Paleoenvironment evolution and organic matter enrichment mechanisms in the first member of the Qingshankou Formation, Songliao Basin, China

Abstract

Organic matter is the basis for oil and gas generation, and the depositional environment controls its enrichment. The first member of the Qingshankou Formation (K₂qn¹) in Songliao Basin has a thick organic-rich shale and so is an important target section for shale oil exploration and development. In the Gulong Sag, shale samples from this unit were collected over the full length of the section. The characterization of the environments of deposition (EOD) of K₂qn¹ was improved by utilizing lithological characteristics, thin section observations, elemental compositions, and organic carbon concentrations. Combined with the normalization coefficients proposed in this paper, an organic matter correlation model was established to elucidate the factors that influence organic matter enrichment. From the bottom to the top of K₂qn¹, the lake depth gradually becomes shallower, the primary productivity first decreases and then increases, the reducing conditions become stronger and then weaker, the water salinity gradually decreases, the climate first becomes semi-humid and then warm and humid, and the input of terrigenous debris first decreases and then increases. A major marine transgression at the base of the K₂qn¹᾽s brought in nutrients to increase primary productivity, and the density-stratified reducing environment preserved and enriched organic matter. High primary productivity occurred during the middle of the deposition of the K₂qn¹, while terrigenous input is low. Organic matter is preserved in reduced deep lake environments, resulting in organic matter-rich black shale. The lake became shallower, and the salinity decreased in the upper part of K₂qn¹. Benthic organisms rapidly multiplied, consuming large amounts of oxygen and destroying the previously depositional environment, resulting in a reducing environment disturbed by benthic organisms with poor preservation conditions and the lowest organic matter content.

Graphical abstract

Keywords

major and trace elements / paleoenvironment evolution / OM enrichment mechanism / lacustrine shale / Songliao Basin / Qingshankou Formation

1 Introduction

Since the shale gas revolution in North America, unconventional oil and gas resources have become a major focus of global exploration (Jarvie, 2012). The Songliao Basin is the largest Cretaceous continental sedimentary basin in Asia and is a major source of petroleum, including the Daqing and Jilin oilfields (Zou et al., 2019; Guan et al., 2021). The Qingshankou Formation is a major oil-producing formation in the Songliao Basin and has thick, organic-rich black shale that offer excellent shale oil exploration prospects (Liu et al., 2019; Sun et al., 2021). Sufficient organic matter is a prerequisite for oil and gas generation, and the depositional environment (EOD) controls its enrichment (Peters et al., 1986; Hakimi et al., 2014). To encourage unconventional oil and gas exploration and production, it is essential to study the depositional environment evolution and organic matter enrichment mechanisms (Zhao et al., 2020).

The Qingshankou Formation is a lacustrine environment and several studies have been done previously to reconstruct the Qingshankou Formation’s shale sedimentary environments. Based on spore-pollen data, Huang et al. (1999) found that evergreen broad-leafed forests, representing a warm-humid environment, were prevalent during the deposition of the Qingshankou Formation. According to Wang et al. (1996), the intrusion of seawater during the deposition of the Qingshankou Formation caused the lake water to stratify, resulting in the formation of black shale in a stably stratified lake environment. Hou et al. (2003) determined occurrences of anoxic episodes and marine transgression events in the Cretaceous Songliao Basin, particularly at the base of the Qingshankou Formation, where reducing conditions were strong. Wu et al. (2008) established a floating astronomical time scale for the Qingshankou Formation and determined that the paleolake anoxic event occurred close to the Cretaceous Oceanic Anoxic Event 2 (OAE2). Feng et al. (2011) studied the sedimentary biomarkers and observed that K₂qn¹ lake water was highly saline and stratified.

Numerous academics have studied the evolutionary features of the sedimentary environment and organic matter enrichment mechanisms in K₂qn¹ in recent years. According to Wang et al. (2015), in K₂qn¹, shore-shallow lakes with oxygenated water and high energy hydrodynamics had poor organic matter preservation conditions, while semi-deep and deep lakes had favorable preservation conditions. Good preservation conditions with low energy hydrodynamic conditions and a strongly reducing environment promote organic matter enrichment in K₂qn¹. Wang et al. (2019) used thin section observations and geochemical data analysis to show that the organic matter in K₂qn¹ was deposited in a reducing environment with low energy hydrodynamics, but that the reducing environment was disturbed when terrigenous debris input increased, implying that terrigenous debris input was also an important control factor for organic matter enrichment in K₂qn¹. However, Song et al. (2016) noted that the enrichment of organic materials in K₂qn¹ is not only controlled by preservation conditions but also by high primary productivity. Stratified reducing conditions with high primary productivity and salinity jointly control the enrichment of organic matter in K₂qn¹. According to elemental and biomarker compound analysis, Zheng et al. (2020) also found that organic matter abundance is highest when primary productivity is highest and reducing conditions are the most intense, and that high salinity also influences organic matter enrichment in K₂qn¹. Furthermore, Fu et al. (2022) suggested that under a warm and humid climate, high salinity, high primary production, and weak terrigenous debris input enriched organic matter in K₂qn¹, and the reducing environment was not a major controlling factor.

In summary, there is still no agreement on the major controlling factors of organic matter enrichment in K₂qn¹. Previous research focused on primary productivity and redox conditions with little consideration of other factors. Currently, the studies of the paleoenvironmental features of K₂qn¹ only characterize lake water depth, salinity, or redox conditions. Few studies have completely investigated the paleoenvironment of deposition, including the redox conditions, water salinity, paleoclimate, terrigenous debris input, primary productivity, and water depth. Consequently, based on lithological characteristics, thin section observation, elemental composition, and organic carbon abundance data, this study aims to: 1) provide a detailed description of the paleoenvironment features (including redox conditions, water salinity, paleoclimate, terrigenous debris input, and water depth) in K₂qn¹; 2) establish the TOC correlation model with comprehensive multi-factor control and comprehensively analyze the effects of various factors influencing the enrichment of organic matter in K₂qn¹ in order to provide a reference for the study of shale organic matter enrichment in the Songliao Basin and new geochemical evidence for shale oil exploration.

2 Geological setting

The Songliao Basin is located in north-east China and has an area of approximately 26 × 10⁴ km². It is one of the most prolific terrestrial basins in terms of oil and gas resources in the world. The basin is divided into six structural units: the northern plunge, the central depression, the north-eastern uplift, the south-eastern uplift, the south-western uplift, and the western slope (Fig.1(a)). The major oil and gas producing area is the central depression, including the Qijia-Gulong sag, Daqing placanticline, Sanzhao sag, Changling sag, and the Chaoyanggou terrace (Feng et al., 2010, 2021). The focus of the research is the Gulong Sag, which is west of the central depression in the Songliao Basin.

The basin contains Jurassic, Cretaceous, Eogene, and Neogene clastic deposits (Li, 1996). The Cretaceous sedimentary period was one of the warmest periods of the Phanerozoic, when significant oceanic anoxic events (OAEs) occurred globally (Jenkyns, 1980; Wu et al., 2009). Upper Cretaceous formations include Qingshankou, Yaojia, Nenjiang, Sifangtai, and Mingshui (Fig.2) (Gao and Cai, 1997). The occurrences of marine transgressive events during this time have been demonstrated by paleontology, geochemistry, and other geological techniques (Gao et al., 1992; Hou, 1999; Feng et al., 2009). A warm and humid climate during the Turonian–Coniacian period promoted aquatic organism blooms, and widespread water column stratification with bottom water anoxia favored organic matter preservation, resulting in the deposition of organic matter-rich layer series in large parts of the Songliao paleolake at that time (Fig.2) (Xu et al., 2015).

The Qingshankou Formation is a favorable stratum for the development of the Gulong and Gaotaizi oil layers, and its seismic reflection horizons are T₂ and T₁¹, which correspond to the bottom and top surfaces (Fig.1(c) and Fig.2). Based on lithology, the Qingshankou Formation is classified into three units (K₂qn¹, K₂qn², and K₂qn³). Large-scale marine transgression occurred during the depositional period of K₂qn¹, and the lake basin area reached its maximum. The semi-deep lacustrine-deep lacustrine facies was formed in this period (Fig.1(b)), and its lithology is mainly large sets of dark shale and oil shale, with thin dolomite, siltstone, muddy siltstone, and shell limestone interlayers (Fig.2). Organic rich shales in K₂qn¹ are the main oil source rock, with high OM abundance. The R_o of the organic rich shales lies between 1.0%−1.6% in the main depression region, which could be a key shale oil exploration target (Liu et al., 2022). The central depression area, in particular, is the most developed high-quality source rock and a favorable interval for Gulong shale oil exploration and development (Sun et al., 2021). In 2021, Daqing Oilfield discovered the K₂qn¹ shale oil reservoir in Gulong Sag, with an oil-bearing area of 1413 km² and a predicted reserve of 12.68 × 10⁸ t (Li et al., 2022).

3 Materials and methods

To study the evolution of the depositional environments in the K₂qn¹, samples were taken through the entire interval in Well G (Fig.1(a)), with a depth range of 2287–2377 m (Fig.2). A total of 133 samples were analyzed for TOC content and 32 samples for elemental content. After sampling, all core samples were stored in plastic bags to ensure as little contamination and oxidation as possible.

Total organic carbon (TOC) content analyses were all performed by an Eltre CS580A-type carbon and the experimental process was based on the national standard GB/T 19145-2003. The accuracy of the analysis was greater than 0.5%. The major, trace, and rare earth element (REE) concentrations for the shale samples were measured at 14°C and 30% relative humidity. All samples were crushed below 200 mesh for further examination. The melt sheet method and X-ray fluorescence spectrometry (XRF) were used for quantitative element analysis. Approximately 0.7 g of sample powder was baked in a muffle furnace at 1000°C for 3−5 h before being mixed with 7.7 g of anhydrous Li₂B₄O₇ solvent. After that, the Analymate-V4D melting apparatus formed a melting sheet that was measured by an Epsilon 3XLE X-ray fluorescence spectrometer. The experimental process was based on GB/T 14506.28-2010 and GB/T 14506.14-2010, with an analytical error of less than 5%. Trace elements and REE were dissolved by mixed acid closed digestion and measured by inductively coupled plasma mass spectrometry (ICP-MS). The experimental process was based on the national standards GB/T 14506.30-2010 and GB/T 14506.11-2010, with an analytical error of less than 5%.

4 Results

4.1 Shale properties

The TOC content of K₂qn¹ shale samples gradually decreases from bottom to top (Fig.3), while the total concentrations vary from 0.70% to 4.94%, with an average value of 1.84%. The TOC concentrations in the lower, middle, and upper portions of K₂qn¹ exhibit a regular pattern of first increasing, and subsequently decreasing, demonstrating a cyclic characteristic. The lithology of K₂qn¹ is dominated by black shale; nevertheless, in the lower, middle, and upper parts of K₂qn¹, the lithofacies assemblages show substantial variation. The lower sedimentary section is dominated by black shale and oil shale, and the oil shale deposits correspond to the sections with the most enriched TOC content. The central sedimentary section contains mostly black shale deposits, which indicates a depositional environment with few or no benthic organisms. The upper sedimentary section is significantly different from the central section since the upper black shale is intercalated with several thin layers of argillaceous siltstone and dolomite (Fig.3).

4.2 Major, trace, and REE concentrations

Appendix A lists major element analytical results. Analysis of the major elements show that SiO₂ and Al₂O₃ are the most abundant constituents (Fig.4(a)). Higher concentrations of K₂O compared to Na₂O (Fig.4(a)) indicate more K-feldspar or K-bearing minerals. Ti is not affected by diagenetic processes and its oxide (TiO₂) correlates with Al₂O₃, indicating a consistent source of detrital material in K₂qn¹ (Fig.4(b)). Appendix B contains trace element analysis results. Normalized to post-Archean Australian shale (PAAS) (Taylor and McLennan, 1985) and plotted on a line plots (Fig.4(c)), trace elements show consistent distribution patterns, indicating that K₂qn¹ may have the same sedimentary provenance, with significant differences only at the contact of the Qingshankou and Quantou Formations (Fig.2 and Fig.4(c)). The rare earth elements (REE) distribution is similar, among which the light rare earth elements (LREE) mainly include La, Ce, Pr, Nd, Pm, Sm, and Eu, with negative Eu anomalies (Fig.4(d)). The heavy rare earth elements (HREE) mainly include Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu, and Y. The light rare earth elements are substantially enriched, while the heavy rare earth elements are distributed more evenly, with a smaller difference. The formula for calculating (La/Yb)_N is (La/Yb)_N = (La/Yb)_sample/(La/Yb)_chondrite, where (La/Yb)_sample is the La/Yb ratio of the sample and (La/Yb)_chondrite is the La/Yb ratio of the chondrite standard (Taylor and McLennan, 1985). In this paper, the calculated (La/Yb)_N varies from 7.70 to 11.58, clearly indicating the difference between LREE and HREE.

4.3 Formation subdivision characteristics

Terrigenous debris input affects (e.g., dilutes or enhances) the sediment’s authigenic major and trace element concentrations. To eliminate the influence of terrigenous debris, enrichment factors (EFs) can be used to define element enrichment or depletion (Tribovillard et al., 2006), which are calculated as follows:

(1)X_{\mathrm{E}\mathrm{F}}={(X/\mathrm{A}\mathrm{l})}_{\mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}/{(X/\mathrm{A}\mathrm{l})}_{\mathrm{a}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{g}\mathrm{e}\mathrm{s}\mathrm{h}\mathrm{a}\mathrm{l}\mathrm{e}},

where X is the element to be calculated and the post-Archean Australian shale (PAAS) is used for the average shale. If X_EF > 1, the element is enriched relative to the PAAS while if X_EF < 1, the element is depleted.

The EF values of nine major elements and 16 trace elements are displayed in Fig.3. From bottom to top, the EF values of each element in the first member of the Qingshankou Formation show stages of regular cyclic increases and decreases (Fig.3). K₂qn¹ is a third-order sequence that contains, from bottom to top, a transgressive system tract (TST), highstand system tract (HST), and regressive system tract (RST) (Jia et al., 2013). By comparing the differences in the lithofacies assemblages of the three system tracts and the cyclic features of the TOC content (Fig.3) indicate that the first member of the Qingshankou Formation can be further divided into three units, from bottom to top: Unit A, Unit B, and Unit C (Fig.3).

Unit A has the highest TOC content, with a maximum of 4.94%; Unit B has a moderately high TOC content, with an average of 1.74% and a maximum of 2.98%; and Unit C has the lowest TOC content, with an average of 1.54%. Relative to the PAAS, Ca, Na, K, and P are enriched, while Fe, Ti, and Mn are depleted in all three units (Fig.5(a)). High Ca content may be due to calcite and abundant bivalves or gastropod fossils. Ba, Zn, Ga, Pb, Sr, Zr, U, and Mo are enriched, while V, Cr, Co, Ni, Cu, Th, Rb, and Nb are depleted in all three units (Fig.5(b)). All elements show consistent enrichment characteristics, indicating that the three units may have the same sedimentary provenance.

5 Discussion

5.1 Primary productivity and paleoenvironment evolution

5.1.1 Primary productivity evolution

Phosphorus (P) is a structural element of Deoxyribo Nucleic Acid (DNA), ribonucleic acid (RNA), and many biomolecules, which are essential components of living organisms (Haddad and Martens, 1987); uranium (U) is preserved in a reduced environment by complexation with trace elements contained in primary producers, so U can be used to restore primary productivity under reducing conditions (Chase et al., 2001; Yang and Yu, 2002). When P and U are present as biological phosphorus ({\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}}) and biological uranium ({\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}}), they can be used to restore the primary productivity. The formula for {\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}} is

(2)\mathrm{w}\left({\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}}\right)= \mathrm{w}\left({\mathrm{P}}_{\mathrm{t}}\right)-\mathrm{w} \left({\mathrm{A}\mathrm{l}}_{\mathrm{t}}\right)\times {\left(\mathrm{w}\right(\mathrm{P})/\mathrm{w}(\mathrm{A}\mathrm{l}\left)\right)}_{\mathrm{P}\mathrm{A}\mathrm{A}\mathrm{S}},

where ({\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}}) is biological phosphorus, ({\mathrm{P}}_{\mathrm{t}}) is total phosphorus in the sediment, ({\mathrm{A}\mathrm{l}}_{\mathrm{t}}) is total aluminum in the sediment, and {\left(\mathrm{w}\right(\mathrm{P})/\mathrm{w}(\mathrm{A}\mathrm{l}\left)\right)}_{\mathrm{P}\mathrm{A}\mathrm{A}\mathrm{S}} is the ratio of phosphorus to aluminum in PAAS. {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}} is calculated in the same way.

{\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}} is mostly positive, with an average of 0.07%; {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}} is all positive, ranging from 0.18% to 10.11%, with an average of 2.14%, indicating high primary productivity. In Units A, B, and C, primary productivity all showed a regular evolution of increasing and then decreasing (Fig.6(b)). Units A and C have relatively high {\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}} and {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}}, indicating relatively high primary productivity. From the bottom to the top of K₂qn¹, primary productivity fell then rose (Fig.7(a) and 7(b)).

Influenced by the global sea level rise of late Albian (112–97 Ma) (Jenkyns, 1980), a large-scale transgression occurred during the K₂qn¹, which was a reduction environment of semi-deep lake and deep lake. During this period, two slight uplift-subsidence processes occurred, and the delta advanced in different directions to the lake basin, forming a lithological combination of thick black mudstone/shale, with gray siltstone and fine sandstone (Liu et al., 2018). The lake became connected to the marine environment during the K₂qn¹, and the invading seawater not only provided nutrients but also changed the lake᾽s physicochemical properties (Xu et al., 2021). A large number of ostracod fossils were deposited in the Qingshankou Formation, among which the freshwater ostracods have strict salinity limits (Carbonel et al., 1988). A large-scale marine transgression occurred in Unit A, which resulted in a major die-off of freshwater organisms due to salinity intolerance. Simultaneously, the nutrients carried by seawater cause plankton blooms, which resulted in high primary productivity in Unit A. The scale of marine transgression decreased in Unit B, and the nutrient input from the seawater incursion was lower than in Unit A. Meanwhile, saline lake water limited the freshwater organisms’ survival and reproduction, lowering primary productivity. According to Wang et al. (1994), during the first marine transgression in the Songliao Basin, conchostracan genera and species were relatively rare at the base of the K₂qn¹, but after the marine transgression, conchostracans quickly propagated in large quantities, and there was a rapid increase in conchostracan genera and species. In Unit C, lake organisms basically had adapted to the fresh and brackish water and evolved new genera and species, resulting in a rebound in primary productivity.

5.1.2 Paleoenvironment evolution

1) Redox conditions

Trace elements like V, Cr, and Ni will mainly be adsorbed by colloidal particles or clay and then deposited. The rate of deposition of V is higher than Ni and is more efficient than that of Cr in reducing conditions, so V/Cr and V/V + Ni can be used to indicate the redox status (Wignall, 1994; Rimmer et al., 2004; Wang et al., 2017). Ratios of V/Cr > 4.25, V/Cr between 2 and 4.25, and V/Cr < 2 indicates anoxic, suboxic to dysoxic, and oxic environments respectively (Jones and Manning, 1994); V/(V + Ni) > 0.84, V/(V + Ni) between 0.6 and 0.84, and V/(V + Ni) < 0.6, indicated anoxic, dysoxic, and oxic environments respectively (Dill, 1986; Zhang et al., 2012).

The first member of the Qingshankou Formation has a small but variable range of redox conditions, from suboxic to dysoxic (Fig.6(c)). Unit B has the highest V/Cr and V/(V + Ni) ratios, indicating the strongest reducing environment. From K₂qn¹’s bottom to top, the reducing conditions became stronger and then weakened (Fig.7(c) and 7(d)). When the marine transgression occurred in K₂qn¹, the oxygen-enriched surface seawater flowed into the lake, causing a lessening of the severity of the dysoxic conditions in Unit A. Bioturbation can disrupt the depositional environment. The occurrence of bioturbation in Unit C is evident from the thin section observations (Fig.8(a) and Fig.8(b)), demonstrating that following the primary productivity recovery, the bioturbation in Unit C᾽s bioturbation will disrupt the environment.

2) Lake water salinity

The trace element ratio Sr/Ba has been widely used in paleosalinity restoration (Vincent et al., 2006). Sr/Ba greater than 1.0 indicates saline water, Sr/Ba between 0.5 and 1.0 indicates brackish water, and Sr/Ba less than 0.5 indicates fresh water (Rimmer, 2004). In addition, the element Mg occurring in sea water and the terrestrial element Al can be used as indicators of paleosalinity. The ratio of the concentrations of the two oxides is defined as the m-value, and a higher m-value indicates a higher salinity (Zhang, 1988; Chen et al., 1997), which is calculated as

(3)m=100\times (\mathrm{M}\mathrm{g}\mathrm{O} /{\mathrm{A}\mathrm{l}}_2{\mathrm{O}}_3).

The lake water salinity decreases from bottom to top in K₂qn¹, mostly showing a brackish water environment (Fig.6(d)), with the highest Sr/Ba ratio and m-value in Unit A, followed by Unit B, and the lowest in Unit C, indicating the lowest salinity in Unit C (Fig.7(e) and 7(f)). The influx of seawater during deposition of Unit A causes a sudden rise in the salinity of the lake. Rivers pour freshwater into the lake when the climate is warm and humid (Jia et al., 2013; Wang et al., 2022). The amount of seawater entering the lake decreased as the scale of the marine transgression decreased during deposition of Unit B. In addition, the continuing input of freshwater further reduced the salinity. During the deposition of Unit C, the environment becomes more humid, resulting in increased input of fresh water and a further decline in salinity.

3) Paleoclimate

Elements Fe, Mn, Cr, Ni, V, and Co are usually enriched in humid climates, whereas evaporation enriches Ca, Mg, Sr, Ba, K, and Na in arid climates (Getaneh, 2002). A paleoclimate index, the C-value, has been developed based on the concentrations of these elements (Cao et al., 2012). The C-value is less than 0.2, between 0.2 and 0.4, between 0.4 and 0.6, between 0.6 and 0.8, and greater than 0.8, indicating arid, semi-arid, semi-arid to semi-humid, semi-humid, and humid environments in that order. The C-value is calculated as follows:

(4)C=\frac{\sum \left[\left(\mathrm{F}\mathrm{e}\right)+\left(\mathrm{M}\mathrm{n}\right)+\left(\mathrm{C}\mathrm{r}\right)+\left(\mathrm{N}\mathrm{i}\right)+\left(\mathrm{V}\right)+\left(\mathrm{C}\mathrm{o}\right)\right]}{\sum [\left(\mathrm{C}\mathrm{a}\right)+\left(\mathrm{M}\mathrm{g}\right)+\left(\mathrm{S}\mathrm{r}\right)+\left(\mathrm{B}\mathrm{a}\right)+\left(\mathrm{K}\right)+(\mathrm{N}\mathrm{a}\left)\right]}.

The C-value of the first member of the Qingshankou ranges from 0.26 to 0.85, indicating that the paleoclimate fluctuates greatly, with alternating semi-humid and semi-arid transformation characteristics (Fig.6(e)). From the bottom to the top, the C-value decreases and then increases, with the highest C-value in Unit C, where the climate is the most humid (Fig.7(g)). Climate is a major factor influencing the sediment input from the sediment source area into the sedimentary system (Cecil, 1990) and so affects the input of terrigenous debris. When the climate of Unit C becomes warm and humid in K₂qn¹, the seasonally heavy rainfall may bring a large input of terrigenous debris (Liu et al., 2020; Wang et al., 2022).

4) Terrigenous detrital input

Titanium (Ti) is widely used as an indicator of terrigenous input and the Ti/Al ratio in particular is widely utilized as an index of terrestrial debris input (Brumsack, 2006; Hetzel et al., 2011). A Ti/Al ratio larger than 0.03 suggests a high input from terrestrial sources (Murphy et al., 2000; Chen et al., 2019).

The Ti/Al ratios in the K₂qn¹ range from 0.035 to 0.057, with an average of 0.040, indicating a relatively high terrigenous debris input. The terrigenous debris input is lowest in unit B, which basically has a stable input (Fig.6(f)). From bottom to top, the Ti/Al ratio decreases and then increases, being highest in Unit C (the average is 0.042), indicating that the input of terrigenous debris is the highest in the upper sedimentary section of K₂qn¹ (Fig.7(h)). At this time, seasonally heavy rainfall in Unit C may result in a large input of terrigenous debris, forming the thin layers of argillaceous siltstone and dolomite with unequal thicknesses (Fig.4).

5) Lake water depth

The transport and enrichment of both Rb and K in water are closely related to clay content, and Rb is more likely to be adsorbed by clay minerals and move farther than K. Therefore, a higher Rb/K ratio indicates a greater depth of lake water (Meng et al., 2014; Sun et al., 2020).

The Rb/K ratio is greatest in Unit A, indicating that the lake water depth of K₂qn¹ steadily decreases from bottom to top (Fig.7(i)). The lake water depth abruptly deepens in Unit A, reaches a peak depth, and then decreases; the lake water depth decreases slowly in both Units B and C (Fig.6(g)). The rivers around the sag will advance toward the center of the lake when the lake depth of the Qingshankou Formation in the Gulong Sag decreases, and the terrigenous detrital materials in the deep-water sediments will increase (Wang et al., 2019). When the lake depth becomes shallow in Unit C, sedimentation is dominated by bottom currents and turbidity current transport. The occurrence of bottom currents is supported by lenticular bedding and directionally aligned bioclasts in the shale (Fig.8(c) and 8(d)). Bottom and turbidity currents transport debris from shallow to deep water,and increase terrigenous material input (Fig.7(h)).

5.2 Factors influencing organic matter enrichment

The depositional environment controls the organic matter enrichment in lake sediments (Bohacs, 1990; Bohacs et al., 2000):

(5)\mathrm{O}\mathrm{r}\mathrm{g}\mathrm{a}\mathrm{n} \mathrm{i}\mathrm{c}\mathrm{E} \mathrm{n}\mathrm{r}\mathrm{i}\mathrm{c}\mathrm{h} \mathrm{m}\mathrm{e}\mathrm{n}\mathrm{t}=(\mathrm{P}\mathrm{r}\mathrm{o} \mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i} \mathrm{o}\mathrm{n}-\mathrm{D}\mathrm{e} \mathrm{s}\mathrm{t}\mathrm{r}\mathrm{u}\mathrm{c} \mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n})/\mathrm{D} \mathrm{i}\mathrm{l}\mathrm{u}\mathrm{t}\mathrm{i} \mathrm{o}\mathrm{n}.

From Eq. (5), it᾽s evident that organic matter enrichment is favored by high primary productivity, good preservation conditions, and a weak dilution effect (Talbot, 1988). Recent studies have shown that several factors influence the elements in Eq. (5), including primary productivity, redox conditions, paleosalinity, paleoclimate, and water depth (Ding et al., 2021; Hu et al., 2021).

In the past, when many indicators jointly characterized one control factor, such as primary productivity indicators {\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}} and {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}}, the correlations between {\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}} and TOC content, and between U_bio and TOC content had to be analyzed and then integrated. Since this is a time-consuming process, we proposed to simplify the above analysis by using the normalization coefficient method. Using the normalization coefficient approach, only the connection between the normalization coefficients and the TOC content needs to be studied. The normalization coefficient of primary productivity ({\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}} for short) is the average of normalized {\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}} and {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}}; the normalization coefficient of redox condition ({\mathrm{R}\mathrm{e}\mathrm{d}\mathrm{o}\mathrm{x}}_{\mathrm{n}\mathrm{o}\mathrm{r}} for short) is the average of normalized V/Cr and V/(V + Ni); the normalization coefficient of water salinity ({\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}} for short) is the average of normalized Sr/Ba and m-value. Taking {\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}} as an example:

(6)\begin{array}{rl}{\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}}& ={\left[\right(\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}}-{\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{n}})/({\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{n}})\\ & +({\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}}-{\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{n}})/({\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{a}\mathrm{x}}-{\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{n}}\left)\right]/2,\end{array}

where P_bio is biological phosphorus, {\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{n}} is its minimum, and {\mathrm{P}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{a}\mathrm{x}} is its maximum; {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}} is biological uranium, {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{i}\mathrm{n}} is its minimum, and {\mathrm{U}}_{\mathrm{b}\mathrm{i}\mathrm{o}\mathrm{m}\mathrm{a}\mathrm{x}} is its maximum.

Using the conventional crossplot approach, it was found that the influence of each single factor on organic matter enrichment was not clear (Fig.9). This may be because organic matter enrichment in K₂qn¹ is the consequence of the integrated influence of numerous factors. Consequently an approach was used that incorporated numerous control factor indicators to jointly fit the measured TOC, and a multi-factor TOC correlation model was established. Each single element was used as an independent influencing factor when creating the correlation model since the correlation coefficients between any two factors were less than 0.7 (Fig.10). Due to the considerable differences in the values of the control factors, the data need to be preprocessed (minimum-maximum normalization) before fitting to improve the fitting effect for comparison. Appendices C1, C2, and C3 show the normalized data results for Unit A, Unit B, and Unit C, respectively. The minimum-maximum normalization is calculated as follows:

(7)X_{\mathrm{n}\mathrm{o}\mathrm{r}}=(X-X_{\mathrm{m}\mathrm{i}\mathrm{n}}) /(X_{\mathrm{m}\mathrm{a}\mathrm{x}}-X_{\mathrm{m}\mathrm{i}\mathrm{n}}),

where X is original value to be calculated, X_{\mathrm{n}\mathrm{o}\mathrm{r}} is normalized datum, X_{\mathrm{m}\mathrm{i}\mathrm{n}} is minimum, and X_{\mathrm{m}\mathrm{a}\mathrm{x}} is maximum.

In Unit A, normalized {\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}} is the most important control factor, followed by normalized {\mathrm{R}\mathrm{e}\mathrm{d}\mathrm{o}\mathrm{x}}_{\mathrm{n}\mathrm{o}\mathrm{r}}, normalized Ti/Al, and normalized Rb/K (Fig.11(a)). Normalized {\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}} is Unit B᾽s most essential control factor, and normalized Ti/Al follows (Fig.11(b)). The most important control factor in Unit C is normalized Rb/K, followed by normalized {\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}}, normalized C-value, and normalized {\mathrm{R}\mathrm{e}\mathrm{d}\mathrm{o}\mathrm{x}}_{\mathrm{n}\mathrm{o}\mathrm{r}} (Fig.11(c)). To improve the TOC correlation model᾽s accuracy, each control factor indicator with an importance greater than 0.1 was chosen for fitting.

Unit A᾽s TOC correlation model is as follows:

(8)\begin{array}{rl}{\mathrm{T}\mathrm{O}\mathrm{C}}_{\mathrm{M}\mathrm{o}\mathrm{d}\mathrm{e}\mathrm{l}}=& -0.283+3.522\times {\mathrm{A}}_1+1.424\times {\mathrm{A}}_2\\ & +2.417\times {\mathrm{A}}_3-1.762\times {\mathrm{A}}_4,\end{array}

where A₁ is normalized {\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}}, with larger values representing higher salinities; A₂ is normalized {\mathrm{R}\mathrm{e}\mathrm{d}\mathrm{o}\mathrm{x}}_{\mathrm{n}\mathrm{o}\mathrm{r}}, and larger values represent stronger reduction conditions; A₃ is normalized Ti/Al, with larger values representing higher terrigenous debris input; A₄ is normalized Rb/K, with larger values representing deeper water depth.

Unit A᾽s TOC_Model (fitted TOC) and TOC_Measured (measured TOC) fit well (R² = 0.8411; Fig.11(d)). From the model᾽s coefficient values, it is clear that organic matter enrichment is mainly influenced by lake water salinity in Unit A, and the marine transgression affects K₂qn¹᾽s salinity-controlled organic matter enrichment. Intruding seawater supplies nutrients to Unit A, which increases primary productivity and promotes organic matter enrichment. It also causes salinity stratification, establishing a reducing environment with high salinity at the lake bottom, which is beneficial to organic matter preservation. In Unit A, organic matter enrichment is also controlled by terrigenous debris input. Talbot (1988) showed that debris input dilutes organic matter, yet a moderate input of nutrient-rich detrital material with a weak dilution effect can increase primary productivity. Moderate terrigenous debris input in Unit A weakly dilutes organic matter enrichment and brings in some terrestrial organic matter, resulting in a higher organic matter concentration. However, increased water depth generally results in longer residence times of the organic matter in the water column and higher oxic degradation, which reduces organic matter abundance.

Unit B᾽s TOC correlation model is as follows:

(9){\mathrm{T}\mathrm{O}\mathrm{C}}_{\mathrm{M}\mathrm{o}\mathrm{d}\mathrm{e}\mathrm{l}}=1.282+1.516\times {\mathrm{B}}_1- 0.717\times {\mathrm{B}}_2,

where B₁ is normalized {\mathrm{P}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{v}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}}, with bigger values representing higher primary productivity; B₂ is normalized Ti/Al.

Unit B᾽s TOC_Model and TOC_Measured fit well (R² = 0.9483; Fig.11(e)). From the model᾽s coefficient values, it᾽s clear that primary productivity is the main influence on the enrichment of organic matter in Unit B. The higher the primary productivity, the more the organic matter is enriched. The constant invasion of Unit B by nutrient-rich saltwater fed planktonic organisms, leading to a large increase in primary productivity. The strongly reducing environment with high salinity and high sulfur inhibits the decomposition of algae and other organisms by bacteria, and sulfate reduction occurs in large amounts of metabolizable organic matter, forming stable biopolymers (Feng et al., 2011), which ensures Unit B᾽s good organic matter preservation. Unit B᾽s terrigenous debris input had a weak inhibitory effect on organic matter enrichment. Discussion 5.1 shows that the terrigenous debris input in this unit is low, therefore its inhibition effect on organic matter enrichment is weak and does not affect the enrichment of organic matter.

Unit C᾽s TOC correlation model is as follows:

(10)\begin{array}{rl}{\mathrm{T}\mathrm{O}\mathrm{C}}_{\mathrm{M}\mathrm{o}\mathrm{d}\mathrm{e}\mathrm{l}}& =2.687-1.345\times {\mathrm{C}}_1+0.704\times {\mathrm{C}}_2\\ & -0.597\times {\mathrm{C}}_3-0.207\times {\mathrm{C}}_4,\end{array}

where C₁ is normalized Rb/K; C₂ is normalized {\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{t}\mathrm{y}}_{\mathrm{n}\mathrm{o}\mathrm{r}}; C₃ is normalized {\mathrm{R}\mathrm{e}\mathrm{d}\mathrm{o}\mathrm{x}}_{\mathrm{n}\mathrm{o}\mathrm{r}}; and C₄ is normalized C-value, with higher values indicating a wetter climate.

Unit C᾽s TOC_Model and TOC_Measured fit well (R² = 0.9391; Fig.11(f)). Unit C has the lowest organic matter content, and the model᾽s coefficient values show that the deep water environment inhibits organic matter enrichment. Actually, increased water depth generally results in longer residence times of the organic matter in the water column and higher oxic degradation, which dilutes the organic matter concentration (Bohacs et al., 2000; Bohacs et al., 2005). In addition, the water depth in lakes is also heavily influenced by input from rivers, which are also influenced by overall rainfall levels. Thus, the humid climate that brings large amounts of rainfall also dilutes the concentration of organic matter in Unit C. Suitable water salinity promotes biological reproduction, and fast-growing benthic organisms consume oxygen, lowering the lake’s oxygen content. Simultaneously, benthic organisms᾽ biological activity can further destabilize the previously depositional environment (Wang et al., 1994; Wang et al., 2019). Finally, in Unit C, a reducing environment disturbed by benthic organisms forms, and organic matter cannot be properly preserved, resulting in a low organic matter content. Tab.1 lists the environmental characteristics of Units A, B, and C as well as their influences on organic matter enrichment.

5.3 Organic matter enrichment mechanism

A large-scale marine transgression occurred in Unit A. The invading seawater altered the lake water’s physicochemical properties, such as a sudden rise in salinity, which caused many freshwater organisms to die off suddenly due to salinity intolerance. However, it also brought abundant nutrients, which caused plankton blooms, greatly enhancing primary productivity. Additionally, the injection of seawater generated density stratification, which prevented exchange between top and bottom lake waters, so the lake bottom became oxygen-depleted, eventually forming black shale. Small amounts of terrestrial debris input slightly diluted the autochthonous organic matter while bringing in terrestrial organic matter, which may increase the organic matter content. The abundant organic matter was well-preserved and eventually formed the most organic-rich unit in K₂qn¹ (Fig.12(b)).

The black laminated shale was deposited in an anoxic environment with few or no benthic organisms. The continuous deposition of black laminated shale in Unit B also demonstrates that the basin bottom was anoxic and lacked benthic life. The decrease in the scale of the marine transgression decreased the abundance of nutrients transported into the lake system. However, these nutrients can still induce plankton blooms and increase the primary productivity of the lakes. Meanwhile, invading seawater causes lake water stratification and generates strong reducing environments at the lake bottom, which preserve organic matter due to a lack of exchange between top and bottom lake water. In addition, a modest amount of terrigenous debris input will not affect the depositional environment at the lake᾽s bottom, and an organic-rich unit will be formed in K₂qn¹ (Fig.12(c)).

The scale of marine transgression got smaller, the lake basin area of Unit C got smaller, and the rivers surrounding the basin advanced toward the lake᾽s center. Bottom currents and turbidity currents moved debris from shallow to deep water areas, generating numerous layers of argillaceous siltstone and dolomite with non-uniform thicknesses that separate the shale beds. River input dilutes the salinity of the lake, and benthic organisms multiply when lake salinity drops. Although the increased benthic organisms consume a huge quantity of oxygen and reduce the lake᾽s oxygen content, their biological activities would further disrupt the previously reducing deposition environment, resulting in a reducing environment disturbed by benthic organisms. Organic matter would not be well-preserved and the unit with the lowest organic matter content in K₂qn¹ was finally formed (Fig.12(d)).

6 Conclusions

In this work, the paleoenvironment evolutionary features in K₂qn¹ of the Gulong sag in the Songliao Basin are systematically studied, and the factors influencing the enrichment of organic matter are determined. As a result, the mechanism of organic matter enrichment in the K₂qn¹ is elucidated.

1) The cyclic variation of TOC content and elemental enrichment factor (EF) values, as well as the lithology variations, indicate that K₂qn¹ from bottom to top can be subdivided into three units, termed (from base to top) Units A, B, and C. Unit A has the highest TOC content and Unit C has the lowest. The analysis of elemental indicators shows that K₂qn¹ was deposited in a reducing brackish deep lake environment with a warm, humid climate and high primary productivity. From the bottom to the top of K₂qn¹, primary productivity decreases and then increases, reducing conditions increase initially, then decrease, lake water salinity gradually decreases, the climate gets warmer and more humid, terrigenous debris input decreases and then increases, and water depth gets shallower.

2) Based on the normalization coefficients, the correlation models of organic matter enrichment demonstrate that the organic enrichment in Unit A is mainly influenced by lake water salinity, and that the strong reducing environment and moderate terrigenous debris input can also enhance it. The organic enrichment in Unit B is mainly influenced by primary productivity, and the small input of terrigenous debris has little effect. The deep water environment and humid climate in Unit C both inhibit organic matter enrichment. Even though benthic organisms reduce the oxygen content of lake water, they also destroy the environment, resulting in the poor preservation of the organic matter.

3) A large-scale marine transgression occurred at the base of K₂qn¹ (Unit A). The nutrients carried by seawater promoted primary production, and the reducing environment due to density stratification enhanced organic matter preservation, resulting in the most enriched organic matter. The middle section (Unit B) lacked benthic bioturbation, and the high primary productivity and favorable preservation conditions resulted in organic matter enrichment. The lake shallowed and the salinity decreased in the upper interval of K₂qn¹ (Unit C). Benthic organisms multiplied rapidly, destroying the previously existing environment and resulting in poor organic matter preservation conditions and the lowest organic matter content.

7 Appendices

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