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Article

Impact of Pore Structure on Seepage Capacity in Tight Reservoir Intervals in Shahejie Formation, Bohai Bay Basin

by
Shaogong Zhu
1,†,
Yudong Cao
1,†,
Qiangtai Huang
1,2,*,
Haotong Yu
1,
Weiyan Chen
3,
Yujie Zhong
1 and
Wenchao Chen
1
1
School of Marine Sciences, Sun Yat-sen University, Zhuhai 519082, China
2
Guangdong Provincial Key Laboratory of Marine Resources and Coastal Engineering, Zhuhai 519082, China
3
Research Institute of Petroleum Exploration and Development, Beijing 100089, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
J. Mar. Sci. Eng. 2024, 12(9), 1496; https://doi.org/10.3390/jmse12091496
Submission received: 26 July 2024 / Revised: 26 August 2024 / Accepted: 28 August 2024 / Published: 29 August 2024
(This article belongs to the Special Issue Recent Developments and Advances in Geological Oceanography and Ocean Observation in the Pacific Ocean and Its Marginal Basins)
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Abstract

:
The exploration and development of conventional oil and gas resources are becoming more difficult, and the proportion of low-permeability reservoirs in newly discovered reservoir resources has expanded to 45%. As the main focus of the oil industry, the global average recovery rate of low-permeability reservoir resources is only 20%, and most crude oil is still unavailable, so our understanding of such reservoirs needs to be deepened. The microscopic pore structure of low-permeability reservoir rocks exhibits significant complexity and variability; reservoir evaluation is more difficult. For elucidating the internal distribution of storage space and the mechanisms influencing seepage, we focus on the low-permeability sandstone reservoir of the Shahejie Formation, located on the northern slope of the Chenjiazhuang uplift, Bohai Bay. Employing a suite of advanced analytical techniques, including helium expansion, pressure pulse, high-pressure mercury intrusion (HPMI), and micro-computed tomography (micro-CT) scanning, we examined the main pore–throat size affecting reservoir storage and seepage in the reservoir at both the micrometer and nanometer scales. The results reveal that pores with diameters exceeding 40 μm are sparsely developed within the low-permeability reservoir rocks of the study area. However, pores ranging from 0 to 20 μm predominate, exhibiting an uneven distribution and a clustered structure in the three-dimensional pore structure model. The pore volume showed a unimodal and bimodal distribution, thus significantly contributing to the storage space. The main sizes of the reservoir in this study area are 40–80 μm and 200–400 μm. Micron-sized pores, while present, are not the primary determinants of the reservoir’s seepage capacity. Instead, coarser submicron and nano-pores exert a more substantial influence on the permeability of the rock. Additionally, the presence of micro-fractures is found to enhance the reservoir’s seepage capacity markedly. The critical pore–throat size range impacting the permeability of the reservoir in the study area is identified to be between 0.025 and 0.4 μm.

1. Introduction

As conventional reservoir exploration and development become more difficult, traditional oil resources are no longer sufficient to meet the demand. Low-permeability oil and gas resources, widely distributed, have become the replacement of oil and gas resources [1]. In recent years, the proportion of newly discovered low-permeability reservoirs has risen to 45% [2]. Global low-permeability reservoirs account for about 38% of the total oil and gas reserves [3]. Low-permeability reservoirs exist both at sea and on land, and early deposition is an important factor affecting the heterogeneity of the reservoir. For example, the lithology of the reservoir in northwest Borneo is affected by the sedimentary process of the massive sandstone [4]. In China, the study on low-permeability reservoirs started late, and low-permeability reservoirs have been found in Ordos Basin, Songliao Basin, and Bohai Bay Basin [5]. It is difficult to exploit low-permeability reservoirs, and the global average recovery rate is only about 20% [6]. Insufficient understanding of the reservoirs’ microscopic pore structure restricts the development of the low-permeability reservoir. Clear reservoir hole–throat characteristics are very important, such as those of the dense oil reservoir discovered in 2010, the Ordos Basin, with seven long reservoirs, which was discovered through a series of experimental studies. It is concluded that the micron hole, the nanopore, is an important storage space, providing a theoretical basis for further research [7].
The northern slope of the Chenjiazhuang uplift is notable for its rich oil and gas reservoirs, with the Shahejie Formation serving as a critical hydrocarbon-bearing horizon. This formation is a focal point in our study due to its low-permeability sandstone reservoir, which is characterized by suboptimal physical properties, low permeability, pronounced heterogeneity, and poor sorting. These characteristics are primarily attributed to the earlier sedimentation and compaction processes [8,9,10]. Consequently, understanding the microscopic pore structure and its influence on seepage capacity within this formation is crucial for improving hydrocarbon recovery strategies.
Reservoir seepage capacity has a weak correlation with porosity but is significantly influenced by pore structure characteristics; small pores and narrow throats create substantial resistance to petroleum migration and accumulation, making it challenging to predict geological reserves accurately within such reservoirs using conventional methods; thus, the micro-pore structure of reservoir rocks is a critical factor affecting oil and gas storage capacity [11,12,13,14]. The reservoir space is composed of a complex pore network with numerous micro- and nano-pores. It is crucial for effective reservoir development to explore the reasons of the differences in seepage capacity from a microscopic perspective [15,16].
Previous studies have shown that the micro-pore structure is the primary factor influencing reservoir seepage capacity, including pore–throat size, distribution, and connectivity [17,18,19]. The pore–throat structure of low-permeability sandstone reservoirs is relatively complex. Current methods for characterizing micro-pore structures can be divided into two categories: direct observation and indirect measurement methods. Direct observation methods, including casting thin sections and scanning electron microscopy, can provide strong visual information, but it is difficult to obtain three-dimensional pore structure parameters. Indirect measurement methods, including mercury intrusion experiments, nuclear magnetic resonance, and gas adsorption, can offer high precision in pore structure parameters but lack strong visual representation [20,21,22,23]. With the emergence of digital core technology, three-dimensional scanning, and X-ray technology for reconstructing pore–throat structures in rock samples, the rapid, non-destructive, and detailed characterization of internal microstructures in reservoirs is now achievable [24,25,26,27]. These methods provide information on the morphology, size, and distribution of pore–throat structures but are limited by the range of pore size measurements. Therefore, multiple methods are typically combined in research processes to understand the complex pore structures in low-permeability reservoirs [28,29].
Pore–throat characteristics are important evaluation factors for reservoirs. Wu et al. [30] combined mercury intrusion and nuclear magnetic resonance to characterize the pore structures of tight sandstones in the Ordos Basin, concluding that complex pore–throat structures reduce the storage space and permeability of the reservoir, with reservoir space and seepage capacity being primarily controlled by large pore throats. Ma et al. [31] analyzed pore structures in reservoir cores from the Ordos Basin using casting thin sections, scanning electron microscopy, and mercury intrusion experiments, classifying reservoirs into four categories based on throat size and identifying medium-throat macro-pores and fine-throat meso-pores as having better pore structures. Cao et al. [32] combined mercury intrusion experiments and scanning electron microscopy to analyze the relationship between tight sandstone reservoirs and pore structures, concluding that large pore throats determine reservoir permeability and fluid flow. As unconventional oil and gas development becomes a focus, experimental data prove that small pore throats can also serve as primary storage spaces and migration pathways. Bai et al. [33] used nano–micro multi-scale CT three-dimensional imaging to characterize the micro-pore–throat structure of tight sandstone reservoirs comprehensively, identifying nano-scale tubular micro-pores as having dual functions of throats and pores. Bi et al. [34] combined casting thin sections and high-pressure mercury intrusion to analyze the differences in micro-pore structures of low-permeability reservoirs, concluding that pore–throat structures are the main factors affecting reservoir storage and seepage. Low-permeability reservoirs have fewer large nano-scale pore throats, which significantly impact seepage capacity, while small pore throats are more prevalent and mainly contribute to storage space. Therefore, further experiments are necessary to clarify the mechanisms affecting seepage in low-permeability sandstone reservoirs.
Low-permeability reservoir storage and seepage capacity are controlled by micro-pore structures. Among current observation methods, the helium expansion method can accurately measure pore sizes larger than 2 nm [35,36], high-pressure mercury intrusion can measure pore structure parameters with a diameter greater than 50 nm [37,38], and micro-CT scanning can obtain micron-level rock pore distribution characteristics. This study used the low-permeability sandstone reservoir of the Shahejie Formation in the Chenjiazhuang area as an example, combining helium expansion, pressure pulse, high-pressure mercury intrusion, and micro-CT scanning technologies to clarify the micro-pore structure characteristics of low-permeability sandstone reservoirs and explore the impact of pores at different scales on reservoir seepage capacity.

2. Regional Geology

The Chenjiazhuang uplift is centrally situated within the Jiyang depression, extending longitudinally from east to west. It is bounded to the north by a gentle slope zone transitioning into the Zhanhua sag, while the southern boundary is delineated by the Chenan fault adjacent to the Dongying sag. To the west lies the Wudi uplift, and to the east, the Qingtuozi uplift (Figure 1). Notably, significant hydrocarbon reservoirs have been identified within the Shahejie and Dongying formations along the northern slope of the uplift. The central region hosts the Chenjiazhuang Oilfield within the Guantao Formation, with additional reservoirs discovered in both the western and eastern sections of the Shahejie and Guantao formations. Moreover, shallow gas reservoirs have been identified in the Guantao and Minghuazhen formations at relatively shallower depths [39].
This study focuses on the northern segment of the Chenjiazhuang uplift, characterized by well-developed Paleogene and Neogene strata. Hydrocarbon-bearing reservoirs in this area are primarily situated within the Guantao, Dongying, and Shahejie formations, which predominantly consist of deltaic and fan-deltaic deposits. The lithology of the Shahejie Formation reservoirs mainly comprises sandstone, siltstone, and argillaceous sandstone, with porosity values ranging from 0.9% to 36.9% and permeability ranging from 0.014 to 3301.8 mD [40]. The third sedimentary period of the Shahejie Formation experienced the lake basin expansion stage, with abundant material sources and high abundance of organic matter. With the compaction, cementation, and dissolution of the diagenesis process, the reservoir rock particles become tight, resulting in the reduction of porosity and permeability. These reservoirs demonstrate rapid lithological variability and pronounced heterogeneity, presenting significant challenges for conventional reservoir evaluation methods. The pronounced pore–throat variations in low-permeability reservoirs are particularly noteworthy, and a comprehensive understanding of these characteristics is crucial for guiding the development of these reservoirs.
Jmse 12 01496 g001
Figure 1. (a) Map illustrating the geographical location of the Chenjiazhuang uplift in the Bohai Bay Basin. (b) The Chenjiazhuang uplift is situated in the northeastern part of the Jiyang Depression. (c) Map of the Jiyang Depression, indicating the specific study area location. (d) Serigraphic profile, as shown in Figure 1c (modified from [39,41,42,43]).
Figure 1. (a) Map illustrating the geographical location of the Chenjiazhuang uplift in the Bohai Bay Basin. (b) The Chenjiazhuang uplift is situated in the northeastern part of the Jiyang Depression. (c) Map of the Jiyang Depression, indicating the specific study area location. (d) Serigraphic profile, as shown in Figure 1c (modified from [39,41,42,43]).
Jmse 12 01496 g001

3. Samples and Experiments

3.1. Samples

A total of thirty samples (2.5 cm in diameter and approximately 5 cm in length) were collected from wells Chen 311 and Chen 372 in the central region and Ken 119, Ken 71, Yi 98, Yi 137, Yi 633, and Luo 353 in the eastern sector of the study area. Sampling depths ranged from 1250 m to 1450 m in the Guantao Formation and 2335 m to 2777 m in the Shahejie Formation (Table 1). The predominant lithologies encountered were sandstone and siltstone. The porosity and permeability of the thirty samples were determined using the gas measurement method, as depicted in Figure 2. Porosity spans ranged from 0.85% to 23.53%, with an average of 8.05%, while permeability ranged from 0.03 to 391 mD, with an average of 0.18 mD, excluding anomalously high values, indicating a reservoir characterized by low porosity and low permeability.
A positive correlation between porosity and permeability was observed, with permeability generally increasing alongside porosity, consistent with prior studies [44,45]. However, some samples with high porosity exhibited low permeability (Figure 2). Four representative samples were selected for high-pressure mercury intrusion and micro-CT scanning experiments (Table 2, Figure 3), complemented by the gas measurement method to characterize the pore structure of low-permeability samples quantitatively and investigate the pore–throat sizes affecting rock sample permeability.

3.2. Experiments

3.2.1. Helium Expansion Method

The gas expansion method, grounded in Boyle’s law, measures pressure changes during gas expansion to determine pore volume and calculate porosity. This method is commonly used to assess the interconnected porosity of core samples. Helium, nitrogen, and other inert gases are typically employed as filling gas. In this study, helium, the smallest non-adsorptive gas molecule, was used for its accuracy in measuring core porosity. The method is straightforward, quick, and minimally impacts the samples, allowing for their reuse in subsequent experiments.

3.2.2. Nitrogen Pressure Pulse Method

The pressure pulse decay method is a transient technique frequently utilized to measure the permeability of low-permeability cores. By applying a pressure pulse differential to the core and recording the pressure difference and time at both ends as the pressure propagates through, permeability is calculated. Nitrogen gas is used as the medium, making it suitable for low-permeability cores, offering short measurement time and high accuracy.

3.2.3. Micro-CT Scanning

CT scanning technology employs X-rays to penetrate objects, with X-ray attenuation varying according to the object’s density, in accordance with Beer’s law. Recording the attenuated X-rays yields a non-destructive density distribution image of the object, used to distinguish pores, rock frameworks, and mineral components. This technology provides detailed characterization of rock samples and is a vital three-dimensional pore characterization technique for reservoirs. Due to the high resolution of CT scanning, sample sizes are relatively small. Micro-CT scanning accuracy must reach micron levels to distinguish pores and mineral matrices effectively, with scanned rock sample sizes at the millimeter scale. This study utilized the nanoVoxel-3502E CT scanner. The scanned images underwent median filtering to eliminate noise, and image processing techniques such as threshold control were used to binarize the grayscale images, resulting in binarized images that distinguished the pores and reconstructed the three-dimensional digital core corresponding to the rock sample.

3.2.4. High-Pressure Mercury Intrusion Method

The high-pressure mercury intrusion method involves the gradual intrusion of mercury into pores under increasing pressure, adhering to the Washburn’s equation. As pressure increases, mercury penetrates finer pore throats, thus delineating the pore size distribution characteristics of the samples. The samples used in this experiment were those tested by gas measurement, which were oil-washed, dried, and vacuum-treated before high-pressure mercury intrusion testing. The testing was conducted, under conditions of 24.6 °C and 16% RH.

4. Results and Discussion

4.1. Pore–Throat Characteristics

4.1.1. Micron-Scale Pore–Throat Characteristics

CT scans of four representative samples revealed porosities of 3.11%, 1.18%, 3.79%, and 2.54%, which are notably lower than those measured by gas methods. Particularly, the porosity of sample 4-Z obtained from CT scanning is an order of magnitude lower than that determined by gas measurements. For samples 6 and 6-Z, the discrepancies between the two measurement techniques are minimal (Table 3). Helium porosity measurements encompass a broader range and are closer to the true values, whereas micro-CT primarily measures micron-scale porosities, indicating the presence of numerous nano-scale and isolated pores within the rock core [46]. The distribution of micron-scale pores (Figure 4) reveals that the primary pore size range for the four samples is 0–20 μm. Sample 4-Z exhibits significantly fewer pores in the 0–10 μm range compared to the others, while sample 6 contains more large pores, and sample 6-Z has a higher concentration of small pores.
Regarding pore volume distribution (Figure 5), sample 4 shows a relatively uniform distribution across different pore sizes, with the largest proportion (16.82%) found in pores sized between 40–80 μm. Sample 4-Z exhibits a bimodal distribution in pore volume, with peaks at 40–80 μm and 400–600 μm, accounting for 24.2% and 16.13% of the total volume, respectively. Pores in the 0–10 μm range in sample 4-Z constitute only 2.38% of the total volume. Samples 6 and 6-Z display unimodal distributions, primarily featuring pores sized between 200–400 μm pores, constituting 41.79% and 32.64% of the volume, respectively, with other pore sizes distributed more evenly. Although large pores are fewer in number, they significantly contribute to the total pore volume and serve as the principal storage spaces within the reservoir [47]. The dominant pore diameters contributing to storage are 40–80 μm for samples 4 and 4-Z and 200–400 μm for samples 6 and 6-Z.
The helium expansion method is accurate in measuring core porosity and the results are closer to the true values, whereas micron CT primarily measures micron-scale porosities.
The 3D visualization models from CT scanning (Figure 6) depict the transparent rock matrix, with pores highlighted in red, providing insights into the quantity, size, and distribution of micron-scale pores [48]. Sample 4 shows minimal variation in pore sizes and a uniform distribution. In contrast, sample 4-Z exhibits significantly fewer pores with larger size variations and an uneven distribution, characterized by sheet-like fractures containing small pores and isolated pores surrounding these fractures. Samples 6 and 6-Z display similar pore morphology and distribution patterns, with sample 6 containing more large pores and sample 6-Z featuring more small pores. Both samples exhibit clustered distributions with isolated pores interspersed. The 3D pore structure models indicate that sample 4 possesses the most favorable pore structure, followed by samples 6 and 6-Z, whereas sample 4-Z exhibits the least favorable structure.

4.1.2. Nano-Scale Pore–Throat Characteristics

Figure 7 illustrates the relationship between capillary force and mercury volume/saturation, providing insights into the pore structure characteristics of sandstone reservoirs. As pressure increases, mercury penetrates smaller throats to enter the pores, showing three distinct stages on the curve. Initially, mercury enters larger pores at relatively low pressures. The second stage features a segment where pressure changes minimally while mercury saturation significantly increases, indicating intrusion into medium-sized pores. In the final stage, at higher pressures, mercury enters smaller pores [49,50,51,52]. During the first stage, samples 4 and 4-Z exhibit significant mercury intrusion at relatively low pressures (1.362 MPa and 1.365 MPa), corresponding to larger pore throats, whereas samples 6 and 6-Z require higher pressures (5.504 MPa and 5.501 MPa), indicating smaller pore throats. In the second stage, the flat sections of the mercury intrusion curves for samples 4 and 4-Z align with larger pore throats, showing mercury increments of 27% and 30%, indicating less-developed pore throats. Samples 6 and 6-Z exhibit longer flat sections during mercury intrusion, with mercury increments of 66%, indicating more extensive pore–throat development, which enhances rock permeability. Although the pore throats in samples 6 and 6-Z are smaller, their development is more extensive. In the third stage, the curves for samples 4 and 4-Z show longer sharp peaks, with a significant increase in intrusion pressure, yet less than 5% mercury intrusion. Despite some mercury entering capillaries at this stage, resistance is high, resulting in minimal mercury intrusion. These smaller pore throats have a limited impact on rock permeability, with some not participating in the flow. Conversely, samples 6 and 6-Z display shorter, sharp peaks, indicating that small pores remain developed and actively participate in storage and flow.
The maximum mercury intrusion saturation reflects the storage and flow capacity of the reservoir. At maximum pressure (200 MPa), mercury intrusion saturation exceeds 90% for samples 6 and 6-Z, whereas it remains below 50% for samples 4 and 4-Z. As mercury enters the rock, it fills the pores and throats. During mercury extrusion, some mercury remains in the pores, where the extruded volume often corresponds to the throat volume. The difference between the intrusion and extrusion volumes indicates the pore volume. Therefore, the intrusion and extrusion curves also provide insights into the pore and throat volumes within rock samples [53,54]. In comparison, samples 6 and 6-Z exhibit larger pore and throat volumes, with pore volumes of 59.4% and 34.8%, and throat volumes of 58.8% and 37.8%, respectively. Conversely, samples 4 and 4-Z display steeper extrusion curves indicative of smaller throat volumes. Sample 4 has pore and throat volumes of 36% and 7.6%, while sample 4-Z shows volumes of 30.5% and 6.2%, respectively.
The pore–throat distribution diagrams obtained from high-pressure mercury intrusion experiments are depicted in Figure 8. All four samples exhibit unimodal distributions of pore–throat radii. Samples 4 and 4-Z show limited development of pore throats, primarily in the range of 0.063–0.4 μm, with minimal development of pore throats smaller than 0.063 μm. In contrast, samples 6 and 6-Z display a wider range of pore–throat sizes, spanning from 0.004 to 0.1 μm, predominantly centered around 0.016–0.04 μm, indicating finer pore–throat sizes overall. The permeability contribution images shift to the right compared to the frequency distribution of pore throats. Larger pore throats, although less frequent (accounting for less than 10% of the distribution), contribute significantly to permeability (up to 40%). In contrast, smaller pore throats, despite higher distribution frequencies, contribute less to permeability. For instance, pore throats ranging from 0.16–0.4 μm in samples 4 and 4-Z contribute over 95% to permeability, whereas those ranging from 0.025–0.1 μm in samples 6 and 6-Z also contribute over 95%, with smaller throats making negligible contributions. In summary, samples 4 and 4-Z feature larger nano-scale pore throats primarily in the 0.063–0.4 μm range, albeit with smaller volumes and less developed throats. Conversely, samples 6 and 6-Z exhibit smaller nano-scale pore throats mainly between 0.016–0.04 μm, with larger volumes and better-developed throats.
The pore and throat systems within reservoir rocks are often interconnected in a complex network. Parameters derived from mercury intrusion experiments can elucidate the distribution characteristics and connectivity of pore throats (Table 4). The maximum pore–throat radius (Ra) signifies the dimension of the throat at which mercury first penetrates the pore network, serving as the primary filtration conduit. The sorting coefficient (SP) denotes the degree of concentration in pore–throat size distribution; a smaller SP indicates more uniform pore throats, manifesting as a flat section on the intrusion curve. Skewness (SKP) and kurtosis (KP) describe the relative position and steepness of the pore–throat frequency distribution mode. A positive SKP indicates coarser skewness, while a negative SKP indicates finer skewness. Kurtosis reflects the steepness of the distribution curve; a higher KP signifies a steeper curve, indicating a higher frequency of pore throats. The homogeneity coefficient (a) assesses the uniformity of the pore–throat distribution; within the 0–1 range, a larger value suggests a more uniform distribution [23,55,56,57]. Samples 4 and 4-Z exhibit relatively coarser pore throats, with a flatter frequency distribution and finer skewness. Conversely, samples 6 and 6-Z display finer pore throats, with a sharper frequency distribution and coarser skewness. Considering the overall development of pore–throat sizes, samples 6 and 6-Z are inferred to possess more uniform pore–throat distributions. Displacement pressure (Pcd) represents the capillary pressure when mercury continually infiltrates the rock sample, corresponding to the maximum pore–throat radius. Maximum mercury intrusion saturation (Smax) and final residual saturation (Sr) reflect the storage and flow capacities of the rock sample. The structural coefficient indicates the tortuosity of the pore throats; a higher value signifies greater tortuosity [58,59]. Samples 4 and 4-Z exhibit lower displacement pressures—aligning with coarser pore throats—and lower maximum mercury intrusion saturations, with extrusion efficiencies of only 17.412%. The throats are highly tortuous, as suggested by the larger structural coefficients, indicating poorer storage and flow capacities, with more hourglass-type pore structures. In contrast, samples 6 and 6-Z display higher displacement pressures, generally finer pore throats, maximum mercury intrusion saturations exceeding 90%, and extrusion efficiencies approaching 40%, suggesting less tortuosity. Hence, samples 6 and 6-Z possess superior nano-scale pore structures compared to the poorer structures of samples 4 and 4-Z.

4.2. Permeability Characteristics

4.2.1. Pore–Throat Distribution

Porosity and permeability are pivotal parameters in reservoir characterization, exhibiting a strong interrelationship. Test results from samples in the Chenjiazhuang area demonstrate instances of low permeability, even in rocks with relatively high porosity. In gas measurement experiments of four representative samples, samples 4 and 4-Z exhibit porosities of 7.85% and 11.74%, respectively, with corresponding permeabilities of 0.0369 mD and 0.0834 mD, indicating a significant disparity. Conversely, samples 6 and 6-Z, with smaller porosities of 4.62% and 4.69%, exhibit higher permeabilities of 0.0764 mD and 0.0964 mD, respectively. Micro-CT scan images reveal that sample 4, despite having a porosity of 3.11% and well-developed micropores with good distribution, possesses a permeability of only 0.0369 mD. In comparison, samples 6 and 6-Z, with similar porosities of 3.79% and 2.54%, exhibit pore diameters primarily within 10 μm and a pore volume distribution frequency mainly between 200–400 μm, reflecting an uneven distribution and the presence of many unconnected pores. Nonetheless, their permeabilities are significantly higher, at 0.0764 mD and 0.0964 mD, respectively. This suggests that micropore structure alone does not account for the differences in permeability.
For samples 6 and 6-Z, the nano-scale pore structure data from high-pressure mercury intrusion experiments exhibit remarkable similarities. The intrusion and extrusion curves display only subtle differences, and the distributions of pore–throat sizes and their contributions to permeability are consistent. It is inferred that the development of nano-scale pore structures has a minor impact on the differences in porosity and permeability. Micro-CT scan images reveal that sample 6 possesses more-developed coarse pores and throats at the micro-scale, with larger volumes. Pores with diameters of 80–300 μm account for 62.33% of the volume, while those smaller than 10 μm account for only 10.75%. Conversely, sample 6-Z shows more developed fine pores and throats at the micro-scale, with 80–300 μm pores accounting for 45.85% of the volume and those smaller than 10 μm comprising 23.16%. Both samples display numerous isolated pores in the images, likely resulting from relatively closed pores due to compaction. Nevertheless, small etched pores within rock particles can serve as efficient transport channels, enhancing reservoir filtration [60]. The abundant 10 μm pores and throats in sample 6-Z can connect larger pores, thereby improving permeability, making it superior to sample 6 in conditions where there is minimal difference in the development of nano-scale pores and throats. In low-permeability reservoirs, larger pores may significantly reduce their contribution to permeability due to compaction, while well-developed small pores can act as transport channels between larger pores. Thus, in addition to nano-scale pores and throats, fine pores at the micro-scale can enhance permeability.

4.2.2. Capillary Pressure

High-pressure mercury intrusion experiments more accurately depict the development characteristics of pores and throats at the nano-scale and above. A comparison of the capillary pressure curves for samples 4, 6, and 6-Z reveals substantial differences in the smooth sections of the curves. For sample 4, there is a sharp inflection appears when mercury saturation reaches 40%, indicating that pore–throat sizes have minimal impact on permeability. The area between the intrusion and extrusion curves further indicates that sample 4 has a small pore and throat volume, particularly a small throat volume, resulting in a low extrusion efficiency of only 17.412%. This leads to the phenomenon of high porosity yet low permeability. Samples 6 and 6-Z exhibit mercury saturation of more than 90%; when the pressure is large, mercury can still enter the throat; hence, the development of its permeability is superior. In low-permeability reservoirs, a complex pore network is often present. Pores provide excellent storage spaces, while throats are crucial for reservoir flow. The absence of flow-contributing throats in the reservoir rock leads to the development of large-pore–micro-throat structures, which weakly contribute to permeability. The development of sub-micron and nano-scale pores and throats significantly enhances reservoir flow capacity [61,62].

4.2.3. Micro-Crack

The micro-CT scan results for sample 4-Z reveal a suboptimal distribution of pores and throats in its structure, characterized by a sparse and uneven network of pores and throats. Pores within the 0–10 μm range are relatively fewer compared to the other three samples, suggesting poor connectivity. However, the three-dimensional images show numerous micro-cracks. The mercury intrusion experiment indicates a paucity of nano-scale pores and throats in this rock sample. The maximum mercury intrusion saturation is 36.733%, slightly lower than the 43.622% observed in sample 4, with a residual mercury saturation of 30.53%. Throats with radii of 0.25–0.4 μm contribute over 90% of the permeability. In comparison, sample 4-Z exhibits better development of coarser nano-scale pores and throats. Considering the pore structure parameters, the connectivity of pores and throats in sample 4 is superior to that in sample 4-Z, with sample 4-Z showing a permeability of 0.083 mD, better than sample 4 of 0.037 mD. In low-permeability reservoirs, the presence of micro-cracks significantly impacts permeability.

5. Conclusions

By integrating gas measurement experiments, high-pressure mercury intrusion techniques, and micro-CT scanning, a comprehensive analysis was conducted on the micropore structure of low-permeability sandstone reservoirs from the Shahejie Formation, situated on the northern slope of the Chenjiazhuang uplift. This paper explores the impact of pore and throat dimensions on reservoir storage capacity and permeability at both micro- and nano-scales. Four representative core samples from the region underwent meticulous examination to characterize the number, structural distribution, and pore parameters of micro- and nano-pores, yielding the following findings:
(1)
Reservoir pores in the study area exhibit significant heterogeneity, characterized by predominantly small pore sizes, clustered distributions, and numerous isolated pores. Micro-scale pore diameters range from 0 to 600 μm, with a majority falling within 0–20 μm and few exceeding 40 μm. The distribution curve of pore diameters reveals two distinct types: a unimodal distribution concentrated in the 200–400 μm range, conducive to hydrocarbon accumulation, and a bimodal distribution peaking at 40–80 μm and 400–600 μm. Nano-scale pore distribution spans 0.004 to 0.4 μm, displaying a unimodal curve that significantly contributes to reservoir storage capacity.
(2)
Large micro-scale pores within the reservoir require small throats to establish effective flow channels. However, the presence of well-developed micro-scale pores is not the principal factor influencing reservoir flow. In rocks with well-developed micro-scale pore structures, permeability remains low. Mercury injection experiments indicate that in low-permeability reservoirs, sub-micron- and nano-scale pores predominantly govern permeability. Well-developed nano-scale pores with favorable structures serve as efficient flow conduits. Critical pore–throat sizes influencing filtration range from 0.025 to 0.4 μm, representing a relatively coarse category within nano-scale pore throats. Additionally, micro-cracks within the reservoir rock notably enhance permeability.

Author Contributions

S.Z.: Methodology, Supervision, Validation, Visualization, Writing—original draft, Writing—review and editing. Y.C.: Methodology, Supervision, Validation, Visualization, Writing—original draft, Writing—review and editing. Q.H.: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Writing—review and editing. H.Y.: Data curation, Formal analysis, Investigation. W.C. (Weiyan Chen): Methodology, Data curation, Formal analysis, Investigation. Y.Z.: Methodology, Data curation, Formal analysis, Investigation. W.C. (Wenchao Chen): Methodology, Data curation, Formal analysis, Investigation. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Shengli Oilfield Science and Technology Project (Grant No. 30200020-22-FW2022-0001).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The full data are provided in the in text tables.

Acknowledgments

We would like to thank Jianbing Zhu and Hongmei Li for their help in the fieldwork.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Figure 2. Relationship between porosity and permeability of sandstone reservoirs from Shahejie and Guantao formations.
Figure 2. Relationship between porosity and permeability of sandstone reservoirs from Shahejie and Guantao formations.
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Figure 3. Photographs of core samples. From left to right: sample 4 (well 199-14, 2529.6 m; 2.5 cm in diameter and approximately 5.2 cm in length); sample 4-Z (well 199-14, 2529.6 m; 2.5 cm in diameter and approximately 3.8 cm in length); sample 6 (well 199-8, 2370 m; 2.5 cm in diameter and approximately 5.3 cm in length); sample 6-Z (well 199-8, 2370 m; 2.4 cm in diameter and approximately 4.3 cm in length).
Figure 3. Photographs of core samples. From left to right: sample 4 (well 199-14, 2529.6 m; 2.5 cm in diameter and approximately 5.2 cm in length); sample 4-Z (well 199-14, 2529.6 m; 2.5 cm in diameter and approximately 3.8 cm in length); sample 6 (well 199-8, 2370 m; 2.5 cm in diameter and approximately 5.3 cm in length); sample 6-Z (well 199-8, 2370 m; 2.4 cm in diameter and approximately 4.3 cm in length).
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Figure 4. Distribution of pores of different diameters in the core samples via micro-CT scanning.
Figure 4. Distribution of pores of different diameters in the core samples via micro-CT scanning.
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Figure 5. Volume ratio of pores with different diameters in the core samples via micro-CT scanning.
Figure 5. Volume ratio of pores with different diameters in the core samples via micro-CT scanning.
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Figure 6. Micro-CT scanning model of pore structure: (a) sample 4; (b) sample 4-Z; (c) sample 6; (d) sample 6-Z.
Figure 6. Micro-CT scanning model of pore structure: (a) sample 4; (b) sample 4-Z; (c) sample 6; (d) sample 6-Z.
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Figure 7. Mercury injection and extrusion curves derived from high-pressure mercury intrusion (HPMI) analysis.
Figure 7. Mercury injection and extrusion curves derived from high-pressure mercury intrusion (HPMI) analysis.
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Figure 8. Relationships between permeability contribution and pore–throat size distribution derived from high-pressure mercury intrusion (HPMI) analysis.
Figure 8. Relationships between permeability contribution and pore–throat size distribution derived from high-pressure mercury intrusion (HPMI) analysis.
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Table 1. Basic physical parameters of 30 core samples.
Table 1. Basic physical parameters of 30 core samples.
WellNumberDepthFormationLithologyDiameter,
mm		Length,
mm		Density, g/cm3Porosity,
%		Permeability,
mD
K119-141–42529.6Es3sandstone25.152.182.5397.850.0369
1–4–Z2529.6Es3sandstone2538.082.42811.740.0834
1–322529.6Es3sandstone37.8940.522.5410.850.04079
K119-21–12181.8Es3sandstone2559.32.5167.680.1358
K119-81–62370–2377Es3sandstone2553.482.5934.620.0764
1–6–Z2370–2377Es3sandstone24.543.142.5824.690.0964
1–132370–2377Es3sandstone37.86552.5871.610.04489
K71-11–21439.5–1449.5Ngsandstone25.2640.12.5632.050.1309
1–2–Z1439.5–1449.5Ngsandstone25.1260.12.5712.490.0384
1–81439.5–1449.5Ngsandstone25.2434.252.5741.560.0624
1–251439.5–1449.5Ngsandstone3854.182.5872.160.0358
1–201439.5–1449.5Ngsandstone38.154.82.5452.750.0756
1–211439.5–1449.5Ngsandstone38.1642.742.5852.960.21734
C 3112–11250.5Ngsiltstone24.42148.6352.5386.6657.2046
C 3722–21248.7Ngsiltstone24.28350.8552.6142.340.0607
2–31254.6Ngsandstone24.57843.5952.553.3920.2034
2–4–11256.7Ngsiltstone24.56144.2352.5942.3020.0914
2–4–21256.7Ngsiltstone24.57443.8952.6122.2780.0845
C 982–52773.2Es3siltstone24.29943.272.21514.3084.3016
2–62776.5Es3siltstone24.47950.4852.27513.1350.9793
2–6–Z2776.5Es3siltstone24.45913.422.20116.0240.2379
2–6–12776.5Es3siltstone24.46245.4252.29615.4250.8464
2–6–22776.5Es3siltstone24.45412.8552.24514.8450.8742
C 1372–72353.6Es3sandstone24.27343.7351.99820.884113.598
2–82335.6Es3sandstone23.98243.42.05819.146391.196
Y 6332–92734.3Es3mudstone24.57648.6352.3938.5976.5225
2–9–Z2734.3Es3mudstone24.38421.7152.4296.9470.0389
2–102731.25Es3sandstone24.26324.662.4057.6570.5902
L 3532–11–12433.9Es3sandstone24.12726.9051.99723.53147.167
2–11–22433.9Es3sandstone24.21525.9852.03522.84550.134
Table 2. Basic physical parameters of four representative sandstone samples.
Table 2. Basic physical parameters of four representative sandstone samples.
SampleDensity/g/cm3Porosity/%Permeability/%
42.5397.850.0369
4-Z2.42811.740.0834
62.5934.620.0764
6-Z2.5824.690.0964
Table 3. Comparison of the porosity results tested via the helium expansion method and micro-CT scanning.
Table 3. Comparison of the porosity results tested via the helium expansion method and micro-CT scanning.
SampleLithologyPorosity/% (He)Porosity/% (CT)
4sandstone7.853.11
4-Zsandstone11.741.18
6sandstone4.623.79
6-Zsandstone4.692.54
Table 4. Sandstone reservoirs in northern slope of Chenjiazhuang Uplift.
Table 4. Sandstone reservoirs in northern slope of Chenjiazhuang Uplift.
SampleRaRpSPSKPKPɸaPcdSmaxSrWe
40.5400.1762.497−1.0000.4908.2530.3261.36243.62236.02717.412
4-Z0.5380.2392.628−1.0000.46710.0180.4431.36536.73330.53016.888
60.1340.0351.3110.2061.3020.0920.2615.50494.18259.35736.976
6-Z0.1340.0371.3070.1671.2020.0820.2755.50196.57858.77339.145
Ra: maximum pore–throat radius; Rp: average pore–throat radius; SP: sorting coefficient; SKP: skewness; KP: kurtosis; ɸ: structural coefficient; a: homogeneity coefficient; Pcd: displacement pressure; Smax: maximum mercury intrusion saturation; Sr: final residual saturation; We: exit efficiency.
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Zhu, S.; Cao, Y.; Huang, Q.; Yu, H.; Chen, W.; Zhong, Y.; Chen, W. Impact of Pore Structure on Seepage Capacity in Tight Reservoir Intervals in Shahejie Formation, Bohai Bay Basin. J. Mar. Sci. Eng. 2024, 12, 1496. https://doi.org/10.3390/jmse12091496

AMA Style

Zhu S, Cao Y, Huang Q, Yu H, Chen W, Zhong Y, Chen W. Impact of Pore Structure on Seepage Capacity in Tight Reservoir Intervals in Shahejie Formation, Bohai Bay Basin. Journal of Marine Science and Engineering. 2024; 12(9):1496. https://doi.org/10.3390/jmse12091496

Chicago/Turabian Style

Zhu, Shaogong, Yudong Cao, Qiangtai Huang, Haotong Yu, Weiyan Chen, Yujie Zhong, and Wenchao Chen. 2024. "Impact of Pore Structure on Seepage Capacity in Tight Reservoir Intervals in Shahejie Formation, Bohai Bay Basin" Journal of Marine Science and Engineering 12, no. 9: 1496. https://doi.org/10.3390/jmse12091496

APA Style

Zhu, S., Cao, Y., Huang, Q., Yu, H., Chen, W., Zhong, Y., & Chen, W. (2024). Impact of Pore Structure on Seepage Capacity in Tight Reservoir Intervals in Shahejie Formation, Bohai Bay Basin. Journal of Marine Science and Engineering, 12(9), 1496. https://doi.org/10.3390/jmse12091496

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