Tight conglomerate reservoirs pose challenges to development due to their strong heterogeneity and anisotropy, while existing characterization technologies have limitations such as cumbersome sample preparation and low efficiency. Additionally, the microscale coupling mechanism among pores, elements, and components remains unclear. To address these issues, this study aims to reveal the controlling mechanisms of such reservoir features and establish an integrated characterization system. This system couples macrolens infrared thermal imaging, umbrella deconstruction, field emission scanning electron microscopy, and energy dispersive spectroscopy, and adopts eight-directional physical slicing to systematically characterize the pores, elements, and components of tight conglomerate reservoirs. Results indicate that pores are more developed in specific directions. Characteristic elements exhibit distinct directional enrichment and depletion: Some elements reach high contents in certain directions, while others drop to very low levels. Mineral contents show angle-dependent variations; for example, the proportion of weakly weathered feldspar increases significantly with increasing angle. All these features are synergistically controlled by the original sedimentary fabric and late-stage diagenesis. This work enriches the microscopic characterization theory of tight reservoirs, provides microscopic evidence for identifying favorable reservoir zones, and offers direct technical support for optimizing wellbore deployment and avoiding high-risk fracturing areas in engineering practice.

This study introduces the potential applications of infrared thermal imaging under a macro lens in the realm of geo-energy. Leveraging disparities in the thermal radiation of objects, this technology captures minute thermal signals from small objects through its macro lens, offering benefits such as straightforward sample preparation, rapid testing, and non-destructive imaging. In the context of static attribute characterization of reservoirs, it facilitates the acquisition of temperature data and the identification of macroscopic geological attributes like lithology via machine learning. It also enables precise characterization of microscopic solid components and fluid distribution, based on variances in thermophysical properties, and aids in determining multidisciplinary properties of rocks. In studies concerning dynamic behavior, it allows for real-time monitoring of structural changes during reservoir heating or cooling, the design of in-situ conversion heating schemes for low-maturity shale oil, tracking of fluid-rock interactions and microbial oil extraction characteristics, and provides dynamic information to optimize extraction schemes in energy development and utilization. Although there are challenges in practical applications, innovative ideas and technological progress are expected to overcome these obstacles, supporting the efficient exploration and sustainable development of geo-energy.

While petroleum scientists and engineers have increasingly acknowledged the significance of integrating geology with engineering for efficient petroleum development, the precise integration of above two aspects still requires substantial enhancement. This study identifies several potential future research hotspots in the precise integration of geology and engineering within low-permeability oil reservoirs. These include the accurate identification of sedimentary facies, which is constrained by horizontal wellbore logging, the three-dimensional continuous distribution modeling of heterogeneous start-up pressure gradients, and the determination of advantageous oil displacement paths driven by geomodels. The recommendation for future research is to employ advanced data analysis techniques to determine the correlation between experimental data at a small core scale indoors and multifunctional logging data. Additionally, fine geological modeling methods should be utilized to develop heterogeneous continuous distribution models of diverse reservoir geology and development attributes. This work offers several fresh perspectives for the efficient exploitation of China’s continental low-permeability oil reservoirs in subsequent stages.

A comprehensive understanding of the characteristics and mechanisms underlying hydrocarbon generation from organic matter has emerged as a pivotal challenge in deciphering the “life mystery” of oil and gas, thereby guiding strategic planning for the global petroleum industry. The swift advancements in materials science, drilling engineering, computer technology, big data, and artificial intelligence have furnished robust methodologies and tools for research into organic hydrocarbon generation. This perspective offers an analysis and synthesis of three distinct research paradigms pertinent to organic hydrocarbon generation: Theoretical analysis, experimental exploration, and numerical simulation. These three research modalities probe the mechanisms of organic hydrocarbon generation across varied scales, with their findings mutually reinforcing and validating each other. This synergy provides invaluable insights that contribute to a holistic understanding of organic hydrocarbon generation, facilitating a comprehensive assessment of the potential of subterranean oil and gas resources.

In this study, a new image-based method for the extraction and characterization of pore-throat network for unconventional hydrocarbon storage and exploitation is proposed. “Pore-throat solidity”, which is analogous to particle solidity, and a new method for automatic identification of pores and throats in tight sandstone oil reservoirs are introduced. Additionally, the “pore-throat combination” and “pure pore” are defined and distinguished by drawing the cumulative probability curve of the pore-throat solidity and by selecting an appropriate cutoff point. When the discrete grid set is recognized as a pore-throat combination, Legendre ellipse fitting and minimum Feret diameter are used. When the pore and throat grid sets are identified as pure pores, the pore diameter can be directly calculated. Using the new method, the analytical results for the physical parameters and pore radius agree well with most prior studies. The results comparing the maximum ball and the new model could also prove the accuracy of the latter's in micro and nano scales. The new model provides a more practical theoretical basis and a new calculation method for the rapid and accurate evaluation of the complex processes of oil migration.