, (c), stage III.

6. Conclusion

The following results were reached after a thorough analysis of the geochemical properties of Lutetian shale samples from the Everek area, including elemental composition, C isotopic signature, Rock-Eval parameters, GC and GC-MS saturated and aromatic hydrocarbon parameters.

It was determined that in the HI -Tmax covariation, 7 shale samples included Type II-III kerogen, while three shale samples included Type II kerogen. S2/S3 ratios of the analyzed samples are widely distributed and vary between 1.28 and 62.45 and according to various classifications, the kerogen content of these samples varies between Type I and Type III. δ13Corg isotope values ranging between −28.23 and −28.22 support this, which illustrates the low contribution of marine OM and the strong OM intake from land during the deposition of shales. GC parameters such as n-C17/n - C27, Pr/n-C17 - /Ph/n-C18 and TAR show that the OM contained in the samples is both terrestrial and marine, but terrestrial OM is more dominant. To clarify the sedimentation environment conditions of the black shales, a variety of biomarker analyses have been conducted. The dominance of C29ααα20R steranes over C28ααα20R and C27ααα20R steranes, low C3122R/C30H ratios, high C29/C27 sterol ratios and the order C29MA>C28MA>C27MA indicate that terrestrial OM is more dominant than marine OM.

Low CIA, C-values, high Th/U ratios (inorganic proxies for palaeo-climate), low Cu/Al, Ni/Al and Zn/Al ratios (inorganic proxies for palaeo-productivity) of the samples indicate hot-arid palaeo-climate conditions and low productivity. The moderate Ti/Al ratios represent moderate terrestrial detrital input during the depositional period. High Ni/Co, Pr/Ph, moderate V/(V+Ni), low Cu/Zn, C35/C34 ratios and low HHI values of the shale samples indicate oxic-dyoxic conditions during the Lutetian period. Sr/Ba and TS/TOC ratios showing a wide range indicate that the Lutetian basin changed between freshwater and marine facies and was a terrestrial-marine transition environment. The low gammacerane/C30hopane ratios of the samples also support this.

According to maturity estimations derived from Tmax, calculated vitrinite reflectance values and biomarker maturity criteria, the studied shales have achieved the mature level of the oil window.

Overall, the results obtained, the Lutetian sequence was transported and deposited by low-density turbidite and hyperpycnal turbidite currents. During the deposition of the studied rocks, turbidite flows carried more terrestrial OM to the basin due to hot-dry climate conditions and this caused the amount of terrestrial OM to be more dominant than the marine one. Low-density turbidites contained higher amounts of TOC than hyperpycnal turbidites, suggesting that the turbidite current energy also affects the OM content. In addition, OM enrichment is thought to be controlled by palaeo-redox and palaeo-salinity as well as seawater level.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0016756824000281

Acknowledgements

The authors gratefully acknowledge Editor Dr. Bas Van de Schootbrugge for editorial handling The authors thank three anonymous reviewers for their constructive comments and suggestions to improve the manuscript.

Competing interests

The author declares that I have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

Ahmed, A, Jahandad, S, Hakimi, MH, Gharib, AF, Mehmood, S, Kahal, AY and Lashin, A (2022) Organic matter characteristics and conventional oil potentials of shales from the early Jurassic datta formation in the Upper Indus Basin, Northern Pakistan. Journal of Asian Earth Sciences 224, 104975.CrossRefGoogle Scholar
Alexander, R, Kagi, RI and Sheppard, PN (1983) Relative abundance of dimethylnaphthalene isomers in crude oils. Journal of Chromatography 267, 367–72.CrossRefGoogle Scholar
Algeo, TJ and Maynard, JB (2004). Trace-element behavior and redox facies in core shales of Upper Pennsylvanian Kansas-type cyclothems. Chemical Geology 206, 289318.CrossRefGoogle Scholar
Bechtel, A, Gratzer, R and Sachsenhofer, RF (2001) Chemical characteristics of upper cretaceous (Turonian) jet of the gosau group of gams/hieflau (Styria, Austria). International Journal of Coal Geology 46, 2749.CrossRefGoogle Scholar
Bechtel, A, Jia, JL, Strobl, SAI, Sachsenhofer, RF, Liu, ZJ, Gratzer, R and Püttmann, W (2012) Paleoenvironmental conditions during deposition of the Upper Cretaceous oil shale sequences in the Songliao Basin (NE China): implications from geochemical analyses. Organic Geochemistry 46, 7695.CrossRefGoogle Scholar
Boon, JJ, Hine, SH, Burlingame, AI et al. (1983) Organic geochemical studies of Solar Lake laminated cyanobacterial mats. In Int., Advances in Organic Geochemistry 1981 (Eds. Bjoray, M, Albrecht, C., Cornford, C et al., John Wiley & Sons, New York, pp. 207–27.Google Scholar
Bordenave, ML, Espitalié, J, Leplat, PO, Oudin, JL and Vandenbroucke, M. (1993) Screening techniques for source rock evaluation. In: Applied Petroleum Geochemistry, (Eds. Bordenave, M. L.) Paris: Editions Technip, pp. 217–78.Google Scholar
Bourbonniere, RA and Meyers, PA (1996) Anthropogenic influences on hydrocarbon contents of sediments deposited in eastern Lake Ontario since 1800. Environmental Geology 28, 2228.CrossRefGoogle Scholar
Brassell, SC and Eglinton, G (1981) Biogeochemical significance of a novel sedimentary C27 stanol. Nature 290, 579–82.CrossRefGoogle Scholar
Brumsack, H (2006) The trace metal content of recent organic carbon-rich sediments: implications for cretaceous black shale formation. Palaeogeography, Palaeoclimatology, Palaeoecology 232, 344–61.CrossRefGoogle Scholar
Buratti, N, De Luca, R, Garuti, L, Sorci, A, Spina, A and Clayton, G (2024) Thermal maturity evaluation on mildly artificially oxidised sporomorphs: A comprehensive calibration of palynomorph darkness index (PDI) with vitrinite reflectance. Marine and Petroleum Geology 162, 106672.CrossRefGoogle Scholar
Calvert, SE and Pedersen, TF (1993) Geochemistry of recent oxic and anoxic marine sediments: implications for the geological record. Marine Geology 113, 6788.CrossRefGoogle Scholar
Canfield, DE (1994) Factors influencing organic carbon preservation in marine sediments. Chemical Geology 114, 315–29.CrossRefGoogle ScholarPubMed
Cao, J., Wu, M., Chen, Y., Hu, K., Bian, L., Wang, L. & Zhang, Y. 2012. Trace and rare earth element geochemistry of Jurassic mudstones in the northern Qaidam Basin, northwest China. Chemie der Erde Geocemistry 72, 245–252.Google Scholar
Cardinal, D Savoye, N, Trull, TW, Andre, L, Kopczynska, EE and Dehairs, F (2005) Variations of carbon remineralisation in the Southern Ocean are illustrated by the Baxs proxy. Deep-Sea Research I 52, 355–70.CrossRefGoogle Scholar
Carroll, AR and Bohacs, KM (1999) Stratigraphic classification of ancient lakes: balancing tectonic and climatic controls. Geology 27, 99102.2.3.CO;2>CrossRefGoogle Scholar
Chandra, K, Mishra, CS, Samanta, U, Gupta, A and Mehrotra, KL (1994) Correlation of different maturity parameters in the Ahmedabad–Mehsana Block of the Cambay Basin. Organic Geochemistry 21, 313–21.CrossRefGoogle Scholar
Cirilli, S, panfili, G, Buratti, N and Frixa, A (2018) Paleoenvironmental reconstruction by means of palynofacies and lithofacies analyses: An example from the Upper Triassic subsurface succession of the Hyblean Plateau Petroleum System (SE Sicily, Italy). Review of Palaeobotany and Palynology 253, 7087.CrossRefGoogle Scholar
Clementz, DM, Demaison, GJ and Daly, AR (1979) Well Site Geochemistry by Programmed Pyrolysis. Proceedings of the 11th Annual Offshore Technology Conference, Houston, OTC 3410, 1, 465-470.CrossRefGoogle Scholar
Coffin, RB, Fry, B., Peterson, BJ and Wright, RT (1989) Carbon isotopic compositions of estuarine bacteria. Limnology and Oceanography 34, 1305–10.CrossRefGoogle Scholar
Connan, J, Bourouller, J, Dessort, D and Albrechht, P, (1986) The microbial input in carbonate-anhydrite facies of a sabkha paleoenvironment from Guatemala: a molecular approach. Organic Geochemistry 10, 2950.CrossRefGoogle Scholar
Cranwell, P.A., Eglinton, G. and Robinson, N, (1987) Lipids of aquatic organisms as potential contributors to lacustrine sediments-II. Organic Geochemistry 11, 513–27.CrossRefGoogle Scholar
Curiale, JA, Cameron, D and Davis, DV (1985) Biological marker distribution and significance in oils and rocks of the Monterey Formation, California. Geochemica et Cosmochimica Acta 49, 271–88.CrossRefGoogle Scholar
Dehairs, F, Chesselet, R and Jedwab, J (1980) Discrete suspended particles of barite and the barium cycle in the open ocean. Earth and Planetary Science Letters 49, 528–50.CrossRefGoogle Scholar
Deng, HW and Qian, K (1993) Sedimentary Geochemistry and Environment Analysis. Gansu Technology Publishing House, Lanzhou, pp. 1150.Google Scholar
Didyk, BM, Simoneit, BRT and Brassell, SC (1978) Geochemical Indicators of Paleoenvironmental Conditions of Sedimentation. Nature 272, 216–22.CrossRefGoogle Scholar
Dokuz, A, Külekçi, E, Aydinçakir, E, Kandemir, R, Alçiçek, MC, Pecha, ME and Sünnetçi, K. (2017) Cordierite-bearing strongly peraluminous Cebre Rhyolite from the eastern Sakarya Zone, NE Turkey: Constraints on the Variscan Orogeny. Lithos 278–281, 285302.CrossRefGoogle Scholar
Dymond, J, (1981) Geochemistry of Nazca plate surface sediments: an evaluation of hydrothermal, biogenic, detrital, and hydrogenous sources. In Nazca Plate: Crustal Formation nd Andean Convergence (Eds. Kulm, L.V.D., Dymond, J., Dasch, E.J., Hussong, D.M. and Roderick, R.,) p. 133 Geological Society of America. https://doi.org/10.1130/MEM154.CrossRefGoogle Scholar
Dymond, J, Suess, E and Lyle, M (1992) Barium in deep-sea sediment: a Geochemical proxy for paleoproductivity. Paleoceanography Paleoclimatology 7, 163–81.CrossRefGoogle Scholar
Eglinton, G and Hamilton, RJ (1967) Leaf epicuticular waxes. Science 156, 1322–35.CrossRefGoogle ScholarPubMed
English, J.M., Fowler, M, Johnston, ST, Mihalynuk, MG and Wight, KL (2004) Thermal Maturity in the Central Whitehorse Trough, Northwest British Columbia. Summary of Activities 2004, BC Ministry of Energy and Mines. Crown Publications, British Columbia, 79–85.Google Scholar
Eric, BE, Adama, A, Etutu, EMM, Kwankam, FN, Betrant, B. D. and Esue, MF (2023) Paleoclimate characteristics of source area weathering and metallogenic implication of cretaceous black shales in the Mamfe basin, (SW Cameroon): evidence from lithogeochemistry. Helyon 9, e17142.CrossRefGoogle Scholar
Espitalié, J, Laporte, JL Madec, M, Marquis, F, Leplat, P, Paulet, J and Boutefeu, A (1977) Methode rapide de caracterisation des roches meres de leur potentiel petrolier et de leur degre d‘evolution. Revue de l’Institut Francais du Petrole. 32, 2342.Google Scholar
Eyuboğlu, Y, Dudas, FO, Thorkelson, D, Zhu, D-C, Liu, Z and Chatterjee, N (2017) Eocene granitoids of northern Turkey: Polybaric magmatism in an evolving arc–slab window system. Gondwana Research 50, 311–45.CrossRefGoogle Scholar
Feng, L, Chu, X, Zhang, Q and Zhang, T (2003) CIA (Chemical index of alteration) and its applications in the Neoproterozoic clastic rocks. Earth Science Frontiers 10, 539–43.Google Scholar
Ficken, KJ, Street-Perrott, FA, Perrott, RA, Swain, DL, Olago, DO and Eglinton, G (1998) Glacial/interglacial variations in carbon cycling revealed by molecular and isotope stratigraphy of Lake Nkunga. Mt. Kenya East Africa. Organic Geochemistry 29, 1701–19.CrossRefGoogle Scholar
Fu, X, Wang, J, Chen, W, Feng, X, Wang, D, Song, C and Zeng, S (2016) Elemental geochemistry of the early Jurassic black shales in the Qiangtang Basin, eastern Tethys: constraints for palaeoenvironment conditions. Geological Journal 51, 443–54.CrossRefGoogle Scholar
Gani, MR (2004) From turbid to lucid: a straight forward approach to sediment gravity flows and their deposits. Sedimentary Record 2, 48.CrossRefGoogle Scholar
George, SC, Ruble, TE, Dutkiewicz, A and Eadington, PJ (2001) Assessing the maturity of oil trapped in fluid inclusions using molecular geochemistry data and visually-determined fluorescence colors. Applied Geochemistry 16, 451–73.CrossRefGoogle Scholar
Goldberg, ED and Arrhenius, GOS (1958) Chemistry of Pacific pelagic sediments. Geochimica et Cosmochimica Acta 13, 158212.CrossRefGoogle Scholar
Goldberg, K and Humayun, M, (2010) The applicability of the Chemical Index of Alteration as a paleoclimatic indicator: an example from the Permian of the Parana Basin, Brazil. Palaeogeography, Palaeoclimatology, Palaeoecology 293, 175–83.CrossRefGoogle Scholar
Gücer, MA (2021) Origin, petrogenesis and geodynamic implications of the early Eocene Altınpınar adakitic andesites in the eastern Sakarya Zone, northeastern Turkey. Chem- Erde-Geochemistry 81, 125766.CrossRefGoogle Scholar
Güven, IH (1993) 1/100000 scaled geological map series of Turkey No:57-60 MTA Publication, AnkaraGoogle Scholar
Hakimi, MH, Abdullah, WH and Shalaby, MR (2011) Organic geochemical characteristics of crude oils from the Masila Basin, eastern Yemen. Organic Geochemistry 42, 465–76.CrossRefGoogle Scholar
Hartkopf-Fröder, C, Königshof, P, Littke, R and schwarzbauer, J (2015) Optical thermal maturity parameters and organic geochemical alteration at low grade diagenesis to anchimetamorphism: a review. International Journal Coal Geology 150-151, 74119.CrossRefGoogle Scholar
Hatch, JR and Leventhal, JS, (1992) Relationship between inferred redox potential of the depositional environment and geochemistry of the upper Pennsylvanian (Missourian) Stark shale member of the Dennis limestone, Wabaunsee County, Kansas, USA. Chemical Geology 99, 6582.CrossRefGoogle Scholar
Hatem, BA Abdullah, WH, Hakimi, MH, Mustapha, KA (2016) Origin of organic matter and paleoenvironment conditions of the Late Jurassic organic-rich shales from Shabwah sub-basin (western Yemen): Constraints from petrology and biological markers. Marine and Petroleum Geology 72, 8397.SCrossRefGoogle Scholar
He, J, Ding, W, Jiang, Z, Jiu, K, Li, A and Sun, Y (2017) Mineralogical and chemical distribution of the Es3L oil shale in the Jiyang Depression, Bohai Bay Basin (E China): Implications for paleoenvironmental reconstruction and organic matter accumulation. Marine and Petroleum Geology 81, 196219.CrossRefGoogle Scholar
Hu, J, Li, Q, Song, C, Wang, S and Shen, B (2017) Geochemical characteristics of the Permian sedimentary rocks from Qiangtang Basin: constraints for paleoenvironment and paleoclimate. Terrestrial, Atmospheric and Oceanic Sciences 28, 271–82.CrossRefGoogle Scholar
Huang, H, Larter, SR and Love, GD (2003) Analysis of wax hydrocarbons in petroleum source rocks from the Damintun depression, eastern China, using high-temperature gas chromatography. Organic Geochemistry 34, 1673–168.CrossRefGoogle Scholar
Huang, WY and Meinschein, WG (1979) Sterols as ecological indicators. Geochimica et Cosmochimica Acta 43, 739–45.CrossRefGoogle Scholar
Huang, Y, Dupont, L, Sarnthein, M, Hayes, JM and Eglinton, G (2000) Mapping of C4 plant input from North West Africa into North East Atlantic sediments. Geochimica Et Cosmochimica Acta 64, 3505–13.CrossRefGoogle Scholar
Hunt, JM (1996) Petroleum Geochemistry and Geology. W.H. Freeman and Company, New York.Google Scholar
Ilevbare, M and Adeleye, RA (2023) Paleoenvironment of deposition and hydrocarbon potential of Maastritchian Shale Sediments, Southern Anambra Basin, Edo State, Nigeria. Arabian Journal of Geosciences 16, 607.CrossRefGoogle Scholar
Jarvie, DM, Claxton, BL, Henk, F and Breyer, JT (2001) Oil and shale gas from the Barnett Shale, Ft, Worth Basin, Texas (abs), AAPG Annual Meeting Program, pp. A100.Google Scholar
Jarvie, DM, Hill, RJ, Ruble, TE and Pollastro, RM (2007) Unconventional shale-gas systems: The Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment. AAPG Bulletin 91, 475–99.CrossRefGoogle Scholar
Jones, B and Manning, DA (1994) Comparison of geochemical indices used for the interpretation of palaeoredox conditions in ancient mudstones. Chemical Geology 111, 111–29.CrossRefGoogle Scholar
Kaygusuz, A and Öztürk, M, (2015) Geochronology, geochemistry, and petrogenesis of the Eocene Bayburt intrusions, Eastern Pontide, NE Turkey: implications for lithospheric mantle and lower crustal sources in the high-K calc-alkaline magmatism. Journal of Asian Earth Sciences 108, 97116.CrossRefGoogle Scholar
Kaygusuz, A, Yücel, C, Aydinçakir, E, Gücer, MA and Ruffet, G (2022) 40Ar–39Ar dating, whole–rock and Sr–Nd isotope geochemistry of the Middle Eocene calc–alkaline volcanic rocks in the Bayburt area, Eastern Pontides (NE Turkey): Implications for magma evolution in an extension–related setting. Mineralogy and Petrology 116, 379–99.CrossRefGoogle Scholar
Keskin, İ, Korkmaz, S, Gedik, İ, Ateş, M, Gök, L, Küçümen, Ö and Erkal, T (1990) Geology of Bayburt region, MTA report Ankara, No: 8995.Google Scholar
Kidder, D, Xa, L, Erwin, D and Xa, H, (2001) Secular distribution of biogenic silica through the phanerozoic: comparison of silica 2010; replaced fossils and bedded cherts at the series level. Journal of Geology 109, 509–22.CrossRefGoogle Scholar
Killops, S and Killops, V (2005) Introduction to Organic Geochemistry, second ed. Blackwell Publishing, Oxford.Google Scholar
Koralay, DB (2021) Investigation of the paleodepositional environment of the Middle Miocene aged organic matter-rich rocks (Tavas/Denizli/SW Turkey) by using biomarker parameters and stable isotope compositions (13C and 15N). Bulletin Mineral Research Exploration 164, 3952.Google Scholar
Köster, J, Van Kaam-Peters, HM, Koopmans, MP, De Leeuw, JW and Damsté, JSS (1997) Sulphurisation of homohopanoids: Effects on carbon number distribution, speciation, and 22S22R epimer ratios. Geochimica et Cosmochimica Acta 61, 2431–52.CrossRefGoogle Scholar
Kostova, I, Zdravkov, A, Bechtel, A, Botoucharov, N, Grob, D, Dochev, D and Apostolova, D (2022) Characterization of organic matter from the Cretaceous sedimentary and volcano-sedimentary strata from Livingston Island, Antarctic Peninsula: Insights from organic petrology, molecular proxies and carbon and hydrogen isotopes. International Journal of Coal Geology, 252, 103940.CrossRefGoogle Scholar
Kumar, D, Ghosh, S, Tiwari, B, Varma, AK, Mathews, RP and Chetia, R. (2021) Palaeocene-Eocene organic sedimentary archives of Bikaner-Nagaur Basin, Rajasthan, India: An integrated revelation from biogeochemical and elemental proxies. International Journal of Coal Geology, 247, 103848.CrossRefGoogle Scholar
Lafargue, E, Marquis, F and Pillot, D (1998) Rock-Eval 6 applications in Hydrocarbon Exploration, production, and Soil Contamination Studies. Oil Gas Science Technology 53, 421–37.Google Scholar
Lamb, AL, Wilson, GP and Leng, MJ (2006) A review of coastal palaeoclimate and relative sea-level reconstructions using δ13C and C/N ratios in organic material. Earth-Science Reviews 75, 2957.CrossRefGoogle Scholar
Li, M, Zhang, S, Snowdon, L and Issler, D. (2008) Oil-source correlation in Tertiary deltaic petroleum systems: a comparative study of the Beaufort-Mackenzie Basin in Canada and the Pearl River Mouth Basin in China. Organic Geochemistry. 39, 1170–75.CrossRefGoogle Scholar
Li, Q, Wu, SH, Xia, DL, You, XL, Zhang, HM and Lu, H, (2020) Major and trace element geochemistry of the lacustrine organic-rich shales from the Upper Triassic Chang 7 Member in the southwestern Ordos Basin, China: implications for paleoenvironment and organic matter accumulation. Marine and Petroleum Geology 111, 852–67.CrossRefGoogle Scholar
Li, TY, HE, S and Yang, Z (2008) The marine source rock formation conditions and control factors. Geological Science and Technology Information 27, 6370. (in Chinese with English abstract).Google Scholar
Liang, C, Wu, J, Jiang, Z, Cao, Y and Song, G (2018) Sedimentary environmental controls on petrology and organic matter accumulation in the upper fourth member of the Shahejie Formation (Paleogene, Dongying depression, Bohai Bay Basin, China). International Journal of Coal Geology. 186, 13.CrossRefGoogle Scholar
Liang, H, Xu, G, Xu, F, Yu, Q, Liang, J and Wang, D (2020) Paleoenvironmental evolution and organic matter accumulation in an oxygen-enriched lacustrine basin: A case study from the Laizhou Bay Sag, southern Bohai Sea (China). International Journal of Coal Geology, 217, 103318.CrossRefGoogle Scholar
Lin, XH, Zhan, ZW, Zou, YR, Cai, YL, Liang, T and Shi, J. (2019) Elemental geochemical characteristics of the Lucaogou Formation oil shale in the southeastern Junggar Basin and its depositional environmental implications. Geochimica 048, 6778.Google Scholar
Makeen, Y M, Hakimi, MH and Abdullah, WH (2015). The origin, type and preservation of organic matter of the Barremian-Aptian organic-rich shales in the Muglad Basin, Southern Sudan, and their relation to paleoenvironmental and paleoclimate conditions. Marine and Petroleum Geology 65, 187–97.CrossRefGoogle Scholar
Mallick, M, Banerjee, B, Hassan, T, Kumar, TV, Babu, EVSSK, Krishna, K and Kumar, R (2022) Geochemistry of Permian carbonaceous shales from Raniganj sub-basin, Damodar Valley, India: implications for provenance, weathering, tectonics and source of organic matter. Applied Geochemistry 146, 105469.CrossRefGoogle Scholar
Martin, JH and Knauer, GA (1973) The elemental composition of plankton. Geochimica et Cosmochimica Acta 37, 1639–53.CrossRefGoogle Scholar
Mckay, JL, Pedersen, TF and Mucci, A (2007) Sedimentary redox conditions in continental margin sediments (N.E. Pacific) - influence on the accumulation of redox-sensitive trace metals. Chemical Geology 238, 180–96.CrossRefGoogle Scholar
Mclennan, SM, Hemming, S, Mcdaniel, DK and Hanson, GN. (1993) Geochemical approaches to sedimentation, provenance, and tectonics. In Processes controlling the composition of clastic sediments (eds Johnson, MJ and Basu, A), pp.2140. Geological Society of America, Special Papers, 285CrossRefGoogle Scholar
Mello, MR and Maxwell, JR (1990) Organic geochemical and biological marker characterization of source rocks and oils from lacustrine environments in the Brazilian Continental Margin. In: Lacustrine Basin Exploration. (Eds. Katz, BJ), pp. 7797. Tulsa, OK, USA: AAPG Memoirs.Google Scholar
Meng, Q, Liu, Z, Bruch, AA, Liu, R and Hu, F (2012) Palaeoclimatic evolution during Eocene and its influence on oil shale mineralization, Fushun basin, China. Journal of Asian Earth Sciences 45, 95105.CrossRefGoogle Scholar
Meyers, PA (2003) Applications of organic geochemistry to paleolimnological reconstructions: a summary of examples from the Laurentian Great Lakes. Organic Geochemistry 34, 261–89.CrossRefGoogle Scholar
Meyers, PA and ishiwatari, R (1993) Lacustrine organic geochemistry—an overview of indicators of organic matter sources and diagenesis in lake sediments. Organic Geochemistry 20, 867900.CrossRefGoogle Scholar
Moldowan, JM, Sundararaman, P. and Schoell, M (1986) Sensitivity of biomarker properties to depositional environment and/or source input in the lower Toarcian of SW-Germany. Organic Geochemistry 10, 915–26.CrossRefGoogle Scholar
Mukhopadhyay, PK, Wade, JA and Kruge, MA (1995) Organic facies and maturation of Jurassic/Cretaceous rocks, and possible oil-source rock correlation based on pyrolysis of asphaltenes, Scotion Basin, Canada. Organic Geochemistry 22, 85104.CrossRefGoogle Scholar
Murphy, A.E., Sageman, BB, Hollander, DJ and Lyons, TW (2000) Black shale deposition and faunal overturn in the Devonian Appalachian Basin: clastic starvation, seasonal water-column mixing, and efficient biolimiting nutrient recycling. Paleoceanography 15, 280–91.CrossRefGoogle Scholar
Musaoğlu, A (1987) Bayburt-Maden Kop Region Geology and Mining Projection Report, MTA General Directorate Compilation Report no: 8541, Ankara.Google Scholar
Mutti, E, Bernoulli, D and Lucchi, FR (2009) Turbidites and turbidity currents from Alpine flysch to the exploration of continental margins. Sedimentology 56, 267318.CrossRefGoogle Scholar
Nesbitt, HW and Young, GM (1982) Early Proteozoic climate and plate motions inferred from major element chemistry of lutites. Nature 299, 715–17.CrossRefGoogle Scholar
Ortiz, JE., Torres, T, Delgado, A, Llamas, FJ and Valle, M (2010) Palaeoenvironmental changes in the Padul Basin (Granada, Spain) over the last 1 Ma B.P. based on the biomarker content. Palaeogeography, Palaeoclimatology, Palaeoecology 298, 286–99.CrossRefGoogle Scholar
Ortiz, JE, Torres, T, Delgado, D, Valle, M, Soler, V, Araujo, R, Rivas, MR, Julià, R, Sanchez-Palencia, Y and Vega-Panizo, R (2021) Bulk and compound-specific δ13C and n-alkane indices in a palustrine intermontane record for assessing environmental changes over the past 320 ka: the Padul Basin (Southwestern Mediterranean realm). Journal of Iberian Geology 47, 625–39.CrossRefGoogle Scholar
Peters, KE and Cassa, MR (1994) Applied source rock geochemistry. In the petroleum system from source to trap (Eds. Magoon, L.B. and Dow, W.G.) AAPG Memoir, 60, p. 93120.Google Scholar
Peters, KE and Moldowan, JM (1993) The Biomarker Guide, Interpreting Molecular Fossils in Petroleum and Ancient Sediments. Englewood Cliff, New Jersey: Prentice Hall. pp. 63.Google Scholar
Peters, KE, Walters, CC and Moldowan, JM (2005) The Biomarker Guide. Volume 2. In: Biomarkers and Isotopes in Petroleum Exploration and Earth History. pp. 633634. Cambridge, UK: Cambridge University Press.Google Scholar
Philp, PR (1994) Geochemical characteristics of oils derived predominantly from terrigenous source materials. In. Coal and Coal-Bearing Strata as Oil-Prone Source Rocks? (eds Scot, AC, Fleet, AJ,) Special Publications No. 77. pp. 7191. London, UK: Geological Society.Google Scholar
Piper, DZ and Perkins, RB (2004) A modern vs. Permian black shale— the hydrography, primary productivity, and water-column chemistry of deposition. Chemical Geology 206, 177–97.CrossRefGoogle Scholar
Powell, TG and Mckirdy, DM (1973) Relationship between ratio of pristane to phytane, crude oil composition and geological environment in Australia. Nature Physical Science 243, 3739.CrossRefGoogle Scholar
Qiao, J., Baniasad, A., Zieger, L., Zhang, L., Luo, Q. and Littke, R. (2021) Paleo-depositional environment, origin and characteristics of organic matter of the Triassic Chang 7 Member of the Yanchang Formation throughout the mid-western part of the Ordos Basin, China. International Journal of Coal Geology 237, 103636.CrossRefGoogle Scholar
Radke, M (1987) Organic geochemistry of aromatic hydrocarbons. Advances in petroleum geochemistry 2, 141207.Google Scholar
Radke, M and Willsch, H (1994) Extractable Alklydibenzothiophenes in Posidonia Shale (Toarcian) Source Rocks: Relationship of Yields to Petroleum Formation and Expulsion. Geochimica et Cosmochimica Acta 23, 5223–44.CrossRefGoogle Scholar
Riboulleau, A, Spina, A, Vecoli, M, Riquier, L, Quijada, M, Tribovillard, N and Averbuch, O (2018) Organic matter deposition in the Ghadames Basin (Libya) during the Late Devonian—A multidisciplinary approach. Palaeogeography, palaeoclimatology, palaeoecology 497, 3751.CrossRefGoogle Scholar
Rimmer, SM (2004) Geochemical paleoredox indicators in Devonian–Mississippian black shales, Central Appalachian Basin (USA). Chemical Geology 206, 373–91.CrossRefGoogle Scholar
Rohmer, M and OURISSON, G (1976) D´eriv´es du bact´eriohopane: variations structurales et r´epartition. Tetrahedron Letters 17, 3637–40.CrossRefGoogle Scholar
Samanta, A, Bera, M.K., Ghosh, R., Bera, S., Filley, T., Pande, K., Rathore, S.S., Rai, J. and Sarkar, A. (2013) Do the large carbon isotopic excursions in terrestrial organic matter across Paleocene–Eocene boundary in India indicate intensification of tropical precipitation? Palaeogeography, Palaeoclimatology, Palaeoecology 387, 91103.CrossRefGoogle Scholar
Saydam Eker, C (2012) Petrography and geochemistry of Eocene sandstones from eastern Pontides (NE Turkey): Implications for source area weathering, provenance and tectonic setting. Geochemistry International 50, 683701.CrossRefGoogle Scholar
Saydam Eker, C (2013) Organic Geochemical Characteristics and Depositional Environments of the Eocene Deposits in the Eastern Black Sea Region, NE Turkey. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 35, 413–25.CrossRefGoogle Scholar
Saydam Eker, Ç (2022) Geochemical properties of Eocene Turbiditic Sequence from Bayburt (NE Turkey): Organic matter input, paleoenvironment and paleoclimatic conditions. Arabian Journal of Geosciences, 15, 1733.CrossRefGoogle Scholar
Saydam Eker, Ç., Akpinar, I. and Sipahi, F. (2016a) Organic geochemistry and element distribution in coals formed in Eocene Lagoon facies from the Eastern Black Sea Region, NE Turkey, Turkish Journal of Earth Science 25, 467–89.CrossRefGoogle Scholar
Saydam Eker, Ç., Akpinar, İ., Sipahi, F. and Yapici, E. (2016b) Concentrations of Elements in Lias Coals from the Eastern Black Sea Region, NE-Turkey. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 38, 1643–52.CrossRefGoogle Scholar
Saydam Eker, Ç and Ari, UV (2020) Geochemistry of the Middle Jurassic sediments in Gümüşhane, north-eastern Turkey: Implications for weathering and provenance: Geological Journal 55, 4954–76.CrossRefGoogle Scholar
Saydam Eker, Ç. and Demirkol, Kiliç, E. (2018) Geochemistry of Çoruh River bed sediments in NE Turkey: Implications in weathering-sedimentary cycle, provenance, and metal pollution. Geochemistry International 56, 579600.CrossRefGoogle Scholar
Saydam Eker, Ç. and Demirkol, Kiliç, E. (2024) Pollution level, environmental risk, and source of potentially toxic elements in the sediment of Çoruh River (Bayburt, NE Türkiye). Arabian Journal of Geosciences 17, 52.CrossRefGoogle Scholar
Saydam Eker, Ç., Sipahi, F. and AKPINAR, I. (2015) Organic Maturity and Hydrocarbon Potential of Liassic Coals from the Eastern Pontides, NE Turkey. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 37, 1260–67.CrossRefGoogle Scholar
Scalan, RS and Smith, JE (1970) An improved measure of the odd-even predominance in the normal alkanes of sediment extracts and petroleum. Geochimica et cosmochimica acta 34, 611–20.CrossRefGoogle Scholar
Schito, A, Corrado, S, Trolese, M, Aldega, L, Caricchi, C, Cirilli, S and Valentim, B (2017) Assessment of thermal evolution of Paleozoic successions of the Holy Cross Mountains (Poland). Marine and Petroleum Geology 80, 112–32CrossRefGoogle Scholar
Schoepfer, SD, Shen, J., Wei, H.Y., Tyson, R.V., Ingall, E., Algeo, T. J. (2015) Total organic carbon, organic phosphorus, and biogenic barium fluxes as proxies for paleo-marine productivity. Earth-Science Reviews 149, 2352.CrossRefGoogle Scholar
Seifert, WK and Moldowan, JM, (1978) Applications of steranes, terpanes and monoaromatics to the maturation, migration and source of crude oils. Geochimica et Cosmochimica Acta 42, 7795.CrossRefGoogle Scholar
Seifert, WK and Moldowan, JM (1986) Use of biological markers in petroleum exploration. Methods in geochemistry and geophysics 24, 261–90.Google Scholar
Shanmugam, G (1985) Significance of Coniferous rain Forests and Related Organic Matter in Generating Commercial Quantities of Oil, Gippsland Basin, Australia1. AAPG Bulletin 69 (8), 1241–54Google Scholar
Shen, J, Schoepfer, SD, Feng, Q, Zhou, L, Yu, J, Song, H, Wei, H and Algeo, TJ (2015) Marine productivity changes during the end-Permian crisis and Early Triassic recovery. Earth-Science Reviews 149, 136–62.CrossRefGoogle Scholar
Sim, MS, Bosak, T and Ono, S (2011) Large sulfur isotope fractionation does not require disproportionation. Science 333, 7477.CrossRefGoogle Scholar
Sinninghe Damste, JS, Verschuren, D, Ossebaar, J, Blokker, J, Van Houten, R, Van Der Meer, MTJ, Plessen, B and Schouten, S (2011) A 25,000-year record of climate-induced changes in lowland vegetation of eastern equatorial Africa revealed by the stable carbon-isotopic composition of fossil plant leaf waxes. Earth and Planetary Science Letters 302, 236–46.CrossRefGoogle Scholar
Sorci, A, Cirilli, S, Clayton, G, Corrado, S, Hints, O, Goodhue, R, Schito, A and Spina, A (2020) Palynomorph optical analyses for thermal maturity assessment of Upper Ordovician (Katian-Hirnantian) rocks from Southern Estonia. Marine Petroleum Geology 120(4), 104574.CrossRefGoogle Scholar
Spina, A, Cirilli, S, Sorci, A, Schito, A, Clayton, G, Corrado, S, Fernandes, P, Galasso, F, Montesi, G, Pereira, Z, Rashidi, M and Rettori, R, (2021) Assessing thermal maturity through a multi-proxy approach: a case study from the Permian Faraghan formation (Zagros Basin, Southwest Iran). Geoscience 11(12), 484.Google Scholar
Spina, A, Vecoli, M, Riboulleau, A, Clayton, G, Cirilli, S, Di Michele, A, Marcogiuseppe, A, Rettori, R, Sassi, P, Servais, T and Riquier, L (2018) Application of Palynomorph Darkness Index (PDI) to assess the thermal maturity of palynomorphs: A case study from North Africa. International Journal of Coal Geology 188, 6478.CrossRefGoogle Scholar
Street-Perrott, FA, Huang, Y, Perrott, RA, Eglinton, G, Barker, P, Ben Khelifa, L., Harkness, D. D. and Olago, D. (1997) Impact of lower atmospheric CO2 on tropical mountain ecosystems: carbon-isotope evidence. Science 278, 1422–26.CrossRefGoogle Scholar
Sun, Q, Xie, M, Shi, L, Zhang, Z, Lin, Y, Shang, W, Wang, K, Li, W, Liu, J and Chu, G (2013) Alkanes, compound-specific carbon isotope measures and climate variation during the last millennium from varved sediments of Lake Xiaolongwan, northeast China. Journal of Paleolimnology 50, 331–44.CrossRefGoogle Scholar
Tanaka, K, Akagawa, F, Yamamoto, K, Tani, Y., Kawabe, I. and Kawai, T (2007) Rare earth element geochemistry of Lake Baikal sediment: its implication for geochemical response to climate change during the Last Glacial/Interglacial transition. Quaternary Science Reviews 26, 1362–68.CrossRefGoogle Scholar
Tao, S, Wang, C, Du, J., Liu, L and Chen, Z (2015) Geochemical application of tricyclic and tetracyclic terpanes biomarkers in crude oils of NW China. Marine and Petroleum Geology 67, 460467. CrossRefGoogle Scholar
Tissot, BP and Welte, DH (1984) Petroleum Formation and Occurence. Springer Verlag, Berlin Heidelberg, New York, Tokyo.CrossRefGoogle Scholar
Topuz, G, Altherr, R, Kalt, A., Satir, M., Werner, O. and Schwarz, W. (2004) Aluminous granulites from the Pulur complex, NE Turkey: a case of partial melting, efficient melt extraction and crystallization. Lithos 72, 183207.CrossRefGoogle Scholar
Tribovillard, N, Algeo, TJ, Lyons, T and Riboulleau, A (2006) Trace metals as paleoredox and paleoproductivity proxies: an update. Chemical Geology 232, 1232.CrossRefGoogle Scholar
Tripathy, GR, Singh, SK and Ramaswamy, V (2014) Major and trace element geochemistry of Bay of Bengal sediments: implications to provenances and their controlling factors. Palaeogeography, Palaeoclimatology, Palaeoecology 397, 2030.CrossRefGoogle Scholar
Trudinger, PA, Chambers, LA and Smith, JW (1985) Low-temperature sulphate reduction: biological versus abiological. Canadian Journal of Earth Sciences 22, 1910–18.CrossRefGoogle Scholar
Volkman, JK (2003). Sterols in microorganisms. Applied Microbiology and Biotechnology 60, 495506.CrossRefGoogle ScholarPubMed
Volkman, JK, Barrett, SM and Blackburn, SI (1999) Eustigmatophyte microalgae are potential sources of C29 sterols, C22–C28 n-alcohols and C28–C32 n-alkyl diols in freshwater environments. Organic Geochemistry 30, 307–18.CrossRefGoogle Scholar
Wang, Z., Fu, X., Feng, X., Song, C., Wang, D., Chen, W. and Zeng, S. (2017) Geochemical features of the black shales from the Wuyu Basin, southern Tibet: implications for palaeoenvironment and palaeoclimate. Geological Journal 52, 282–97.CrossRefGoogle Scholar
Waples, DW and Machihara, TM (1991) Biomarkers for Geologists. AAPG Methods in Exploration Series No. 9. American Association of Petroleum Geologists, Tulsa, Oklahoma.Google Scholar
Wei, W. and Algeo, T.J. (2020) Elemental proxies for paleosalinity analysis of ancient shales and mudrocks. Geochimica et Cosmochimica Acta 287, 341–66.CrossRefGoogle Scholar
Welte, DH and Ebhardt, G (1968) Distribution of long chain n-paraffins and n-fatty acids in sediments from the Persian Gulf. Geochimica et Cosmochimica Acta 32, 465–66.CrossRefGoogle Scholar
Welte, DH and Waples, DW (1973) Über die Bevorzugung geradzahliger n-Alkane in Sedimentgesteinen. Die Naturwissenschaften 60, 516–17.CrossRefGoogle Scholar
Whiticar, MJ (1996) Stable isotope geochemistry of coals, humic kerogens and related natural gases. International Journal of Coal Geology 32, 191215.CrossRefGoogle Scholar
Wignall, PB (1994) Black Shales, Clarendon Press, Oxford, 127.Google Scholar
Wu, Z., Zhao, X., Wang, E., Pu, X., Lash, G., Han, W., Zhang, W. and Feng, Y. (2021) Sedimentary environment and organic enrichment mechanisms of lacustrine shale: A case study of the Paleogene Shahejie Formation, Qikou Sag, Bohai Bay Basin. Paleogeography, Palaeoclimatology, Palaeoecology 573, 110404.CrossRefGoogle Scholar
Xie, S., Guo, J., Huang, J., Chen, F., Wang, H. and Farrimond, P. (2004) Restricted utility of δ13C of bulk organic matter as a record of paleovegetation in some loess–paleosol sequences in the Chinese Loess Plateau. Quaternary Research 62, 8693.CrossRefGoogle Scholar
Xu, G., Hannah, J.L., Bingen, B., Georgiev, S. and Stein, H.J. (2012) Digestion methods for trace element measurements in shales: paleoredox proxies examined. Chemical Geology 324–325, 132147.CrossRefGoogle Scholar
Xu, J., Liu, Z., Bechtel, A., Meng, Q., Sun, P., Jia, J., Cheng, L. and Song, Y. (2015) Basin evolution and oil shale deposition during Upper Cretaceous in the Songliao Basin (NE China): Implications from sequence stratigraphy and geochemistry. International Journal of Coal Geology. 149, 923. CrossRefGoogle Scholar
Xu, X. and Shao, L. (2018) Limiting factors in utilization of chemical index of alteration of mudstones to quantify the degree of weathering in provenance. Journal of Palaeogeography 20, 515–22.Google Scholar
Yadav, S and Rajamani, V (2004) Geochemistry of aerosols of northwestern part of India adjoining the Thar Desert. Geochimica et Cosmochimica Acta 68, 1975–88.CrossRefGoogle Scholar
Yan, D., Chen, D., Wang, Q and Wang, J (2010) Large-scale climatic fluctuations in the latest Ordovician on the Yangtze block, South China. Geology 38, 599602.CrossRefGoogle Scholar
Yang, T, Cao, Y and Wang, Y (2015) Status and trends in research on deep - water gravity flow deposits. Acta Geologica Sinica (English edition) 89, 610–31.Google Scholar
Zhang, P Meng, Q., Misch, D, Sachsenhofer, R, Liu, Z, Hu, F and Shen, L (2021) Oil shale potential of the lower cretaceous Jiufotang Formation, Beipiao Basin, Northeast China. International Journal of Coal Geology 236,103640.CrossRefGoogle Scholar
Zhang, S, Wang, X, Wang, H, Bjerrum, C, Hammarlund, E, Haxen, E, Wen, H, Ye, Y and Canfield, D (2019). Paleoenvironmental proxies and what the Xiamaling Formation tells us about the mid-Proterozoic ocean. Geobiology 17 122.CrossRefGoogle ScholarPubMed
Zhang, SH, Liu, CY, Liang, H, Wang, JQ, Bai, JK, Yang, MH, Liu, GH, Huang, H X and Guan, YZ (2018) Paleoenvironmental conditions, organic matter accumulation, and unconventional hydrocarbon potential for the Permian Lucaogou Formation organic-rich rocks in Santanghu Basin, NW China. International Journal of Coal Geology 185, 4460.CrossRefGoogle Scholar
Zhao, Z, Zhao, J, Wang, H, Liao, J and Liu, C, (2007) Distribution characteristics and applications of trace elements in Junggar Basin (in Chinese with English abstract). Natural Gas Exploration and Development 30, 3033.Google Scholar
zhou, W, Xie, S, Meyers, PA and Zheng, Y (2005) Reconstruction of late glacial and Holocene climate evolution in southern China from geolipids and pollen in the Dingnan peat sequence. Organic Geochemistry 36, 1272–84.CrossRefGoogle Scholar
Zhou, K, Sun, J, Yang, M, Zhang, S, Wang, W, Gao, R, Zhang, P, Wang, W, Liu, H, Shao, L. and Lu, J (2023) Geochemical Characteristics of the Middle Jurassic Coal-Bearing Mudstones in the Dameigou Area (Qaidam Basin, NW China): Implications for Paleoclimate, Paleoenvironment, and Organic Matter Accumulation. American Chemical Society, https://doi.org/10.1021/acsomega.3c05433.CrossRefGoogle Scholar
Zonneveld, KAF, Versteegh, GJM, Kasten, S, Eglinton, TI, Emeis, KC, Huguet, C, Koch, B.P., De Lange, G.J., De Leeuw, J.W. Middelburg, J.J., Mollenhauer, G., Prahl, F.G., Rethemeyer, J. and Wakeham, S.G. (2010) Selective preservation of organic matter in marine environments; processes and impact on the sedimentary record. Biogeosciences 7, 483511.CrossRefGoogle Scholar
Figure 0

Figure 1. (a) Simplified geological map of the eastern Pontides (after Güven, 1993) and location map of the study area. (b) Geological map of the study area (after Musaoğlu, 1987).

Figure 1

Figure 2. (a) Stratigraphic section of Eocene rocks, (b) measured stratigraphic sections of Lütetian detrital rocks, (c) and (d) photographs of black shale and (e) photograph of plant fragments.

Figure 2

Table 1. Concentrations of elements in the analyzed groups of black shale

Figure 3

Table 2. Concentrations of elemental ratios in the analyzed groups of black shale

Figure 4

Table 3. Rock-Eval and carbon isotope analysis results and calculated parameters

Figure 5

Table 4. The parameters were calculated from gas chromatograms (GC) for selected shale samples

Figure 6

Figure 3. Organic geochemical proxy profiles of the black shale samples.

Figure 7

Figure 4. Gas chromatograms of saturated hydrocarbons of two representative black shale samples.

Figure 8

Figure 5. The m/z 191 mass fragmentograms (on top) and m/z 217 mas fragmentograms (below) saturated hydrocarbon fractions of two representative black shale samples.

Figure 9

Figure 6. The m/z 178-192, m/z 184-198, m/z 231 and m/z 253 ion fragmentograms aromatic hydrocarbon fractions of two representative black shale samples.

Figure 10

Table 5. Selected saturated and aromatic biomarker parameters for the selected black shale samples

Figure 11

Figure 7 (a) The plot of Tmax vs. HI indicates kerogen types for the black shale samples (Lafargue et al.1998), (b) the plot of S1 vs. S2 and (c) TOC vs. S2/S3 for the black shale samples.

Figure 12

Figure 8. The plot of Pr/n-C17 vs. Ph/n-C18 of the black shale samples (Shanmugam, 1985).

Figure 13

Figure 9. The ternary diagram indicating the distribution of C27, C28, C29 ααα 20R steranes (modified from Huang and Meinschein, 1979, after Qiao et al.2021).

Figure 14

Figure 10 (a), (b). Inorganic geochemical and proxy profiles of the black shale samples.

Figure 15

Figure 11. Cross-plot of sulphur (TS) and V/(V+Ni) ratio, indicating highly marine reducing environmental conditions black shale samples (Bechtel et al.2001).

Figure 16

Figure 12. The plot of Tmax vs. PI shows hydrocarbon potential for the black shale samples.

Figure 17

Figure 13. The plots of biomarker parameters sensitive to the thermal maturity of the two black shale samples a) (a) C29 ααα 20S/(20S + 20R) vs. C29 ββ/(ββ + αα), (b) C31 homohopan S/(S+R) vs. C32 homohopan S/(S+R), (George et al.2001), c)20S(20S+20R) C29 sterane vs. C32 22S(22S+22R) homohopane (modified from Peters and Cassa, 1994, from Hakimi & Abdullah, 2014).

Figure 18

Figure 14. The plots of (a) TOC vs. HI (Zhang et al.,2021) and (b) TOC vs S1+S2 (Kostova et al.2022) show source rock characteristics for the black shale samples.

Figure 19

Figure 15. The plots of (a) TOC vs. RC and (b) TOC vs. PC show hydrocarbon potential for the black shale samples.

Figure 20

Figure 16. Schematic figure showing the organic matter accumulation and sedimentation model of Lutetian clastic rocks, (a) stage I, (b) stage II, (c), stage III.

Supplementary material: File

Saydam Eker supplementary material

Saydam Eker supplementary material
Download Saydam Eker supplementary material(File)
File 22.6 KB