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.