Role of pore structure in the percolation and storage capacities of deeply buried sandstone reservoirs: A case study of the Junggar Basin, China

Qiao, J.C.; Zeng, Jianhui; Jiang, Shu; Ma, Yong; Feng, Song; Huafeng, Xie; Wang, Yanu; Hu, Huiting

doi:10.1016/j.marpetgeo.2019.104129

Cited by 24 publications

(11 citation statements)

References 53 publications

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“…Combined with the results of high-pressure mercury intrusion experiment, for limestone formation, the percentage of micron-and submicron-scale pores has a tendency to increase as permeability increases, but the nanoscale pores still account for a large proportion. While the main contribution to permeability is derived from the micron-and submicron-scale pores, the fluid storage does not match the flow space, resulting in high resistance gradient (Wang et al 2019;Qiao et al 2020;Zhang et al 2020).…”

Section: Resultsmentioning

confidence: 99%

Influence of reservoir lithology on porous flow resistance of gas-bearing tight oil reservoirs and production forecast

Rao

Yang

Zhang

et al. 2021

J Petrol Explor Prod Technol

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The release of dissolved gas during the development of gas-bearing tight oil reservoirs has a great influence on the effect of development. In this article, the high-pressure mercury intrusion experiment was carried out in cores from different regions and lithologies of the Ordos Basin and the Sichuan Basin. The objectives are to study the microscopic characteristics of the porous throat structure of these reservoirs and to analyze the porous flow resistance laws of different lithology by conducting a resistance gradient test experiment. A mathematical model is established and the oil production index is corrected according to the experiment results to predict the oil production. The experimental results show that for tight reservoirs in the same area and lithology, the lower the permeability under the same back pressure, the greater the resistance gradient. And for sandstone reservoirs in different areas, the resistance gradients have little difference and the changes in the resistance coefficients are similar. However, limestone under the same conditions supports a much higher resistance gradient than sandstone reservoirs. Furthermore, the experimental results are consistent with the theoretical analysis indicating that the PVT (pressure–volume-temperature) characteristics in the nanoscale pores are different from those measured in the high-temperature, high-pressure sampler. Only when the pressure is less than a certain value of the bubble point pressure, the dissolved gas will begin to separate and generate resistance. This pressure is lower than the bubble point pressure measured in the high-temperature and pressure sampler. The calculation results show that the heterogeneity of limestone reservoirs and the mismatch of fluid storage and flow space will make the resistance, generated by the separation of dissolved gas, have a greater impact on oil production.

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Section: Resultsmentioning

confidence: 99%

Influence of reservoir lithology on porous flow resistance of gas-bearing tight oil reservoirs and production forecast

Rao

Yang

Zhang

et al. 2021

J Petrol Explor Prod Technol

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“…Therefore, it was difficult to use a single experiment to characterize the complete PSD of tight sandstone reservoirs. Furthermore, even though several scholars have attempted to reveal the overall PSD of tight sandstone reservoirs via the integration of multiple techniques and have established a new method of integrating N 2 GA and NMR via points of connection (POC) to the end of realizing the full PSD of tight sandstone reservoirs [18,25,39], the full PSDs obtained using these methods cannot reveal nanoscale pore characteristics owing to the unsuitable nature of the techniques. Therefore, we attempted to integrate NMRC with NMR using the POC technique to the end of effectively deriving the full range PSD of tight sandstone reservoirs.…”

Section: Discussionmentioning

confidence: 99%

“…The first step to conflating PSD based on NMRC and NMR curves is to define the points of connection (POC); the unit incremental volumes of pores are equal at the point when two PSD curves intersect [18,25]. Thereafter, choosing the appropriate parts of the PSD curves between the different POCs is crucial.…”

Section: Discussionmentioning

confidence: 99%

“…However, pores with diameter larger than 10 μm or less than 0.01 μm were difficult to detect accurately owing to shielding effects [3]. Furthermore, CRMI may overcome the setbacks associated with a high pressure; however, it is limited by the maximum pressure that results when the pore size is below 120 nm [24,25], and reportedly, N 2 GA does not offer the possibility to detect pore sizes that exceed 200 nm; thus, it is unsuitable for the characterization of tight sandstone reservoirs [18]. It has also been observed that NMR only offers the possibility to reflect the approximate outline and range of the PSD, but cannot accurately reflect the pore size changes within a small range [4,26].…”

Section: Introductionmentioning

confidence: 99%

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Integration of NMR and NMRC in the Investigation of the Pore Size Distribution of Tight Sandstone Reservoirs: A Case Study in the Upper Paleozoic of Dongpu Depression

et al. 2021

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Exploring appropriate methods to understanding the pore structure and overall pore size distribution (PSD) of tight sandstone reservoir is important for evaluating the quality of the reservoir. An integration analysis comprising X-ray diffraction (XRD), three beams of argon ion (TIB) polishing approach, scanning electron microscopy (SEM), high-pressure mercury intrusion (HPMI), nuclear magnetic resonance (NMR), and nuclear magnetic resonance cryoporometry (NMRC) was applied to determine the pore structure of the tight sandstone reservoirs in the Upper Paleozoic of Dongpu Depression as well as their relationship with the physical properties of the reservoirs. NMRC offered the possibility to obtain the nanoscale (4-1400 nm) pore structure of the reservoirs directly and accurately. Therefore, an attempt by combining NMRC and NMR can reveal the PSD of tight sandstone reservoirs with different pore structures. The results showed that the tight sandstone reservoirs consisted of intergranular, intragranular, and intercrystalline (clay mineral) pores. The full PSD intelligibly showed pore structure characteristics of four different types of reservoirs, with pore sizes ranging from 2 nm to dozens of microns. Specifically, the overall PSD of type I reservoirs showed a broad unimodal distribution pattern with the peaks in the range 0.1–2 μm, indicating an association with dissolution intergranular pores, and for type II reservoirs, the overall PSD showed a bimodal distribution pattern, with their left and right peaks, in the ranges 0.004–0.01 μm and 0.15–0.4 μm, respectively, showing similar amplitudes, implying the predominance of both intergranular (mesopores) and intergranular (macropores) pores. The full PSDs of type III and IV reservoirs showed much lower amplitudes than type I and II reservoirs, indicating a lower pore number and a complex pore structure. Furthermore, NMRC also demonstrated that different diagenesis resulted in a correlation between pore structure and reservoir physical properties.

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“…MICP can give an important indication of small pore size distribution due to the ultrahigh intrusion pressure, but it is inadequate to describe the large pore size distribution (>40 µm) on account of shielding effects [61]. Moreover, only connected pore-throat network is investigated by mercury intrusion techniques, since isolated pore space cannot be reached during the intrusion process [56].…”

Section: Implications For a Full-range Of Pore Size Distributionmentioning

confidence: 99%

Characterization of Pore Structures and Implications for Flow Transport Property of Tight Reservoirs: A Case Study of the Lucaogou Formation, Jimsar Sag, Junggar Basin, Northwestern China

Zhang

Liu

et al. 2021

Energies

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Quantitate characterization of pore structures is fundamental to elucidate fluid flow in the porous media. Pore structures of the Lucaogou Formation in the Jimsar Sag were investigated using petrography, mercury intrusion capillary porosimetry (MICP) and X-ray computed tomography (X-ray μ-CT). MICP analyses demonstrate that the pore topological structure is characterized by segmented fractal dimensions. Fractal dimension of small pores (r < Rapex) ranges from 2.05 to 2.37, whereas fractal dimension of large pores (r > Rapex) varies from 2.91 to 5.44, indicating that fractal theory is inappropriate for the topological characterization of large pores using MICP. Pore volume of tight reservoirs ranges over nine orders of magnitude (10−1–108 μm3), which follows a power-law distribution. Fractal dimensions of pores larger than a lower bound vary from 1.66 to 2.32. Their consistence with MICP results suggests that it is an appropriate indicator for the complex and heterogeneous pore network. Larger connected pores are primary conductive pathways regardless of lithologies. The storage capacity depends largely on pore complexity and heterogeneity, which is negatively correlated with fractal dimension of pore network. The less heterogeneous the pore network is, the higher storage capability it would have; however, the effect of pore network heterogeneity on the transport capability is much more complicated.

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Role of pore structure in the percolation and storage capacities of deeply buried sandstone reservoirs: A case study of the Junggar Basin, China

Cited by 24 publications

References 53 publications

Influence of reservoir lithology on porous flow resistance of gas-bearing tight oil reservoirs and production forecast

Influence of reservoir lithology on porous flow resistance of gas-bearing tight oil reservoirs and production forecast

Integration of NMR and NMRC in the Investigation of the Pore Size Distribution of Tight Sandstone Reservoirs: A Case Study in the Upper Paleozoic of Dongpu Depression

Characterization of Pore Structures and Implications for Flow Transport Property of Tight Reservoirs: A Case Study of the Lucaogou Formation, Jimsar Sag, Junggar Basin, Northwestern China

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