
==== Front
Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

39232110
71646
10.1038/s41598-024-71646-2
Article
Pore structure of the mixed sedimentary reservoir of Permian Fengcheng Formation in the Hashan area, Junggar Basin
Wang Yue 12
Chang Xiangchun xcchang@sdust.edu.cn

23
Zhang Guanlong 4
Zeng Zhiping 4
Huang Xinglong 1
Wang Ming 1
Ma Mingyong 1
1 Shandong Provincial Research Institute of Coal Geology Planning and Exploration, Jinan, 250104 China
2 https://ror.org/04gtjhw98 grid.412508.a 0000 0004 1799 3811 College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590 China
3 https://ror.org/026sv7t11 grid.484590.4 0000 0004 5998 3072 Laboratory for Marine Mineral Resources, Pilot National Laboratory for Marine Science and Technology, Qingdao, 266071 China
4 grid.418531.a 0000 0004 1793 5814 Research Institute of Petroleum Exploration and Development, Shengli Oilfield Company, Sinopec, Dongying, 257015 China
4 9 2024
4 9 2024
2024
14 2055619 5 2024
29 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
The Permian Fengcheng Formation (P1f.) in the Hashan area, situated on the southwestern margin of the Junggar Basin, has witnessed a remarkable breakthrough in shale oil exploration in recent years with nearly 789 million tons of shale oil resources. As a unique set of mixed sedimentary shales, the Fengcheng Formation in the Hashan area is characterized by mixed sedimentation of terrigenous siliciclastic sediments, authigenic minerals, and tuffaceous materials. However, the understanding of pore characteristics in the mixed sedimentary reservoir still remains limited, prohibiting accurate estimation of the oil content and insights into oil mobility. Scanning electron microscopy (SEM), X-ray diffraction (XRD), mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR), X-Ray Computer Tomography (X-CT), and geochemical analysis were performed to investigate the pore size distribution and main controlling factors of the mixed sedimentary reservoir. Results showed that the main pore types in the mixed sedimentary reservoir are intergranular pores and dissolution pores. The pores of the P1f. mixed shales in the Hashan area were classified into II-micropores (< 25 nm), I-micropores (25–100 nm), mesopores (100–1000 nm) and macropores (> 1000 nm). In general, the mixed sedimentary rocks of P1f. formation feature few macropores but a large number of micropores and mesopores. The CS exhibits the most favourable physical properties among all lithofacies. It is concluded that the abundance and maturity of organic matter, mineral composition, sedimentary structure, and diagenesis of reservoir together impact the pore structure in the mixed sedimentary reservoirs. The maturity of organic matter and the content of tuffaceous minerals are the most significant in influencing the pore structure of P1f. shales. Overall, the pore structure of complex lithologic reservoir formed by mixed deposition and its influence on physical properties are studied, and the characteristics of the microscopic pore-throat system of the dominant lithofacies in the Hashan area are clarified, which is of great significance as a guide for the exploration and development of mixed sedimentary reservoirs in continental shale oil in China.

Keywords

Mixed sedimentary shales
Pore structure
Lithofacies characteristics
Fengcheng Formation
Controlling factors
Subject terms

Geology
Sedimentology
National Natural Science Foundation of China42372160 Chang Xiangchun Shandong Province Natural Science Fund for Distinguished Young ScholarsJQ201311 Chang Xiangchun issue-copyright-statement© Springer Nature Limited 2024
==== Body
pmcIntroduction

As an important unconventional resource, the economic viability and vast potential sources of shale oil have garnered significant attention over the past decade, capturing global interest1–4. Shale reservoirs are typically characterized by low porosity and permeability, with the presence of heterogeneous pore structures being a common occurrence5,6, these factors significantly impede the exploration and development of shale oil7. Compared to North American shale oil, which is characterized by single lithology, separate source and reservoir, offshore deposition, and centralized distribution of sweet spots8–10, Chinese shale oil exhibits terrestrial multi-source mixed sedimentation, transition of sources and reservoirs, and decentralized distribution of sweet spots11.

The term “mixed sediment” normally refers to mixtures with the alternative occurrence of terrigenous clastic and carbonate components as interbedding or interlayers in space12–14. In general, mixed sedimentation is the basic characteristic of shale, which can exist in both marine and terrestrial strata15,16. Since the early 1980s, mixed sediments and mixed sedimentary rocks have gradually attracted the attention of scholars both domestically and internationally. Mixed sediments of shale oil reservoirs in the Luchaogou Formation of the Jimusar Depression are characterized by obvious mixed sedimentation of terrigenous clastic, carbonates and volcanic materials17. The mixed sedimentary rocks of the Shahezi Formation in the Lishu Fault Depression, southern Songliao Basin, are greatly affected by volcanic activities. Frequent volcanic activities led to the migration of nutrient elements, which promoted the propagation of algae in the water, increased the biological productivity and organic carbon content, and formed organic-rich mixed shale18. Previous studies on mixed sedimentary rocks have primarily focused on petrology and sedimentology, including diagenesis processes, depositional environment and facies models, as well as classification and definition schemes of the mixed sedimentary rocks19–21; some scholars have also examined sequence stratigraphic characteristics in mixed siliciclastic − carbonate depositional regimes22–24. However, the geological conditions vary greatly from basin to basin, resulting in different diagenetic events of mixed sedimentary rocks, and the corresponding diagenetic evolution and reservoir physical properties vary significantly25. During the sedimentary period of the Paleogene Shahejie Formation in Laizhou Bay Depression, volcanic activity was intense and the volcanics-lacustrine carbonate mixed sedimentation were developed. Influenced by volcanic eruption, a large number of feldspar soluble minerals were developed in the mixed sedimentary reservoir, which provided a good material basis for the late dissolution transformation26. The compositional components of the mixed sedimentary reservoir of Lucaogou Formation in Jimsar Sag include terrigenous felsic clastic, volcanic clastic, intra-basin clastic, carbonate minerals and clay minerals. The genesis of the mixed sedimentary rocks is mainly from the mother source, and its development is controlled by both sedimentary microfacies and event volcanic eruption17. The mixed sediments of shale oil reservoirs in the Fengcheng Formation of the Mahu Sag, Junggar Basin, is rich in oil and gas, with rapid lithofacies changes and many mineral types27. Mao et al.27 use the lithology scan logging method to form the lithology identification chart for the mixed sedimentary rocks of Fengcheng Formation, which provides a reference for logging lithology identification of mixed shale reservoirs. However, there are few studies about the characteristics and genesis of mixed shale reservoirs of Fengcheng Formation.

The Fengcheng Formation of the Hashan area, Junggar Basin, is the oldest alkaline lake deposit found in China, it is home to unconventional oil and gas potential28,29. At present, a major breakthrough has been made in shale oil exploration of Permian Fengcheng Formation in Mahu Sag, with proven tertiary reserves of shale oil resources up to 1.27 × 108t30, which has become a major shale oil exploration area. The Fengcheng Formation in the Hashan area is characterized by mixed sedimentation31–33. The deposition period was characterized by frequent volcanic eruptions and intensive tectonic activities, leading to the extensive distribution of volcanic and pyroclastic rocks. Macroscopically, the mixed sedimentary rock is lithologically complex, composed of terrigenous siliciclastic sediments, authigenic minerals, and tuffaceous materials. Microscopically, carbonate minerals, clay minerals, and organic matters are distributed in layers or masses34,35.

Shale oil reservoirs are characterized by low porosity, low permeability, and poor mobility, so how to select high-quality reservoirs is the key to commercial development of shale oil. Reservoir pore structure controls the porosity and mobility of shale oil reservoirs, which is an important basis for selecting shale oil rich areas. Pore type, size, and connectivity are all examined as part of the research of pore structure. High-resolution scanning electron microscopy (SEM) is the most direct means of analyzing the size of shale reservoir space, as it can show the pore types of shales visually and clearly through images36. MICP is a method to obtain pore information by injecting mercury into porous media with mercury injection instrument under high pressure. NMR is an important technique for evaluating the physical properties of shale reservoirs, which can effectively reveal the pore size distribution characteristics of reservoirs in the range of a few nanometres to hundreds of microns37. X-CT is a non-destructive detection technology, which can quantitatively and dynamically analyze the internal structure and fluid characteristics of rocks38. Accurately identifying and analyzing pore structures using only one method is challenging due to the different characteristics of the measurement methods and resolution limitations. Therefore, it is necessary to combine several testing methods. Zeng et al. conducted a preliminary study on shale pore types and reservoir control factors of Fengcheng Formation in the Hashan area through organic geochemical testing and scanning electron microscopy analysis33. Zhang et al.39 studied the favorable lithofacies and shale oil content of the Fengcheng Formation in the Hasan area, and initially established the shale oil enrichment model of the Fengcheng Formation in the Hasan area. So far, a detailed study of pore type, pore structure, and controlling factors of mixed sedimentary shale reservoirs in the Hashan area is still in vacancy.

Hashan area is located in the northwest of Mahu Sag. In recent years, SINOPEC's shale oil exploration in Fengcheng Formation in Hashan area has achieved good results, and the wells such as HSX1, HS1 and HS6 have obtained rich oil and gas, among which the HQ6 well has obtained the peak daily oil production of 6.28 m333, which revealed that the Fengcheng Formation in the Hashan area has a broad prospect for shale oil exploration. Investigating the Hashan area can significantly guide the selection of high-quality reservoirs in this region and provide a crucial foundation for understanding the characteristics of continental mixed sedimentary shale reservoirs. The purpose of this paper is to quantitatively characterize the pore structure of mixed shale reservoirs, and analyze the controlling factors of pore structure in combination with the mixed sedimentary characteristics in the Hashan area. This study employed thin section observation, X-ray diffraction (XRD), SEM, MICP, X-CT, and NMR to achieve a comprehensive characterization of mixed shale reservoirs.

Geological setting

The Junggar Basin is a typical large petroliferous basin in western China40,41 (Fig. 1a). The Hashan area, situated on the northwestern margin of the Junggar Basin, is encompassed by the Shixi Sag to the east, the Zhayier Mountains to the west, the Heshtologi Basin to the north, and the Wuxia fault belt to the south (Fig. 1b). The Hashan area covers an area of about 1600 km2 and is distributed in a NE-SW belt, with the general characteristics of high in the northeast and low in the southwest42,43.Fig. 1 (a) Location of the Junggar Basin in China; (b) Location of the Hashan area in northwestern margin of Junggar Basin; (modified after Wang et al.44) (c) Structural framework and major wells in the Hashan area; and (d) Generalized stratigraphic column of the Hashan area.

The present-day thrust nappe structure of the Hala'alate Mountain is a result of Hercynian to the Himalayan tectonic movements, and its tectonic evolution can be divided into four stages45,46. The first stage is from the late Carboniferous to the early Permian when severe collisional forces and multi-stage volcanic activities led to the formation of a northern nappe. The second stage is from the late Hercynian to the Indosinian (late Permian to the late Triassic) when the large nappe and thrust faults reactivated and some new secondary faults were created, the Hala'alate Mountain was uplifted again to take their shape. The third stage is from the Jurassic to the Cretaceous when tectonic activities weakened dramatically, and the slow subsidence led to the deposition of Jurassic and Cretaceous strata overlying the Triassic or ancient nappe strata. The fourth stage refers to the interval following the Cenozoic, when the Hala'alate Mountain underwent another uplift and a strike-slip adjustment.

The Permian Fengcheng Formation was deposited in an alkaline lake environment and has long been recognized as the high-quality source rock in the Junggar Basin47,48. The lower Permian Fengcheng Formation in the Hashan area can be divided into the lower (P1f1), middle (P1f2), and upper (P1f3) sections from bottom to top28. The Fengcheng Formation mainly consists of dark mudstone, dolomite, conglomerates, tuff, and sandstones (Fig. 1d). In the early Permian, the deposition environment of the Hashan area changed from marine to lacustrine conditions28,49. Volcanic and pyroclastic rocks are widely distributed due to frequent volcanic eruptions and intense tectonic activity50. As a consequence, the Fengcheng Formation exhibits a highly intricate lacustrine mixed sedimentation, encompassing dust, volcanic ash, and clasts derived from volcanic eruptions; terrigenous siliciclastic sediments resulting from weathering processes; as well as authigenic minerals precipitated from brine and shallow groundwater5.

Samples and experiments

In this study, total of 46 shale samples with different lithofacies were collected from four wells in the Hashan area as shown in Fig. 1c. The sampling depth of Well HS11 is from 3922.36 m to 3933.90 m. The sampling depths of Well HSX1 are 3345.10–3352.44 m, 3682.10–3684.18 m, and 3942.20–3942.26 m. The sampling depth of Well HQ6 is 1562.00–1563.50 m, 1918.60–1920.55 m, and 2697.43–2699.50 m; the sampling depth of Well HS1 is 2098.30–2103.10 m and 2152.00–2156.75 m. A relatively complete experimental project was performed, including the total organic carbon content (TOC), rock pyrolysis, XRD analysis, thin section observations, SEM, NMR, X-CT, and MICP.

TOC measurement

Shale core samples were cleaned and crushed to powder finer than 100 mesh, and approximately 1 g was soaked in hydrochloric acid to dissolve calcite minerals at room temperature for 3 h. The sample is then repeatedly rinsed with distilled water to neutrality, and dried for 12 h at 60–80 °C. Finally, the samples were put into LECO CS-230 instrument and analyzed following the national standards of the People’s Republic of China for the determination of TOC in sedimentary rock (GB/Y 19,145–2003).

(2) Rock–Eval analysis.

To conduct the Rock–Eval analysis, the shale core samples were crushed to 100 mesh. The Rock–Eval pyrolysis was performed using a Rock–Eval-VI instrument. S1 was determined at a constant temperature of 300 °C for 3 min, and subsequently the temperature was raised to 600 °C at a rate of 25 °C /min to obtain S2.

(3) X-ray Diffraction

Shale core samples were crushed to 200 mesh, the analysis was conducted using a Bruker X-ray diffractometer (XRD) equipped with Cu-Kα radiation source at a scanning angle of 25°. Stepped scanning measurements were conducted at a rate of 2°/min and with a step size of 0.02° 2θ. The analysis was performed under room temperature and relative humidity of 30%. The whole rock and clay minerals can be identified based on the relevant diffractograms, where the peaks of highest intensity provide a semi-quantitative abundance of mineral phases. The analysis was carried out in accordance with the criteria of the Chinese standard SY/T 5163–2010.

(4) Thin-section observations.

Thin-section observations were carried out using a Leica DM2500 microscope equipped with LED illumination and a digital camera detection system (LAS V4.2) to validate the mineral composition and lithologic characteristics of the core samples.

(5) Scanning Electron Microscopy

The shale samples for SEM tests were analyzed using a Phenom prox scanning electron microscope. The samples were cut parallel to the bedding surface, mounted on stubs, hand-polished, and subsequently argon-ion milled to obtain a flat surface. To quantitatively extract the relevant data of shale pore structure, the software Photoshop and Image J were employed to analyze SEM images51. The SEM images were processed through a three-step procedure (eg. Sample HSX1-14; Fig. 2): Firstly, the images were stitched together using Photoshop software (Fig. 2a). Secondly, the gray threshold values of pores in the SEM images were determined by comparing visual inspection with original images (Fig. 2b). Thirdly, the SEM images were converted into pore binary images (Fig. 2c). Finally, the pore size distribution curve was obtained (Fig. 2d).Fig. 2 Analysis process of pore size distribution obtained from SEM images.

(6) Mercury Injection Capillary Pressure (MICP)

The mercury injection capillary pressure (MICP) technique is commonly used for reservoir evaluation. The Laplace–Washburn (1921) equation describes the relationship between pressure and pore radius, allowing us to accurately determine the pore size distribution of samples based on the injection volume under increasing pressure. In this study, MICP analyses were conducted on shale cores following the SY/T 5346–2005 standard. The analyses were performed using the Micromeritics 9505 instrument under controlled conditions of a temperature of 16 °C, relative humidity of 50%, and atmospheric pressure. Mercury intrusion/extrusion curves were obtained for each sample at precise pressure intervals of 0.02e182 MPa, corresponding to pore radius ranges from 36.75 mm to 4.04 nm.

(7) Nuclear Magnetic Resonance (NMR)

For NMR analysis, we adopted the methodology of Zhang52 which denoted that T2 spectrum distribution corresponding to larger pore sizes exhibits longer relaxation times, whereas smaller pores exhibit shorter relaxation times. The NMR experiments were conducted using a Niumag (China) MicroMR23-060H-1 instrument, whose magnetic field strength measures 0.5 T at a frequency of 21.36 MHz, and was operated at 32 °C. The The measurement parameters were set as follows: waiting time = 3000 ms, echo number = 6000, echo time = 0.07 ms, and number of scans = 64.

(8) X-Ray Computer Tomography (X-CT)

X-CT is a powerful non-constructive technique used for accurately reflecting mineral composition, pores and cracks distribution. The MicroXCT-200 μm CT scanner produced by Xradia Corporation (United States) was used to scan the 25-mm-diameter plunger samples from the top to the bottom along the axial direction, and 1571 single images of 2048 × 2048 pixels were obtained for each scanning. The equipment involves a 150 kV/15W high power focus X-ray tube, and the maximum resolution is 1.0 μm. Then the 3D spatial distributions of various mineral composition could be reconstructed by superimposing these single images using ImageJ software. The dark blue part on the image of the digital cores represents pores and microfractures. However, due to the limitation of resolution, the X-CT scan cannot recognize some micropores that are too small.

Results and discussion

Lithofacies classification

The lithofacies classification of reservoirs is effective and significant to understand oil and gas exploration and development. Wang et al.53 identified and classified rocks of the P1f. formation in the Hashan area into five main types on the basement of the mineral composition, including dolomitic/calcareous shale (DS/CS), tuff-bearing dolomite (TD), dolomitic/calcareous tuffs (DT/CT), tuffaceous shale (TS), and argillaceous siltstone (AS). In addition, the lithofacies of mixed rocks can be divided into three categories according to the proportion of carbonate minerals, felsic minerals, and tuff in the sample: carbonate minerals (e.g. TD), terrestrial sedimentary rocks (e.g. AS, DS/CS, TS) and volcanic-sedimentary transitional rocks (e.g. DT/CT). In this study, we dig further to provide a more detailed lithologic description of the P1f. mixed sedimentary rocks, more factors are considered including color, sedimentary structure, and geochemical parameters.

The identification of sedimentary structures is an important basis for dividing lithofacies and analyzing their genesis21. Through the core observation and microscopic analysis, three types of sedimentary structure of the P1f. formation samples in the Hashan area can be identified, including laminated bedding (Fig. 3a, b), layered bedding (Fig. 3c, d), and massive bedding (Fig. 3e, f). The horizontally layered bedding and laminated structures indicate a stable deep-water sedimentary environment22. While the rapid accumulation of sediments that forms the massive bedding typically occurs in a strong hydrodynamic environment54. The core observation showed that laminated bedding only develops in CT, CS, and TS, all of which are dark grey or grey in color. Layered bedding develops in CS, TS, CT, and TD with dark grey or dark color, the laminae are mainly composed of dolomitic laminae and organic laminae. The massive samples, which make up more than 80% of the P1f. formation samples in the Hashan area, develop in all lithofacies (Fig. 4a).Fig. 3 Core photos of (a) laminated samples, (c) layered samples, and (e) massive samples of Fengcheng Formation, Hashan area. And the corresponding thin section observation images of them (b, d, f).

Fig. 4 Statistical diagram of (a) organic matter abundance types and (b) sedimentary structure types of P1f. shales in the Hashan area.

The TOC values of all samples vary from 0.12% to 5.13%, with an average of 1.17%. The majority of the samples from the P1f. formation exhibit a significant presence of organic matter and demonstrate moderate to high petroleum generative potential55. Among all lithofacies, the CS exhibits the highest TOC values, within the scope of 0.21–5.13%. Corresponding with the classification and evaluation criteria of enriched resources, low efficient resources, and ineffective resources52,56, the organic matter abundance of P1f. shale in the Hashan area can be divided into three categories: organic-rich (TOC > 2%), organic-moderate (1% < TOC < 2%), and organic-poor (TOC < 1%). The proportion of organic-rich, organic-moderate, and organic-poor samples is 16%, 35%, and 49%, respectively (Fig. 4b). Samples of AS, TD, and DT / CT have more organic-poor samples, half of the TS are organic-moderate samples, and CS has the most organic-rich samples of all lithofacies.

Taking mineral composition, sedimentary structure, and organic matter characteristics into account, the lithofacies classification comprising sedimentary structure + organic matter abundance + lithofacies is more accurate and reasonable for P1f. mixed sedimentary rocks in the Hashan area. Massive organic-poor DT, massive organic-poor AS, massive organic-poor DS, massive organic-moderate TS, massive organic-moderate CS, and massive organic-rich CS are the most common lithofacies of P1f. mixed sedimentary rocks in the Hashan area.

Petrological characteristics

The microscopic analysis revealed that the massive organic-poor AS mainly consists of plagioclase and clay minerals, exhibits a granular structure devoid of laminae or fractures, with a grain size larger than that observed in other lithofacies (Fig. 5a). CT is not common in the mixed sedimentary samples, and only one laminated organic-rich CT sample was found (Fig. 5b), it is characterized by black in color, compact lamina, plagioclase, and calcite are dominant mineral compositions. The massive organic-rich TS mainly consists of quartz, clay minerals, and plagioclase, the presence of quartz is obvious under the microscope because of its larger grain size (Fig. 5c). Figure 5d and e showed that the massive organic-rich DS and massive organic-moderate CS are mainly composed of quartz, dolomite/calcite, and clay minerals, no fractures developed, and some dissolution pores can be found under the microscope. The microscopic characteristics of layered organic-poor TD are distinct from other lithofacies due to the presence of a large amount of volcanic and pyroclastic rocks (Fig. 5f). Dolomite is the dominant mineral composition of laminae.Fig. 5 Optical photomicrographs of different lithofacies of P1f. mixed sedimentary rocks in the Hashan area. Stitched plane-polarized light photos of (a) massive organic-poor AS, HSX1-16, 3683.80 m (b) laminated organic-rich CT, HS1-4, 2099.20 m (c) massive organic-rich TS, HS1-7, 2100.73 m (d) massive organic-rich DS, HSX1-14, 3682.10 m (e) massive organic-moderate CS, HS1-6, 2100.40 m (f) layered organic-poor TD, HSX1-19, 3942.26 m.

The analysis of the physical properties of the mixed sedimentary reservoir in the Hashan area reveals that the porosity distribution predominantly falls below 10%, averaging at 4.45%. The permeability ranges from 0.02 to 10mD, with an average of 0.23mD. This reservoir can be classified as a typical ultra-low porosity and ultra-low permeability system.

Pore types

The SEM technique enables a comprehensive examination of the shale's pore morphology. Depending on the development locations of nanoscale pores, four pore types were recognized as follows: organic-matter pores (Fig. 6c), intragranular pores (Fig. 6a), including dissolution (Fig. 6d, e), cleavage, and intercrystalline pores (Fig. 6b), intergranular pores (Fig. 6f, g), and fracture pores (Fig. 6h). The most common pore types are intergranular pores and dissolution pores. For the laminated samples, the intergranular pores between calcite and clay minerals are the most common pore types, some fracture pores can also be found. For the layered samples, intragranular pores in the clay minerals are the dominant pore types, only a few fracture pores can be found under the microscope. In comparison to laminated and layered samples, the massive samples have a much lower number of pores. The most common pore types in the massive samples are dissolution pores in quartz and calcite, only small amounts of intergranular pores can be found.Fig. 6 The identification of pore types from the SEM images of the samples in the Hashan area. (a) HS1-2101.33 m, massive organic-moderate TS; (b) HSX1-3345.10 m, massive organic-rich CS; (c) HSX1-3349.20 m, massive organic-rich CS; (d) HSX1-3942.26 m, layered organic-poor dolomite containing pyroclastic rocks; (e) HQ6-2699.5 m, massive organic-moderate TD containing pyroclastic rocks; (f) HS1-2101.33 m, massive organic-moderate TS; (g) HS1-2099.90 m, laminated organic-moderate CT; (h) HS1-2156.20 m, layered organic-poor dolomite.

Classification of pore system based on MICP

MICP is an effective technique to qualitatively identify shale pores, the pore distribution differences can be reflected by the mercury intrusion curves. Through the analysis of 14 samples in the Hashan area, three typical mercury intrusion curves can be identified.

In the profiles of Type I mercury intrusion curves (Fig. 7a), one turning point T3 was recognized at mercury intrusion pressures of approximately 58.8 MPa. After reaching the T3 turning point, the profiles of Type I mercury intrusion curves present an “upward convex” shape, which reflects that higher mercury intrusion pressures contribute to a higher mercury intrusion rate. The pore size distribution of Type I shale is in a unimodal shape (Fig. 7d), most pore throat diameters are in the range of less than 20 nm, and the pore volume increases with the decrease of pore throat diameter. In the profiles of Type II mercury intrusion curves (Fig. 7b), two turning points T2 and T3 were recognized at mercury intrusion pressures of 14.7 MPa and 58.8 MPa, respectively. Between the turning points T2 and T3, the mercury intrusion rate reaches its maximum and then slowly decreases. The pore size distribution of Type II shale is in a unimodal shape with a peak of 30–100 nm (Fig. 7e). In the profiles of Type III mercury intrusion curves (Fig. 7c), three turning points T1, T2, and T3 were recognized at mercury intrusion pressures of 1.47 MPa, 14.7 MPa, and 58.8 MPa, respectively. Between the turning points T1 and T2, the mercury intrusion rate reaches its maximum. The pore size distribution of Type III shale is in a unimodal shape with a peak of approximately 100–500 nm (Fig. 7f). The Type III mercury intrusion curves of samples have the biggest pore throat diameter, which is the optimal type of all samples.Fig. 7 (a–c) Mercury intrusion/extrusion curves and (d–f) pore size distributions of mixed sedimentary rocks samples determined by MICP and the corresponding (g–i) fracture dimension (D) characteristics of shale pore throats.

From the base to the summit of the mercury intrusion curves, three distinct turning points (T1, T2, and T3) were discerned, effectively categorizing the pores into macropores (> 1000 nm in diameter), mesopores (100–1000 nm), I-micropores (25 ~ 100 nm), and II-micropores (< 25 nm; Table 1).Table 1 MICP pore structure parameters of P1f. shales.

Samples	Pore volume (cm3/g)	Surface area (m2/g)	Mean pore throat diameter (nm)	The proportion of different pore volume (%)	Mercury intrusion curves types	
II-micropores	I-micropores	Mesopores	Macropores	
HS11-1	0.08	19.41	14.00	11.59	1.00	7.40	80.02	I	
HS11-4	0.07	21.81	10.00	13.87	1.93	2.43	81.78	I	
HS11-7	0.04	11.11	10.00	18.71	4.64	5.13	71.51	I	
HS11-8	0.09	23.34	12.00	10.23	0.88	6.53	82.36	I	
HS11-9	0.09	29.01	10.00	10.83	1.50	1.90	85.77	I	
HS11-10	0.09	28.29	12.00	8.36	1.56	2.59	87.49	I	
HS11-11	0.14	42.86	12.00	7.77	2.48	3.03	86.73	I	
HS11-12	0.10	25.72	12.00	9.68	2.43	4.70	83.20	I	
HS11-14	0.09	29.54	8.00	10.39	3.43	2.85	83.33	I	
HS11-16	0.09	28.29	12.00	8.36	1.56	2.59	87.49	I	
HS11-5	0.10	17.59	38.00	7.68	3.91	43.29	45.12	II	
HS11-13	0.10	18.84	28.00	7.68	2.95	38.47	50.90	II	
HS11-2	0.09	9.42	82.00	16.18	35.34	23.58	24.90	III	
HS11-6	0.08	4.58	198.00	11.76	61.17	15.38	11.69	III	

Fractal dimension is widely used in the heterogeneity analysis of shale microscopic pore structure57. The fractal dimension was determined by analyzing the slope at which lg(1-SHg) intersects with lgPc58 (Fig. 7 g–i). The fitting results show that the MICP fractal presents segmental characteristics, four segments can be recognized and the correlation within each segment is good. Four segments proved that the fractal dimension of macropores, mesopores, I-micropores, and II-micropores are different, and classification of pore system based on MICP is feasible.

SEM pore size distribution

In this study, the SEM pore size distribution of 24 shale samples was analyzed by the software ImageJ (Table 2). The range of surface porosity is between 2.37% and 9.97%, with an average of 4.32%. The mean pore diameter ranges from 254.97 nm to 1845.15 nm, with an average of 766.67 nm. The pore size distribution of P1f. mixed sedimentary rocks in the Hashan area is dominated by mesopores, the range of which is between 40.69% and 83.99% (66.3% on average). Among the three pore types, the proportion of micropores is the lowest, with the range of 1.29–34.39% (13.89% on average). The proportion of macropores ranges from 2.12 to 52.11% (19.8% on average).Table 2 SEM pore extraction parameters of P1f. shales.

Lithofacies	Samples	Image number	Resolution (nm)	Gray threshold values	Surface porosity (%)	Mean pore diameter (nm)	The proportion of pores (%)	
Micropores	Mesopores	Macropores	
CS	HSX1-7	16	32.76	64	7.37	783.47	10.29	71.98	17.74	
HSX1-13	24	32.76	91	3.66	347.75	18.02	79.32	2.66	
HSX1-11	24	32.76	71	6.77	543.72	23.24	59.63	16.81	
HS11-1	20	32.76	50	9.97	1124.32	10.98	57.90	31.12	
TD	HS1-16	24	32.76	93.00	2.37	585.00	11.15	78.57	10.28	
HQ6-20	24	32.76	81.00	5.01	628.73	16.13	68.69	15.18	
HS11-5	20	32.76	74	4.94	1195.20	12.15	48.95	38.89	
TS	HS1-8	24	32.76	87.00	3.25	565.07	14.13	75.97	9.89	
HS11-12	16	32.76	82.00	4.73	732.46	15.20	60.47	24.34	
HQ6-3	16	32.76	61.00	5.76	508.80	8.86	82.11	9.03	
DS	HSX1-14	24	32.76	74	5.20	787.11	10.43	71.34	18.23	
HQ6-14	24	32.76	83.00	3.54	495.28	8.79	83.99	7.22	
DT	HSX1-17	24	32.76	99	2.43	405.97	15.22	79.40	5.38	
HS11-10	16	32.76	83.00	3.77	588.01	18.98	64.02	17.00	
HS11-14	16	32.76	85.00	3.18	542.04	25.99	60.99	13.02	
HS11-16	16	32.76	81.00	2.59	1354.54	7.47	42.37	50.16	
HS11-4	16	32.76	49.00	4.66	1632.69	1.29	50.18	48.53	
HS11-7	20	32.76	60.00	4.69	1845.15	7.20	40.69	52.11	
HS11-9	16	32.76	85.00	2.55	398.68	20.20	76.57	3.23	
CT	HS11-13	16	32.76	89.00	2.46	1313.52	8.89	48.48	42.63	
HS1-5	25	32.76	86.00	3.35	791.73	9.94	66.63	23.43	
AS	HQ6-6	25	32.76	76	4.55	528.23	9.49	80.94	9.57	
HS1-11	22	32.76	80.00	4.41	447.70	14.88	78.46	6.66	
HSX1-18	24	32.76	90	2.52	254.97	34.39	63.49	2.12	

The pore diameter distribution characteristics of different lithofacies are also different (Fig. 8). The lithofacies with the smallest average pore diameter is AS, which is only 410.30 nm (254.97–528.23 nm). The average pore diameter of CT is the biggest among all lithofacies, which is 1052.63 nm.Fig. 8 SEM pore extraction parameters of P1f. shales.

The pore size distribution of AS is dominated by mesopores and micropores, and the proportion of macropores is the lowest (6.12% on average) among all lithofacies. In all fine-grained lithofacies, CS has the highest micropore proportion, with an average of 15.63%. DS has the highest mesopore proportion, with an average of 77.67%. DT has the highest macropore proportion, with an average of 33.03%. The mean surface porosity of CS is the highest, with an average of 6.94% (3.66%–9.97%). CT and DT have the lowest mean surface porosity among all lithofacies, which is 2.91% and 3.41% on average, respectively. The results show that the increase of macropore proportion is conducive to the increase of average pore diameter, and the increase of micropore proportion is conducive to the increase of mean surface porosity.

It has been proved that SEM, affected by image resolution, will underestimate the proportion of micropores and macropores, and is more suitable for characterizing the pore size distribution characteristics of mesopores (100–1000 nm)51.

NMR pore size distribution

It’s theoretically proved that NMR measurement can provide an accurate porosity of petroleum reservoir59, and NMR porosity (φN) is commonly calculated by a model based on the amplitude of T2 spectrum59,60. The NMR porosity of 46 shale samples from Fengcheng Formation ranges from 0.21% to 6.58%, with an average value of 2.57%, the porosity of more than 85% samples is less than 5% (Fig. 9a; Table 3). The φN of CS ranges from 0.24% to 6.58%, which is the highest among all lithofacies (3.76% on average; Fig. 9b). The φN of DS and DT is also high, with the average of 3.31% and 1.65%, respectively. CT has the lowest φN among all lithofacies, with an average of 1.1%.Fig. 9 (a) NMR porosity frequency distribution and (b) NMR porosity distribution of different lithofacies of P1f. shales in the Hashan area.

Table 3 NMR T2 spectra parameters of P1f. shales.

Sample number	Lithofacies	φN (%)	Porosity of T2 spectra peak (%)	Proportion of T2 spectra peak (%)	
p1	p2	p3	p1	p2	p3	
HQ6-1	Organic-poor CS	4.33	0.48	3.66	0.08	11.41	86.64	1.95	
HQ6-5	4.37	0.14	3.79	0.45	3.23	86.57	10.20	
HSX1-13	3.35	0.85	3.23	0.37	19.09	72.58	8.32	
HQ6-2	4.32	0.47	3.77	0.09	10.77	87.26	1.98	
HSX1-7	Organic-moderate CS	6.52	0.67	5.11	0.74	10.22	78.45	11.33	
HS1-6	0.24	0.02	0.19	0.03	7.42	78.94	13.64	
HS1-14	1.60	0.36	0.96	0.24	22.86	61.71	15.43	
HS11-1	1.56	0.06	1.23	0.24	19.58	55.65	24.78	
HSX1-1	Organic-rich CS	3.71	1.21	2.02	0.48	32.65	54.49	12.86	
HSX1-2	3.01	0.97	1.65	0.30	33.26	56.61	10.13	
HSX1-4	6.58	1.97	3.46	0.93	30.96	54.36	14.68	
HSX1-8	3.82	0.39	3.27	0.17	41.22	41.22	17.56	
HSX1-11	5.43	0.47	4.27	0.69	8.70	78.63	12.66	
HQ6-3	Organic-poor TS	4.27	0.35	3.70	0.12	42.50	42.50	14.99	
HQ6-10	2.91	0.09	2.57	0.25	3.18	88.33	8.48	
HS1-8	Organic-moderate TS	0.48	0.13	0.29	0.06	27.86	60.29	11.85	
HS11-12	0.18	0.05	0.10	0.03	25.81	57.69	16.50	
HS1-17	2.24	0.27	1.62	0.29	12.26	74.57	13.17	
HS1-7	Organic-rich TS	0.94	0.17	0.60	0.14	18.64	65.64	15.72	
HQ6-8	Organic-poor AS	2.64	0.10	2.31	0.23	3.82	87.36	8.82	
HSX1-12	2.29	0.13	1.65	0.51	5.69	72.03	22.29	
HSX1-16	0.88	0.08	0.66	0.13	9.28	76.10	14.62	
HS1-11	1.53	0.06	1.23	0.24	3.66	80.46	15.88	
HS1-15	0.46	0.05	0.34	0.05	11.53	76.19	12.28	
HQ6-12	Organic-poor DS	2.24	0.21	1.93	0.10	9.33	86.19	4.48	
HQ6-14	2.44	0.15	2.16	0.13	6.09	88.54	5.37	
HQ6-15	5.59	0.03	4.54	1.26	0.55	77.88	21.57	
HQ6-9	Organic-moderate DS	5.53	2.11	3.00	0.42	38.19	54.27	7.54	
HS1-12	0.63	0.13	0.43	0.05	20.81	70.53	8.67	
HSX1-14	Organic-rich DS	3.45	0.85	2.47	0.13	24.63	71.47	3.91	
HQ6-13	Organic-poor DT	3.24	0.47	2.55	0.22	14.55	78.66	6.79	
HQ6-16	4.04	0.03	4.54	1.26	0.55	77.88	21.57	
HS11-16	0.19	0.05	0.09	0.06	24.62	46.18	29.20	
HSX1-15	2.38	0.03	2.11	0.24	1.42	88.63	9.95	
HSX1-17	1.54	0.10	1.31	0.09	6.40	87.60	6.00	
HS11-2	1.71	0.08	0.94	0.69	4.66	55.23	40.11	
HS11-8	0.21	0.01	0.13	0.08	2.94	60.23	36.82	
HQ6-19	Organic-moderate DT	1.01	0.18	0.35	0.49	17.38	34.45	48.17	
HS11-13	0.51	0.15	0.28	0.08	28.66	55.19	16.15	
HSX1-6	Organic-poor CT	1.27	0.05	1.07	0.12	4.03	86.50	9.47	
HS1-2	Organic-moderate CT	1.28	0.08	0.98	0.22	6.19	76.68	17.12	
HS1-3	0.97	0.19	0.53	0.23	19.61	55.81	24.58	
HS1-13	1.52	0.42	0.91	0.19	27.85	59.89	12.26	
HS1-4	Organic-rich CT	0.44	0.04	0.27	0.11	9.10	63.99	26.91	
HS1-16	Organic-poor dolomite	0.44	0.02	0.29	0.13	5.53	64.61	29.86	
HQ6-20	Organic-moderate dolomite	2.11	0.36	1.43	0.32	17.10	67.87	15.03	

NMR T2 spectrum can effectively reflect the distribution characteristics of reservoir pores. NMR T2 spectra were measured for 46 cores and shown as solid lines in Fig. 10. The T2 spectra of samples show three peaks, i.e., p1 at 0.01–0.5 ms, p2 at 0.5–20 ms, and p3 at > 20 ms, which is corresponding to the micropores, mesopores, and macropores, respectively47. For most P1f. shales, the amplitude of the p3 peak is lower than the p1 and p2 peaks, which denotes that the samples have few macropores but large number of micropores and mesopores. The NMR T2 curves of different lithofacies are also shown in Fig. 10. The p2 and p3 peaks of organic-poor samples (blue lines) are generally higher, while their p1 peaks are lower. It shows that organic-poor samples are dominated by mesopores and macropores, while the organic-rich samples (red lines) and organic-moderate samples (green lines) are dominated by micropores and mesopores.Fig. 10 NMR T2 spectra of mixed sedimentary rocks samples. (organic-poor samples in blue lines, organic-moderate samples in green lines, and organic-rich samples in red lines.)

The samples with different pore structures have different T2 spectrum parameters. The geometric mean value of the T2 spectrum (T2,gm) is the key parameter to characterize the pore structure of shale and reflect the overall characteristics of the T2 spectrum distribution. The T2,gm of 46 samples vary from 1.23 ms to 44.01 ms with an average of 4.94 ms. There is a good correlation between T2,gm and p1 peak porosity, a higher p1 peak porosity contributes to a higher proportion of micropores and a smaller T2,gm value (Fig. 11a). The value of T2,gm is quite different between different lithofacies, and the T2,gm of DT and TD are obviously higher than the other lithofacies, indicating that the proportion of micropores is low in DT and TD (Fig. 11b).Fig. 11 (a) T2,gm distribution of different lithofacies of P1f. shales and (b) Relationship between T2,gm and p1 peak porosity of P1f. shales.

X-CT

Based on the X-ray CT scanning imaging data, shale pores were recognized and extracted using Image J software. The results show that the X-CT 3D reconstruction images can reflect the 3D spatial distribution of pores and fractures in shale reservoirs (Fig. 12), which provides a reference for the study of the microscopic pore structure of different lithofacies.Fig. 12 X-CT 3D reconstruction of pores in P1f. shales. (a) HS11-3922.36 organic-moderate massive CS; (b) HQ6-1563.50 organic-poor massive TS; (c) HS1-2101.33 organic-moderate massive TS; (d) HS11-3926.15 organic-moderate massive DT; (e) HS1-2099.90 organic-moderate laminated CT; (f) HSX1-3942.26 organic-moderate layered dolomite containing pyroclastic rocks.

The X-CT 3D digital core shows that the heterogeneity of CS samples (Fig. 12a) is weak, the pore space is very developed and evenly distributed, the connectivity between pores is good, large cracks are not developed. The pore space of TS (Fig. 12b, c) is developed, and the pores is evenly distributed in Fig. 12b. In Fig. 12c, the cracks and pores are developed along the lamina in the sample. The heterogeneity of DT (Fig. 12d) is weak, large cracks are not developed, and the connectivity between pores is good. The pores of CT sample (Fig. 12e) are mostly developed along the laminae, and the content of large pores is high, the overall heterogeneity of sample is strong. The pore distribution of the dolomite containing pyroclastic rocks samples (Fig. 12f) is heterogeneous, large fractures are not developed, and the samples are dominated by micropores with an overall low pore content.

Pore structure characteristics of different lithofacies

The main pore types of CS are intergranular pores between quartz and intergranular pores between carbonate minerals, with few organic matter pores visible. The surface porosity was the highest among all lithofacies, ranging from 3.66% to 9.97% (6.94% on average). And the SEM mean pore diameter ranged from 347.75 nm to 1125.32 m (699.82 nm on average). The NMR porosity was also the highest among all lithofacies, ranging from 0.24 to 6.58% (3.76% on average). The heterogeneity of CS is weak and the pore connectivity is good. The proportion of mesopore is the highest and macropores is the lowest in CS.

The main pore types of DS are intergranular pores between quartz and dissolution pores in carbonate minerals, some pyrite intercrystalline pores are visible. The average surface porosity is 4.37%, and the SEM mean pore size ranges from 495.28 nm to 787.11 nm (641.20 nm on average); the NMR porosity is second only to that of CS, ranging from 0.63 to 5.59% (3.31% on average). The proportion of mesopore is the highest and macropores is the lowest in DS.

The main pore types of TS are intergranular pores between quartz and dissolution pores in the quartz. The surface porosity ranged from 3.25 to 5.76% (4.58% on average), SEM mean pore diameter ranged from 508.9 to 732.46 nm (602.11 nm on average). NMR porosity ranged from 0.18 to 4.27% (1.84% on average). The proportion of mesopore is the highest and macropores is the lowest in TS. The heterogeneity of TS is strong, and fractures and pores are mostly developed along the laminae.

The main pore types of TD are dissolution pores in carbonate minerals and dissolution pores in the quartz. The surface porosity ranged from 2.37 to 5.01% (4.11% on average), and the SEM mean pore diameter ranged from 585.0 to 1195.2 nm (802.98 nm on average). The NMR porosity was low, with an average of 1.28%. The proportion of mesopore is the highest and micropores is the lowest in TD.

The pore types of DT are dominated by intergranular pores in the quartz and dissolution pores in the quartz, with surface porosity ranging from 2.43% to 4.69% (3.41% on average), SEM mean pore diameters ranging from 398.68 to 1845.15 nm (966.73 nm on average), with a lower average surface porosity and larger mean pore diameters, which indicates a higher proportion of macropores. NMR porosity ranges from 0.19% to 4.04%, with an average value of 1.65%. The proportion of mesopore is the highest and micropores is the lowest in DT. The heterogeneity of DT is weak, and the connectivity between the pores is good.

The main pore types of CT are intergranular pores in the quartz and dissolution pores in the carbonate minerals, with the lowest surface porosity, while the SEM mean pore diameter is the largest among all lithofacies, with an average value of 2.91% and 1052.63 nm, respectively, indicating that the contribution of macropores is higher. NMR porosity is the lowest of all lithofacies, averaging only 1.1%. The proportion of mesopore is the highest and micropores is the lowest in CT. The heterogeneity of CT is strong, and the pores are mostly developed along the laminae.

The pore types of AS were dominated by dissolution pores in carbonate minerals and pyrite intercrystalline pores, with surface porosity ranging from 2.52 to 4.55% (3.83% on average). The SEM mean pore diameters is the lowest among all lithofacies, ranging from 254.97 to 528.23 nm (410.3 nm on average), which denoted a very low proportion of macropores. The NMR porosities is low, ranging from 0.46 to 2.64% (The average is only 1.56%). The mesopores account for the majority of the pores in AS.

The comparison indicates that CS exhibits the most optimal pore characteristics in the mixed shale reservoirs of the Fengcheng Formation. The SEM mean pore size of CS is notably large, and the pore connectivity is good. CS also exhibits the highest surface porosity and NMR porosity. DS is only second to CS, while AS has the least favorable pore structure. The results show that terrestrial sedimentary rocks (CS/DS) are more likely to exhibit a higher surface porosity and NMR porosity.

Controlling factors of pore structure

TOC

TOC is an important parameter affecting the pore structure of shale. TOC content is positively correlated with the average pore diameter obtained by SEM and MICP methods (Fig. 13a, b), indicating that the average pore diameter of P1f. shales increases with the increase of organic matter abundance. SEM surface porosity, NMR porosity and peak p1 porosity are positively correlated with TOC (Fig. 13c–e), while the correlation between peak p2, peak p3 porosity and TOC is very weak (Fig. 13f, g). The results show that the increase of TOC is beneficial to the development of shale pores, especially micropores, but has little influence on mesopores and macropores.Fig. 13 Relationship between TOC versus (a) SEM average pore diameter (b) MICP average pore diameter (c) SEM porosity (d) NMR porosity (e) p1 peak porosity (f) p2 peak porosity (g) p3 peak porosity of P1f. shales. And relationship between porosity versus (h) Ro (i) quartz (j) tuffaceous mineral of P1f. shales.

Jarvie et al.61 proposed that the development of shale pores is linked to the maturity of organic matter. The Ro values (vitrinite reflectance) of P1f. shales in Hashan area range from 0.67% to 0.8%, and the organic matter is mainly in a low maturity stage. As maturity increases, the porosity of P1f. shales gradually rises (Fig. 13h), with Ro showing a positive correlation with porosity. This can be attributed to the dissolution of unstable minerals by organic acids produced during thermal evolution, resulting in numerous dissolution pores and increased storage capacity. On the other hand, the abnormal high pressure generated in the process of hydrocarbon generation and expulsion of organic matter can also lead to the opening of fractures and promote the development of reservoir pores37. Because the degree of organic matter thermal evolution is generally low, organic matter pores formed by kerogen pyrolysis and hydrocarbon generation are rarely seen in shales. In a word, the presence of organic matter favors the development of reservoir pores in the P1f. shales.

Mineral composition

Changes in the composition and content of minerals will lead to differences in the physical properties of the reservoir space, thereby impacting pore development. The mineral composition and content were obtained from XRD analysis. The quartz content of P1f. shale minerals is positively correlated with the porosity, suggesting that the increase of quartz is conducive to the development of shale pores (Fig. 13i). Tuffaceous mineral content and porosity was found to be roughly negative (Fig. 13j), indicating that high tuffaceous mineral content has a strong inhibition on the development of pores. From the perspective of lithofacies, the pores of shale samples (CS/DS/TS) are well developed, and the porosity of them is high, which is related to the high quartz content in the mineral composition. However, the porosity of tuffaceous samples (CT/DT) are generally low, which is influenced by tuffaceous minerals.

Both quartz and tuffaceous minerals play an important role in controlling the development of shale pore structure. This is because quartz, as a rigid particle, has a strong anticompaction ability, the increase of quartz content can enhance the compaction resistance of the reservoir, so that more pores would be preserved during the burial process. Figure 14 shows that the change trend of micropore content (p1 peak) in P1f. shales is similar to that of quartz content and porosity, indicating that the increase of quartz content is conductive to the development of micropores.Fig. 14 Comprehensive map of NMR porosity and mineral composition of P1f. shales.

The particle size of tuffaceous minerals (mainly composed of volcanic ash and other detrital materials) is small, most of them are in porphyry-like structures, the large minerals are filled with small minerals, and only small amounts of residual intergranular pores were found in the tuffaceous minerals. Moreover, the chemical properties of tuffaceous minerals are stable, which makes it hard to form dissolution pores, resulting in a strong inhibition of the development of pores.

In addition, the influence of carbonate minerals on pores is reflected in that when the content of dolomite + calcite is less than 40%, the increase of carbonate minerals will promote the development of pores. When the content of dolomite + calcite is higher than 40%, the increase of carbonate minerals will inhibit the development of pores (Fig. 14). This is because calcites are rigid minerals, which are easy to form rigid skeletons, the skeletons can resist compaction and retain pores. Meanwhile,  carbonate minerals are unstable and easy to form dissolution pores, which is also conducive to the development of pores. However, a large number of carbonate mineral aggregates tend to form extensive calcareous cementation, resulting in a decrease in the overall porosity of the reservoir, which is not conducive to the preservation of pores.

Sedimentary structure

The development of sedimentary structure also affects the pore structure of shale, laminated samples often develop more pores. Under the microscopic observation, it was found that minerals in the laminated samples are arranged directionally (Fig. 15a), and more intergranular pores are developed (Fig. 15b). At the same time, many microfractures are developed in the laminated samples, which can promote the interconnectivity of pores and greatly improve the permeability of the reservoir. The layered samples are denser than laminated samples (Fig. 15c), with fewer pores and microfractures, and the massive samples have the poorest reservoir physical properties (Fig. 15d).Fig. 15 Diagenesis characteristics of P1f. shales under SEM. (a) HS1-2099.90 m, laminated CT; (b) intergranular pores in HQ6-1919.60 m, laminated AS; (c) HSX1-3942.26 m, layered dolomite containing pyroclastic rocks, siliceous cementation; (d) HS1-2101.33 m, massive TS, carbonate cementation; (e) HS1-2156.20 m, layered dolomite, dissolution pores in the dolomite; (f) HQ6-1563.50 m, massive TS, dissolution pores in the quartz.

Diagenesis

The P1f. shales are in the immature to low mature stage of organic matter evolution, and the reservoir is in the early stage of diagenes. Diagenesis, including compaction, cementation and dissolution, will directly affect the pore structure characteristics of shale and lead to the change of reservoir physical properties.

Compaction is the main factor for the decrease of reservoir porosity in the early diagenetic stage. Under the compaction of the overlying strata, the contact between the rock particles becomes tighter. By decreasing the pore volume between rock particles, compaction destroys the primary intergranular pores. The fluid in the pores is squeezed and discharged, the number and volume of pores are reduced, resulting in the reduction of reservoir physical properties. In the process of compaction, the degree of plastic deformation of quartz is relatively low, and the existence of such rigid particles can support the skeleton, which is conducive to retaining the primary intergranular pores.

Carbonate cementation and siliceous cementation are widespread in shale reservoirs of Fengcheng Formation. A large number of intergranular pores are filled and blocked (Fig. 15c–e), pore connectivity decreases rapidly, and the pore structure of the reservoir is destroyed. During the diagenetic process, the P1f. shales were affected by multiple phases of volcanic activities, which formed a large amount of alkaline pore fluids and promoted the formation of carbonate cementation.

Dissolution is very common in P1f. shales, usually caused by acidic solutions produced by diagenesis and organic acids produced during the thermal evolution of organic matter. Dissolution pores are usually developed within or at the periphery of unstable minerals like calcite and dolomite (Fig. 15f). These pores exhibit small diameters and are predominantly dispersed. Volcanic activities have elevated the formation temperature, thereby promoting the maturation of the hydrocarbon source rocks, and generating more organic acids and CO2, which led to an increase in the porosity of P1f. shales, and enhanced their reservoir physical properties.

In summary, the development of pore structure of P1f. shales in Hashan area is controlled by the abundance and maturity of organic matter, mineral composition, sedimentary structure, and diagenesis. Among them, organic matter, mineral composition and diagenesis have obvious influence on the P1f. shales, and the maturity of organic matter and the content of tuffaceous minerals are the most important factors affecting the pore structure of P1f. shales. The increase of organic matter abundance promotes the development of micropores, while increased maturity enhances shale reservoir space. The increase of quartz content is beneficial to the development of shale pores, while the increase of tuffaceous mineral content will hinder the development of pores. Diagenesis is complex and significantly impacts the structure and physical characteristics of reservoir space.

Conclusions

An integrated investigation was conducted to examine the pore structure of the mixed sedimentary shales in the Hashan area, Junggar Basin, through a comprehensive analysis of petrological observations, organic geochemistry, SEM observation, X-CT, MICP, and NMR T2 spectra. Some preliminary conclusions are as follows.The most common pore types of P1f. shales in the Hashan area are intergranular pores in the quartz, dissolution pores in the quartz and dissolution pores in the carbonate minerals.

A classification has been established to subdivide the pore system of the P1f. mixed shales in the Hashan area, and the pores were classified into II-micropores (< 25 nm), I-micropores (25–100 nm), mesopores (100–1000 nm) and macropores (> 1000 nm).

The pore size distribution of P1f. shales in the Hashan area is characterized by a high proportion of mesopores, with macropores and micropores representing the second and lowest proportions, respectively. The CS exhibits the most favourable physical properties among all lithofacies, with the highest surface porosity and NMR porosity, while the physical properties of AS are the least favourable.

The development of pore structure of P1f. shales in Hashan area is controlled by the abundance and maturity of organic matter, mineral composition, sedimentary structure, and diagenesis. Among the aforementioned factors, the maturity of organic matter and the content of tuffaceous minerals are the most significant in influencing the pore structure of P1f. shales.

Acknowledgements

This study was co-funded by the National Natural Science Foundation of China (Grant No. 42372160, 42072172), Shandong Province Natural Science Fund for Distinguished Young Scholars (Grant No. JQ201311). We express our gratitude to the Shengli Oilfield Company of Sinopec for granting permission to publish.

Author contributions

Y.W.: Methodology, Figure plotting, Writing—Original Draft. X.C.: Conceptualization, Writing—Review & Editing. G.Z.: Data Duration, Resources. Z.Z.: Formal analysis. X.H. & M.W. & M.M.: Writing—Review & Editing.

Data availability

The data generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare no competing interests.

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
==== Refs
References

1. Cui JF Cheng L A theoretical study of the occurrence state of shale oil based on the pore sizes of mixed Gaussian distribution Fuel. 2017 206 564 571 10.1016/j.fuel.2017.06.047
Cui, J. F. & Cheng, L. A theoretical study of the occurrence state of shale oil based on the pore sizes of mixed Gaussian distribution. Fuel. 206, 564–571 (2017).10.1016/j.fuel.2017.06.047
2. Liu B Geochemical characterization and quantitative evaluation of shale oil reservoir by two-dimensional nuclear magnetic resonance and quantitative grain fluorescence on extract: A case study from the Qingshankou Formation in Southern Songliao Basin, northeast China Mar. Pet. Geol. 2019 109 561 573 10.1016/j.marpetgeo.2019.06.046
Liu, B. et al. Geochemical characterization and quantitative evaluation of shale oil reservoir by two-dimensional nuclear magnetic resonance and quantitative grain fluorescence on extract: A case study from the Qingshankou Formation in Southern Songliao Basin, northeast China. Mar. Pet. Geol. 109, 561–573 (2019).10.1016/j.marpetgeo.2019.06.046
3. Bai CY Yu BS Han SJ Shen ZH Characterization of lithofacies in shale oil reservoirs of a lacustrine basin in eastern China: Implications for oil accumulation J. Petrol. Sci. Eng. 2020 195 107907 10.1016/j.petrol.2020.107907
Bai, C. Y., Yu, B. S., Han, S. J. & Shen, Z. H. Characterization of lithofacies in shale oil reservoirs of a lacustrine basin in eastern China: Implications for oil accumulation. J. Petrol. Sci. Eng. 195, 107907 (2020).10.1016/j.petrol.2020.107907
4. Wang BY Liu B Yang JG Bai LH Li SC Compatibility characteristics of fracturing fluid and shale oil reservoir: A case study of the first member of Qingshankou Formation, northern Songliao Basin Northeast China J. Petrol. Sci. Eng. 2022 211 110161 10.1016/j.petrol.2022.110161
Wang, B. Y., Liu, B., Yang, J. G., Bai, L. H. & Li, S. C. Compatibility characteristics of fracturing fluid and shale oil reservoir: A case study of the first member of Qingshankou Formation, northern Songliao Basin Northeast China. J. Petrol. Sci. Eng. 211, 110161 (2022).10.1016/j.petrol.2022.110161
5. Yu KH Cao YC Qiu LW Sun PP The hydrocarbon generation potential and migration in an alkaline evaporite basin: The Early Permian Fengcheng Formation in the Junggar Basin, northwestern China Mar. Pet. Geol. 2018 98 12 32 10.1016/j.marpetgeo.2018.08.010
Yu, K. H., Cao, Y. C., Qiu, L. W. & Sun, P. P. The hydrocarbon generation potential and migration in an alkaline evaporite basin: The Early Permian Fengcheng Formation in the Junggar Basin, northwestern China. Mar. Pet. Geol. 98, 12–32 (2018).10.1016/j.marpetgeo.2018.08.010
6. Chen D shale oil potential and mobility of low-maturity lacustrine shales: Implications from NMR analysis in the Bohai Bay Basin Energy Fuels. 2021 35 2209 2223 10.1021/acs.energyfuels.0c03978
Chen, D. et al. shale oil potential and mobility of low-maturity lacustrine shales: Implications from NMR analysis in the Bohai Bay Basin. Energy Fuels. 35, 2209–2223 (2021).10.1021/acs.energyfuels.0c03978
7. Gong L Quantitative prediction of natural fractures in shale oil reservoirs Geofluids. 2021 3 1 15
Gong, L. et al. Quantitative prediction of natural fractures in shale oil reservoirs. Geofluids. 3, 1–15 (2021).
8. Abarghani A Gentzis T Liu B Khatibi S Bubach B Preliminary investigation of the effects of thermal maturity on redox-sensitive trace metal concentration in the bakken source Rock, North Dakota, USA ACS Omega. 2020 5 7135 7148 10.1021/acsomega.9b03467 32280854
Abarghani, A., Gentzis, T., Liu, B., Khatibi, S. & Bubach, B. Preliminary investigation of the effects of thermal maturity on redox-sensitive trace metal concentration in the bakken source Rock, North Dakota, USA. ACS Omega. 5, 7135–7148 (2020).32280854 10.1021/acsomega.9b03467
9. Bai LH Distribution characteristics and oil mobility thresholds in lacustrine shale reservoir: Insights from N2 adsorption experiments on samples prior to and following hydrocarbon extraction Pet. Sci. 2022 19 2 486 497 10.1016/j.petsci.2021.10.018
Bai, L. H. et al. Distribution characteristics and oil mobility thresholds in lacustrine shale reservoir: Insights from N2 adsorption experiments on samples prior to and following hydrocarbon extraction. Pet. Sci. 19(2), 486–497 (2022).10.1016/j.petsci.2021.10.018
10. Ozotta O Pore structure alteration of organic-rich shale with Sc-CO2 exposure: The bakken formation Energy Fuels. 2021 35 5074 5089 10.1021/acs.energyfuels.0c03763
Ozotta, O. et al. Pore structure alteration of organic-rich shale with Sc-CO2 exposure: The bakken formation. Energy Fuels. 35, 5074–5089 (2021).10.1021/acs.energyfuels.0c03763
11. Yang ZF Tang Y Guo XG Huang LL Chang QS Diagenesis and reservoir space types of alkaline lake-type shale in Fengcheng Formation of Mahu Sag, Junggar Basin China Arabian J. Geosci. 2021 14 2356 10.1007/s12517-021-08634-7
Yang, Z. F., Tang, Y., Guo, X. G., Huang, L. L. & Chang, Q. S. Diagenesis and reservoir space types of alkaline lake-type shale in Fengcheng Formation of Mahu Sag, Junggar Basin China. Arabian J. Geosci. 14, 2356 (2021).10.1007/s12517-021-08634-7
12. Zhang XH Classification and origin of mixosedimentite Geol. Sci. Technol. Inf. 2000 19 4 31 34
Zhang, X. H. Classification and origin of mixosedimentite. Geol. Sci. Technol. Inf. 19(4), 31–34 (2000) (in Chinese with English abstract).
13. Liu HM Wang Y Yang YH Zhang S Sedimentary environment and lithofacies of fine-grained hybrid sedimentary in Dongying Sag: A case of fine-grained sedimentary system of the Es4 Earth. Sci. 2020 45 10 3543 3555
Liu, H. M., Wang, Y., Yang, Y. H. & Zhang, S. Sedimentary environment and lithofacies of fine-grained hybrid sedimentary in Dongying Sag: A case of fine-grained sedimentary system of the Es4. Earth. Sci. 45(10), 3543–3555 (2020) (in Chinese with English abstract).
14. Zhang JY Sun ML Liu GD Cao Z Kong YH Geochemical characteristics, hydrocarbon potential, and depositional environment evolution of fine-grained mixed source rocks in the Permian Lucaogou Formation, Jimusaer Sag Junggar Basin Energy Fuels. 2021 35 264 282 10.1021/acs.energyfuels.0c02500
Zhang, J. Y., Sun, M. L., Liu, G. D., Cao, Z. & Kong, Y. H. Geochemical characteristics, hydrocarbon potential, and depositional environment evolution of fine-grained mixed source rocks in the Permian Lucaogou Formation, Jimusaer Sag Junggar Basin. Energy Fuels. 35, 264–282 (2021).10.1021/acs.energyfuels.0c02500
15. Li TT Zhu RK Bai B Wang CX Li TF Characteristics of mixed sedimentary reservoir: Taking the Lower Cretaceous mixed sedimentary rock of Qingxi depression in Jiuquan Basin as an example Acta. Sedimentol. Sin. 2016 33 2 376 384
Li, T. T., Zhu, R. K., Bai, B., Wang, C. X. & Li, T. F. Characteristics of mixed sedimentary reservoir: Taking the Lower Cretaceous mixed sedimentary rock of Qingxi depression in Jiuquan Basin as an example. Acta. Sedimentol. Sin. 33(2), 376–384 (2016) (in Chinese with English abstract).
16. Luo NN Sedimentary model of mixed rocks in the Upper Es3 of Paleogene in the Dawangzhuang Area, Raoyang Sag Bohai Bay Basin. Acta. Sedimentol. Sin. 2020 38 5 1037 1048
Luo, N. N. et al. Sedimentary model of mixed rocks in the Upper Es3 of Paleogene in the Dawangzhuang Area, Raoyang Sag. Bohai Bay Basin. Acta. Sedimentol. Sin. 38(5), 1037–1048 (2020) (in Chinese with English abstract).
17. Wang J Genesis and pore development characteristics of Permian Lucaogou migmatites, Jimsar Sag Junggar Basin. Pet. Geol. Exp. 2022 44 3 413 424
Wang, J. et al. Genesis and pore development characteristics of Permian Lucaogou migmatites, Jimsar Sag. Junggar Basin. Pet. Geol. Exp. 44(3), 413–424 (2022) (in Chinese with English abstract).
18. Li YH Hybrid sedimentary conditions of organic-rich shales in faulted lacustrine basin during volcanic eruption episode: A case study of Shahezi formation (K1sh Fm) Lishu faulted depression south Songliao Basin Earth Sci. 2022 47 5 1728 1747
Li, Y. H. et al. Hybrid sedimentary conditions of organic-rich shales in faulted lacustrine basin during volcanic eruption episode: A case study of Shahezi formation (K1sh Fm) Lishu faulted depression south Songliao Basin. Earth Sci. 47(5), 1728–1747 (2022) (in Chinese with English abstract).
19. Sha QA Discussion on mixing deposit and hunji rock J. Palaeogeogr. 2001 3 3 63 66
Sha, Q. A. Discussion on mixing deposit and hunji rock. J. Palaeogeogr. 3(3), 63–66 (2001).
20. Liu GH The effect of tuffaceous material on characteristics of different lithofacies: A case study on Lucaogou Formation fine-grained sedimentary rocks in antanghu Basin J. Pet. Sci. Eng. 2019 179 355 377 10.1016/j.petrol.2019.04.072
Liu, G. H. et al. The effect of tuffaceous material on characteristics of different lithofacies: A case study on Lucaogou Formation fine-grained sedimentary rocks in antanghu Basin. J. Pet. Sci. Eng. 179, 355–377 (2019).10.1016/j.petrol.2019.04.072
21. Yang Z Division of fine-grained rocks and selection of “sweet sections” in the oldest continental shale in China: Taking the coexisting combination of tight and shale oil in the Permian Junggar Basin Mar. Pet. Geol. 2019 109 339 348 10.1016/j.marpetgeo.2019.06.010
Yang, Z. et al. Division of fine-grained rocks and selection of “sweet sections” in the oldest continental shale in China: Taking the coexisting combination of tight and shale oil in the Permian Junggar Basin. Mar. Pet. Geol. 109, 339–348 (2019).10.1016/j.marpetgeo.2019.06.010
22. Liu GH Hydrocarbon distribution pattern and logging identification in lacustrine fine-grained sedimentary rocks of the Permian Lucaogou Formation from the Santanghu basin Fuel. 2018 222 207 231 10.1016/j.fuel.2018.02.123
Liu, G. H. et al. Hydrocarbon distribution pattern and logging identification in lacustrine fine-grained sedimentary rocks of the Permian Lucaogou Formation from the Santanghu basin. Fuel. 222, 207–231 (2018).10.1016/j.fuel.2018.02.123
23. Zhang JY Characteristics and formation mechanism of multi-source mixed sedimentary rocks in a saline lake, a case study of the Permian Lucaogou Formation in the Jimusaer Sag, northwest China Mar. Pet. Geol. 2019 102 704 724 10.1016/j.marpetgeo.2019.01.016
Zhang, J. Y. et al. Characteristics and formation mechanism of multi-source mixed sedimentary rocks in a saline lake, a case study of the Permian Lucaogou Formation in the Jimusaer Sag, northwest China. Mar. Pet. Geol. 102, 704–724 (2019).10.1016/j.marpetgeo.2019.01.016
24. Wan L Dai LM Tang GM Hao YW Gao XL Multi-Scale characterization and evaluation of pore-throat combination characteristics of lacustrine mixed rock reservoir Earth Sci. 2020 45 10 3841 3852
Wan, L., Dai, L. M., Tang, G. M., Hao, Y. W. & Gao, X. L. Multi-Scale characterization and evaluation of pore-throat combination characteristics of lacustrine mixed rock reservoir. Earth Sci. 45(10), 3841–3852 (2020) (in Chinese with English abstract).
25. Bian WH Hornung J Liu ZH Wang PJ Hinderer M Sedimentary and palaeoenvironmental evolution of the Junggar Basin, Xinjiang Northwest China Palaeobio. Palaeoenv. 2010 90 175 186 10.1007/s12549-010-0038-9
Bian, W. H., Hornung, J., Liu, Z. H., Wang, P. J. & Hinderer, M. Sedimentary and palaeoenvironmental evolution of the Junggar Basin, Xinjiang Northwest China. Palaeobio. Palaeoenv. 90, 175–186 (2010).10.1007/s12549-010-0038-9
26. Liu XJ Wang QB Dai LM Liu SL Hao YW Reservoir characteristics and formation mechanisms of lacustrine Carbonate and volcanics mixing sediments Laizhouwan Sag Earth Sci. 2020 45 10 3579 3588
Liu, X. J., Wang, Q. B., Dai, L. M., Liu, S. L. & Hao, Y. W. Reservoir characteristics and formation mechanisms of lacustrine Carbonate and volcanics mixing sediments Laizhouwan Sag. Earth Sci. 45(10), 3579–3588 (2020) (in Chinese with English abstract).
27. Mao R Shen ZM Zhang H Chen SH Fan HT Lithology identification for diamictite based on lithology scan logging: A case study on Fengcheng formation Mahu Sag Xinjiang Petrol. Geol. 2022 43 6 743 749
Mao, R., Shen, Z. M., Zhang, H., Chen, S. H. & Fan, H. T. Lithology identification for diamictite based on lithology scan logging: A case study on Fengcheng formation Mahu Sag. Xinjiang Petrol. Geol. 43(6), 743–749 (2022) (in Chinese with English abstract).
28. Zhang GY Characteristics of lacustrine dolomitic rock reservoir and accumulation of tight oil in the Permian Fengcheng Formation, the western slope of the Mahu Sag, Junggar Basin NW China J. Asian Earth Sci. 2019 178 64 80 10.1016/j.jseaes.2019.01.002
Zhang, G. Y. et al. Characteristics of lacustrine dolomitic rock reservoir and accumulation of tight oil in the Permian Fengcheng Formation, the western slope of the Mahu Sag, Junggar Basin NW China. J. Asian Earth Sci. 178, 64–80 (2019).10.1016/j.jseaes.2019.01.002
29. Tang Y Source rock evaluation and hydrocarbon generation model of a Permian alkaline lakes—A case study of the Fengcheng Formation in the Mahu Sag Junggar Basin Minerals 2021 11 644 10.3390/min11060644
Tang, Y. et al. Source rock evaluation and hydrocarbon generation model of a Permian alkaline lakes—A case study of the Fengcheng Formation in the Mahu Sag Junggar Basin. Minerals 11, 644 (2021).10.3390/min11060644
30. Tao KY Geochemistry and origin of natural gas in the petroliferous Mahu sag, northwestern Junggar Basin, NW China: Carboniferous marine and Permian lacustrine gas systems Organic Geochem. 2022 100 62 79 10.1016/j.orggeochem.2016.08.004
Tao, K. Y. et al. Geochemistry and origin of natural gas in the petroliferous Mahu sag, northwestern Junggar Basin, NW China: Carboniferous marine and Permian lacustrine gas systems. Organic Geochem. 100, 62–79 (2022) ((in Chinese with English abstract)).10.1016/j.orggeochem.2016.08.004
31. Jia FJ Sedimentary facies and depositional model of Permian Fengcheng Formation in Kexia Area of northwest margin of Junggar Basin Fault-Block Oil & Gas Field 2016 23 6 681 686
Jia, F. J. Sedimentary facies and depositional model of Permian Fengcheng Formation in Kexia Area of northwest margin of Junggar Basin. Fault-Block Oil & Gas Field 23(6), 681–686 (2016) (in Chinese with English abstract).
32. Yu HZ Geochemical characteristics of dolomite rocks reservoir of Fengcheng Formation in Hashan block, the Northern Junggar Basin J. Northeast Petrol. Univ. 2019 43 1 1 9
Yu, H. Z. Geochemical characteristics of dolomite rocks reservoir of Fengcheng Formation in Hashan block, the Northern Junggar Basin. J. Northeast Petrol. Univ. 43(1), 1–9 (2019) (in Chinese with English abstract).
33. Zeng ZP Shale oil reservoir characteristics and controlling factors of Permian Fengcheng Formation in Hashan area, northwestern margin of Junggar Basin Lithol. Reservoirs. 2023 35 1 25 35
Zeng, Z. P. et al. Shale oil reservoir characteristics and controlling factors of Permian Fengcheng Formation in Hashan area, northwestern margin of Junggar Basin. Lithol. Reservoirs. 35(1), 25–35 (2023) (in Chinese with English abstract).
34. Yang YJ Mixed sedimentary characteristics and controlling factors of Upper Ordovician Sangtamu Formation in Tarim Basin Geol. Rev. 2011 57 2 185 192
Yang, Y. J. et al. Mixed sedimentary characteristics and controlling factors of Upper Ordovician Sangtamu Formation in Tarim Basin. Geol. Rev. 57(2), 185–192 (2011) (in Chinese with English abstract).
35. Ma K Pore throat characteristics of fine-grained mixed deposits in shale oil reservoirs and their control on reservoir physical properties: A case study of the Permian Lucaogou Formation, Jimsar Sag Junggar Basin. Oil & Gas Geol. 2022 43 5 1194 1205
Ma, K. et al. Pore throat characteristics of fine-grained mixed deposits in shale oil reservoirs and their control on reservoir physical properties: A case study of the Permian Lucaogou Formation, Jimsar Sag. Junggar Basin. Oil & Gas Geol. 43(5), 1194–1205 (2022) (in Chinese with English abstract).
36. Lu H Zhao AK Tang HM Lu LZ Jiang LP Pore characterization and its controlling factors in the WufengLongmaxi Shale of North Guizhou Southwest China. Energy Fuels. 2020 34 15763 15772 10.1021/acs.energyfuels.0c02169
Lu, H., Zhao, A. K., Tang, H. M., Lu, L. Z. & Jiang, L. P. Pore characterization and its controlling factors in the WufengLongmaxi Shale of North Guizhou. Southwest China. Energy Fuels. 34, 15763–15772 (2020).10.1021/acs.energyfuels.0c02169
37. Iqbal O Padmanabhan E Mandal A Dvorkin J Characterization of geochemical properties and factors controlling the pore structure development of shale gas reservoirs J. Petrol. Sci. Eng. 2021 206 109001 10.1016/j.petrol.2021.109001
Iqbal, O., Padmanabhan, E., Mandal, A. & Dvorkin, J. Characterization of geochemical properties and factors controlling the pore structure development of shale gas reservoirs. J. Petrol. Sci. Eng. 206, 109001 (2021).10.1016/j.petrol.2021.109001
38. Li YR Pore structure characteristics and their controlling factors of deep shale: a case study of the Lower Silurian Longmaxi Formation in the Luzhou Area Southern Sichuan Basin ACS Omega. 2022 7 14591 14610 10.1021/acsomega.1c06763 35557656
Li, Y. R. et al. Pore structure characteristics and their controlling factors of deep shale: a case study of the Lower Silurian Longmaxi Formation in the Luzhou Area Southern Sichuan Basin. ACS Omega. 7, 14591–14610 (2022).35557656 10.1021/acsomega.1c06763
39. Zhang KH Shale dominant lithofacies and shale oil enrichment model of Lower Permian Fengcheng Formation in Hashan area Junggar Basin Petrol. Geol. & Exp. 2023 45 4 593 605
Zhang, K. H. et al. Shale dominant lithofacies and shale oil enrichment model of Lower Permian Fengcheng Formation in Hashan area Junggar Basin. Petrol. Geol. & Exp. 45(4), 593–605 (2023).
40. Imin A Accumulation mechanism and controlling factors of the continuous hydrocarbon plays in the Lower Triassic Baikouquan Formation of the Mahu Sag, Junggar Basin China. J. Nat. Gas Geosci. 2016 1 309 318
Imin, A. et al. Accumulation mechanism and controlling factors of the continuous hydrocarbon plays in the Lower Triassic Baikouquan Formation of the Mahu Sag, Junggar Basin. China. J. Nat. Gas Geosci. 1, 309–318 (2016).
41. Wu HG A unique lacustrine mixed dolomitic-clastic sequence for tight oil reservoir within the middle Permian Lucaogou Formation of the Junggar Basin, NW China: Reservoir characteristics and origin Mar. Petrol. Geol. 2016 76 115 132 10.1016/j.marpetgeo.2016.05.007
Wu, H. G. et al. A unique lacustrine mixed dolomitic-clastic sequence for tight oil reservoir within the middle Permian Lucaogou Formation of the Junggar Basin, NW China: Reservoir characteristics and origin. Mar. Petrol. Geol. 76, 115–132 (2016).10.1016/j.marpetgeo.2016.05.007
42. Dong CQ Exploration results of permian system in Hashan area Spec. Oil Gas Reserv. 2014 21 5 52 54
Dong, C. Q. Exploration results of permian system in Hashan area. Spec. Oil Gas Reserv. 21(5), 52–54 (2014) (in Chinese with English abstract).
43. Wang SZ Wu QQ Cheng SW Xue Y Chen P Hydrocarbon transmission system and accumulation in Hala’alat mountain structural belt in the northern Margin of Junggar Basin Acta. Sedimentol. Sin. 2017 35 2 405 412
Wang, S. Z., Wu, Q. Q., Cheng, S. W., Xue, Y. & Chen, P. Hydrocarbon transmission system and accumulation in Hala’alat mountain structural belt in the northern Margin of Junggar Basin. Acta. Sedimentol. Sin. 35(2), 405–412 (2017).
44. Wang Y Chang XC Liu ZQ Shi BB Zhang PF Xu YD New insights on the petroleum migration and accumulation in the basal conglomerate reservoir of Cretaceous Qingshuihe Formation of Yongjin area Central Junggar Basin Geol. J. 2021 56 9 4429 4450 10.1002/gj.4192
Wang, Y. et al. New insights on the petroleum migration and accumulation in the basal conglomerate reservoir of Cretaceous Qingshuihe Formation of Yongjin area Central Junggar Basin. Geol. J. 56(9), 4429–4450 (2021).10.1002/gj.4192
45. Zhang Z Xu GS Yuan HF Wang C Fan L Characteristics and controlling factors of Carboniferous volcanic reservoir in Hashan area of Junggar basin J. Northeast Petrol. Univ. 2013 37 4 39 46
Zhang, Z., Xu, G. S., Yuan, H. F., Wang, C. & Fan, L. Characteristics and controlling factors of Carboniferous volcanic reservoir in Hashan area of Junggar basin. J. Northeast Petrol. Univ. 37(4), 39–46 (2013) (in Chinese with English abstract).
46. Lin HX Guo RC Gong YJ Chen ZH Zeng ZP Geochemical characteristics of crude oil and cogenetic-Bidirectional charging effect in Hashan area Spec. Oil Gas Reserv. 2017 24 2 35 39
Lin, H. X., Guo, R. C., Gong, Y. J., Chen, Z. H. & Zeng, Z. P. Geochemical characteristics of crude oil and cogenetic-Bidirectional charging effect in Hashan area. Spec. Oil Gas Reserv. 24(2), 35–39 (2017) (in Chinese with English abstract).
47. Ma ZJ Geochemical characteristics and source correlation of biodegraded oils from the Western Halaalate Area Geochimica. 2020 49 5 549 562
Ma, Z. J. et al. Geochemical characteristics and source correlation of biodegraded oils from the Western Halaalate Area. Geochimica. 49(5), 549–562 (2020) (in Chinese with English abstract).
48. Wang S Wang GW Huang LL Song LT Zhang YL Logging evaluation of lamina structure and reservoir quality in shale oil reservoir of Fengcheng Formation in Mahu Sag China. Mar. Petrol. Geol. 2021 133 105299 10.1016/j.marpetgeo.2021.105299
Wang, S., Wang, G. W., Huang, L. L., Song, L. T. & Zhang, Y. L. Logging evaluation of lamina structure and reservoir quality in shale oil reservoir of Fengcheng Formation in Mahu Sag. China. Mar. Petrol. Geol. 133, 105299 (2021).10.1016/j.marpetgeo.2021.105299
49. Cao J Ancient high-quality alkaline lacustrine source rocks discovered in the Lower Permian Fengcheng Formation Junggar Basin Acta. Petrolei. Sinica. 2015 36 7 781 790
Cao, J. et al. Ancient high-quality alkaline lacustrine source rocks discovered in the Lower Permian Fengcheng Formation Junggar Basin. Acta. Petrolei. Sinica. 36(7), 781–790 (2015) (in Chinese with English abstract).
50. Zhu SF Genesis and hydrocarbon significance of vesicular welded tuffs: A case study from the Fengcheng Formation, Wu-Xia area, Junggar Basin NW China. Pet. Explor. Dev. 2012 39 2 173 183 10.1016/S1876-3804(12)60030-5
Zhu, S. F. et al. Genesis and hydrocarbon significance of vesicular welded tuffs: A case study from the Fengcheng Formation, Wu-Xia area, Junggar Basin. NW China. Pet. Explor. Dev. 39(2), 173–183 (2012).10.1016/S1876-3804(12)60030-5
51. Zhang PF Comparisons of SEM, Low-Field NMR, and Mercury Intrusion Capillary Pressure in characterization of the pore size distribution of lacustrine shale: A case study on the Dongying Depression, Bohai Bay Basin China Energy Fuels. 2017 31 9232 9239 10.1021/acs.energyfuels.7b01625
Zhang, P. F. et al. Comparisons of SEM, Low-Field NMR, and Mercury Intrusion Capillary Pressure in characterization of the pore size distribution of lacustrine shale: A case study on the Dongying Depression, Bohai Bay Basin China. Energy Fuels. 31, 9232–9239 (2017).10.1021/acs.energyfuels.7b01625
52. Zhang, P.F. Research on Shale Oil Reservoir, Occurrence and Movability using Nuclear Magnetic Resonance (NMR). China University of Petroleum Doctoral Dissertation. (2019).
53. Wang Y Occurrence state and oil content evaluation of Permian Fengcheng Formation in the Hashan area as constrained by NMR and multistage Rock-Eval Pet. Sci. 2023 20 1363 1378 10.1016/j.petsci.2022.11.019
Wang, Y. et al. Occurrence state and oil content evaluation of Permian Fengcheng Formation in the Hashan area as constrained by NMR and multistage Rock-Eval. Pet. Sci. 20, 1363–1378 (2023).10.1016/j.petsci.2022.11.019
54. Luo, Sedimentary pattern of the Shaofanggou Formation in the North Santai high area of the eastern Junggar Basin and its control on reservoir development Spec. Oil Gas Reserv. 2023 30 9 18
Luo, et al. Sedimentary pattern of the Shaofanggou Formation in the North Santai high area of the eastern Junggar Basin and its control on reservoir development. Spec. Oil Gas Reserv. 30, 9–18 (2023) (in Chinese with English abstract).
55. Peters KE Cassa MR Applied source rock geochemistry AAPG Memoir. 1994 60 93 120
Peters, K. E. & Cassa, M. R. Applied source rock geochemistry. AAPG Memoir. 60, 93–120 (1994).
56. Lu SF Several key issues and research trends in evaluation of shale oil Acta. Petrolei. Sinica. 2016 37 10 1309 1322
Lu, S. F. et al. Several key issues and research trends in evaluation of shale oil. Acta. Petrolei. Sinica. 37(10), 1309–1322 (2016) (in Chinese with English abstract).
57. Gao WZ Characterization on structure and fractal of shale nanopore: A case study of Fengcheng formation in Hashan area, Junggar Basin China Processes. 2023 11 677 10.3390/pr11030677
Gao, W. Z. et al. Characterization on structure and fractal of shale nanopore: A case study of Fengcheng formation in Hashan area, Junggar Basin China. Processes. 11, 677 (2023).10.3390/pr11030677
58. Wang JY Guo SB Study on the relationship between hydrocarbon generation and pore evolution in continental shale from the Ordos Basin China. Pet. Sci. 2021 18 1305 1322 10.1016/j.petsci.2021.01.002
Wang, J. Y. & Guo, S. B. Study on the relationship between hydrocarbon generation and pore evolution in continental shale from the Ordos Basin. China. Pet. Sci. 18, 1305–1322 (2021).10.1016/j.petsci.2021.01.002
59. Coates, G.R., Xiao, L.Z. & Prammer, M.G. NMR Logging Principles and Applications; Halliburton Energy Services: Houston, TX. pp. 36−52 (1999).
60. Dunn, K.J., Bergman, J.D. & Latorraca, A.G. Nuclear magnetic resonance: Petrophysical and logging applications. Handbook of Geophysical Exploration: Seismic Exploration, Pergamon. 32, 197-245 (2002).
61. Jarvie DM Hill RJ Ruble TE Pollastro RM Unconventional shale gas systems: The Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment AAPG Bulletin. 2007 91 4 475 499 10.1306/12190606068
Jarvie, D. M., Hill, R. J., Ruble, T. E. & Pollastro, R. M. Unconventional shale gas systems: The Mississippian Barnett Shale of north-central Texas as one model for thermogenic shale-gas assessment. AAPG Bulletin. 91(4), 475–499 (2007).10.1306/12190606068
