SUMMARY Permeability is a critical parameter for reservoir characterization and hydrocarbon development, yet its accurate prediction remains a challenge. Pore structure, as the intrinsic factor governing both the elastic and hydraulic transport properties of rocks, serves as a bridge between these properties and facilitates permeability prediction from well logs and seismic data. To accurately describe the variation in the physical properties of tight sandstone reservoirs with pressure, our study aims to construct a physical model that relates rock elastic properties with permeability. We developed a dual-porosity rock physics model by coupling David & Zimmerman’s pore-structure inversion method with Dienes’s percolation theory. Our model divides the pore space into pressure-insensitive stiff pores and pressure-sensitive compliant microcracks. By inverting the microcrack density and aspect ratio distribution—which evolve with pressure—from elastic wave velocities, we quantitatively predict permeability variations using Dienes statistical percolation model. To validate this model, we measured porosity, permeability and P- and S-wave velocities on four tight sandstone samples under effective pressures of 5–50 MPa. The results show that the proposed model accurately captures the evolution of both elastic parameters and permeability with effective pressure, demonstrating strong predictive capability for the experimental data. The significance of this study lies in achieving a quantitative relation between elastic and transport properties by explicitly characterizing the pore structure and integrating percolation theory, which is then calibrated with real experiment data, thereby providing solid physical basis for better prediction of reservoir permeability using acoustic logs and seismic data.

Abstract In the infrared imaging scene where the target is at a long distance and the background is cluttered, due to the interference of noise and background texture information, the infrared image is prone to problems such as low contrast between the target and the background, and feature confusion, which makes it difficult to accurately extract and detect the target. To solve this problem, firstly, the infrared image is enhanced by combining DDE and MSR algorithm to improve the contrast and detail visibility of the image. For the RT-DETR network structure, the EMA attention mechanism is introduced into the backbone to enhance the feature extraction ability of the model by extracting context information. The CAMixing convolutional attention module is introduced into CCFM, and the multi-scale convolutional self-attention mechanism is introduced to focus on local information and enhance the detection ability of small targets. The filtering rules of the prediction box are improved, combined with Shape-IoU, and the convergence speed of the loss function in the detection and the detection accuracy of small targets are improved by paying attention to the influence of the intrinsic properties of the bounding box itself on the regression. In the experiment, the infrared weak target image dataset of the National University of Defense Technology was selected, labeled and trained. Experimental results show that compared with the original DETR algorithm, the average precision of the improved algorithm (mAP) is increased by 3.2%, and it can effectively detect infrared weak and small targets in different complex backgrounds, which reflects good robustness and adaptability, and can be effectively applied to infrared weak and small target detection in complex backgrounds.

The targeted reservoir, which is referred as the first member of Cretaceous Qingshankou Formation in Gulong Sag, Songliao Basin, NE China, is characterized by the enrichment of clay and lamellation fractures. Aiming at the technical challenge of determining oil saturation of such reservoir, nano-pores were accurately described and located through focused ion beam scanning electron microscopy and quantitative evaluation of minerals by scanning electron microscopy based on Simandoux model, to construct a 4D digital core frame. Electrical parameters of the shale reservoir were determined by finite element simulation, and the oil saturation calculation method suitable for shale was proposed. Comparison between the results from this method with that from real core test and 2D nuclear magnetic log shows that the absolute errors meet the requirements of the current reserve specification in China for clay-rich shale reservoir. Comparison analysis of multiple wells shows that the oil saturation values calculated by this method of several points vertically in single wells and multiple wells on the plane are in agreement with the test results of core samples and the regional deposition pattern, proving the accuracy and applicability of the method model.

A scaling-down experiment system of array laterolog resistivity was developed, and a corresponding formation model was built by 3 D finite element numerical method to study the effect of different factors on the logging response quantitatively. The error between the experimental and numerical results was less than 5%, validating the reliability of the numerical simulation method. The single factor analysis of the formation relative dip, resistivity anisotropy and drilling fluid invasion was carried out by numerical simulation method, and the results show that:（1） The increase of relative dip can lead to the increase of formation resistivity, but the increasing value is relatively small, and the values of five array resistivity curves will reverse when the relative dip angle reaches a certain degree.（2） The increase of anisotropy coefficient λ can also cause the formation resistivity to rise, and the resistivity will increase by about 10% when λ increases from 1.0 to 1.5 in vertical wells.（3） Drilling fluid invasion has a more significant effect on the logging response than the former two factors. The order of the five curves will change due to drilling fluid invasion in anisotropic formation and the change rule is contrary to resistivity anisotropy. Taking the logging data of the Yingxi oilfield in the Qaidam Basin as an example, an anisotropic formation model considering drilling fluid invasion was built, and the numerical simulation results from the above methods were basically consistent with the logging data, which verified the accuracy of the method again. The results of this study lay a theoretical foundation for multiple-parameter inversion in anisotropic formation under complex well conditions.

Experiments of electrical responses of waterflooded layers were carried out on porous, fractured, porous-fractured and composite cores taken from carbonate reservoirs in the Zananor Oilfield, Kazakhstan to find out the effects of injected water salinity on electrical responses of carbonate reservoirs. On the basis of the experimental results and the mathematical model of calculating oil-water relative permeability of porous reservoirs by resistivity and the relative permeability model of two-phase flow in fractured reservoirs, the classification standards of water-flooded layers suitable for carbonate reservoirs with complex pore structure were established. The results show that the salinity of injected water is the main factor affecting the resistivity of carbonate reservoir. When low salinity water (fresh water) is injected, the relationship curve between resistivity and water saturation is U-shaped. When high salinity water (salt water) is injected, the curve is L-shaped. The classification criteria of water-flooded layers for carbonate reservoirs are as follows: (1) In porous reservoirs, the water cut (fw) is less than or equal to 5% in oil layers, 5%–20% in weak water-flooded layers, 20%–50% in moderately water-flooded layers, and greater than 50% in strong water-flooded layers. (2) For fractured, porous-fractured and composite reservoirs, the oil layers, weakly water-flooded layers, moderately water-flooded layers, and severely water-flooded layers have a water content of less than or equal to 5%, 5% and 10%, 10% to 50%, and larger than 50% respectively.

To fundamentally study the effect of wettability on sandstone conductivity, a series of experiments, including rock-electricity, nuclear magnetic resonance (NMR) and wettability tests, were conducted systematically on high- and low-permeability sandstone samples. The results show that wettability had different influence on the conductivity laws of high- and low-permeability sandstones, which was mainly caused by the complex combination of pore and pore-throat. The conductivity laws of oil-wet high-permeability sandstones, which mainly developed large pores and coarse throats with small water-wet bound space, were mainly followed the oil-wet conduction law. However, the preferentially oil-wet low-permeability sandstones primarily developed middleto-small pores and micro throats with large water-wet bound space. Hence, the large amount of bound space followed the water-wet conduction law, while the relatively large pore with oil-wet property was dominated by oil-wet conduction law. Consequently, the conductivity of oil-wet sandstones with low-permeability was cocontrolled by the wettability and pore structure. The study can result in a quite different saturation under the same resistivity compared with the Archie's law, and provide a meaningful guidance for establishing oil-saturation calculation model, which can improve the oil-layer identification accuracy and eventually enhance the oil-wet reservoir recovery.

Understanding the electrical characteristics of carbonate formation and accurately determining the electrical parameters (cementation exponent m and saturation exponent n in Archie equation) are very important for carbonate formations evaluation. However, the study of electrical characteristics faces great challenge because of the variable pore types, the complicated pore structure and the big heterogeneity in carbonates. We selected representative carbonate cores to carry out experiment research based on newly developed technologies in digital core analysis and resistivity test. Three types of cores were selected: the void space is mainly intergranular and intercrystalline; the vugs are developed; the fractures are developed. Firstly, the porosity and permeability of the selected cores have been tested. Then micro-CT with high resolution is used to scan the cores and NMR T2 spectrums of the cores both in water-saturated state and in bound water state are obtained. Finally, the resistivity of the cores in different water saturation is tested by using gas displacement technology. The analysis results of the experimental data show that the intergranular and intercrystalline pore and the fracture both have great influence on R0 while the influence of secondary vug on R0 is slight. Cementation exponent m and saturation exponent n have great difference between different cores and there is no obvious relation between m, n and reservoir parameters (φ or K). However, if we classify the cores based on the pore type, and the values of both m and n have good relationship with bound water saturation.