This study aims to determine the variation and controlling factors of shale gas adsorption capacity in reservoirs in the Upper Ordovician Wufeng Formation and the Lower Silurian Longmaxi Formation (also referred to as the WF-LMX formations), South China. Based on data obtained using scanning helium ion microscopy (HIM) and nitrogen (N₂) and methane (CH₄) adsorption experiments, this study analyzed the organic pore heterogeneity of shales in the WF-LMX formations in well A and its effect on shale gas adsorption. Using the Frenkel-Halsey-Hill (FHH) model, data from N₂ adsorption experiments were converted into fractal dimensions, which can reflect the complexity and heterogeneity of organic pores while also serving as a novel indicator for quantitatively assessing the pore structure complexity. The results indicate that shales in the WF-LMX formations in well A can be divided into two sections: (Ⅰ) the Wufeng Formation and the lower Longmaxi Formation (depths: ca. 2871.0–2898.6 m), and (Ⅱ) the upper Longmaxi Formation (depths: < 2871.0 m). Organic pores in Section Ⅰ typically exhibit complex internal structures, coarse surfaces, and interconnectivity, whereas those in Section Ⅱ are simple, smooth, and isolated. Moreover, the former possesses larger specific surface areas (SSAs) than the latter. A fractal analysis reveals that organic pores in the shale sequence can be classified into micropores (<2 nm), mesopores (2–10 nm), and macropores (>10 nm). The calculated fractal dimensions show greater heterogeneity of organic pores, especially macropores, in Section Ⅰ compared to Section Ⅱ. The results also reveal that organic macropores are the primary pores controlling the SSAs of organic pores in shale reservoirs in the WF-LMX formations. Organic pores in Section Ⅰ manifest a superior shale gas adsorption capacity compared to Section Ⅱ. The heterogeneity of organic pores might affect the adsorption capacity of shales in the formations. Generally, organic macropores in Section Ⅰ of the shale sequence exhibit more complex structures and larger SSAs, leading to a stronger absorption capacity of shale reservoirs in Section Ⅰ compared to Section Ⅱ.

Fault-karst reservoir is of a special type distributed in the Ordovician strata in the Tarim Basin, China. It’s characterized by deep burial, complex genesis and strong heterogeneity. Due to sparse well data and low seismic quality and other adverse conditions, its accurate characterization and fine modeling are faced with great challenges. In the study, an integration of drilling, core, outcrop and 3D seismic data is applied to build a deep learning-based training dataset for the fault-karst reservoir with the guidance of architecture mode of fault-controlled fractured-vuggy reservoir. Based on the comprehensive analysis of deep learning network, we propose a deep learning-based modeling method suitable for fault-karst reservoirs. The results show that the “in-situ, equal-scale” training dataset established based on multi-source data is the basis for deep learning-based modeling of fault-karst reservoirs. The selected pix 2 pix (P2P) neural network could realize the 3D model prediction of fault-karst reservoirs by seismic data. A 3D faultkarst reservoir model is then established for the south segment of the No. 5 fault zone in Shunbei area following the built of training network. The model is conformed to the geological mode and distribution pattern of the reservoir type on all fronts, and also highly consistent with the reservoir prediction based on drilling data. One of the key research directions therefore lies in improving the accuracy and conditional degree of deep learning-based geological modeling of fault-karst reservoirs.

Exploration and development of deep and ultra-deep carbonate reservoirs have been a hot and key research topic in the industry. Accurately depicting the spatial distribution and physical property parameters of the reservoirs has been a major challenge for an efficient oil and gas exploration and development. Based on an analysis of current development of reservoir geological analysis, logging evaluation, seismic prediction, geological modeling and other related technologies, this study is focused on figuring out the development mechanisms and distribution patterns of highquality deep carbonate reservoirs by overcoming the data issues (scarcity, low quality and inaccuracy) and the high heterogeneity nature of the reservoir. A series of key technologies for characterization and modelling of the deep carbonate reservoirs have been developed, including technologies for construction of multi-scale and multi-attribute deep carbonate reservoir knowledge base;new technologies for geological analysis such as macroscopic to microscopic geological observation, in-situ micro-area qualitative and quantitative analysis for reservoir sedimentation and diagenetic environment, experiment and numerical simulation technologies for mechanism and process of reservoir development;new logging interpretation technologies, such as reservoir type identification and quantitative parameter evaluation based on global logging simulation, and sedimentary microfacies identification based on machine learning;new seismic prediction methods, such as seismic petrophysical modeling, machine learning technologies for rock physics guided reservoir parameter prediction and uncertainty evaluation;new geological modeling technologies such as new algorithm of multipoint geostatistics, geological process simulation, and geological modeling based on artificial intelligence. The technological processes of geological modeling of carbonate reservoirs under the control of karst unconformity, fault and sedimentary facies have been established respectively and applied to oil and gas reservoirs in Tahe, Shunbei and Yuanba blocks in the Tarim Basin and the Sichuan Basin, providing scientific basis for exploration and development deployment. The future research direction of geological modeling for deep and ultra-deep carbonate reservoirs is also predicted: updating geological knowledge base to support geological modeling;expanding the modeling technology based on geological process and improving its application;developing geophysical interpretation and prediction technologies based on artificial intelligence to improve the ability to depict complex reservoirs;developing new modeling methods based on artificial intelligence to continuously improve the accuracy of reservoir characterization and the reliability of models;and establishing rapid updating technology of geological models for deep reservoirs to continuously improve the efficiency and accuracy of model updating.

Water-rock interactions in fracture systems and their significance to reservoir formation have always been a hot topic of interest for scholars around the world. Fluid may flow and transport along the fractures, dissolve surrounding rocks, precipitate new minerals, and change the morphology of storage space, all playing critical roles in the formation and distribution of carbonate reservoirs as well as hydrocarbon migration and accumulation. It is therefore of great theoretical and practical significance to identify the genetic mechanism of deep and ultra-deep fractured carbonate reservoirs. In this study, we carried out high-temperature and high-pressure dissolution simulation experiments on samples from the Ordovician Yijianfang Formation in the Shunbei area of Tarim Basin and performed numerical simulation with tools such as TOUGHREACT to identify the interaction mechanism between brine with dissolved CO₂ and carbonate rocks, to investigate the influence of temperature, pressure, fluid property and physical heterogeneity, and to calculate the Ca²⁺ diffusion properties and mineral dissolution/precipitation trends. The results show that the overall reaction is dominated by calcite dissolution with an increase in fracture width, number and volume, as well as sample permeability and porosity, indicating improvement of reservoir quality. This study clarifies that the physical heterogeneity and fluid hydraulic properties promote the main fractures as the main flow channels. The flow and reaction processes promote each other and together determine that the main fractures will not only be the dominant channels for fluid flow and the main place where water-rock reactions occur, but will also be the dominant reservoir space for oil and gas.

Weathering has always been a concerned around the world, as the first and most important step in the global cycle of elements, which leads to the fractionation of isotopes on the scale of geological age. The Middle Ordovician Majiagou Formation in Daniudi area of the Ordos Basin had experienced weathering for >130 Myr. Through thin section observation, major and trace element analysis, carbon, oxygen, and magnesium isotopes composition analysis, the dolomitization modes and weathering of ancient dolomite in Daniudi area were analyzed in detail. The results showed that the Sabkha and brine-reflux dolomitization modes had developed, and the Mg isotopes in different layers of the karst crust were fractionated by various factors. The vertical vadose zone was affected by weathering, the Mg isotope of dolomite (δ²⁶Mg_dol) showed a downward decreasing trend; the horizontal underflow zone was controlled by diagenesis and formation fluid, δ²⁶Mg_dol showed a vertical invariance and negative; the main reason for Mg isotope fractionation in the deep slow-flow zone was the brine-reflux dolomitization mode during early burial period, which showed a vertical downward increase. Finally, the Mg isotope characteristic data of the ancient weathering crust were provided and the process of Mg isotope fractionation in the karst crust was explained.

Reconstructing paleoenvironments has long been considered a vital component for understanding the development and evolution of carbonate reservoirs. The Middle Ordovician Period is considered the archetypical greenhouse interval, and also a critical period in biological evolution. The Middle Darriwilian isotope carbon excursion has been observed in many areas of the world and may be related to the biological explosions caused by decreases in the temperature. The thick carbonate rocks in the fifth member of the Middle Ordovician Majiagou Formation in the Dingbei area of the Ordos Basin were chosen as an example, based on the concentration of major, trace and rare earth elements as well as C, O and Sr isotopic analyses, the paleoenvironment was reconstructed. And its impact on natural gas exploration was analyzed. The results show that the seawater paleotemperature was 29 ℃, suboxic-anoxic paleoredox conditions were observed, and the seawater paleosalinity was high. A large number of plankton in the biological explosion caused a rapid increase in the total organic carbon in carbonate rocks, which provided natural gas as supplemental source rocks. Affected by early meteoric water, the dissolution of gypsum laid the foundation for high-quality reservoirs, and the residual gypsum also further preserved natural gas. This study provides new data for the paleoenvironment and a theoretical basis for further natural gas exploration.