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Article

Study on the Key Factors Controlling Oil Accumulation in a Multi-Source System: A Case Study of the Chang 9 Reservoir in the Triassic Yanchang Formation, Dingbian Area, Ordos Basin, China

by
Zishu Yong
1,
Jingong Zhang
1,*,
Jihong Li
1,
Baohong Shi
2,
Zhenze Wang
1 and
Feifei Wang
3
1
State Key Laboratory of Continental Dynamics, Department of Geology, Northwest University, Xi’an 710069, China
2
College of Earth Sciences & Engineering, Xi’an Shiyou University, Xi’an 710065, China
3
Geological Research Institute of CNPC Greatwall Drilling Company, Panjin 124214, China
*
Author to whom correspondence should be addressed.
Minerals 2025, 15(3), 303; https://doi.org/10.3390/min15030303
Submission received: 30 January 2025 / Revised: 5 March 2025 / Accepted: 13 March 2025 / Published: 15 March 2025
(This article belongs to the Section Mineral Exploration Methods and Applications)
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Abstract

:
Reservoir evaluation in multi-source systems is challenging because studies generally follow single-source principles. This limitation has substantially hindered the understanding of reservoir and hydrocarbon accumulation processes in source–reservoir systems. This study examines the Dingbian area of the Ordos Basin, China, and investigates the key factors controlling hydrocarbon accumulation in the Chang 9 reservoir of the Triassic Yanchang Formation within a multi-source system. The study area spans approximately 0.9 × 104 km2. First, by comparing the biological markers in Chang 9 crude oil with those of potential source rocks, the oil source of the Chang 9 reservoir was identified. The study area was subsequently divided into three provenance zones—northeast, northwest, and central mixed source areas—based on heavy mineral content and the orientation of sedimentary sand bodies. Additionally, well logging data, oil production data, petrographic thin sections, scanning electron microscopy (SEM), and mercury injection porosimetry were used to investigate the reservoir characteristics, oil reservoir features, and crude oil properties across different source areas. The results indicate that the oil source of the Chang 9 reservoir in the Dingbian area is the Upper Chang 7 source rock. The northwest source area exhibits superior reservoir properties compared to the other two zones. In the northwest source area, lithology-structure oil reservoirs are predominant, whereas the central mixed source area is characterized by structural-lithology oil reservoirs, and the northeast source area predominantly features lithology-controlled reservoirs. From the northwest to the central mixed source areas, and finally to the northeast source area, crude oil density and viscosity increase gradually, while the degree of oil–water separation decreases correspondingly. Based on these findings, the study concludes that the distribution of structures, lithology, and source rocks significantly influences the Chang 9 reservoirs in the Dingbian area. The controlling factors of oil reservoirs differ across the various source zones. In multi-source systems, evaluating oil reservoirs based on source zones provides more precise insights into the characteristics of reservoirs in each area. This approach provides more accurate guidance for exploration and development in multi-source regions, as well as for subsequent “reserve enhancement and production increase” strategies.

1. Introduction

Previous studies on the sedimentary characteristics and reservoirs of deltaic deposits in small- to medium-scale source–reservoir systems generally followed a single-source model [1,2,3]. However, applying this approach to a deltaic depositional system controlled by multiple sources can introduce bias, as it tends to overlook the multifaceted influences of multiple sources on sedimentary facies and reservoir properties. The study of reservoirs in multi-source systems through well logs plays a pivotal role in geosciences, with applications spanning a wide range of scientific fields, including seismotectonic zoning. Well logs provide invaluable subsurface data, aiding in the characterization of geological structures and fault activity. This approach has been successfully applied in Italy, as shown by Lavecchia et al. [4], who integrated well-log data with seismotectonic analyses to explore the relationship between hydrocarbon fields and active thrust belts. Additionally, well-log data are essential for reservoir characterization, as combining seismic and well-log data enhance our understanding of reservoir properties [5]. Methods for estimating petrophysical parameters from well logs in tight oil reservoirs have also been developed to improve the precision of subsurface models [6]. Furthermore, a generalized approach for interpreting geophysical well logs in groundwater studies provides valuable insights into environmental and engineering applications [7]. The study of reservoirs in multi-source systems presents significant challenges due to the marked differences in grain size, mineral composition, and pore structure between sediments from different sources, which result in highly complex physical and chemical properties [8,9,10,11].
The sediment composition in multi-source systems is influenced not only by the number and type of sediment sources but also by the distribution of grain size, mineral content, and sedimentary structure [12,13,14,15,16,17]. For example, the mixing of clayey and sandy sediments often leads to pore heterogeneity, while coarser sandy materials tend to enhance permeability [18]. Additionally, sediments from different sources undergo varying degrees of diagenetic alteration, particularly under deep and high-pressure conditions, where mineral transformations and changes in porosity during diagenesis are particularly significant [19]. Spatial heterogeneity in reservoirs is especially pronounced in multi-source systems. Due to the diversity of source rocks and depositional environments, reservoir properties such as porosity, permeability, and fluid distribution typically exhibit strong spatial variability [20]. This heterogeneity can influence hydrocarbon accumulation and migration pathways, thereby impacting reservoir development efficiency [21,22]. Therefore, understanding multi-source systems is crucial for investigating sedimentary provenance, depositional environments, and their implications for reservoir quality.
The Ordos Basin, as a major energy resource hub in China, plays a pivotal role in the exploration of coal, oil, and natural gas [23]. The Triassic Yanchang Formation in the basin is not only one of the earliest studied stratigraphic sections of China’s terrestrial Triassic formations but also one of the first to yield significant oil and gas discoveries. It has long been a key target for hydrocarbon exploration and development. The Chang 2, Chang 3, Chang 4 + 5, Chang 6, Chang 7, and Chang 8 members of the Yanchang Formation host large oil reservoirs and have seen substantial exploration and development success, yielding significant economic returns [24]. Major oil fields, including those in Longdong and Jiyuan, have been discovered with reserves exceeding one hundred million tons, demonstrating the region’s vast development potential [25].
In recent years, with the rapid expansion of exploration in the Yanchang Formation, a wealth of new drilling and testing data have been accumulated, revealing key geological features across the region [26,27]. Particularly in the Jiyuan area, significant discoveries in the Chang 8 member have spurred breakthroughs in the exploration of the Chang 9 member. The Dingbian area, located adjacent to Jiyuan, has also shown promising potential with multiple prospective oil zones. However, exploration in the Dingbian region has uncovered some complexities. Specifically, the Yanchang Formation in this area contains two sets of hydrocarbon source rocks: the Li Jiapan shale of the Chang 9 member and the Zhangjiatan shale of the Chang 7 member. Additionally, the Chang 9 member in Dingbian is influenced by two source directions (northwest and northeast), resulting in significant variation in the degree of hydrocarbon enrichment across different regions [28,29] (Figure 1). Furthermore, the oil–water relationship in the Chang 9 reservoir is highly complex, and the main controlling factors remain unclear, making them a major obstacle to effective exploration [30].
The study area, located in the central-western part of the Ordos Basin, spans the eastern Tianhuan Depression and the western Yishan Slope, covering an area of approximately 0.9 × 104 km2 (Figure 2a). The region is characterized by an elevated eastern portion, with high points in the northwest and southwest, and an overall westward and southwestward dip. The structural relief is modest, with a difference of approximately 700 m, though local anticlinal structures are present (Figure 2b).
This study focuses on the Chang 9 oil reservoir in the Dingbian area of the northwest Ordos Basin. Based on oil–source correlation and reservoir characterization, the research aims to explore the main controlling factors for hydrocarbon accumulation in the Chang 9 reservoir of this region. The findings will provide a scientific foundation and theoretical support for future petroleum exploration in the area.

2. Geological Background

The Ordos Basin is located in northern-central China and covers an area of approximately 25 × 104 km2. It is characterized by overall uplift and subsidence, with migrating depocenters and relatively simple tectonics. The basin is classified as a large, multi-cycle cratonic basin [31]. Based on current tectonic activity and geological evolution, previous studies have divided the basin into six regional tectonic units: the Yishan Slope, the Western Jinxi Flexural Zone, the Tianhuan Depression, the Western Boundary Fault Zone, the Yimeng Uplift, and the Wei Bei Uplift [32]. The Yishan Slope region within the basin is relatively flat, with an overall westward dip and localized anticlinal structures.
The Yanchang Formation in the Ordos Basin consists of a set of gray-green and gray medium-thick fine sandstones, siltstones, and dark gray to gray-black mudstones. The lower part is dominated by medium- to coarse-grained fluvial sandstone, while the middle part features lake-delta deposits. The upper part consists of river and lake-delta sandstones and mudstones. The grain size of the Yanchang Formation generally decreases from north to south, with thickness decreasing to the north and increasing to the south. The total thickness ranges from 800 to 1500 m. Lithologically, the formation shows clear rhythmic variations, with multiple cycles of deposition. These variations are highly comparable regionally, and the formation is subdivided into ten segments based on shale, carbonaceous mudstone, coal seams, and other marker horizons, as well as their distinctive features on the well [33].
In the study area, the Chang 9 member predominantly consists of dark mudstones interbedded with gray fine sandstones, with dark shale at the top. Since the Chang 92 sub-member is not a primary oil-bearing layer, the Chang 91 sub-member is the main focus of this study (Figure 3).

3. Samples and Methods

3.1. Samples

This study aims to identify the main controlling factors for hydrocarbon accumulation in the Chang 9 reservoir of the Dingbian area, under a multi-source system. To achieve this, the research focuses on oil–source comparison, reservoir characteristics, reservoir types, and crude oil properties. Based on the directional distribution of source areas and previous studies on the sedimentary environment and facies in the Dingbian region [33], the study area is divided into three regions: the northwest source area, the northeast source area, and the central mixed source area.
For the oil–source comparison, crude oil samples from the Chang 9 interval in both the northwest and northeast source areas of Dingbian, as well as source rock samples from the Chang 7 and Chang 9 intervals, were selected for laboratory analysis (Table 1).
For the reservoir study, core samples from the Chang 9 interval were collected from wells located in the three source areas. A total of 104 wells were sampled. Research on reservoir types and crude oil properties was supported by data collected from 468 wells within the study area (Figure 4).

3.2. Methods

In this study of the Chang 9 reservoir, the primary objective was to compare the oil source characteristics. This comparison was based on the analysis of biomarkers, focusing on the oil source rocks from the Chang 7 and Chang 9 intervals and the oils from the Chang 9 reservoir.
Selecting appropriate comparison parameters is crucial when using biomarkers for oil source comparison. The chosen parameters should have clear geochemical significance and should effectively reflect the characteristics of different source rocks. Furthermore, they must be relatively unaffected by later physical and chemical changes in the oil, such as migration, washing, or bacterial degradation.
The pentacyclic triterpanes primarily belong to the 17α(H), 21β(H) hopane series, with a carbon number distribution ranging from C27 to C34. Within this range, C30 is typically the dominant peak, and hopane stereoisomers from C31 to C34 occur in pairs, showing a stepwise decreasing distribution pattern. Ts (a thermal degradation product of hopane) generally increases with maturity. However, recent studies suggest that Ts may have alternative sources and may not be entirely controlled by temperature. Similarly, Tm (another maturity indicator) may have other origin pathways and is less influenced by thermal evolution. For this reason, the Ts/Tm ratio is commonly used as a maturity indicator [34].
Sterols are precursors to sterane compounds and primarily originate from eukaryotes [35], such as algae, phytoplankton, and higher plants. The relative distribution of C27, C28, and C29 sterols differs based on the biological source. Phytoplankton predominantly contains C27 and C28 sterols, with C29 as a minor component; zooplankton primarily contain C27, while higher plants are characterized by C29 sterols, with some C28 sterols present. However, in carbonate–evaporite environments, strong biodegradation and the high preservation potential of saline water can lead to the extensive formation of C29 steranes. Additionally, some marine algae contain high levels of C29 sterols. High concentrations of C29 steranes are often observed in marine organic matter in various regions, such as southern China and the Tarim Basin, where the C29 > C27 sterane ratio is typical [36,37,38].
Based on the aforementioned conditions, samples 1 to 4 of mudstone shale were crushed to 100 mesh. The Soxhlet extraction method was applied for 72 h, and the soluble components were precipitated with n-hexane to isolate the bitumen. These were then separated using a chromatographic column (silica gel and alumina in a 3:2 ratio), and the saturated hydrocarbon fraction was eluted with n-hexane. Oil samples were subjected to bitumen precipitation using n-hexane and then underwent column chromatography for separation. The analysis was conducted using a GC-MS-QP2010SE mass spectrometer coupled with a gas chromatograph, equipped with an HP-5MS elastic quartz capillary column (60 m × 0.25 mm × 0.25 μm). The carrier gas was 99.99% helium, with a sample inlet temperature maintained at 280 °C, and the injection rate was 1 mL/min. The transfer line temperature was set at 300 °C. Electron ionization (EI, 70 eV) was employed, with a filament current of 100 mA and an ion source temperature of 250 °C. Compound quantification was based on characteristic ion peaks in the mass chromatograms. Stable isotope testing was conducted on crude oil samples 5 and 6 using an Elementar Isoprime 100 isotope mass spectrometer. The comparison of biomarker compounds in crude oil from Chang 9, Chang 7 mudstone shale, and Chang 9 mudstone shale was performed, focusing on parameters such as the relative ratio of Ts to Tm, the relative abundance of C30 hopane to 17α(H) rearranged hopane, and the abundance of regular steranes (C27, C28, C29). These analyses were conducted to identify the source of the Chang 9 oil.
Petrographic studies of the reservoir were conducted on cores extracted from wells in three areas of the study zone: the northwestern source of Chang 91, the northeastern source, and the central mixed source. Thin rock sections were prepared and analyzed under a polarized light microscope to identify mineral types (e.g., quartz, feldspar, clay minerals) and cementing materials (e.g., carbonate, siliceous cement). Mineral and cement content was quantified using ImageJ software (version 2.1.4.6) by circumscribing target minerals and cements. High-resolution scanning electron microscope (SEM) observations were performed to study the distribution of cements and the mineral composition, providing insights into the reservoir mineralogical characteristics of different source areas.
The study of reservoir porosity types followed the same methodology. Cores from wells in the three source areas were analyzed using polarized light microscopy and SEM to observe reservoir porosity characteristics and micro-pore structures. Porosity in the different source areas was quantified using ImageJ software (version 2.1.4.6), and statistical analysis was performed to establish the porosity characteristics for each source area.
Core samples from wells in the three source areas were cut into cylindrical samples (2.5 cm in diameter and 3–5 cm in length), cleaned, and dried at 105 °C for 48 h. Mercury intrusion porosimetry (AutoPore IV 9500, McMurdic Instruments, Inc. in Norcross, Norcross, GA, USA) was used to measure the pressure variation of mercury saturation at pressures ranging from 0.1 to 60,000 psi. Capillary pressure curves, mercury saturation, and pore throat distribution parameters (such as median radius and displacement pressure) were derived to assess the pore structure of the different source areas.
Extensive porosity and permeability measurements have been performed on core samples from the study area, with the experimental results provided by the Changqing Oilfield Branch of PetroChina. Statistical analysis of the core physical property data from the three source areas allowed for the identification of reservoir physical characteristics, culminating in the creation of permeability and porosity distribution maps.
In the study of reservoir characteristics, the Chang 9 interval was subdivided into two smaller layers: Chang 911 and Chang 912. Since most reservoirs are concentrated in the Chang 911 sublayer, a detailed characterization of the sand body distribution in this sublayer was conducted. Additionally, structural features at the top of the sandstone were carefully analyzed to accurately map the structural form. By clarifying the coupling relationship between structure and lithology, the study aimed to better reveal the oil–water distribution pattern, laying the groundwork for further investigation of the controlling factors in the reservoir.
The physical properties of crude oil are influenced by factors such as the nature of the source rock, thermal maturation, and secondary alterations, making it essential to study these properties. The investigation of crude oil properties in the study area focused on the density and viscosity of crude oil. Statistical analysis of crude oil density and viscosity in the northwestern, northeastern, and central mixed source areas was carried out. These data, provided by the Changqing Oilfield Branch of PetroChina, were used to analyze the properties of crude oil from different source areas.

4. Results

4.1. Oil Source Comparison

Biomarker compounds from the Chang 7 source rocks were analyzed in two wells, one from the northwest source area and the other from the central mixed-source area. The results of the analysis revealed distinct chemical signatures for both samples. Specifically, both Sample 1 and Sample 2 exhibited the following characteristics: the Ts/Tm ratio was less than 1, the content of 17α(H) rearranged hopane was significantly lower than that of C30 hopane, and the distribution of regular steranes followed a C29 > C27 > C28 pattern. Additionally, the relative abundances of C27, C28, and C29 steranes showed an inverse “L”-shaped distribution (Figure 5).
Biomarker compounds from the Chang 9 source rocks in two wells—one from the northeast source area and the other from the central mixed-source area—were analyzed. The results revealed the following characteristics for Sample 3 and Sample 4: the Ts/Tm ratio was greater than 1, the content of 17α(H) rearranged hopane was significantly higher than that of C30 hopane, and the regular sterane distribution followed the pattern C27 > C29 > C28. Additionally, the distribution of C27, C28, and C29 steranes displayed a “V”-shaped pattern (Figure 6).
Biomarker compounds in the Chang 9 crude oil samples from the northwest and northeast source areas were also analyzed. The results showed that for Sample 5 and Sample 6, the Ts/Tm ratio was less than 1, the 17α(H) rearranged hopane content was notably lower than that of C30 hopane, and the regular sterane distribution followed C29 > C27 > C28. The distribution of C27, C28, and C29 steranes displayed an inverse “L”-shaped pattern (Figure 7).

4.2. Reservoir Petrographic Characteristics

The petrographic composition of the Chang 91 sandstone in the Dingbian area was statistically analyzed for three source areas: northwest source area, northeast source area, and central mixed-source area (Table 2). In the northwest source area, a total of 186 sandstone thin sections from 42 wells were analyzed, revealing the following average mineral contents: quartz + chert (29.8%), feldspar (orthoclase + plagioclase) (34.5%), and lithic fragments (25.5%). In the northeast source area, 83 sandstone thin sections from 26 wells were examined, yielding the following average contents: quartz + chert (28.8%), feldspar (orthoclase + plagioclase) (39.1%), and lithic fragments (20.2%). In the central mixed-source area, 178 thin sections from 36 wells were analyzed, showing the following: quartz + chert (30.4%), feldspar (orthoclase + plagioclase) (37.1%), and lithic fragments (18.5%).
Comparing the northwest and northeast source areas, the northwest area exhibits a higher lithic fragment content, while the northeast area shows a higher feldspar content. The central mixed-source area is characterized by a higher quartz content. In the Chang 91 reservoir of Dingbian, the cementing materials primarily consist of chlorite films, silica, zeolite, and ferroan calcite (Figure 8). The northwest source area has relatively low cementing material content, particularly for ferroan calcite, which is lower than in the other two areas. Chlorite films are generally more abundant in all three areas (Table 3).
Scanning electron microscope (SEM) observations revealed the morphological characteristics of authigenic clay minerals in the Chang 91 sandstone reservoirs. Honeycomb-like illite–smectite mixed layers were observed growing on the surface of particles. Chlorite films were found to grow in a sheet-like structure, vertically aligned on the surface of clasts, while acicular chlorite filled the pores between the particles. Additionally, other types of flaky clay minerals were observed. In terms of quartz, both secondary and authigenic quartz were found filling the pores between the chlorite film particles. Notably, both types of quartz exhibited high idiomorphic degrees, indicating well-developed intergranular pores during their growth. Furthermore, well-formed calcite was observed filling the pores in particles attached to chlorite films [39].

4.3. Reservoir Physical Property

The main pore types in the Chang 91 reservoir include intergranular pores and feldspar dissolution pores, with smaller amounts of lithic fragment dissolution pores, zeolite dissolution pores, as well as intragranular pores and microfractures. For the Chang 9 reservoir, pore types were statistically analyzed for the northwest, northeast, and central mixed-source areas (Figure 9). In the northwest source area, the total porosity rate was 6.78%, with intergranular pores being the dominant pore type (5.63%), followed by feldspar dissolution pores (0.92%), zeolite dissolution pores (0.39%), and lithic fragment dissolution pores (0.29%). In the northeast source area, the porosity rate was 5.60%, with intergranular pores making up 4.35%, feldspar dissolution pores at 1.03%, lithic fragment dissolution pores at 0.37%, and zeolite dissolution pores at 0.20%. In the central mixed-source area, the porosity rate was 5.40%, with intergranular pores (3.96%) and feldspar dissolution pores (0.89%) as the main types, followed by lithic fragment dissolution pores (0.29%) and zeolite dissolution pores (0.35%).
The northwest source area has the highest porosity rate and develops a variety of pore types. Overall, all three source areas are dominated by intergranular and feldspar dissolution pores, with lithic fragments and zeolite dissolution pores being secondary pore types (Figure 10) [39].
Biomarker analysis of the Chang 9 source rocks from two wells in the northeast and central mixed-source areas revealed the following characteristics for Samples 3 and 4. In addition, a statistical analysis of capillary pressure data for the Chang 91 samples in the Dingbian area was conducted, yielding several key parameters. The average displacement pressure of the sandstone ranged from 0.42 to 0.53 MPa. The median throat pressure was found to be between 1.69 and 6.02 MPa, while the median throat radius ranged from 0.29 to 0.42 μm. The maximum mercury saturation (SHg) varied between 69.99% and 80.52%, and the mercury drainage efficiency ranged from 23.48% to 26.67%.
Based on these statistical data, all Chang 9 reservoirs in the Dingbian area, across different source regions, exhibit relatively low displacement pressures, small median throat radii, and low mercury drainage efficiencies. The pore throats are characterized as fine to microfine (Table 4).
Further analysis of the mercury injection curves for the Chang 91 reservoirs in different source areas showed that all reservoirs exhibit high permeability, low displacement pressures, small median throat radii, poor sorting, and low mercury drainage efficiencies (Figure 11).
A systematic analysis of the physical property data for the Chang 91 reservoir in the study area revealed that the porosity values predominantly range between 8% and 16%, with an average porosity of 12.2%. The permeability values are mainly distributed between 1.0 and 10 mD, with an average permeability of 8.4 mD. Overall, the reservoir is classified as a low-porosity, ultra-low permeability to low permeability reservoir.
Further statistical analysis was conducted for different source regions. In the Northwest source area, data from 57 wells showed that the porosity mainly ranged from 12% to 16%, with an average value of 13.4%. The permeability predominantly ranged from 1 to 10 mD, with an average value of 16.25 mD. In the northeast source area, based on data from 26 wells, the porosity was mainly between 10% and 14%, with an average of 11.8%. The permeability ranged from 1.0 to 5 mD, with an average of 5.01 mD. In the central area, data from 69 wells indicated that the porosity mainly ranged from 8% to 14%, with an average value of 11.4%. The permeability was predominantly between 1.0 and 5 mD, with an average value of 3.11 mD (Table 5).
Comparative analysis of the data from different source regions clearly shows that while the porosity values in the northeast and northwest source areas are similar, there is a significant difference in permeability between the two regions.
Contour maps of porosity (Figure 12a) and permeability (Figure 12b) for the Chang 91 reservoir in the Dingbian area were plotted based on the physical property data. The maps show that the porosity and permeability are relatively continuous across the region. The northwest source area is superior to the northeast and central source areas in terms of overall physical properties, with regions having permeability values greater than 10 mD mainly distributed in the northwest source area.

4.4. Reservoir Type

A detailed analysis of the discovered Chang 9 oil reservoirs in the study area reveals that different regions exhibit distinct reservoir types. In the northwest source area, lithological-structural reservoirs are predominant, while in the central mixed-source area, structural-lithological reservoirs are more common. The northeast source area mainly consists of lithological reservoirs.
The reservoirs in the northwest source area are characterized by large-scale sandstone bodies, stable distribution, and excellent petrophysical properties. The lithological-structural oil reservoirs in this region generally exhibit higher production, primarily producing crude oil. However, the lateral extent of these reservoirs is relatively short. For example, in the H60–H260 oil reservoir profile, located in the northwest source area, the average porosity of the reservoir is 14.3%, and the average permeability reaches 16.08 mD, reflecting excellent reservoir properties. The reservoir is primarily controlled by structural factors. This profile is situated along the axis of the Tianhuan depression, intersecting an east–west-oriented nose-like structure, where significant structural variations occur, leading to the development of multiple nose-like anticlines and smaller oil reservoirs.
At well Y45, located at a structural high point, good oil saturation is observed, and an oil test produced 21.59 tons of pure oil. However, at the slightly lower structural position of well H321 to the west, oil saturation decreases, with the test showing both oil and water production. Further to the structural low, well H60 displays poor oil shows. Approximately 3 km southeast of Y45, well H292 also shows poor oil saturation due to a lower structural position. In contrast, well Y46, located to the east of H292, is positioned at a higher structural level, and the oil test yielded industrial oil flow (Figure 13).
The reservoirs in the central mixed-source area exhibit relatively thin sandstone bodies, which are predominantly lens-shaped. These sand bodies show rapid lateral variation. However, the petrophysical properties of the reservoirs remain relatively favorable. The reservoirs are mainly characterized as structural-lithological oil reservoirs, with high production and predominantly crude oil output. The lateral extent of these reservoirs ranges from 2 to 4 km.
For example, the C119–C230 reservoir profile, which is representative of this area, has an average porosity of 10.2% and an average permeability of 1.81 mD. These values are relatively lower compared to other areas. The thin sand body thickness leads to a significant influence of lithology on the reservoir, and the oil-bearing sand bodies exhibit diverse and complex stratigraphic characteristics. The main structural feature in this region is nose-like anticlines, which play a significant role in the formation and distribution of the reservoirs.
When examining the profile along the dip direction of the nose-like structure, wells C70 and C230 are located above different channel sand bodies, while wells C119, C339, and C288 are positioned above other channel sands. In the updip direction, the sand bodies gradually thin and are increasingly covered by mudstones, resulting in the formation of two traps. Well C238, located in the underdeveloped Chang 911 sandstone body, did not form a reservoir due to insufficient development. However, in the well-developed Chang 912 sandstone body, a successful oil reservoir formation occurred (Figure 14).
The reservoirs in the northeast source area are primarily formed by multiple generations of channel sand bodies, which show significant thickness variations due to the overlapping of these sand bodies. However, there are notable differences in the petrophysical properties between the individual sand bodies, with some regions developing high-permeability reservoirs. This area is dominated by lithological reservoirs, which tend to be larger in scale, with the lateral extent generally exceeding 4 km. However, due to the migration distance of the source rocks and the extent of oil charging, most of the reservoirs exhibit oil–water co-production.
For example, the H5-A106 reservoir profile shows an average porosity of 11.7% and an average permeability of 1.24 mD, reflecting relatively poor overall petrophysical properties. The northeast source area is characterized by multiple sets of sand bodies, with individual sand body thicknesses being relatively thin. The petrophysical heterogeneity between sand bodies is significant, leading to strong reservoir non-homogeneity and the potential for tight sandstone barriers to form. As a result, the oil reservoirs are mainly controlled by lithology, and the oil-bearing sand bodies exhibit diverse and complex stratigraphic features.
In terms of the profile, the Chang 911 small layer sandstones in wells A184 and A106 have undergone compaction, resulting in poor oil-bearing potential. These sandstones serve as barriers to oil accumulation in wells A242 and A222, leading to the formation of lithological traps (Figure 15).

4.5. Crude Oil Properties

The physical properties of crude oil are influenced by various factors, including the characteristics of the source rock, the degree of thermal maturity, and secondary alterations. Systematic statistical analysis of crude oil in the Dingbian area reveals that its density is less than 0.85 t/m3, classifying it as light oil. When comparing different regions, the average crude oil densities for the northwest, central mixed source, and northeast source areas are 0.835 t/m3, 0.84 t/m3, and 0.847 t/m3, respectively, showing a gradual increase (Figure 16a).
The viscosity of the crude oil ranges from 2.02 to 13.89 Pa·s, indicating generally low viscosity. Further regional analysis shows that the average crude oil viscosities for the northwest, central mixed source, and northeast source areas are 4.67 Pa·s, 6.17 Pa·s, and 7.51 Pa·s, respectively, also reflecting a gradual increase (Figure 16b).

5. Discussion

5.1. Impact of Structural Control on Oil Composition and Reservoir Characteristics in Different Source Areas

In the process of secondary migration, smaller molecules with lower molecular weight, lower polarity, and higher water solubility tend to migrate more freely [40]. This differentiation leads to a series of changes in the crude oil composition [41]. The general trend is as follows: with increasing migration distance, the content of heavier components such as resins, asphaltenes, porphyrins, and vanadium-nickel metals gradually decreases, while the lighter components increase. In terms of hydrocarbon composition, the proportion of alkanes increases, and the proportion of aromatics decreases. Within the alkane group, the content of low-molecular hydrocarbons rises, while that of high-molecular hydrocarbons declines. These compositional changes are further reflected in the physical properties of the oil, which show a decrease in density, a lighter color, and a reduction in viscosity [42,43,44,45]. Therefore, when a reservoir is more strongly influenced by structural factors, it is more likely to undergo localized adjustments, resulting in more significant oil–water differentiation and a reduction in both viscosity and density.
Based on these characteristics, it is observed that crude oil from the northwest source area exhibits the lowest viscosity and density, while crude oil from the northeast source area has the highest viscosity and density. This suggests that the reservoirs in the northwest source area are more strongly controlled by structural factors, while those in the northeast source area are less influenced by structural controls. This aligns with the findings from the study of reservoir characteristics in different source areas. The majority of the northwest source area lies within the Tianhuan Depression, which experiences significant structural changes, with the development of faults and small nose-shaped structures providing favorable trapping conditions for oil accumulation. In contrast, both the central mixed source area and the northeast source area are located on the Yishan Slope, where structural variations are minimal. Although small nose-shaped structures are locally developed, the northeast source area contains multiple sets of sand bodies. These sand bodies are relatively thin, and the physical properties between the sand bodies show significant differences, resulting in highly heterogeneous reservoirs. The reservoirs in this area are primarily controlled by lithology, and the oil-bearing sand bodies exhibit diverse and complex stratigraphy.

5.2. Origin and Migration Path of Crude Oil in the Chang 9 Reservoir: Evidence from Biomarker Analysis

By carefully comparing the characteristic parameters of steroid and terpane biomarkers, such as Ts/Tm, 17α(H) rearranged hopane, C30 hopane, and rearranged steranes (C27, C28, C29), in source rocks from different source areas and Chang 9 crude oil, the results indicate that the biomarker characteristics of crude oil from the Chang 9 reservoir closely resemble those of the Chang 7 source rock. However, significant differences were observed when compared to the Chang 9 source rock.
Based on this analysis, it can be concluded that the crude oil in the Chang 9 reservoir of the Dingbian area originates from the Chang 7 source rock located above it. The oil migrated downward through the Chang 8 strata to accumulate in the Chang 9 reservoir. This suggests that the distribution of the Chang 9 source rock in the Dingbian area is relatively limited and unable to supply sufficient crude oil for its own reservoir.
The distribution of the Chang 7 source rock within the study area is heterogeneous. In the northeastern source area, the Chang 7 source rock is limited in extent and relatively thin. Moreover, based on reservoir studies across different source areas, significant variations in mineral composition, cementing materials, pore space, and physical properties were observed. These differences contribute to the strong heterogeneity of reservoirs across various regions.

5.3. Oil Accumulation Models in the Dingbian Area: A Zonal Study of Different Source Areas

The different blocks of the Chang 9 reservoir in the Dingbian area exhibit various types of oil accumulations. Therefore, it is necessary to conduct zonal studies under a multi-source background. The differences in source rocks, reservoirs, and trapping conditions in different source areas should be investigated, and the key controlling factors for accumulation should be summarized to develop a model of oil accumulation (Figure 17).
In the northwest source area, located in the central part of the Chang 7 Lake Basin, a set of dark to black mudstones with a thickness of 40 to 100 m was deposited during the Chang 7 period, providing the material basis for petroleum generation. During later tectonic movements, the northern region experienced significant adjustments, resulting in the formation of many small nose-shaped structures, gentle anticlines, and faults. Because of the favorable reservoir properties, including large pore throats, significant structural variations, and steep dips, the buoyancy forces acting on the oil were greater. This buoyancy provided the driving force for secondary migration and adjustment. As a result, oil underwent corresponding adjustments, with oil–water differentiation becoming more pronounced, and oil accumulating in more favorable traps.
In the central mixed source area, located near the center of the Chang 7 Lake Basin, a set of dark to black mudstones with a thickness of 30 to 80 m was also deposited during the Chang 7 period, providing a material foundation for petroleum generation. In the later stages of tectonic movement, reservoirs were primarily controlled by lithology, with only slight adjustments in the central structural area. The formation of aligned small nose-shaped structures led to oil and water differentiation and accumulation in favorable traps.
In the northeast source area, the Chang 7 source rock was deposited at the delta front, with underwater distributary channel sand bodies developed. However, the thickness of the dark to black mudstones is relatively thin. When the Chang 7 source rock in the lake basin matured and began to expel hydrocarbons, the oil migrated laterally along the extensive Chang 9 sand bodies, which were deposited in a stacked and continuous manner. At this time, the top of the Chang 9 formation exhibits a relatively gentle structure with minimal structural variation. Even though minor tectonic adjustments occurred during later movements, their impact on the reservoir was limited. Oil primarily accumulated in sand bodies with better physical properties, with minimal oil–water differentiation. In this area, the oil is largely controlled by lithology. Additionally, due to the strong heterogeneity and relative tightness of the reservoirs, some oil and gas accumulate in the downdip portions of the sand bodies rather than migrating upward.
Different source areas lead to varying petroleum accumulation models due to different geological conditions. The northwest and central mixed source areas, which are both underlain by hydrocarbon source rocks, exhibit an “upward generation, downward storage” accumulation pattern, with oil accumulating in favorable traps. The northeast source area, where no source rocks are present, experiences lateral migration of oil to favorable lithologic traps, resulting in a “side-generation, side-storage” accumulation pattern.

5.4. Exploration Insights and Technological Outlook

The oil and gas accumulation patterns in different source areas of the Dingbian region vary significantly. Based on the aforementioned research methods, the multi-source convergence area is divided into source zones according to the source direction. Hydrocarbon source rocks, reservoirs, and structural characteristics of each source zone are studied separately. A detailed evaluation of the oil and gas reservoir characteristics within each zone is conducted. This approach not only provides important references for exploration and the “reserve increase and production uplift” efforts in the region but also offers valuable insights for reservoir evaluation in other regions with stable subsidence and simple structures under multi-source systems globally.
Oil and gas reservoir evaluation in multi-source convergence areas requires breaking away from traditional single-source thinking. Future evaluation methods must gradually evolve, incorporating innovations in high-precision source rock analysis, multi-scale modeling, and dynamic reservoir formation simulation technologies. Additionally, the establishment of sedimentary–geophysical–geochemical databases, combined with the use of graph neural networks (GNNs) to uncover hidden correlations in multi-source systems (such as source rock-reservoir-accumulation chain responses), will enable a shift from “static descriptions” to “dynamic predictions”.

6. Conclusions

This study focuses on the Dingbian region, which is divided into three source areas: the northwest source area, the northeast source area, and the central mixed source area. Two sets of hydrocarbon source rocks are present in the study area. Based on the oil source comparison, it has been determined that the oil in the Chang 9 reservoir of the Dingbian region originates from the Upper Chang 7 source rock.
The distribution of source rocks significantly controls the formation of oil reservoirs, with substantial differences observed across large blocks. In the northwest and central mixed source areas, hydrocarbon source rocks are well developed, resulting in the discovery of numerous Chang 9 oil reservoirs. In contrast, in the northeast source area, source rocks are underdeveloped, and only a few oil reservoirs are found, indicating clear source-controlled accumulation. The influence of structural and lithological factors on the Chang 9 reservoir operates at a reservoir-level scale. In the northwest and central mixed source areas, most of the discovered reservoirs are situated within nose-like structures. These reservoirs are structurally controlled, with their horizontal shapes aligning with the underlying structural features. In contrast, the reservoirs in the northeast source area are controlled by lithology, with oil accumulating in local high-permeability zones within a low-permeability background, forming lithological traps. The shapes of these reservoirs are not strongly influenced by structural features. In the northwest and central mixed source areas, the reservoir accumulation pattern follows the “upper generation, lower storage” model, whereas, in the northeast source area, where source rocks are absent, oil migrates laterally into favorable lithological traps, forming a “lateral generation, side storage” model.
In multi-source systems, it is essential to divide the study area based on source direction and the distribution of sedimentary sand bodies. The study of the factors controlling oil and gas reservoir formation in different source rock backgrounds can be explored within these source zones. This research methodology is applicable not only to the current study area but also provides a basis for studying other multi-source convergence areas and stratigraphic levels in the Ordos Basin. It offers valuable insights into oil reservoir evaluation in regions with stable subsidence and simple structures within global multi-source systems.

Author Contributions

Conceptualization, J.Z. and Z.Y.; methodology, Z.Y.; validation, J.L.; formal analysis, J.Z. and Z.Y.; investigation, B.S.; data curation, Z.W.; writing—original draft preparation, Z.Y.; writing—review and editing, Z.Y.; visualization, F.W.; supervision, J.Z. and Z.Y.; project administration, J.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author, upon reasonable request.

Acknowledgments

This study was supported by technology and data provided by CNPC Changqing Exploration Institute.

Conflicts of Interest

Author Feifei Wang was employed by the Geological Research Institute of CNPC Greatwall Drilling Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Distribution characteristics of source rocks and hydrocarbon source rocks in the Dingbian area, Ordos Basin: (a) distribution of heavy minerals in the Chang 9 section of the Dingbian area; (b) distribution characteristics of hydrocarbon source rocks in the Dingbian area.
Figure 1. Distribution characteristics of source rocks and hydrocarbon source rocks in the Dingbian area, Ordos Basin: (a) distribution of heavy minerals in the Chang 9 section of the Dingbian area; (b) distribution characteristics of hydrocarbon source rocks in the Dingbian area.
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Figure 2. Comprehensive study map of the Dingbian area, Ordos Basin: (a) location map of the study area; (b) structural map of the top of the Chang 9 formation in the Dingbian area.
Figure 2. Comprehensive study map of the Dingbian area, Ordos Basin: (a) location map of the study area; (b) structural map of the top of the Chang 9 formation in the Dingbian area.
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Figure 3. Stratigraphic division of the Yanchang formation in the Dingbian area.
Figure 3. Stratigraphic division of the Yanchang formation in the Dingbian area.
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Figure 4. Well location map in the Dingbian area, Ordos Basin.
Figure 4. Well location map in the Dingbian area, Ordos Basin.
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Figure 5. Biomarker chromatograms of steranes and terpanes from the Chang 7 hydrocarbon source rocks in the Dingbian area: (a) Sample 1 (Chang 7 source rock, 2215 m) sterane and terpane chromatogram; (b) Sample 2 (Chang 7 source rock, 556.5 m) sterane and terpane chromatogram.
Figure 5. Biomarker chromatograms of steranes and terpanes from the Chang 7 hydrocarbon source rocks in the Dingbian area: (a) Sample 1 (Chang 7 source rock, 2215 m) sterane and terpane chromatogram; (b) Sample 2 (Chang 7 source rock, 556.5 m) sterane and terpane chromatogram.
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Figure 6. Biomarker chromatograms of steranes and terpanes from the Chang 9 hydrocarbon source rocks in the Dingbian area: (a) Sample 3 (Chang 9 source rock, 1410.89 m) sterane and terpane chromatogram; (b) Sample 4 (Chang 9 source rock, 1335.3 m) sterane and terpane chromatogram.
Figure 6. Biomarker chromatograms of steranes and terpanes from the Chang 9 hydrocarbon source rocks in the Dingbian area: (a) Sample 3 (Chang 9 source rock, 1410.89 m) sterane and terpane chromatogram; (b) Sample 4 (Chang 9 source rock, 1335.3 m) sterane and terpane chromatogram.
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Figure 7. Biomarker chromatograms of steranes and terpanes from crude oil in the Chang 9 reservoir in the Dingbian area: (a) Sample 5 (Chang 9 crude oil, 2756–2758 m) sterane and terpane chromatogram; (b) Sample 6 (Chang 9 crude oil, 2348 m) sterane and terpane chromatogram.
Figure 7. Biomarker chromatograms of steranes and terpanes from crude oil in the Chang 9 reservoir in the Dingbian area: (a) Sample 5 (Chang 9 crude oil, 2756–2758 m) sterane and terpane chromatogram; (b) Sample 6 (Chang 9 crude oil, 2348 m) sterane and terpane chromatogram.
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Figure 8. Scanning electron microscope (SEM) images of pore-filling material types in Chang 9 reservoirs in the Dingbian area: (a) Well H120, 2439.6 m, intergranular filling of authigenic quartz with honeycomb-like illite-chlorite mixed layers on particle surfaces; (b) Well A26, 2122.6 m, intergranular filling with sodium feldspar grains and acicular authigenic chlorite on particle surfaces; (c) Well B38, 2805.6 m, intergranular filling with calcite, acicular chlorite, and minor spherulitic asphaltite; (d) Well Hu158, 2656.9 m, quartz overgrowth, authigenic quartz, chlorite membranes, and benthic illite; (e) Well Yuan127, 2441.35 m, most intergranular pores filled with illite–chlorite mixed layers; (f) Well Hu171, 2691.85 m, diagenetic clinoptilolite with residual crystals filling pore throats.
Figure 8. Scanning electron microscope (SEM) images of pore-filling material types in Chang 9 reservoirs in the Dingbian area: (a) Well H120, 2439.6 m, intergranular filling of authigenic quartz with honeycomb-like illite-chlorite mixed layers on particle surfaces; (b) Well A26, 2122.6 m, intergranular filling with sodium feldspar grains and acicular authigenic chlorite on particle surfaces; (c) Well B38, 2805.6 m, intergranular filling with calcite, acicular chlorite, and minor spherulitic asphaltite; (d) Well Hu158, 2656.9 m, quartz overgrowth, authigenic quartz, chlorite membranes, and benthic illite; (e) Well Yuan127, 2441.35 m, most intergranular pores filled with illite–chlorite mixed layers; (f) Well Hu171, 2691.85 m, diagenetic clinoptilolite with residual crystals filling pore throats.
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Figure 9. Histogram of pore type content in the Chang 9 reservoirs in the Dingbian area.
Figure 9. Histogram of pore type content in the Chang 9 reservoirs in the Dingbian area.
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Figure 10. SEM images of pore types in Chang 9 reservoirs in the Dingbian area: (a) Well Hu153, 2719.36 m, intergranular pores, intergranular filling with authigenic quartz; (b) Well C220, 2497.39 m, feldspar dissolution pores; (c) Well A26, 2805.6 m, feldspar dissolution pores and more developed intragranular dissolution pores; (d) Well C220, 2497.39 m, intergranular pores, with some intergranular pore filling dissolved remnants; (e) Well G272, 2607.4 m, micropores in pore-filling materials; (f) Well C239, 2425.3 m, intergranular pores with partial feldspar dissolution and minor intragranular dissolution pores.
Figure 10. SEM images of pore types in Chang 9 reservoirs in the Dingbian area: (a) Well Hu153, 2719.36 m, intergranular pores, intergranular filling with authigenic quartz; (b) Well C220, 2497.39 m, feldspar dissolution pores; (c) Well A26, 2805.6 m, feldspar dissolution pores and more developed intragranular dissolution pores; (d) Well C220, 2497.39 m, intergranular pores, with some intergranular pore filling dissolved remnants; (e) Well G272, 2607.4 m, micropores in pore-filling materials; (f) Well C239, 2425.3 m, intergranular pores with partial feldspar dissolution and minor intragranular dissolution pores.
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Figure 11. Comparison of mercury injection capillary pressure (MICP) curves for the Chang 9 reservoirs in the Dingbian area.
Figure 11. Comparison of mercury injection capillary pressure (MICP) curves for the Chang 9 reservoirs in the Dingbian area.
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Figure 12. Planar distribution characteristics of reservoir physical properties in the Dingbian area, Ordos Basin: (a) porosity contour map for Chang 9 reservoirs in the Dingbian area; (b) permeability contour map for Chang 9 reservoirs in the Dingbian area.
Figure 12. Planar distribution characteristics of reservoir physical properties in the Dingbian area, Ordos Basin: (a) porosity contour map for Chang 9 reservoirs in the Dingbian area; (b) permeability contour map for Chang 9 reservoirs in the Dingbian area.
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Figure 13. Reservoir profile in the northwest source area of the Dingbian region, Ordos Basin.
Figure 13. Reservoir profile in the northwest source area of the Dingbian region, Ordos Basin.
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Figure 14. Reservoir profile in the central mixed source area of the Dingbian region, Ordos Basin.
Figure 14. Reservoir profile in the central mixed source area of the Dingbian region, Ordos Basin.
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Figure 15. Reservoir profile in the northeast source area of the Dingbian region, Ordos Basin.
Figure 15. Reservoir profile in the northeast source area of the Dingbian region, Ordos Basin.
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Figure 16. Statistical analysis of crude oil properties in the Chang 9 reservoir in the Dingbian area: (a) comparison of crude oil densities in the Chang 9 reservoir; (b) comparison of crude oil viscosities in the Chang 9 reservoir.
Figure 16. Statistical analysis of crude oil properties in the Chang 9 reservoir in the Dingbian area: (a) comparison of crude oil densities in the Chang 9 reservoir; (b) comparison of crude oil viscosities in the Chang 9 reservoir.
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Figure 17. Petroleum accumulation models in the Dingbian area, Ordos Basin.
Figure 17. Petroleum accumulation models in the Dingbian area, Ordos Basin.
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Table 1. Oil–source comparison sampling table for the Dingbian area.
Table 1. Oil–source comparison sampling table for the Dingbian area.
Sample NameSample TypeStratigraphic PositionSource Area
Sample 1Source RockChang 7Northwest Area
Sample 2Source RockChang 7Central Mixed Area
Sample 3Source RockChang 9Northeast Area
Sample 4Source RockChang 9Central Mixed Area
Sample 5Crude OilChang 9Northwest Area
Sample 6Crude OilChang 9Northeast Area
Table 2. Statistical analysis of the mineral composition of reservoir rocks in the Chang 91 formation of the Dingbian area.
Table 2. Statistical analysis of the mineral composition of reservoir rocks in the Chang 91 formation of the Dingbian area.
Source RegionQuartz (%)Feldspar (%)Lithic Fragments (%)
GraniteVolcanic RockSilver OreHigh-grade Metamorphic RockQuartziteSchistPhylliteMetamorphic SandstoneSlateSiltstoneMudstoneMicaChloriteTotal (%)
NorthWest Source Area29.834.50.14.91.93.23.01.73.11.62.000.23.40.425.5
North East Source Area28.839.10.21.40.14.85.20.91.50.81.000.13.80.420.2
Central Mixed-Source Area30.437.10.41.91.43.93.40.11.01.11.30.10.13.50.518.5
Table 3. Statistical analysis of pore-filling materials in the Chang 91 reservoir of the Dingbian area.
Table 3. Statistical analysis of pore-filling materials in the Chang 91 reservoir of the Dingbian area.
Source RegionKaolinite (%)Muscovite (%)Chlorite Film (%)Tuff (%)Calcite (%)Ferroan Calcite (%)Zeolite (%)Silica (%)Total (%)
Northwest Source Area0.11.03.700.30.22.03.010.2
Northeast Source Area0.21.53.60.31.61.72.01.011.9
Central Mixed-Source Area0.10.84.200.31.53.24.114.0
Table 4. Evaluation of pore structure for Chang 91 reservoirs in the Dingbian area.
Table 4. Evaluation of pore structure for Chang 91 reservoirs in the Dingbian area.
Source AreaMedian Radius (μm)Median Pressure (MPa)Displacement Pressure (MPa)Maximum SHg (%)Mercury Drainage Efficiency (%)
Northwest Source Area0.421.690.4280.5226.67
Northeast Source Area0.296.020.5369.9924.49
Central Mixed-Source Area0.314.970.5279.6923.48
Table 5. Comparative statistical analysis of physical properties in the Chang 91 formation, Dingbian area.
Table 5. Comparative statistical analysis of physical properties in the Chang 91 formation, Dingbian area.
Source RegionPorosity Range (%)Average Porosity (%)Permeability Range (mD)Average Permeability (mD)
Northwest Source Area12–1613.41–1016.25
Northeast Source Area10–1411.81–55.01
Central Mixed-Source Area8–1411.41–53.11
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Yong, Z.; Zhang, J.; Li, J.; Shi, B.; Wang, Z.; Wang, F. Study on the Key Factors Controlling Oil Accumulation in a Multi-Source System: A Case Study of the Chang 9 Reservoir in the Triassic Yanchang Formation, Dingbian Area, Ordos Basin, China. Minerals 2025, 15, 303. https://doi.org/10.3390/min15030303

AMA Style

Yong Z, Zhang J, Li J, Shi B, Wang Z, Wang F. Study on the Key Factors Controlling Oil Accumulation in a Multi-Source System: A Case Study of the Chang 9 Reservoir in the Triassic Yanchang Formation, Dingbian Area, Ordos Basin, China. Minerals. 2025; 15(3):303. https://doi.org/10.3390/min15030303

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Yong, Zishu, Jingong Zhang, Jihong Li, Baohong Shi, Zhenze Wang, and Feifei Wang. 2025. "Study on the Key Factors Controlling Oil Accumulation in a Multi-Source System: A Case Study of the Chang 9 Reservoir in the Triassic Yanchang Formation, Dingbian Area, Ordos Basin, China" Minerals 15, no. 3: 303. https://doi.org/10.3390/min15030303

APA Style

Yong, Z., Zhang, J., Li, J., Shi, B., Wang, Z., & Wang, F. (2025). Study on the Key Factors Controlling Oil Accumulation in a Multi-Source System: A Case Study of the Chang 9 Reservoir in the Triassic Yanchang Formation, Dingbian Area, Ordos Basin, China. Minerals, 15(3), 303. https://doi.org/10.3390/min15030303

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