Geothermal energy has been recognized as an important clean renewable energy. Accurate assessment of geothermal resources is an essential foundation for their development and utilization. The North Jiangsu Basin (NJB), located in the Lower Yangtze Craton, is shaped like a wedge block of an ancient plate boundary and large-scale carbonate thermal reservoirs are developed in the deep NJB. Moreover, the NJB exhibits a high heat flow background because of its extensive extension since the Late Mesozoic. In this study, we used the Monte Carlo method to evaluate the geothermal resources of the main reservoir shallower than 10 km in the NJB. Compared with the volumetric method, the Monte Carlo method takes into account the variation mode and uncertainties of the input parameters. The simulation results show that the geothermal resources of the sandstone thermal reservoir in the shallow NJB are very rich, with capacities of (6.6–12) × 10²⁰ J (mean 8.6 × 10²⁰ J), (5.1–16) × 10²⁰ J (mean 9.1 × 10²⁰ J), and (3.2–11) × 10²⁰ J (mean 6.6 × 10²⁰ J) for the Yancheng, Sanduo and Dai’nan sandstone reservoir, respectively. In addition, the capacity of the geothermal resource of the carbonate thermal reservoir in the deep NJB is far greater than the former, reaching (9.9–15) × 10²¹ J (mean 12 × 10²¹ J). The results indicate capacities of a range value of (1.2–1.7) × 10²¹ J (mean 1.4 × 10²² J) for the whole NJB (<10 km).

The Pearl River is one of the largest rivers entering the South China Sea, yet its initiation time remains debated, a topic we address using Pb isotopes in detrital K‐feldspar. Based on these Pb data, Eocene and Early Oligocene sandstones from the northern South China Sea are interpreted to have been supplied with sediment by proximal rivers draining the Cathaysia Block. In contrast, the Late Oligocene and Miocene sandstones are mainly derived from the western Pearl tributaries (e.g., Hongshui River), suggesting that the Pearl River had formed by the Late Oligocene. Detrital zircon data from the Beibuwan Basin previously suggested that the western tributaries flowed into this basin before being captured by the paleo‐Pearl River. These lines of evidence suggest that progressive headward erosion of the eastern Pearl River and late Oligocene integration of this large fluvial system can be linked to contemporaneous sea‐floor spreading of the South China Sea.

The study of thermal conductivity anisotropy is of great importance for more accurate heat flow calculations, geodynamic studies, development and utilization of hot dry rock, and simulation of heat transfer in geological reservoirs of nuclear waste, and so on. To study the thermal conductivity anisotropy of rocks, 1158 cores from 60 boreholes in East China were tested for thermal conductivity, including thermal conductivity values parallel to (λ_∥) and perpendicular to (λ_⊥) structural planes of basalt, mudstones, gneisses, sandstones, carbonates, evaporites, and metamorphic rocks. The thermal conductivity anisotropy is not obvious for sand, clay, and evaporate, and the average anisotropic factors of 1.19 ± 0.22, 1.18 ± 0.17, and 1.18 ± 0.17 for tuff/breccia, granitoid and contact metamorphic rocks, respectively, indicate that these three rocks have strong anisotropy characteristics. Finally, the effect of thermal conductivity anisotropy on heat flow is studied and discussed in detail, showing that the results of thermal conductivity tests have a significant effect on the calculation of heat flow and thermal structure, and the data show that a deviation of about 10% in thermal conductivity causes a deviation of about 11% in heat flow, which may lead to a misperception of deep thermal structure studies. The regular and anisotropic characteristics of thermal conductivity of various rocks in Eastern China obtained in this paper can provide parameter support for projects such as heat flow calculations, thermal structure studies, and geothermal resource development and utilization.

The thermal conductivity of a stratum is a key factor to study the deep temperature distribution and the thermal structure of the basin. A huge expense of core sampling from boreholes, especially in offshore areas, makes it expensive to directly test stratum samples. Therefore, the use of well logging (the gamma-ray, the neutron porosity, and the temperature) to estimate the thermal conductivity of the samples obtained from boreholes could be a good alternative. In this study, we measured the thermal conductivity of 72 samples obtained from an offshore area as references. When the stratum is considered to be a shale–sand–fluid model, the thermal conductivity can be calculated based on the mixing models (the geometric mean and the square root mean). The contents of the shale and the sand were derived from the natural gamma-ray logs, and the content of the fluid (porosity) was derived from the neutron porosity logs. The temperature corrections of the thermal conductivity were performed for the solid component and the fluid component separately. By comparing with the measured data, the thermal conductivity predicted based on the square root model showed good consistency. This technique is low-cost and has great potential to be used as an application method to obtain the thermal conductivity for geothermal research.