Songtao Wu

The laminae of lacustrine shale in China have been systematically identified and characterized by a combination of core/slice observations, mineral compositions, geochemical analysis, pore structure characterization, and oil-bearing evaluation. The shale of the Chang 7 Member, Yanchang Formation, Ordos Basin was examined as an example in the study. Four types of laminae are developed in the Chang 7 Member, including felsic laminae (FQL), clay laminae (CLL), organic matter laminae (OML), and tuff laminae (TUL). The shale reservoirs exhibit significant heterogeneity. Of these, FQL and TUL have superior reservoir characteristics. The pore diameter of TUL is primarily composed of micrometer-sized secondary pores that are generated during the diagenesis process, while mesopore and macropore development are dominant in FQL. The main source laminae in the Chang 7 Member of the Ordos Basin are the OML and CLL, while the main reservoir laminae are the FQL and TUL. Some of the hydrocarbons produced by hydrocarbon generation are stored in the pore space inside the laminae, while the majority migrate to the inorganic pores of the adjacent FQL and TUL. It confirms that OML and CLL afford abundant shale oil, the combination of organic pores and inorganic pores in FQL and TUL serve as reservoir space, and the “clay generation-siliceous reservoir” shale oil enrichment model is established in the Chang 7 Member of Ordos Basin.

Introduction: Clay minerals are critical components of lacustrine shale systems, where their associated pores govern reservoir properties. The diagenetic transformation of these minerals, particularly illitization, profoundly impacts reservoir quality, yet the mechanisms driving illitization and its influence on pore evolution remain poorly understood. This study investigates the illitization processes and pore characteristics in the Cretaceous Qingshankou Shale (QSK shale) to elucidate their implications for unconventional hydrocarbon storage.Methods: Core samples from the QSK shale in the Gulong Sag, Songliao Basin, were analyzed using a multi-method approach: field-emission scanning electron microscopy (FE-SEM) for pore morphology, QEMSCAN® for mineralogical mapping, X-ray diffraction (XRD) for clay mineral quantification, and nitrogen adsorption for pore-size distribution analysis.Results: Key findings include: (i) Clay minerals in the QSK shale are dominated by illite and illite/smectite mixed layers (average >40% content), with intense illitization yielding >60% illite in clay fractions. (ii) Pores within clay minerals (micropores and mesopores 800nm in chlorite) constitute primary storage spaces, interconnected by microcracks. (iii) Illitization occurs via two pathways: transformation of illite/smectite mixed layers and albite alteration, with the former dominating. Porosity initially increases with illite content (up to ∼30%) but declines progressively beyond this threshold.Discussion: The threshold effect of illitization on porosity highlights a critical balance between pore generation (via mineral dissolution) and occlusion (from authigenic illite precipitation). These findings provide a mechanistic framework for predicting reservoir quality in lacustrine shale systems, emphasizing the dual role of illitization in enhancing or degrading storage capacity depending on diagenetic maturity.

Continental shale oil is diversified, differentiated, and complex. It has disadvantages such as low production and inferior development benefits. Given this, the movability and productivity of shale oil were proposed in this research to evaluate the producible capacity and development potential of shale oil. Taking the Yingxiongling shale oil reservoir as an example, the microscopic movability and macroscopic productivity of the main lithofacies were systematically investigated via the NMR tests, imbibition experiments, uniaxial compression tests, and CT imaging. The characteristics of different lithofacies were clarified, and the favorable targets were identified. The results showed that the layered limy dolomite of the shale oil reservoir has the highest microscopic movability, followed by that of the laminated limy dolomite and the least of the laminated clayed shale. The laminated limy dolomite has better fluid flow properties, higher capacity to form fracture networks, and the best macroscopic productivity. The layered limy dolomite has medium macroscopic productivity, and that of the clayed shale is the least. Based on the field testing and experimental understanding of layered limy-dolomitic shale as high-quality targets, the laminated limy-dolomitic shale is further identified as a favorable target. It features a stronger capacity to form fracture networks, better imbibition performance, medium microscopic movability, and relatively high macroscopic productivity. This research further clarifies the correlation between microscopic movability and macroscopic productivity and provides theoretical support for exploring and developing the continental shale oil reservoir.

Carbon neutrality has become a global common goal. CCUS, as one of the technologies to achieve carbon neutrality, has received widespread attention from academia and industry. After CO₂ enters the formation, under the conditions of formation temperature and pressure, supercritical CO₂, formation water, and rock components interact, which directly affects the oil and gas recovery and carbon sequestration efficiency. In this paper, the recent progress on CO₂ water–rock interaction was reviewed from three aspects, including (i) the investigation methods of CO₂ water–rock interaction; (ii) the variable changes of key minerals, pore structure, and physical properties; and (iii) the nomination of suitable reservoirs for CO₂ geological sequestration. The review obtains the following three understandings: (1) Physical simulation and cross-time scale numerical simulation based on formation temperature and pressure conditions are important research methods for CO₂ water–rock interaction. High-precision mineral-pore in situ comparison and physical property evolution evaluation are important development directions. (2) Sensitive minerals in CO₂ water–rock interaction mainly include dolomite, calcite, anhydrite, feldspar, kaolinite, and chlorite. Due to the differences in simulated formation conditions or geological backgrounds, these minerals generally show the pattern of dissolution or precipitation or dissolution before precipitation. This differential evolution leads to complex changes in pore structure and physical properties. (3) To select the suitable reservoir for sequestration, it is necessary to confirm the sequestration potential of the reservoir and the later sequestration capacity, and then select the appropriate layer and well location to start CO₂ injection. At the same time, these processes can be optimized by CO₂ water–rock interaction research. This review aims to provide scientific guidance and technical support for shale oil recovery and carbon sequestration by introducing the mechanism of CO₂ water–rock interaction, expounding the changes of key minerals, pore structure, and physical properties, and summarizing the sequestration scheme.

The heterogeneity, sedimentary characteristics, and distribution of fine-grained sediments of millimeter-scale laminae were studied in alkaline lacustrine strata in the lower Permian Fengcheng Formation (P₁f₂) in the Mahu Sag to provide a sound theoretical basis for shale oil exploration and development. They were investigated by using core and thin-section observation, geochemical and elemental analysis, mineral identification, and pore examination. Five types of laminae were distinguished, with different mineral compositions, pore characteristics, and distributions. These laminae occur in four distinct combinations. The pore systems predominantly consist of intercrystalline pores, intragranular pores, and dissolution pores of feldspar and dolomite and also contain imporous alkaline mineral particles. Influenced by variations in salinity, the influx of volcanic–hydrothermal material, and the participation of both endogenous and exogenous materials, the formation has gone through five stages of sedimentary evolution. Furthermore, felsic laminae (FQL), dolomite laminae (DOL)/reedmergnerite laminae (RL)/shortite laminae (SL), and chert laminae (CL) developed in single-terrestrial-source still water deposition, hybrid-source still water deposition, and single-intrasource deposition, respectively. Vertically, the FQL-DOL combination shows favorable reservoir characteristics and is the most extensively developed lamina combination in the Fengcheng Formation that primarily developed in the period of the late Feng 1 Member (P₁f₁), the early Feng 2 Member (P₁f₂), the late Feng 2 Member (P₁f₂), and the early Feng 3 Member (P₁f₃). The FQL-RL/SL combination primarily developed in the period of the middle P₁f₂, and the DOL-CL combination is the counterpart in the period of the early P₁f₂ and the late P₁f₂ stages. Considering this in conjunction with the longitudinal distribution of lamina combinations, a model is proposed for the distribution of fine-grained sediments in alkaline lacustrine strata.

Lacustrine sedimentary processes exhibit high sensitivity to paleoenvironmental changes, often manifesting as high-frequency sedimentary cycles that control the complex variations in sedimentary structure, mineral composition, and element distribution. However, the intricate co-variation mechanism among paleoclimate and paleowater properties at a high precision level (centimeter to meter scale) is still controversial. This study focuses on conducting a high-frequency cycle analysis of lacustrine mixed rocks from the Eocene Lower Ganchaigou Formation (LGCG) in the Qaidam Basin, employing petrology, mineralogy, organic geochemistry, and elemental geochemistry techniques. The lithological variation was characterized by the superposition of three lithofacies types from the bottom to the top with a single sequence: massive sandstone, laminated silty shale, and bedded calcareous dolostone. Geochemical data revealed cyclical variations in the paleoenvironment in the vertical profile, which conformed to the high-frequency lithofacies cycles. Based on the reconstruction of the lake level and paleowater properties, a synthesized paleoclimate–sedimentary model that comprised three consecutive periods within an individual sequence was established. From the bottom to the top of each cycle, the Eocene paleoenvironment varied from reduction and desalination to oxidation and salinization, which was controlled by a decline in the lake level resulting from a transformation of the paleoclimate from warm and humid to cold and arid. The variations in petrology and geochemistry observed in the Eocene Qaidam Basin play a crucial role in comprehending the sedimentary response to paleoenvironmental changes at high precision levels within lacustrine settings.

In order to improve the stress concentration in concrete at steel nodes caused by zero thickness springs, the improved Spring2 nonlinear spring model from ABAQUS is used to simulate the bond-slip behavior between non-uniformly corroded reinforcement and concrete. Based on the collected test results with different stirrup spacing, fitting the influence coefficients of bond stress under stirrup corrosion. With the combination of a non-uniformly corroded rebar distribution model, the refined numerical simulation of the drawing process of reinforced concrete specimens was carried out using ABAQUS. The study shows that the improved nonlinear spring model is better than the zero thickness spring model in terms of computational accuracy and efficiency. The stirrup correction coefficient is approximately linear with the stirrup spacing; the bond-slip relationship considering the effect of stirrup spacing, has a better consistency with the relevant tests in the simulation of the pullout test. Weibull distribution for the fitting of non-uniform corrosion of reinforcement is more reasonable than Gumbel distribution.

Basic properties and exploitation strategies of source rock strata

Efficient and accurate evaluation of capillary pressure and relative permeability of oil–water flow in tight sandstone with limited routinely obtainable parameters is a crucial problem in tight oil reservoir modeling and petroleum engineering. Due to the multiscale pore structure, there is complex nonlinear multiphase flow in tight sandstone. Additionally, wetting behavior caused by mineral components remarkably influences oil–water displacement in multiscale pores. All this makes predicting capillary pressure and relative permeability in tight sandstone extremely difficult. This paper proposes a physics-informed neural network, integrating five important physical models, the improved parallel genetic algorithm (PGA), and the neural network to simulate the two-phase capillary pressure and relative permeability of tight sandstone. To describe the nonlinear multiphase flow and the wettability behavior, five physical models, including the non-Darcy liquid flow rate formula, apparent permeability (AP) formula, and contact angle-capillary pressure relationship, are coupled into the neural network to improve the prediction accuracy. In addition, the input parameters and the structure of the physics-informed neural network are simplified based on analyzing the change rule of the oil–water flow with the main controlling factors, which can also save training time and improve the accuracy of the neural network. To obtain the data for training the coupled neural network, the dataset of tight sandstone in Ordos Basin is constructed with experimentally measured data and various fluid flow properties as constraints. The test results demonstrate that the estimated capillary pressure and relative permeability from the physics-informed neural network are in good agreement with the test ones. Finally, we have compared the physics-informed neural network with the quasi-static pore network model (QSPNM), dynamic pore network model (DPNM), and conventional artificial neural network (ANN). The calculation time of QSPNM and DPNM are hundreds of times longer than that of the physics-informed neural network. The coupled neural network has also performed much better than the conventional ANN. As the heterogeneity of pore spaces in tight sandstone increases, the advantages of the physics-informed neural network over ANN are more prominent. The prediction models generated in this study can estimate the capillary pressure and relative permeability based on only four routine parameters in a few seconds. Therefore, the physics-informed neural network in this paper can provide the potential parameters for large-scale reservoir simulation.