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Article

Sedimentary Environment Reconstruction and Organic Matter Enrichment Mechanisms in Various Lithofacies of the Lacustrine Shale: A Case Study of the Da’anzhai Member, Central Sichuan Basin, China

by
Yuting Peng
1,2,*,
Yingxiao Fu
1,2,
Senran Chen
1,2 and
Enze Wang
3,4,5
1
School of Earth and Space Sciences, Peking University, Beijing 100871, China
2
Institute of Oil and Gas, Peking University, Beijing 100871, China
3
State Key Laboratory of Shale Oil and Gas Enrichment Mechanisms and Efficient Development, SINOPEC, Beijing 102206, China
4
Key Laboratory of Shale Oil/Gas Exploration and Production Technology, SINOPEC, Beijing 102206, China
5
Petroleum Exploration and Production Research Institute, SINOPEC, Beijing 102206, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2024, 14(22), 10192; https://doi.org/10.3390/app142210192
Submission received: 20 September 2024 / Revised: 22 October 2024 / Accepted: 28 October 2024 / Published: 6 November 2024
(This article belongs to the Special Issue The Exploration and Development of Unconventional Hydrocarbon Resources, 2nd Edition)
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Abstract

:
Jurassic lacustrine shale in the Sichuan Basin is a focal exploration area in China, while the pronounced heterogeneity presents challenges, necessitating detailed research as a prerequisite. This study aims at the Jurassic Ziliujing Formation Da’anzhai shale in the central Sichuan Basin, systematically characterizing its geological features. Employing geochemical methods, we reconstructed the paleo-sedimentary environments and explored the mechanisms behind the organic matter enrichment. The findings reveal that the Da’anzhai shale exhibits three lithofacies: organic-rich argillaceous shale (ORA), organic-poor argillaceous shale (OPA), and organic-rich mixed shale (ORM). The sedimentary period was marked by a warm and humid climate, predominantly depositing in anoxic environments with freshwater to brackish conditions. The watershed areas that are provenance sources for the shale clastics are experiencing strong weathering. Significant differences in the sedimentary environments of various lithofacies’ shale were observed. Redox conditions and paleoclimate were identified as the primary factors controlling organic matter enrichment in the Da’anzhai shale of the study area. Salinity also played a role in organic matter enrichment, while terrigenous debris influx and paleo-productivity did not exert a significant controlling effect on organic matter enrichment. Utilizing the reconstructed ancient sedimentary environments, we developed sedimentary models for different lithofacies’ shale, contributing to a deeper understanding of lithofacies’ diversity and the mechanisms governing organic matter enrichment in lacustrine environments. This study provides new information for further understanding the response mechanism of lacustrine shales to the Toarcian Oceanic Anoxic Event in the Early Jurassic from the perspective of elemental geochemistry.

1. Introduction

In recent years, notable strides have been made in the exploration of lacustrine shale in China, with positive advancements observed in various basins. These include the Paleogene Shahejie Formation in the Bohai Bay Basin, Permian Lucaogou Formation in the Junggar Basin, Cretaceous Qingshankou Formation in the Songliao Basin, and Jurassic Ziliujing Formation in the Sichuan Basin [1,2,3,4,5,6]. In contrast to the significant industrial achievements of marine facies Longmaxi Formation shale, lacustrine shale exhibits notable heterogeneity. Identifying favorable exploration targets for shale thus emerges as the primary challenge in the exploration and development of lacustrine shale [7,8,9,10].
To identify favorable exploration targets, previous researchers have proposed various methods. Wang et al. (2019) innovatively suggested a matching source kitchen, reservoir depositional facies, and other key factors in oil and gas exploration [11]. Ma et al. (2022) proposed that determining favorable exploration lithofacies is a primary task in lacustrine shale exploration [12]. Li et al. (2022) suggested that the selection of favorable exploration “sweet spots” should consider the combination of sedimentary lithofacies and organic lithofacies [13]. Among these methods, there is a strong emphasis on the significant role of lithofacies in determining sweet spots for shale oil. The differences in lithofacies reflect variations in sedimentary environments and geological characteristics of rocks [14]. Therefore, lithofacies division provides new insights for refined research. Revealing the sedimentary background of different lithofacies helps pinpoint favorable exploration targets, holding significant implications for improving exploration efficiency.
The exploration of Jurassic strata in the Sichuan Basin currently serves as a pivotal focus in lacustrine shale oil exploration in China. Within the Jurassic strata, three sets of organic-rich shale have been identified: the Lianggaoshan Formation, and the Da’anzhai and Dongyuemiao Members of the Ziliujing Formation [15,16,17,18]. Significant breakthroughs have been achieved in the Lianggaoshan Formation and Dongyuemiao Member [19,20,21]. However, substantial progress has yet to be made in the exploration of the Da’anzhai Member shale. Therefore, it is crucial to strengthen relevant geological research to provide theoretical guidance for exploration practices. In this study, we focus on the shale of the Da’anzhai Member in the central part of the Sichuan Basin, systematically characterizing its geological features, reconstructing the paleo-sedimentary environments of shale with different lithofacies through geochemical methods, and exploring the mechanisms of organic matter enrichment. The results of this study complement the geochemical characteristics of the Toarcian Oceanic Anoxic Event (also known as the Jenkyns Event), and contribute to a deeper understanding of the lithofacies diversity of lacustrine shale, enhancing our comprehension of the mechanisms governing organic matter enrichment in a lacustrine sedimentary system. Furthermore, our results provide a theoretical basis for the exploration of Jurassic lacustrine shale oil in the Sichuan Basin.

2. Geological Setting

The Sichuan Basin, one of the most significant oil and gas basins in the southwest of China, is situated in the northwestern part of the Yangtze Platform and extends towards the northwest. The basin is bordered by the Longmen Mountain Fold Belt to the northwest, the Daba Mountain Fold Belt to the northeast, the Qiyue Mountain Fold Belt to the southeast, and the E’mei Mountain Fold Belt to the southwest. According to the basement structure, the basin is composed of a northwest depression, central uplift, and southeast depression (Figure 1a) [22,23,24]. Covering the Ediacaran to middle Mesozoic passive margin, the Sichuan Basin was a Late Mesozoic–Cenozoic foreland basin, which has featured a complex history of tectonics and sedimentation. Since the Chengjiang tectonic movement (ca 700 Ma), the basin has subsequently experienced several significant tectonic episodes, including the Tongwan (ca 570 Ma), Caledonian (ca 439 Ma), Yunnan (ca 270 Ma), Dongwu (ca 256 Ma), Indosinian (ca 205–195 Ma), Yanshanian (ca 180–140 Ma), and Himalayan (ca 80–3 Ma) [23,25,26].
After the uplift of the Yangtze Plate in the Late Triassic, forming the foundation of the Sichuan Basin, the region entered a relatively stable stage of terrestrial basin sedimentation [27,28,29,30]. In the Early Jurassic, the Sichuan Basin was dominated by terrestrial sedimentary facies ranging from a shallow to deep lake, delta, alluvial fan, and alluvial plain [23,26]. Within the lake basin, from the center to the edge, three sub-facies developed in sequence: a deep to semi-deep lake, shallow lake, shell bank, delta, and fan delta (Figure 1a) [23,26,31]. Based on favorable temperature and depth conditions, the Jurassic of the Sichuan Basin is a primary source of shale oil resources [32,33,34].
Applsci 14 10192 g001
Figure 1. The paleogeographic map and stratigraphic column of the Early Jurassic in the Sichuan Basin, and location of the study area. (a) The paleogeographic map of the Early Jurassic in the Sichuan Basin (modified from [16,26,29]). (b) The stratigraphic column of the studied succession (modified from [6,26]).
Figure 1. The paleogeographic map and stratigraphic column of the Early Jurassic in the Sichuan Basin, and location of the study area. (a) The paleogeographic map of the Early Jurassic in the Sichuan Basin (modified from [16,26,29]). (b) The stratigraphic column of the studied succession (modified from [6,26]).
Applsci 14 10192 g001
In the Early Jurassic, the basin formed extensive lacustrine clastic deposits, among which the largest, most extensive, and largest in area was the Zhenba Formation’s Da’anzhai Member’s lacustrine transgression, which has significant potential for hydrocarbon generation. The Jurassic Zhenba Formation from bottom to top can be divided into four members, Zhenzhu Chong, Dongyue Temple, Ma’anshan, and Da’anzhai, which are overlain by the Middle Jurassic Qianfoya Formation. The Da’anzhai Member is 70 to 125 m long and can be further divided into lower, middle, and upper sub-members based on lithological composition, electrical properties, and sedimentary cyclothem characteristics (Figure 1b). The lower sub-member of Da’anzhai represents a shallow lacustrine facies formed during the expansion of lake transgression, characterized by thick-bedded shell limestone. The middle sub-member of Da’anzhai is a semi-deep lake sub-facies with the longest period of lake transgression, developing thick-bedded shale. The upper sub-member of Da’anzhai represents a shallow lacustrine environment formed during lake regression, characterized by the interbedding of thick shell limestone layers with medium to thin mudstone layers [21,35,36].

3. Materials and Methods

3.1. Materials

The samples utilized in this study originated from the core of the Jurassic Da’anzhai Member extracted from the CH60 drilling well in the study area of the Sichuan Basin, China (Figure 1a). A total of 36 well-preserved rock samples were meticulously collected, covering depths ranging from 2955.37 m to 3004.11 m. To ensure the precision of the results, the central segment of each core sample was employed for experimental analyses. The conducted experiments and tests encompassed the determination of total organic carbon (TOC) content, X-ray Diffraction (XRD) testing, and analyses of major and trace elements. All analytical procedures were meticulously carried out at Craton Technology Company in Beijing to maintain consistency and accuracy in the obtained results.

3.2. Experimental Methods

The mineral composition of the rock samples was primarily determined through XRD experiments. These analyses were conducted using an Ultima IV diffractometer manufactured by Rigaku from Japan, which operated on powdered samples (<200 mesh). The testing conditions were set as follows: Cu Kα radiation, 40 kV, 40 mA, with a scanning step width of 0.02°. Comprehensive whole-rock random-powder patterns were recorded within the range of 5 to 45° 2θ during the experiments.
For the precise determination of TOC content, a 12.5% hydrochloric acid solution was incrementally introduced to the samples, which had been reduced to 80 mesh, to eliminate carbonate minerals. The samples were held at 60 °C for over 2 h to ensure that the reaction came to a halt. Subsequently, the samples underwent a gradual rinsing with distilled water until the acidic solution was thoroughly removed, after which they were dried. The TOC content was quantified using a CS-844 analyzer manufactured by Leco from the United States.
In addition to XRD experiments, powdered samples (less than 200 mesh) were employed for major and trace element testing. Major elements were analyzed using an Axios-MAX wavelength-dispersive X-ray fluorescence (XRF) spectrometer manufactured by Rigaku from Japan, with an analytical precision better than 5%. Trace element concentrations were determined using an 7900 inductively coupled plasma mass spectrometer (ICP-MS) manufactured by Agilent from the United States.

3.3. Geochemical Indicators for Identifying Paleoenvironments

The calculation of element enrichment factors (EFs) serves as a method for estimating the degree of authigenic element enrichment, providing valuable insights into the reconstruction of environmental redox conditions. The enrichment factor of an element is determined by the following equation:
E F X = ( X / A l ) s a m p l e / ( X / A l ) P A A S
In the equation, X and Al represent the concentrations of element X and aluminum (Al), respectively, and PAAS denotes the post-Archean Australian shale content of each element [37]. An EF equal to 1 indicates non-enrichment, a value typical of PAAS. EFs exceeding 3 are interpreted as detectable enrichment compared to PAAS, while EFs less than 1 signify depleted concentrations [38].
Various elements exhibit different rates of accumulation under distinct chemical weathering conditions. The Chemical Index of Alteration (CIA) is employed to quantitatively assess the weathering history of the source area recorded by sediments [39] and is calculated according to Equation (2):
C I A = [ ( A l 2 O 3 ) / ( A l 2 O 3 + N a 2 O + K 2 O + C a O * ) ]
In the equation, CaO* represents the CaO content of silicate minerals [40]. CaO* can be determined using Equations (3) and (4) [41]. The Al2O3, Na2O, and K2O denote the contents of the respective compounds in the samples.
C a O # = C a O − 10 × P 2 O 5 / 3  
C a O * = N a 2 O ,   C a O # > N a 2 O C a O # ,   C a O # < N a 2 O
where P2O5 is the content of the P2O5 in samples.

4. Results

4.1. Mineral Composition, TOC Content, and Lithofacies Classification

The mineral composition of the Da’anzhai Member in the study area is depicted in Table 1 and Figure 2. Predominantly, clay minerals constitute the mineral composition, with a distribution range of 36.8% to 74.7% (mean of 58.1%). Siliceous minerals follow, with a content range of 20.0% to 46.8% (mean of 32.6%). Quartz is the primary siliceous mineral, with a distribution range of 11.7% to 39.1% (mean of 28.6%). Feldspar content is relatively low, ranging from 1.6% to 8.3% (mean of 4.4%), predominantly composed of plagioclase, while potassium feldspar generally constitutes less than 1%. Carbonate minerals have the lowest content, ranging from 0% to 24.7% (mean of 7.7%), primarily dominated by calcite (mean of 7.3%), with low levels of dolomite and siderite. Simultaneously, the samples exhibit generally low levels of pyrite, ranging from trace amounts (less than 0.5%) to 3.9%, with a mean of 1.5%. The TOC content in the Da’anzhai Member samples from the study area has a distribution range of 0.4% to 2.3%, with a mean of 1.1%.
Lithofacies serve as indicators reflecting sedimentary environments and rock geological characteristics [14], providing a reliable basis for detailed shale studies [5,13]. Shale, defined as fine-grained sedimentary rocks with a grain size of <0.0039 mm [13,20,42], has been a subject of study since early times, but its investigation is still in the initial stages [43,44], lacking a uniform standard. In this study, we refer to prior research outcomes and primarily conduct lithofacies division based on two criteria: mineral composition and organic matter content [12,13]. It is crucial to note that we adjusted the criteria for determining TOC content. In a previous study [5], TOC content greater than 2% was considered as organic-rich shale. However, their focus was on marine Longmaxi Formation shale, which generally exhibits high TOC content. In this paper, we set TOC = 1% as the threshold for determining shale organic matter content. When TOC content exceeds 1%, the sample is classified as organic-rich shale, and when TOC content is below 1%, the sample falls into the category of organic-poor shale. Considering the geological characteristics outlined above, three types of lithofacies are identified in the study area: organic-rich argillaceous shale (ORA), organic-poor argillaceous shale (OPA), and organic-rich mixed shale (ORM) (Table 1, Figure 2 and Figure 3).

4.2. Major and Trace Elements

As shown in Table 2, the major compound with the highest content is SiO2, ranging from 17.27% to 60.96%, with an approximate mean of 53%. Following SiO2 is Al2O3, with a distribution range of 3.59% to 25.58% and an approximate mean of 20%. MgO, K2O, and Fe2O3 exhibit relatively high contents, generally exceeding 1%. Na2O, P2O5, TiO2, and MnO have very low contents, all less than 1%. It is noteworthy that the content of CaO varies significantly among the samples, ranging from 0.57% to 41.47%, with a mean of 4%.
Trace elements characterizing redox conditions (Table 3), such as Mo, show relatively small variations, ranging from 0.37 to 1.44 ppm (average value = 0.9 ppm). Elements associated with paleo-productivity, including Ni, Cu, and Zn, also exhibit relatively stable concentrations. The content of Ni ranges from 40.98 to 60.17 ppm (average value = 51 ppm), Cu ranges from 29.38 to 49.95 ppm (average value = 41 ppm), and Zn ranges from 76.68 to 163.70 ppm (average value = 123 ppm). Additionally, the distribution ranges of elements V, Cr, Co, Sr, Ba, U, and Th are as follows: 124.87 to 199.38 ppm (average value = 163 ppm), 65.22 to 117.76 ppm (average value = 94 ppm), 13.59 to 25.74 ppm (average value = 18 ppm), 122.15 to 200.72 ppm (average value = 157 ppm), 482.93 to 953.21 ppm (average value = 744 ppm), 1.47 to 3.34 ppm (average value = 2 ppm), and 8.47 to 18.27 ppm (average value = 13 ppm), respectively.

5. Discussion

5.1. Paleoenvironment Reconstruction

5.1.1. Paleoclimate and Weathering

Paleoclimate and weathering conditions play a significant role in influencing the influx of terrigenous debris, salinity conditions, and redox conditions [45]. In this study, two proxies were employed to characterize paleoclimate and weathering conditions (Table 4, Figure 4). Fe/Mn was selected as a proxy for paleoclimate, while the CIA was used for a quantitative description of weathering conditions. CIA values of 80–100, 70–80, and 50–70 reflect strong, moderate, and weak degrees of chemical weathering in sediment source regions, respectively [5]. Simultaneously, under different climatic conditions, Fe and Mn elements display different enrichment tendencies. Hot and dry climatic conditions lead to increased evaporation from lakes, resulting in Mn enrichment of lacustrine deposits. Conversely, a humid environment leads to Fe concentrations in contemporaneous sediments in the form of Fe(OH)3. Elevated Fe/Mn ratios indicate warm and humid climatic conditions [16,23]. The CIA values for the Da’anzhai Member shale in the study area range from 61.8 to 84.1 (average: 77.6), with average values of 75.9, 78.1, and 78.9 for ORA, OPA, and ORM, respectively. This indicates that the basins of detrital sources in the three lithofacies are undergoing moderate weathering, and there is no significant difference in weathering conditions among the different lithofacies. Simultaneously, the Fe/Mn ratio in the Da’anzhai Member shale in the study area ranges from 4.6 to 242.7, with an average of 116.1. The Fe/Mn ratio in this study is similar to that reported by Wang et al. (2023), indicating a similar paleoclimate condition [16]. However, there are significant differences in the Fe/Mn ratio among different lithofacies shales. In general, ORM has the highest Fe/Mn ratio (average of 148.5), followed by OPA (average of 133.7), and ORA has the lowest Fe/Mn ratio (average of 90.4), indicating different paleoclimate conditions for the formation of different lithofacies. The climate during the formation of ORM was the most humid, followed by OPA, and the environment during the formation of ORA was the most arid. Generally, a certain correlation is expected between weathering conditions and paleoclimate, with a wet paleoclimate often associated with strong weathering conditions. However, in this study, Fe/Mn ratios and CIA values do not exhibit a clear correlation (Figure 5). Similar patterns were reported in the studies by Liu et al. (2022) and Wang et al. (2023) on the Da’anzhai Member in the Sichuan Basin, suggesting that weathering processes may not have a significant impact on the input of raw materials at a basin scale [16,46]. In summary, the Da’anzhai Member shale in the study area was deposited in a warm and humid environment, and the watershed of the shale clastics source was undergoing strong weathering. While examining different lithofacies, it becomes evident that weathering processes do not exhibit significant differences, whereas notable distinctions emerge in paleoclimate conditions.

5.1.2. Redox Condition

Redox conditions, a pivotal factor influencing organic matter enrichment, play a crucial role in reconstructing paleo-sedimentary environments [47]. Certain elements, sensitive to the oxygen content in the water column, serve as reliable proxies for characterizing the redox condition, with redox-sensitive trace elements such as Mo and U being noteworthy examples. Additionally, certain ratios of redox-sensitive trace elements, such as V/Cr and Ni/Co, offer insights into the redox environment in the water column [48]. The redox-sensitive trace element ratios for the Da’anzhai Member shale in the study area are illustrated in Figure 6 and Table 4. Results indicate that the Da’anzhai Member primarily deposited in an anoxic environment, with no significant differences in redox conditions observed among different lithofacies. Based on the content and ratios of redox-sensitive elements, the Da’anzhai Member shale in the study area is determined to have deposited in an oxic environment. Furthermore, Algeo and Ingall (2007) proposed that under anoxic conditions, the reductive dissolution of Fe oxyhydroxides can release phosphorus (P) from marine sediments [49]. Therefore, a high Corg/P ratio can reflect a relatively reducing environment. Generally, Corg/P values less than 50, 50 to 100, and more than 100 reflect oxic, suboxic, and anoxic depositional environments, respectively [50]. The Corg/P ratio for the Da’anzhai Member shale in the study area varies from 7.31 to 126.17 (average = 48.6). It is noteworthy that there are differences in the Corg/P ratio among different lithofacies. The distribution ranges of the Corg/P ratio for ORA, ORM, and OPA are 28.9 to 122.2 (average = 65.2), 19.1 to 92.3 (average = 48.5), and 17.2 to 64.1 (average = 35.6), respectively. The Corg/P ratio indicates that the Da’anzhai Member shale in the study area primarily deposited in an anoxic environment, with ORA and ORM depositing in relatively reducing conditions. However, it is essential to note that the results from the Corg/P ratio and the content (ratios) of redox-sensitive elements slightly differ. Considering both the present study and previous research, we conclude that the Da’anzhai Member shale mainly deposited in an anoxic environment.

5.1.3. Salinity

Salinity is a key determinant influencing the paleoenvironmental and paleoecological characteristics of lacustrine systems [45]. The solubility of Sr and Ba varies under different salinity conditions, making the Sr/Ba ratio a valuable proxy for discerning the salinity conditions within a lake’s water column. Sr/Ba ratios below 0.2, between 0.2 and 0.5, and >0.5 typically indicate freshwater, brackish, and marine environments, respectively [51]. It should be noted that the Sr/Ba ratio may not serve as an accurate salinity proxy for samples containing more than 4% CaO because Sr can replace Ca2+ in the CaCO3 lattice [23]. The Sr/Ba ratio for the Da’anzhai Member shale in the study area ranges from 0.13 to 0.29, with an average of 0.20. Considering different lithofacies, the Sr/Ba ratio for ORA (average: 0.19) is slightly lower than OPA (average: 0.21). It is crucial to note that some ORM samples have higher CaO content, and as a result, ORM lacks Sr/Ba ratio data. In addition, under a microscope, it was observed that all three lithofacies contain bivalve debris shaped like elongated shell valves (Figure 7). The bivalves are adapted to freshwater–brackish water conditions, which further supplements the interpretation that the shale of the Da’anzhai Member in the study area was primarily deposited in a freshwater–brackish environment.

5.1.4. Terrigenous Debris Influx and Primary Productivity

In lacustrine sedimentation, the influx of terrigenous debris significantly influences both organic matter enrichment and mineral composition. Aluminum (Al) primarily accumulates in clay, feldspar, and other aluminosilicate minerals. Al is highly stable and remains unaffected by diagenesis [52], making it a reliable proxy for characterizing the input of terrigenous debris. In the study area, the Al content of the Da’anzhai Member shale ranges from 1.9 to 13.5% (average = 10.4%). There are notable differences in Al content among different lithofacies, with argillaceous shale exhibiting higher Al content (the average contents of ORA and OPA are 10.7% and 10.9%, respectively) compared to mixed shale (the average content of ORM is 9.2%), indicating a higher input of terrigenous debris in argillaceous shale.
Primary productivity is a crucial factor determining organic matter enrichment and is also a critical aspect in reconstructing paleo-sedimentary environments. The basic nutrients of the biogeochemical cycle are linked to primary producers and production processes. The contents of related elements such as Cu, Ni, and Si are commonly used to assess the strength of primary productivity in lucustrine sediments [52,53]. In this study, we chose to use (Ni + Cu + Zn) as an indicator of paleo-productivity. The (Ni + Cu + Zn) content in the Da’anzhai Member shale of the study area varies from 32.6 to 255.6 ppm, with an average of 206.2 ppm. From the perspective of different lithofacies, the (Ni + Cu + Zn) values exhibit a pattern similar to Al content, with argillaceous shale having higher (Ni + Cu + Zn) values than mixed shale. Generally, in transitional sedimentary systems from continental to marine, there is often a positive correlation between terrigenous debris input and paleo-productivity [52,53]. Figure 8 delineates the association between terrigenous debris input and paleo-productivity within the Da’anzhai Member. The findings reveal a positive correlation between terrigenous debris input and proxies signifying paleo-productivity, indicating that terrestrial organic matter, accompanied by related nutrients, played a pivotal role in fostering paleo-productivity. To mitigate the influence of terrigenous debris on paleo-productivity assessment, we adopted the (Ni + Cu + Zn)/Al ratio as a proxy to quantify the original primary productivity in the water column. The (Ni + Cu + Zn)/Al ratio in the Da’anzhai Member shale ranges from 0.0015 to 0.0024, with an average value of 0.0020. Remarkably, negligible variation exists in the (Ni + Cu + Zn)/Al ratio among shale samples from different lithofacies, suggesting that the original primary productivity in the water column exhibited minimal divergence during the formation of distinct lithofacies.

5.2. Organic Matter Enrichment Mechanisms and Depositional Models of Various Lithofacies

To unravel the mechanisms behind organic matter enrichment, Figure 9 presents a correlation analysis between proxies representing various paleoenvironments and TOC content in the study area. Proxies for paleoclimate, such as the Fe/Mn ratio, and redox condition indicators (MoEF and Corg/P) exhibit a robust correlation with TOC content. This suggests that a humid paleoclimate and a relatively reducing ancient sedimentary environment are pivotal factors influencing the enrichment of organic matter. According to previous studies, the deposition period of the Da’anzhai Member shale aligns with the Toarcian Oceanic Anoxic Event (also known as the Jenkyns Event), which was a globally significant geological event in the Early Jurassic and occurred about 183.8 million years ago [46,54,55,56]. It is plausible that the T-OAE, marked by the release of a substantial volume of CO2 from the Karoo-Ferrar Large Igneous Province, led to a rapid rise in global temperatures, which had a profound impact on the global climate system [57,58]. This event is linked to worldwide environmental transformations, encompassing the widespread development of anoxia, significant disturbances in the global carbon cycle, and the decline in marine fauna biodiversity [59,60,61,62]. Consequently, T-OAE emerges as a crucial factor contributing to the alterations in paleoclimate and redox conditions in the Da’anzhai Member.
Simultaneously, the proxy for paleosalinity (Sr/Ba ratio) exhibits a discernible negative correlation with TOC content. In certain terrestrial shale sequences, a positive correlation between the Sr/Ba ratio and TOC content has been observed, as exemplified in the Nanpu sag of the Bohai Bay Basin and the Luchagou Formation of the Santanghu Basin [63,64]. This positive correlation is typically attributed to higher salinity inducing water column stratification, fostering a reducing environment at the water’s bottom, and facilitating the preservation of deposited organic matter. However, in this study, a negative correlation is observed between the Sr/Ba ratio and TOC content. This deviation may arise from the Da’anzhai Member primarily depositing in a freshwater to brackish environment, where such salinity conditions may not induce significant water column stratification and the formation of anoxic environments. Instead, salinity likely represents the paleo-depth of the lake in this study. Under conditions of high paleo-depth, weaker evaporation results in lower basin salinity. A higher paleo-depth also creates a relatively reducing environment at the lake bottom, leading to the observed negative correlation between the Sr/Ba ratio and TOC content. Similar phenomena have been reported in previous studies [16,17]. Proxies representing terrigenous debris input (Al content), paleo-productivity ((Ni + Cu + Zn)), and water column original primary productivity ((Ni + Cu + Zn)/Al) show no significant correlation with TOC content in the study area. As mentioned earlier, the increase in terrigenous debris influx promotes the development of paleo-productivity. However, the enhancement of terrigenous debris input also has a negative impact on organic matter enrichment. High terrigenous debris input can disrupt the redox conditions in the water column, leading to changes in the relatively reducing environment and preventing the well-preserved formation of organic matter. Similarly to Al content, the increase in paleo-productivity accompanies the increase in terrigenous debris input; therefore, it does not lead to the organic matter enrichment. Meanwhile, the lack of correlation between the proxy for original primary productivity and TOC content indicates that paleo-productivity is not the primary factor for organic matter enrichment in the Da’anzhai Member shale.
Building upon the outcomes of paleoenvironmental reconstruction, we delve into the sedimentary patterns of shale within distinct lithofacies in the study area (Figure 10). The sedimentary environments of ORA and ORM appear to be relatively similar, both indicative of deposition under warm and humid conditions. This climatic setting aligns with the occurrence of the Toarcian Oceanic Anoxic Event (T-OAE), characterized by a global temperature rise and heightened greenhouse effects leading to increased rainfall [46,54,55,56]. During this period, the paleo-depth of the lake likely remained relatively high, resulting in low water salinity and fostering a relatively reducing sedimentary environment at the lake bottom. The conducive conditions facilitated the preservation of organic matter beneath the water, ultimately forming organic-rich shale. The primary distinction in the sedimentary environment between ORA and ORM lies in the magnitude of terrigenous debris input. In comparison to ORM, ORA exhibits a higher influx of terrigenous debris, introducing a greater amount of clay minerals and contributing to the distinctive characteristics observed in ORA.
OPA predominantly originated in a hot and arid environment, characterized by a relatively shallow paleo-depth of the lake and comparatively higher salinity [36,65]. However, these conditions were not adequate to induce distinct water column stratification. Furthermore, the low paleo-depth failed to generate a relatively reducing environment at the lake bottom. Despite the substantial influx of terrigenous debris, which heightened paleo-productivity to some extent, it also interfered with the original redox condition of the water, impeding the efficient preservation of the formed organic matter. This interference primarily contributed to the formation of OPA.

6. Conclusions

This study focuses on the Jurassic Ziliujing Formation Da’anzhai Member shale in the central part of the Sichuan Basin, systematically characterizing its geological features. Through the application of geochemical methods, we aimed to reconstruct the paleo-depositional environment of shale with different lithofacies and explore the mechanisms of organic matter enrichment. The key findings and conclusions derived from this investigation are outlined below.
The Da’anzhai Member shale in the study area exhibits a distribution of total organic carbon content ranging from 0.4% to 2.3%, with a mean value of 1.1%. The predominant mineral component is clay minerals, followed by siliceous minerals, with carbonate minerals showing the lowest content. Through the analysis of mineral composition and organic matter content, three lithofacies types are distinguished in the Da’anzhai Member shale in the study area: organic-rich argillaceous shale, organic-rich mixed shale, and organic-poor argillaceous shale.
Utilizing geochemical methods, the paleo-depositional environment of the Da’anzhai Member shale in the study area has been effectively reconstructed. The sedimentation period of the Da’anzhai Member was characterized by a warm and humid climate, coupled with moderate to strong weathering conditions in the watershed of the shale clastics source. The primary deposition occurred in an oxygenated environment with freshwater to brackish conditions. The distinctions in sedimentary environments among shale lithofacies are primarily manifested in paleoclimate, redox conditions, terrestrial debris influx, and salinity.
Integrating proxies for paleo-depositional environments with a TOC content analysis, it becomes evident that redox conditions and paleoclimate are the predominant factors influencing organic matter enrichment in the Da’anzhai Member shale in the study area. Salinity, albeit to a lesser extent, also contributes to organic matter enrichment, whereas the input of terrestrial debris and paleo-productivity does not exhibit significant control over organic matter enrichment.

Author Contributions

Writing—original draft, formal analysis, investigation, and data curation, Y.P.; Writing—review and editing, software and visualization, Y.F.; Writing—review and editing, methodology and validation, S.C.; Conceptualization, methodology and funding acquisition, E.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the open fund from the State Key Laboratory of Shale Oil and Gas Enrichment Mechanism and Effective Development of SINOPEC (33550000-22-ZC0613-0337).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

Author Enze Wang was employed by the company China Petroleum & Chemical Corporation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The funder had no role in the design of the study; in the collection, analysis, or interpretation of data, in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

ORAOrganic-rich argillaceous shale
OPAOrganic-poor argillaceous shale
ORMOrganic-rich mixed shale
TOCTotal organic carbon
XRDX-ray Diffraction
XRFX-ray fluorescence
ICP-MSInductively coupled plasma mass spectrometer
EFsEnrichment factors
PAASPost-Archean Australian shale content
CIAChemical Index of Alteration
T-OAEToarcian Oceanic Anoxic Event

References

  1. Guo, T. Key controls on accumulation and high production of large non-marine gas fields in northern Sichuan Basin. Petrol. Explor. Dev. 2013, 40, 139–149. [Google Scholar] [CrossRef]
  2. Hu, T.; Pang, X.; Jiang, S.; Wang, Q.; Zheng, X.; Ding, X.; Zhao, Y.; Zhu, C.; Li, H. Oil content evaluation of lacustrine organic-rich shale with strong heterogeneity: A case study of the Middle Permian Lucaogou Formation in Jimusaer Sag, Junggar Basin, NW China. Fuel 2018, 221, 196–205. [Google Scholar] [CrossRef]
  3. Li, C.; Pang, X.; Huo, Z.; Wang, E.; Xue, N. A revised method for reconstructing the hydrocarbon generation and expulsion history and evaluating the hydrocarbon resource potential: Example from the first member of the Qingshankou Formation in the Northern Songliao Basin, Northeast China. Mar. Pet. Geol. 2020, 121, 104577. [Google Scholar] [CrossRef]
  4. Liu, B.; Sun, J.; Zhang, Y.Q.; He, J.; Fu, X.; Yang, L.; Xing, J.; Zhao, X. Reservoir space and enrichment model of shale oil in the first member of Cretaceous Qingshankou Formation in the Changling Sag, southern Songliao Basin, NE China. Petrol. Explor. Dev. 2021, 48, 608–624. [Google Scholar] [CrossRef]
  5. Wang, E.; Feng, Y.; Guo, T.; Li, M. Oil content and resource quality evaluation methods for lacustrine shale: A review and a novel three-dimensional quality evaluation model. Earth-Sci. Rev. 2022, 232, 104134. [Google Scholar] [CrossRef]
  6. Hu, Z.; Liu, Z.; Li, Q.; Wu, Z. Exploring source rock-reservoir coupling mechanisms in lacustrine shales based on varying-scale lithofacies assemblages: A case study of the Jurassic shale intervals in the Sichuan Basin. Oil Gas Geol. 2024, 45, 893–909, (In Chinese with English abstract). [Google Scholar]
  7. Zou, C.; Dong, D.; Wang, Y.; Li, X.; Huang, J.; Wang, S.; Guan, Q.; Zhang, C.; Wang, H.; Liu, H.; et al. Shale gas in China: Characteristics, challenges and prospects (II). Petrol. Explor. Dev. 2016, 43, 166–178. [Google Scholar] [CrossRef]
  8. Guo, X.; Hu, D.; Li, Y.; Wei, Z.; Wei, X.; Liu, Z. Geological factors controlling shale gas enrichment and high production in Fuling shale gas field. Petrol. Explor. Dev. 2017, 44, 481–491. [Google Scholar] [CrossRef]
  9. Feng, Y.; Xiao, X.; Gao, P.; Wang, E.; Hu, D.; Liu, R.; Li, G.; Lu, C. Restoration of sedimentary environment and geochemical features of deep marine Longmaxi shale and its significance for shale gas: A case study of the Dingshan area in the Sichuan Basin, South China. Mar. Pet. Geol. 2023, 151, 106186. [Google Scholar] [CrossRef]
  10. Feng, Y.; Xiao, X.; Wang, E.; Gao, P.; Lu, C.; Li, G.; Wang, Z.; Zhou, Q. Origins of Siliceous Minerals and Their Influences on Organic Matter Enrichment and Reservoir Physical Properties of Deep Marine Shale in the Sichuan Basin, South China. Energy Fuels 2023, 37, 11982–11995. [Google Scholar] [CrossRef]
  11. Wang, W.; Pang, X.; Chen, Z.; Chen, D.; Zheng, T.; Luo, B.; Li, J.; Yu, R. Quantitative prediction of oil and gas prospects of the Sinian-Lower Paleozoic in the Sichuan Basin in central China. Energy 2019, 174, 861–872. [Google Scholar] [CrossRef]
  12. Ma, Y.; Cai, X.; Zhao, P.; Hu, Z.; Liu, H.; Gao, B.; Wang, W.; Li, Z.; Zhang, Z. Geological characteristics and exploration practices of continental shale oil in China. Acta Geol. Sin. 2022, 96, 155–171, (In Chinese with English abstract). [Google Scholar]
  13. Li, M.; Ma, X.; Jin, Z.; Li, Z.; Jiang, Q.; Wu, S.; Li, Z.; Xu, Z. Diversity in the lithofacies assemblages of marine and lacustrine shale strata and significance for unconventional petroleum exploration in China. Oil Gas. Geol. 2022, 43, 1–25, (In Chinese with English abstract). [Google Scholar]
  14. Dapples, E.C.; Krumbein, W.C.; Sloss, L.L. Tectonic control of lithofacies associations. AAPG (Am. Assoc. Pet. Geol.) Bull. 1948, 32, 1924–1947. [Google Scholar]
  15. He, W.; Bai, X.; Meng, Q.; Li, J.; Zhang, D.; Wang, Y.Z. Accumulation geological characteristics and major discoveries of lucustrine shale oil in Sichuan Basin. Acta Pet. Sin. 2022, 43, 885–898, (In Chinese with English abstract). [Google Scholar]
  16. Wang, E.; Feng, Y.; Guo, T.; Li, M.; Xiong, L.; Lash, G.G.; Dong, X.; Wang, T.; Ouyang, J. Sedimentary differentiation triggered by the Toarcian Oceanic Anoxic Event and formation of lacustrine shale oil reservoirs: Organic matter accumulation and pore system evolution of the Early Jurassic sedimentary succession, Sichuan Basin, China. J. Asian Earth. Sci. 2023, 256, 105825. [Google Scholar] [CrossRef]
  17. Wang, E.; Fu, Y.; Guo, T.; Li, M. A new approach for predicting oil mobilities and unveiling their controlling factors in a lacustrine shale system: Insights from interpretable machine learning model. Fuel 2025, 379, 132958. [Google Scholar] [CrossRef]
  18. Fang, R.; Jiang, Y.; Yang, C.; Deng, H.; Jiang, C.; Hong, H.; Tang, S.; Gu, Y.; Zhu, X.; Sun, S.; et al. Occurrence states and mobility of shale oil in different lithologic assemblages in the Jurassic Lianggaoshan Formation, Sichuan Basin. Oil Gas Geol. 2024, 45, 752–769, (In Chinese with English abstract). [Google Scholar]
  19. Guo, X.; Wei, Z.; Wei, X.; Liu, Z.; Chen, C.; Wang, D. Enrichment conditions and exploration direction of Jurassic continental shale oil and gas in Sichuan Basin. Acta Pet. Sin. 2023, 44, 14–27, (In Chinese with English abstract). [Google Scholar]
  20. Wang, E.; Li, M.; Ma, X.; Qian, M.; Cao, T.; Li, Z.; Yang, W.; Jin, Z. Diahopane and diasterane as the proxies for paleoenvironment, hydrocarbon generation condition, and shale oil accumulation. Chem. Geol. 2024, 670, 122447. [Google Scholar] [CrossRef]
  21. Yang, Y.; Wen, L.; Wang, X.; Hong, H.; Zhu, H.; Xiong, Y.; Li, M.; Lu, J.; Ceng, D.; Yang, W. Geological characteristics and favorable exploration area selection of shale oil and gas of the Lower Jurassic Da’anzhai Member in the Sichuan Basin. Nat. Gas Ind. 2023, 43, 32–42, (In Chinese with English abstract). [Google Scholar]
  22. He, J.; Jian, W.; Harald, M.; Qiu, Z.; Yu, Q. The characteristics and formation mechanism of a regional fault in shale strata: Insights from the Middle-Upper Yangtze, China. Mar. Pet. Geol. 2020, 121, 104592. [Google Scholar] [CrossRef]
  23. Qiu, Z.; He, J.L. Depositional environment changes and organic matter accumulation of Pliensbachian-Toarcian lacustrine shales in the Sichuan basin, SW China. J. Asian Earth Sci. 2022, 232, 105035. [Google Scholar] [CrossRef]
  24. Kong, X.; Zeng, J.; Luo, Q.; Tan, J.; Zhang, R.; Wang, X.; Wang, Q.Y. Controls of Continental Shale Lithofacies on Pore Structure of Jurassic Da’anzhai Member in Central Sichuan Basin. Xinjiang Pet. Geol. 2023, 44, 392–403, (In Chinese with English abstract). [Google Scholar]
  25. Liu, Y.; Qiu, N.; Xie, Z.; Yao, Q.; Zhu, C. Overpressure compartments in the central paleo-uplift, Sichuan Basin, southwest China. AAPG Bull. 2016, 100, 867–888. [Google Scholar] [CrossRef]
  26. Habulashenmu, Y.; Wang, X.; Qiu, L.; Yang, Y.; Chen, S.; Khan, D.; Teng, J.; Hu, Y. Lithofacies characteristics and genetic mechanism of hybrid sedimentary rocks in Da’anzhai member, Sichuan Basin. Mar. Pet. Geol. 2024, 162, 106695. [Google Scholar] [CrossRef]
  27. Li, D.; Xia, Y.; Xu, L. Coupling and formation mechanism of continental intraplate basin and orogen-Examples from the Qinghai-Tibet Plateau and adjacent basins. Earth Sci. Front. 2009, 16, 110–119. [Google Scholar] [CrossRef]
  28. Li, Y.; He, D.; Chen, L.; Mei, Q.; Li, C.; Zhang, L. Cretaceous sedimentary basins in Sichuan, SW China: Restoration of tectonic and depositional environments. Cretac. Res. 2016, 57, 50–65. [Google Scholar] [CrossRef]
  29. Li, Y.; Li, S.; He, D.; Gao, J.; Wang, Y.; Huang, H.; Zhang, J.; Zhang, Y. Middle Triassic tectono-sedimentary development of Sichuan Basin: Insights into the cratonic differentiation. Geol. J. 2021, 56, 1858–1878. [Google Scholar] [CrossRef]
  30. Wang, X.; Yang, Z.; Han, B. Superposed evolution of Sichuan Basin and its petroleum accumulation. Earth Sci. Front. 2015, 22, 161–173. [Google Scholar]
  31. Yang, Y.; Huang, D. Geological characteristics and new understandings of exploration and development of Jurassic lacustrine shale oil and gas in the Sichuan Basin. Nat. Gas Ind. 2019, 39, 22–33. [Google Scholar]
  32. Chen, S.; Zhang, H.; Lu, J.; Yang, Y.; Liu, C.; Wang, L.; Zou, X.; Yang, J.; Tang, H.; Yao, Y.; et al. Controlling factors of Jurassic Da’anzhai Member tight oil accumulation and high production in central Sichuan Basin, SW China. Petrol. Explor. Dev. 2015, 42, 206–214. [Google Scholar] [CrossRef]
  33. Su, K.; Lu, J.; Zhang, G.; Chen, S.; Li, Y.; Xiao, Z.; Wang, P.; Qiu, W. Origin of natural gas in Jurassic Da’anzhai member in the western part of central Sichuan basin, China. J. Pet. Sci. Eng. 2018, 167, 890–899. [Google Scholar] [CrossRef]
  34. Hu, Z.; Wang, R.; Liu, Z. Source-reservoir characteristics and coupling evaluations for the Lower Jurassic lacustrine shale gas reservoir in the Sichuan basin. Earth Sci. Front. 2021, 28, 261–272, (In Chinese with English abstract). [Google Scholar]
  35. Guo, Y.; Zeng, D.; Zhang, R.; Wang, X.; Huang, D.; Zhang, B.; Xie, S. Paleoenvironment and Its Petroleum Geological Significance of the Jurassic Da’anzhai Member in the Central-Eastern Sichuan Basin. Acta Sedimentol. Sin. 2023, 42, 1016–1031, (In Chinese with English abstract). [Google Scholar]
  36. Zou, C.; Yang, Z.; Wang, H.; Dong, D.; Liu, H.; Shi, Z.; Zhang, B.; Sun, S.; Liu, D.; Li, G.; et al. “Exploring petroleum inside source kitchen”: Jurassic unconventional continental giant shale oil & gas field in Sichuan Basin, China. Acta Geol. Sin. 2019, 93, 1551–1562, (In Chinese with English abstract). [Google Scholar]
  37. Taylor, S.R.; McLennan, S.M. The Continental Crust: Its Composition and Evolution; Blackwell: Oxford, UK, 1985; 312p. [Google Scholar]
  38. Tribovillard, N.; Algeo, T.J.; Baudin, F.; Riboulleau, A.J.C.G. Analysis of marine environmental conditions based onmolybdenum–uranium covariation—Applications to Mesozoic paleoceanography. Chem. Geol. 2012, 324, 46–58. [Google Scholar] [CrossRef]
  39. Minyuk, P.S.; Brigham–Grette, J.; Melles, M.; Borkhodoev, V.Y.; Glushkova, O.Y. Inorganic geochemistry of El’gygytgyn Lake sediments (northeastern Russia) as an indicator of paleoclimatic change for the last 250 kyr. J. Paleolimnol. 2007, 37, 123–133. [Google Scholar] [CrossRef]
  40. Nesbitt, H.W.; Young, G.M. Early Proterozoic climates and plate motions inferred from major element chemistry of lutites. Nature 1982, 299, 715–717. [Google Scholar] [CrossRef]
  41. McLennan, S.M.; Hemming, S.; McDaniel, D.K.; Hanson, G.N. Geochemical approaches to sedimentation, provenance, and tectonics. Geol. Soc. Am. Spec. Pap. 1993, 284, 21–40. [Google Scholar]
  42. Zou, C.N.; Zhang, G.; Yang, Z.; Tao, S.; Hou, L.; Zhu, R.; Yuan, X.; Ran, Q.; Li, D.; Wang, Z. Geological concepts, characteristics, resource potential and key techniques of unconventional hydrocarbon: On unconventional petroleum geology. Petrol. Explor. Dev. 2013, 40, 385–399. [Google Scholar] [CrossRef]
  43. Loucks, R.G.; Ruppel, S.C. Mississippian Barnett Shale: Lithofacies and depositional setting of a deep-water shale-gas succession in the Fort Worth Basin, Texas. AAPG (Am. Assoc. Pet. Geol.) Bull. 2007, 91, 579–601. [Google Scholar] [CrossRef]
  44. Gamero-Diaz, H.; Miller, C.; Lewis, R.E. sCore: A mineralogy based classification scheme for organic mudstones. In Proceedings of the SPE Annual Technical Conference, New Orleans, LA, USA, 30 September–2 October 2013. [Google Scholar]
  45. Wu, Z.; Zhao, X.; Wang, E.; Pu, X.; Lash, G.; Han, W.; Zhang, W.; Feng, Y. Sedimentary environment and organic enrichment mechanisms of lacustrine shale: A case study of the Paleogene Shahejie Formation, Qikou Sag, Bohai Bay Basin. Palaeogeogr. Palaeoclimatol. Palaeoecol. 2021, 573, 110404. [Google Scholar] [CrossRef]
  46. Liu, J.; Cao, J.; He, T.; Liang, F.; Pu, J.; Wang, Y. Lacustrine redox variations in the Toarcian Sichuan Basin across the Jenkyns Event. Glob. Planet. Chang. 2022, 215, 103860. [Google Scholar] [CrossRef]
  47. Algeo, T.J.; Liu, J.S. A re-assessment of elemental proxies for paleoredox analysis. Chem. Geol. 2020, 540, 119549. [Google Scholar] [CrossRef]
  48. Jones, B.; Manning, D.A. Comparison of geochemical indices used for the interpretation of palaeoredox conditions in ancient mudstones. Chem. Geol. 1994, 111, 111–129. [Google Scholar] [CrossRef]
  49. Algeo, T.J.; Ingall, E. Sedimentary Corg:P ratios, paleocean ventilation, and Phanerozoic atmospheric pO2. Palaeogeogr. Palaeoclimatol. Palaeoecol. 2007, 256, 130–155. [Google Scholar] [CrossRef]
  50. Zhang, H.; Wang, J.; Ahmed, M.S.; Fu, X.; Shen, L. Lacustrine Environmental Perturbations during the Early Jurassic in the Qiangtang Basin, Northern Tibet. Minerals 2024, 14, 762. [Google Scholar] [CrossRef]
  51. Wei, W.; Algeo, T.J. Elemental proxies for paleosalinity analysis of ancient shales and mudrocks. Geochim. Cosmochim. Acta 2020, 287, 341–366. [Google Scholar] [CrossRef]
  52. Tribovillard, N.; Algeo, T.; Lyons, T.; Riboulleau, A. Trace metals as paleoredox and paleoproductivity proxies: An update. Chem. Geol. 2006, 232, 12–32. [Google Scholar] [CrossRef]
  53. Yang, C.; Gao, Y. Application of trace metal elements in the study of paleolimnological redox states. South. China Geol. 2020, 36, 295–307. [Google Scholar]
  54. Jenkyns, H.C. Geochemistry of oceanic anoxic events. Geochem. Geophys. Geosys. 2010, 11. [Google Scholar] [CrossRef]
  55. Xu, W.; Ruhl, M.; Jenkyns, H.C.; Hesselbo, S.P.; Riding, J.B.; Selby, D.; Naafs, B.D.A.; Weijers, J.W.; Pancost, R.D.; Tegelaar, E.W.; et al. Carbon sequestration in an expanded lake system during the Toarcian oceanic anoxic event. Nat. Geosci. 2017, 10, 129–134. [Google Scholar] [CrossRef]
  56. Liu, J.; Cao, J.; Hu, G.; Wang, Y.; Liao, Z. Water-level and redox fluctuations in a sichuan basin lacustrine system coincident with the Toarcian OAE. Palaeogeogr. Palaeoclimatol. Palaeoecol. 2020, 558, 109942. [Google Scholar] [CrossRef]
  57. Them, T.R., II; Gill, B.C.; Caruthers, A.H.; Grocke, D.R.; Tulsky, E.T.; Martindale, R.C.; Poulton, T.P.; Smith, P.L. High-resolution carbon isotope records of the Toarcian Oceanic Anoxic Event (Early Jurassic) from North America and implications for the global drivers of the Toarcian carbon cycle. Earth Planet Sci. Lett. 2017, 459, 118–126. [Google Scholar] [CrossRef]
  58. Chen, W.; Kemp, D.B.; He, T.; Newton, R.J.; Xiong, Y.; Jenkyns, H.C.; Izumi, K.; Cho, T.; Huang, C.; Poulton, S.W. Shallow- and deep-ocean Fe cycling and redox evolution across the Pliensbachian-Toarcian boundary and Toarcian Oceanic Anoxic Event in Panthalassa. Earth Planet Sci. Lett. 2023, 602, 117959. [Google Scholar] [CrossRef]
  59. Kemp, D.B.; Suan, G.; Fantasia, A.; Jin, S.; Chen, W. Global organic carbon burial during the Toarcian oceanic anoxic event: Patterns and controls. Earth Sci. Rev. 2022, 231, 104086. [Google Scholar] [CrossRef]
  60. Kemp, D.B.; Chen, W.; Cho, T.; Algeo, T.J.; Shen, J.; Ikeda, M. Deep-ocean anoxia across the Pliensbachian-Toarcian boundary and the Toarcian Oceanic Anoxic Event in the Panthalassic Ocean. Glob. Planet. Chang. 2022, 212, 103782. [Google Scholar] [CrossRef]
  61. Qiu, R.; Fang, L.; Lv, P.; Jiang, F.; Zhang, X.; Zhang, X.; Zhang, P.; Zhu, L.; Shi, S. Long eccentricity forcing of the Late Pliensbachian to Early Toarcian (Jurassic) terrestrial wildfire activities in the Tarim Basin, northwestern China. Palaeogeogr. Palaeoclimatol. Palaeoecol. 2023, 613, 111408. [Google Scholar] [CrossRef]
  62. Qiu, R.; Fang, L.; Lu, Y.; Chen, Y.; Huang, R.; Lei, W.; Zhang, P.; Li, M. Cyclostratigraphy of the Lower Jurassic (Toarcian) terrestrial successions in the Sichuan Basin, southwestern China. J. Asian Earth Sci. 2023, 250, 105617. [Google Scholar] [CrossRef]
  63. Liu, H.; Liu, X.; Liu, G.; Li, G.; Wang, J.; Gao, Y.; Sun, B.; Hou, J.; Liu, H.; Su, X. Sedimentary environment controls on the lacustrine shale lithofacies: A case study from the Nanpu depression Bohai Bay Basin. Geoenergy Sci. Eng. 2023, 225, 211704. [Google Scholar] [CrossRef]
  64. Zhang, S.; Liu, C.; Liang, H.; Wang, J.; Bai, J.; Yang, M.; Liu, G.; Huang, H.; Guan, Y. Paleoenvironmental conditions, organic matter accumulation, and unconventional hydro-carbon potential for the Permian Lucaogou Formation organic-rich rocks in Santanghu Basin NW China. Int. J. Coal Geol. 2018, 185, 44–60. [Google Scholar] [CrossRef]
  65. Lin, D.; Xi, Z.; Tang, S.; Lash, G.G.; Guo, Q.; Wang, H.; Zhu, Y. Organic matter enrichment in shale deposited proximal to paleo-uplifts and its impact on shale gas exploration. Palaeogeogr. Palaeoclimatol. Palaeoecol. 2024, 633, 111900. [Google Scholar] [CrossRef]
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Figure 2. A ternary diagram of the contents of quartz and feldspar, clay minerals, and carbonates (vol. %) of the analyzed Da’anzhai Member shale (CM = Clay mineral shale; C = Carbonate shale; S = Siliceous shale; M = Mixed shale; n = 36; n—number of experimental samples).
Figure 2. A ternary diagram of the contents of quartz and feldspar, clay minerals, and carbonates (vol. %) of the analyzed Da’anzhai Member shale (CM = Clay mineral shale; C = Carbonate shale; S = Siliceous shale; M = Mixed shale; n = 36; n—number of experimental samples).
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Figure 3. Microscopic characteristics of different lithofacies in the Da’anzhai Member: (a) 2959.78 m, organic-rich argillaceous shale (ORA); (b) 2972.5 m, organic-rich argillaceous shale (ORA); (c) 2995.1 m, organic-poor argillaceous shale (OPA); (d) 3004.11 m, organic-poor argillaceous shale (OPA); (e) 2961.13 m, organic-rich mixed shale (ORM); (f) 2986.3 m, organic-rich mixed shale (ORM).
Figure 3. Microscopic characteristics of different lithofacies in the Da’anzhai Member: (a) 2959.78 m, organic-rich argillaceous shale (ORA); (b) 2972.5 m, organic-rich argillaceous shale (ORA); (c) 2995.1 m, organic-poor argillaceous shale (OPA); (d) 3004.11 m, organic-poor argillaceous shale (OPA); (e) 2961.13 m, organic-rich mixed shale (ORM); (f) 2986.3 m, organic-rich mixed shale (ORM).
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Figure 4. Various geochemical profiles of the analyzed Da’anzhai Member shale.
Figure 4. Various geochemical profiles of the analyzed Da’anzhai Member shale.
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Figure 5. The correlation between the Fe/Mn ratio and CIA value among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05).
Figure 5. The correlation between the Fe/Mn ratio and CIA value among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05).
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Figure 6. Redox-sensitive trace element ratios for characterizing the redox condition among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05). (a) The cross-plot of V/Cr-Ni/Co; (b) the cross-plot of Ni/Co-U/Th.
Figure 6. Redox-sensitive trace element ratios for characterizing the redox condition among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05). (a) The cross-plot of V/Cr-Ni/Co; (b) the cross-plot of Ni/Co-U/Th.
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Figure 7. Bivalve bioclasts among different lithofacies of the analyzed Da’anzhai Member shale (n = 36; n—number of experimental samples): (a) 2966.31 m, ORA; (b) 2969.37 m, ORA; (c) 2982.09 m, ORM; (d) 3000.3 m, OPA.
Figure 7. Bivalve bioclasts among different lithofacies of the analyzed Da’anzhai Member shale (n = 36; n—number of experimental samples): (a) 2966.31 m, ORA; (b) 2969.37 m, ORA; (c) 2982.09 m, ORM; (d) 3000.3 m, OPA.
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Figure 8. The relationship between Al content and (Ni + Cu + Zn) content among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05).
Figure 8. The relationship between Al content and (Ni + Cu + Zn) content among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05).
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Figure 9. The correlation analysis between proxies representing various paleoenvironments and TOC content among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05). (a) Fe/Mn versus TOC; (b) MoEF versus TOC; (c) Corg/P versus TOC; (d) Sr/Ba versus TOC; (e) Al versus TOC; (f) (Ni + Cu + Zn) versus TOC; (g) (Ni + Cu + Zn)/Al versus TOC.
Figure 9. The correlation analysis between proxies representing various paleoenvironments and TOC content among different lithofacies of the analyzed Da’anzhai Member shale (ORA: organic-rich argillaceous shale; OPA: organic-poor argillaceous shale; ORM: organic-rich mixed shale; n = 36, n—number of experimental samples; p < 0.05). (a) Fe/Mn versus TOC; (b) MoEF versus TOC; (c) Corg/P versus TOC; (d) Sr/Ba versus TOC; (e) Al versus TOC; (f) (Ni + Cu + Zn) versus TOC; (g) (Ni + Cu + Zn)/Al versus TOC.
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Figure 10. Conceptual model that explains sedimentary environment and pore system evolution of Da’anzhai Member induced by T-OAE. (a) Sedimentary environment of T-OAE response section; (b) sedimentary environment of T-OAE unassociated section.
Figure 10. Conceptual model that explains sedimentary environment and pore system evolution of Da’anzhai Member induced by T-OAE. (a) Sedimentary environment of T-OAE response section; (b) sedimentary environment of T-OAE unassociated section.
Applsci 14 10192 g010
Table 1. Mineral composition and TOC content of Da’anzhai Member.
Table 1. Mineral composition and TOC content of Da’anzhai Member.
DepthQuartzPotassium FeldsparPlagioclase FeldsparCalciteFerrodolomiteDolomiteSideritePyriteFluorapatiteSiliceous MineralClay MineralCarbonate MineralTOCLithofacies
(m)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)
2955.3732.4 5.12.1 1.91.6 37.556.55.60.9OPA
2956.1530.9 4.61.2 1.1 35.562.21.20.9OPA
2956.7539.1 7.71.8 0.5 46.850.91.81.0OPA
2957.2229.2 3.44.8 1.9 0.5 32.660.26.70.9OPA
2958.6733.0 6.3 2.72.339.354.80.01.6ORA
2958.8733.0 5.70.8 3.3 38.755.90.81.4ORA
2958.9828.8 5.33.4 1.2 34.160.83.41.3ORA
2959.7836.6 4.71.6 3.9 41.353.21.61.6ORA
2961.1335.1 2.311.3 6.8 37.444.518.11.6ORM
2964.0832.0 1.99.62.9 33.953.612.50.9OPA
2964.2136.8 2.85.9 2.0 0.4 39.652.17.90.9OPA
2965.1120.7 2.71.3 0.6 23.474.71.30.8OPA
2965.1923.0 3.4 0.6 23.073.03.40.8OPA
2966.3125.7 5.26.3 0.60.8 30.961.46.91.1ORA
2966.9831.9 6.5 2.8 31.955.86.51.1ORA
2968.0819.8 2.024.7 2.5 21.850.824.71.4ORA
2968.7426.60.42.26.8 1.7 29.261.96.81.9ORA
2969.3729.0 2.6 1.4 2.1 29.064.94.01.6ORA
2970.0728.0 1.6 2.4 29.667.20.01.6ORA
2972.226.7 4.93.9 0.80.71.9 31.661.15.42.3ORA
2972.4528.5 2.64.0 1.6 31.162.64.01.9ORA
2972.521.2 4.1 1.3 25.372.20.01.8ORA
2978.2329.9 7.32.0 3.30.6 37.256.95.30.9OPA
2980.0731.0 4.311.0 1.1 35.352.611.00.9OPA
2982.0929.3 5.723.4 0.9 35.036.823.41.1ORM
2983.931.6 4.93.3 1.5 36.558.73.30.7OPA
2985.0430.6 5.16.6 35.754.56.60.8OPA
2986.326.3 5.020.0 1.8 31.346.920.01.4ORM
2988.632.0 5.96.7 1.2 37.954.26.70.8OPA
2991.9511.7 8.312.1 7.0 20.054.919.10.6OPA
2995.117.0 4.823.7 0.4 21.854.123.70.7OPA
3000.317.2 3.24.2 1.0 20.474.44.20.4OPA
3004.1139.1 2.34.7 2.2 41.451.76.90.6OPA
Table 2. Major element data of Da’anzhai Member.
Table 2. Major element data of Da’anzhai Member.
DepthTOCSiO2Al2O3MgONa2OK2OP2O5TiO2CaOTFe2O3MnOSO2LOI
(m)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)(%)
2955.370.9457.7019.952.200.673.260.150.841.115.800.080.087.60
2956.150.8856.5521.252.280.653.500.120.830.616.000.050.087.53
2956.750.9560.9618.382.020.722.830.180.841.375.480.060.116.44
2957.220.8659.5218.962.120.583.410.120.691.295.790.050.086.82
2958.671.5756.4419.452.120.693.290.270.671.097.360.051.216.80
2958.871.3857.5418.892.070.653.010.190.661.337.300.041.296.44
2958.981.3258.7418.662.070.643.370.270.640.766.470.030.796.96
2959.380.6352.5918.431.870.653.050.160.824.636.340.051.339.57
2959.781.5558.1119.112.200.643.370.090.720.717.150.050.586.70
2961.131.5654.8218.12.010.472.970.100.674.425.120.090.0610.63
2964.080.8752.7721.142.170.433.500.160.803.146.010.090.059.24
2964.210.9357.2919.561.890.463.130.110.692.914.980.060.088.27
2965.110.8452.7025.32.070.543.640.100.850.685.770.050.107.68
2965.190.7653.3725.312.060.543.660.100.830.575.620.040.137.25
2966.311.0550.5924.172.160.603.620.110.761.956.680.060.128.67
2966.981.1157.02211.810.453.460.100.651.865.030.040.137.87
2967.030.6417.273.590.540.130.580.030.1641.472.030.440.1033.49
2968.081.4445.8515.451.600.392.520.140.4311.665.820.050.8914.76
2968.741.8651.5722.862.160.533.690.090.660.587.280.030.969.07
2969.371.6257.9919.32.070.553.540.120.620.866.300.040.247.80
2970.071.5858.8317.772.060.513.450.170.581.106.730.030.068.12
2972.22.3254.4022.052.100.533.530.160.750.896.560.040.128.33
2972.451.8753.8422.552.150.533.540.160.760.937.150.040.147.69
2972.51.7554.6021.212.010.533.260.230.691.627.010.040.128.14
2978.230.8554.6423.351.960.783.290.150.941.185.650.050.107.37
2980.070.8553.0121.961.800.672.910.120.823.555.700.060.178.70
2982.090.752.6516.611.780.572.210.310.717.475.490.100.1511.42
2983.90.6655.9521.12.120.543.120.160.791.186.970.100.097.32
2985.040.7956.5519.731.720.692.610.200.801.767.260.090.107.93
2986.31.4453.6217.451.960.582.990.250.595.006.940.050.149.90
2988.60.7758.5319.51.850.722.830.240.851.805.600.060.077.38
2991.950.6454.5218.071.880.512.480.220.723.128.710.270.178.79
2995.10.6527.1410.510.930.261.510.060.4630.563.180.180.8924.03
3000.10.2152.7120.911.630.693.110.170.894.575.430.060.189.11
3000.30.453.0325.581.710.603.710.110.921.165.150.040.107.36
3004.110.5659.2519.651.830.473.000.110.851.785.160.060.067.19
Table 3. Trace element data of Da’anzhai Member.
Table 3. Trace element data of Da’anzhai Member.
DepthTOC51V52Cr59Co60Ni63Cu66Zn88Sr95Mo137Ba238U232Th
(m)(%)(ppm)(ppm)(ppm)(ppm)(ppm)(ppm)(ppm)(ppm)(ppm)(ppm)(ppm)
2955.370.94148.7592.9219.2254.8937.04163.70147.710.54796.802.4313.48
2956.150.88174.33100.7218.0654.4739.49138.37146.610.62911.352.2613.27
2956.750.95147.8191.7319.1249.4737.36139.66165.130.72699.402.2813.56
2957.220.86157.4092.2715.6450.0834.50119.96160.710.66726.012.3312.74
2958.671.57169.6877.7117.7949.9749.95135.49166.971.41730.602.1711.96
2958.871.38163.4975.7217.2546.6646.42130.78173.511.19722.771.9611.09
2958.981.32169.7298.0914.9248.0248.15133.77157.290.98771.851.8310.71
2959.380.63164.5093.2215.1043.8243.07111.14197.151.37742.881.479.51
2959.781.55181.0783.9317.6148.5340.27134.44141.451.44775.432.3611.77
2961.131.56133.67100.7122.1049.8029.3876.68147.500.78577.512.2416.79
2964.080.87159.0193.9815.3847.1036.2294.55155.150.37664.972.8217
2964.210.93144.3485.4625.7455.9131.82108.38172.600.79631.442.5216.56
2965.110.84187.7689.6622.3659.7047.15145.11143.690.81858.553.3416.15
2965.190.76187.26102.1923.5460.1745.86137.75149.770.89857.342.9614.58
2966.311.05184.40104.1518.8355.6145.02125.83163.300.70869.592.8213.62
2966.981.11158.5877.7319.5651.1739.07125.50132.171.04604.003.2317.74
2968.081.44132.3369.4513.5942.1232.7184.36197.820.88629.291.869.05
2968.741.86199.38115.0718.4954.8246.84133.20156.001.02912.412.3511.74
2969.371.62176.28100.9415.6050.1145.38125.68127.160.93953.212.2911
2970.071.58184.30109.5215.8253.3941.43132.95137.850.86828.311.678.47
2972.22.32181.58117.7619.2558.6045.61122.22141.990.95903.152.1112.5
2972.451.87193.19111.8518.0953.2443.74133.65149.290.78846.952.2611.95
2972.51.75182.56108.1118.1550.5239.87128.52156.220.72839.972.4311.47
2978.230.85180.11102.8419.9752.7845.74123.72149.920.77807.232.7014.95
2980.070.85159.9991.4618.3349.9840.98156.97200.720.72731.842.4013.26
2982.090.7124.8765.2214.5240.9833.6392.78171.780.90545.092.1513.16
2983.90.66163.3893.2118.5351.9440.08108.99137.060.55801.412.5014.22
2985.040.79145.9584.4417.2244.9540.64113.79139.810.60636.182.2612.49
2986.31.44153.8296.1716.3149.5343.72110.78170.650.71710.431.699.57
2988.60.77158.0398.5917.6250.7843.85117.53147.230.54683.801.9412.26
2991.950.64127.6492.3516.8044.4134.29141.64175.920.58607.752.3313.02
3000.10.21144.2796.7518.1746.7743.69116.74181.331.27700.932.7615.07
3000.30.4175.13107.0414.8850.0044.00115.67137.760.81741.622.7817.33
3004.110.56137.4276.5218.6047.3734.30117.94122.151.37482.932.9318.27
Table 4. Geochemical proxies for reconstructing paleoenvironment.
Table 4. Geochemical proxies for reconstructing paleoenvironment.
Depth (m)Weathering and PaleoclimateRedox ConditionSalinityTerrigenous Detrital Input Al (%)Primary Productivity
CIAFe/MnV/CrNi/CoU/ThMoEFCorg/PSr/BaNi + Cu + Zn (ppm)(Ni + Cu + Zn)/Al
2955.3779.8372.501.602.860.180.5437.060.199.98255.630.0024
2956.1581.70120.001.733.020.170.6243.370.1610.63232.330.0021
2956.7578.8891.331.612.590.170.7231.210.249.19226.490.0023
2957.2278.22115.801.713.200.180.6642.380.229.48204.540.0020
2958.6779.32147.202.182.810.181.4134.390.239.73235.410.0023
2958.8779.10182.502.162.700.181.1942.960.249.45223.860.0022
2958.9879.64215.671.733.220.170.9828.910.209.33229.940.0023
2959.3868.87126.801.762.900.151.3723.290.279.22198.030.0020
2959.7880.19143.002.162.760.201.44101.860.189.56223.240.0022
2961.1369.7256.891.332.250.130.7892.260.269.05155.860.0016
2964.0874.9466.781.693.060.170.3732.160.2310.57177.870.0016
2964.2175.0683.001.692.170.150.7950.000.279.78196.110.0019
2965.1183.89115.402.092.670.210.8149.680.1712.65251.960.0019
2965.1984.14140.501.832.560.200.8944.950.1712.66243.780.0018
2966.3179.66111.331.772.950.210.7056.450.1912.09226.460.0018
2966.9878.45125.752.042.620.181.0465.650.2210.50215.740.0019
2967.0378.844.611.972.690.281.54126.172.511.8032.610.0017
2968.0871.47116.401.913.100.210.8860.830.317.73159.190.0019
2968.7482.65242.671.732.960.201.02122.230.1711.43234.860.0019
2969.3779.59157.501.753.210.210.9379.840.139.65221.170.0022
2970.0777.84224.331.683.370.200.8654.970.178.89227.770.0024
2972.281.67164.001.543.040.170.9585.760.1611.03226.430.0019
2972.4581.85178.751.732.940.190.7869.120.1811.28230.630.0019
2972.579.68175.251.692.780.210.7245.000.1910.61218.910.0019
2978.2381.64113.001.752.640.180.7733.510.1911.68222.240.0018
2980.0775.4995.001.752.730.180.7241.890.2710.98247.930.0021
2982.0961.8454.901.912.820.160.9013.350.328.31167.390.0019
2983.981.3469.701.752.800.180.5524.400.1710.55201.010.0018
2985.0479.5980.671.732.610.180.6023.360.229.87199.380.0019
2986.367.06138.801.603.040.180.7134.070.248.73204.030.0022
2988.678.4793.331.602.880.160.5418.970.229.75212.160.0021
2991.9574.7332.261.382.640.180.5817.200.299.04220.340.0023
2995.174.5317.671.362.730.180.4864.070.425.2682.480.0015
3000.171.4190.501.492.570.181.277.310.2610.46207.200.0019
3000.382.38128.751.643.360.160.8121.510.1912.79209.670.0015
3004.1178.9286.001.802.550.161.3730.110.259.83199.610.0019
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Peng, Y.; Fu, Y.; Chen, S.; Wang, E. Sedimentary Environment Reconstruction and Organic Matter Enrichment Mechanisms in Various Lithofacies of the Lacustrine Shale: A Case Study of the Da’anzhai Member, Central Sichuan Basin, China. Appl. Sci. 2024, 14, 10192. https://doi.org/10.3390/app142210192

AMA Style

Peng Y, Fu Y, Chen S, Wang E. Sedimentary Environment Reconstruction and Organic Matter Enrichment Mechanisms in Various Lithofacies of the Lacustrine Shale: A Case Study of the Da’anzhai Member, Central Sichuan Basin, China. Applied Sciences. 2024; 14(22):10192. https://doi.org/10.3390/app142210192

Chicago/Turabian Style

Peng, Yuting, Yingxiao Fu, Senran Chen, and Enze Wang. 2024. "Sedimentary Environment Reconstruction and Organic Matter Enrichment Mechanisms in Various Lithofacies of the Lacustrine Shale: A Case Study of the Da’anzhai Member, Central Sichuan Basin, China" Applied Sciences 14, no. 22: 10192. https://doi.org/10.3390/app142210192

APA Style

Peng, Y., Fu, Y., Chen, S., & Wang, E. (2024). Sedimentary Environment Reconstruction and Organic Matter Enrichment Mechanisms in Various Lithofacies of the Lacustrine Shale: A Case Study of the Da’anzhai Member, Central Sichuan Basin, China. Applied Sciences, 14(22), 10192. https://doi.org/10.3390/app142210192

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