Sandstone reservoirs exhibit strong heterogeneity and complex microscopic pore structures, presenting challenges for quantitative characterization. This study investigates the Chang 8 tight sandstone reservoir in the Jiyuan, Ordos Basin through analyses of its physical properties, high-pressure mercury injection (HPMI), casting thin sections (CTS), and scanning electron microscopy (SEM). Deep learning techniques were employed to extract the geometric parameters of the pores from the SEM images. Fractal geometry was applied for the combined quantitative characterization of pore parameters and fractal dimensions of the tight sandstone. This study also analyzed the correlations between the fractal dimensions, sample properties, pore structure, geometric parameters, and mineral content. The results indicate that the HPMI-derived fractal dimension (D_MIP) reflects pore connectivity and permeability. D_MIP gradually increases from Type I to Type III reservoirs, indicating deteriorating pore connectivity and increasing reservoir heterogeneity. The average fractal dimensions of the small and large pore-throats are 2.16 and 2.52, respectively, indicating greater complexity in the large pore-throat structures. The SEM-derived fractal dimension (D_SEM) reflects the diversity of pore shapes and the complexity of the micro-scale geometries. As the reservoir quality decreases, the pore structure becomes more complex, and the pore morphology exhibits increased irregularity. D_MIP and D_SEM values range from 2.21 to 2.49 and 1.01 to 1.28, respectively, providing a comprehensive quantitative characterization of multiple pore structure characteristics. The fractal dimension shows negative correlations with permeability, porosity, median radius, maximum mercury intrusion saturation, mercury withdrawal efficiency, and sorting factor, while showing a positive correlation with median and displacement pressures. Among these factors, the correlations with the maximum mercury intrusion saturation and sorting factor are the strongest (R² > 0.8). Additionally, the fractal dimension is negatively correlated with pore circularity and major axis length, but positively correlated with pore perimeter, aspect ratio, and solidity. A higher proportion of circular pores and fewer irregular or long-strip pores correspond to lower fractal dimensions. Furthermore, mineral composition influences the fractal dimension, showing negative correlations with feldspar, quartz, and chlorite concentrations, and a positive correlation with carbonate content. This study provides new perspectives for the quantitative characterization of pore structures in tight sandstone reservoirs, enhances the understanding of low-permeability formation reservoir performance, and establishes a theoretical foundation for reservoir evaluation and exploration development in the study area.

The micro-pore structure of a tight sandstone reservoir remarkably impacts the occurrence characteristics of the tight oil. The micro-pore structure of the Jiyuan Chang 8 tight sandstone reservoir in the Ordos Basin was examined in this research using a core physical property test, an environmental scanning electron microscope, thin section identification, and high-pressure mercury intrusion. Using nano-CT scanning and nuclear magnetic resonance technologies, representative core samples were chosen for studies evaluating the tight oil occurrence statically and dynamically. The micro-pore structure effect of a tight sandstone reservoir on the occurrence of tight oil was investigated, and the occurrence of tight oil in the reservoir forming process was discussed. It was significant to the study of tight oil in the reservoir forming process in Ordos Basin. Findings indicated that the Chang 8 reservoir in Jiyuan, Ordos Basin has poor physical properties and exhibits a high degree of heterogeneity. In addition, the oil charging simulation experiment (oil charging) can be separated into the following three stages: fast growth, gradual growth, and stability. In the process of crude oil charging, oil always preferentially entered into medium pores and large pores. These pores were the primary areas of tight oil distribution. Furthermore, the occurrence of tight oil was affected by pore type, pore structure parameters, throat parameters, and combination mode of pore and throat. First, substantially large and medium pores lead to effective pore connectivity and generate a considerable amount of tight oil. The occurrence morphology includes oil film, cluster, porous, and isolated. Second, the greater the degree of intergranular pore growth and soluble feldspar pore development, the thicker the throat, the more developed the effective throat, and the greater the quantity of tight oil. Finally, oil saturation was negatively correlated with median pressure and displacement pressure and positively correlated with sorting factors, median radius, maximum pore throat radius, and efficiency of inverted mercury.

In the Carboniferous–Permian period, several organic-rich black shales were deposited in a marine–continental transitional environment in the Linfen area on the eastern margin of the Ordos Basin. Integrated sedimentological and organic geochemical analyses are performed on an outcrop in order to clarify the relationship between paleoenvironment and organic matter accumulation. The results of this study show that the marine–continental transitional strata of the Upper Carboniferous Benxi Formation to Lower Permian Taiyuan and Shanxi Formation exposed in the Linfen area are composed of sandstone, shale, coal, and limestone. Total organic carbon (TOC) contents of the studied samples were mainly distributed in the range of 0.59%–35.4%, with an average of 7.32%. From Benxi Formation to Shanxi formation, the humidity gradually increased, and the climate gradually changed from hot and humid to warm and humid during Carboniferous to Permian. The deposition of the Shanxi Formation ended with the climate returning to hot and humid, having an oxic-suboxic conditions and a high paleoproductivity. Paleoredox conditions and paleoproductivity are the two vital factors controlling the formation of organic matter in black shales. The transitional environment characterized by oxic-suboxic, relatively high deposition rate, and various source of organic matter, although different from the marine environment, provides a good material basis for the deposition of organic-rich shales.

This study focuses on low resistivity thick layer sandstone in the X~XII groups of the third member of Qingshankou Formation at Daqingzijing oilfield, along with comprehensive data of logging, core, oil test, and production test. Based on the current data, we characterized the logs of low resistivity thick-layer sandstone, quantitatively identified calcareous sandstone and low resistivity reservoir, predicted the reservoir thickness, and further explored the causes of low resistivity reservoir of the region. The resistivity of thick layer sandstone in the X~XII groups of Qingshankou Formation can be classified into low amplitude logfacies, middle amplitude logfacies, and sharp high amplitude logfacies. Sharp high amplitude logfacies sandstone is the tight sandstone of the calcareous cementation. Low amplitude logfacies sandstone is water layer. For the middle amplitude logfacies sandstone, water layer or oil-water layer can be identified with the identification standard. Low amplitude structure, high clay content, high irreducible water saturation, and high formation water salinity are attributed to the origin of low resistivity oil layer.

Tight sandstone reservoirs are a primary focus of research on the geological exploration of petroleum. However, many reservoir classification criteria are of limited applicability due to the inherent strong heterogeneity and complex micropore structure of tight sandstone reservoirs. This investigation focused on the Chang 8 tight reservoir situated in the Jiyuan region of the Ordos Basin. High-pressure mercury intrusion experiments, casting thin sections, and scanning electron microscopy experiments were conducted. Image recognition technology was used to extract the pore shape parameters of each sample. Based on the above, through grey relational analysis (GRA), analytic hierarchy process (AHP), entropy weight method (EWM) and comprehensive weight method, the relationship index Q1 between initial productivity and high pressure mercury injection parameters and the relationship index Q2 between initial productivity and pore shape parameters are obtained by fitting. Then a dual-coupled comprehensive quantitative classification prediction model for tight sandstone reservoirs was developed based on pore structure and shape parameters. A quantitative classification study was conducted on the target reservoir, analyzing the correlation between reservoir quality and pore structure and shape parameters, leading to the proposal of favourable exploration areas. The research results showed that when Q1 ≥ 0.5 and Q2 ≥ 0.5, the reservoir was classified as type I. When Q1 > 0.7 and Q2 > 0.57, it was classified as type I₁, indicating a high-yield reservoir. When 0.32 < Q1 < 0.47 and 0.44 < Q2 < 0.56, was classified as type II. When 0.1 < Q1 < 0.32 and 0.3 < Q2 < 0.44, it was classified as type III. Type I reservoirs exhibit a zigzag pattern in the northwest part of the study area. Thus, the northwest should be prioritized in actual exploration and development. Additionally, the initial productivity of tight sandstone reservoirs showed a positive correlation with the porosity, permeability, sorting coefficient, coefficient of variation, and median radius. Conversely, it demonstrated a negative correlation with the median pressure and displacement pressure. The perimeters of pores, their circularity, and the length of the major axis showed a positive correlation with the porosity, permeability, sorting coefficient, coefficient of variation, and median radius. On the other hand, they exhibited a negative correlation with the median pressure and displacement pressure. This study quantitatively constructed a new classification and evaluation system for tight sandstone reservoirs from the perspective of microscopic pore structure, achieving an overall model accuracy of 93.3%. This model effectively predicts and evaluates tight sandstone reservoirs. It provides new guidance for identifying favorable areas in the study region and other tight sandstone reservoirs.