Relative permeability, as a key parameter characterizing multiphase fluid flow behavior in porous media, holds significant importance across various fields, such as reservoir evaluation and engineering geology. However, measuring relative permeability is time-consuming and costly. Considering the analogy between fluid flow and electrical current conduction provides a novel approach for studying multiphase flow characteristics using resistivity data. An integrated oil–water relative permeability and resistivity co-measurement experiment was specifically designed for a complex argillaceous sandstone reservoir in a block, referred to as Block A. Research has shown that as the resistance coefficient increases, the water and oil relative permeability decrease and increase, respectively. As the porosity–permeability comprehensive index increases and the shale content decreases, corresponding to the same resistance coefficient, the water and oil relative permeability show increasing and decreasing trends, respectively. The integration of tortuous capillary tube theory and three-water model concepts, combined with the flow-current similarity principle, has enabled the development of a novel relative permeability–resistivity correlation model that is applicable to complex argillaceous sandstone formations. The application of actual data from the study area shows that the relative errors of the water- and oil-phase relative permeability calculated by the proposed model are both small, at 16% and 8.6%, respectively. The model is validated to better characterize multiphase fluid flow in rocks, offering a new approach for accurately calculating relative permeability based on formation resistivity data.

Long-lasting, high-strength plugging materials are required for deep profile control in low-permeability fractured reservoirs. In this study, a series of hyperbranched copolymer hydrogels was prepared through an aza-Michael addition-amidation-one-pot end-group coupling strategy. Linear alkylamines were used as cores to synthesize amino-terminated generation 1.0 G broom-shaped hyperbranched macromolecular backbones via a divergent route. The resulting backbones were subsequently crosslinked with linear α,ω-diepoxy-terminated poly(ethylene glycol), affording three structurally well-defined hydrogels, denoted as C2HG, C6HG, and C8HG. Structural and physicochemical characterization showed that all hydrogels possessed interconnected three-dimensional porous networks, good thermal stability, and a lower critical solution temperature of approximately 37 °C. Rheological analysis demonstrated predominantly elastic behavior, with the storage modulus (G′) consistently exceeding the loss modulus (G″), together with pronounced shear-thinning characteristics favorable for injection into deep, low-permeability formations. By varying the alkyl-chain length of the hyperbranched backbone, the balance between environmental tolerance and plugging performance could be effectively regulated. These findings establish a structure–property relationship between backbone hydrophobicity and hydrogel performance and demonstrate that PEG-crosslinked hyperbranched copolymer hydrogels are promising candidates for deep-profile control and water shutoff in high-salinity, low-permeability fractured reservoirs.

In high-temperature and high-salinity reservoirs, HPAM is prone to thermal degradation, salt-induced chain shrinkage and shear instability, which weakens its mobility-control ability. In view of the above problems, this paper prepared bifunctional modified nano-SiO₂ (KH570@SiO₂-AMPS/ODMA, DF-SiO₂), and constructed a composite gel system with HPAM. Its performance was evaluated by structural and rheological characterization, aging and shear recovery, and heterogeneous core displacement. At 90 °C and about 20,000 mg/L salinity, the viscosity retention rate exceeded 70% after 90 days of aging, and recovered to 94.6% of the initial value after 72 h of standing following shearing. Core displacement shows that the system can improve the flow distribution of heterogeneous reservoirs, and the recovery of high and low permeability layers is 6.95 and 4.41 percentage points higher than that of HPAM, respectively. DF-SiO₂ constructs a dynamic network through interfacial interaction and hydrophobic association to improve the stability and structural recovery ability of the system, which provides a new idea for the application of high-temperature and high-salinity heterogeneous reservoirs.

Oil–water relative permeability is a critical parameter for reservoir fluid property evaluation and productivity prediction, playing a vital role in reservoir identification and development. However, the correlation between relative permeability and resistivity remains unclear for complex conductive mineral-bearing argillaceous sandstone reservoirs. In this study, twenty-eight artificial core samples were prepared and compacted under simulated reservoir temperature and pressure conditions. Simultaneous oil–water relative permeability and resistivity measurements were performed on these samples at two brine salinities (7000 ppm and 3000 ppm). The analysis reveals that under the same resistivity index, both conductive-mineral content and shale content exhibit a negative correlation with water-phase relative permeability but a positive correlation with oil-phase relative permeability. In contrast, porosity–permeability conditions and injected-water salinity show a positive correlation with water-phase relative permeability and a negative correlation with oil-phase relative permeability. Furthermore, the effect of salinity on the relative permeability–resistivity relationship intensifies as porosity–permeability conditions improve. Based on the consistency between movable water seepage and conductive paths, a novel relative permeability–resistivity model was developed for the target reservoirs by integrating seepage and conductive theories, with a generalized Archie’s equation adopted to calibrate the effects of conductive minerals and shale on rock conductivity. The model parameters are optimized using the Newton–Raphson iteration algorithm, and empirical correlations between the undetermined coefficients and reservoir parameters are developed. Validated against two independent cores with the most complex mineral compositions (SH2-3 and SH3-3), the model yields average relative errors of 9.8% and 13.4% for water-phase relative permeability, and 4.4% and 5.4% for oil-phase relative permeability, respectively, demonstrating its high calculation accuracy. It enables efficient prediction of reservoir relative permeability using resistivity data, providing a new theoretical and technical support for low-resistivity oil reservoir identification and productivity assessment.