Biogas resources in the Sanhu area of the Qaidam Basin have great potential, but there are few studies on biogas from shale, especially on the accumulation conditions of shale biogas. The study of biogas accumulation conditions of quaternary shale in the Sanhu area is of great significance to the theory of biogas accumulation and the guidance of exploration and development. This paper takes Quaternary shale in the Sanhu area as the research object. It is analyzed from multiple perspectives of shale hydrocarbon generation conditions, reservoir conditions, as well as hydrodynamic and structural conditions. Through the experiments of soluble organic carbon analysis and porosity and permeability analysis, the accumulation conditions of shale biogas reservoirs are clarified. The results show that the quaternary shale has a high soluble organic carbon content and high salinity formation water, which is conducive to late methane biochemical generation. Quaternary shale has the characteristics of high porosity and low permeability, mainly developing intergranular pores and intragranular pores. The large pore volume and specific surface area provide a lot of storage space for free gas and adsorbed gas, and the reservoir conditions are good. Under the structural characteristics of high in the south and low in the north and the action of formation hydrodynamics, biogas migrated from the south and deep to the north of the basin. The north slope is the main biogas-rich zone. On the whole, the quaternary shale in the Sanhu area has the characteristics of continuous hydrocarbon generation and dynamic accumulation, which has huge resource potential and exploration and development value.

The shale reservoirs of the Lower Cambrian Qiongzhusi Formation are widely distributed in the Sichuan Basin and have abundant gas resources. However, the shale lithofacies of the Qiongzhusi Formation are complex due to frequent sea level changes. The reservoir pore structure characteristics and gas content of different shale lithofacies vary significantly, which makes identifying the ‘sweet spot’ a challenging task. In this study, core observation and X-ray diffraction (XRD) were used to analyze the lithofacies types and characteristics of the study area. The pore types of different shale lithofacies were observed using field emission-scanning electron microscopy. Pore structures were studied using low-temperature gas (including N₂ and CO₂) physisorption, and the pore volume (PV), specific surface area (SSA) and pore structure were systematically characterized. The primary factors influencing pore formation in different types of shale lithofacies were analyzed by combining geochemical experiments and mineral contents. The results indicate that the lithofacies of the Qiongzhusi Formation shale in the study area can be classified into five categories according to mineral compositions: Siliceous argillaceous shale (CM-1), Argillaceous siliceous mixed shale (M-2), Argillaceous siliceous shale (S-3), Siliceous rock (S) and Calcareous siliceous shale (S-2). Pores are abundant in S-3 shale, M-2 shale and CM-1 shale. The S-3 shale is more enriched in organic pores and clay mineral pores compared to other lithofacies shales, and the pore morphology is mainly wedge-shaped and plate-like. M-2 shale and CM-1 shale are rich in clay minerals and mainly develop clay mineral pores and are mainly wedge-shaped and plate-like. The S shale and S-2 shale mainly develop interparticle pores and clay mineral pores, which are mainly slit-like. The results show that TOC, pyrite content, quartz and feldspar mineral content, clay mineral type and content affect the pore structure in the study area. Quartz and feldspar content have a negative effect on micropore and mesopore volumes. TOCs have a weak positive correlation with micropore volume and micropore SSA. Clay mineral content has significant positive effects on the PV and SSA of micropores and mesopores, indicating that clay mineral content is the main factor affecting the pore structure of shale.

Tight oil is an important unconventional hydrocarbon resource. The differences in occurrence characteristics between light components (LCs) and heavy components (HCs) of tight oil profoundly affect its mobility and recovery. Current research has focused mainly on the rapid evaluation of the relative contents of LCs, whereas few studies have systematically analyzed the occurrence characteristics of LCs and HCs and their controlling factors. In this study, the differential occurrence characteristics between LCs and HCs are clarified on the basis of data from thin-section petrography, X-ray diffraction, nuclear magnetic resonance, confocal laser scanning microscopy, and reservoir pyrolysis analysis. An innovative quantitative characterization methodology for the relative occurrence volumes of LCs and HCs is proposed. On the basis of this method, the controlling factors that cause the different occurrence characteristics of LCs and HCs are elucidated. Furthermore, the occurrence characteristics of LCs and HCs in various source–reservoir combinations, physical properties, and development intensities of argillaceous laminae are summarized. Finally, an occurrence model of the crude oil components in the Chang 7 tight reservoir is established. The results show that LCs and HCs in the Chang 7 tight reservoir exhibit differences in occurrence volume, state, morphology, and pore size. These differences are primarily controlled by the hydrocarbon generation intensity of the source rock, the source-to-reservoir distance (SRD), and the content of oil-wet minerals in the reservoir. The source sandwich combination exhibits high physical properties, low hydrocarbon generation intensity, high SRD, and low oil-wet mineral content, resulting in relatively high LCs. The source–reservoir interbed and reservoir sandwich combinations feature a high content of argillaceous laminae, high hydrocarbon generation intensity, low SRD, and high oil-wet mineral content, resulting in relatively low LCs. There are three occurrence models of crude oil components in the Chang 7 tight reservoir: the charging force controlling model, the adsorption effect controlling model, and the argillaceous laminae controlling model. The results of this study provide significant guidance for predicting the fluidity of tight oil, accurately assessing the amount of recoverable tight oil resources, and achieving efficient extraction of tight oil.

Assessing and forecasting hydrocarbon resource potential (HRP) is of great significance. However, due to the complexity and uncertainty of geological conditions during hydrocarbon accumulation, it is challenging to accurately establish HRP models. This study employs machine learning methods to construct a HRP assessment model. First, nine primary controlling factors were selected from the five key conditions for HRP: source rock, reservoir, trap, migration, and accumulation. Subsequently, three prediction models were developed based on the backpropagation (BP) neural network, BP-Bagging algorithm, and BP-AdaBoost algorithm, with hydrocarbon resources abundance as the output metric. These models were applied to the Dongpu Depression in the Bohai Bay Basin for performance evaluation and optimization. Finally, this study examined the importance of various variables in predicting HRP and analyzed model uncertainty. The results indicate that the BP-AdaBoost model outperforms the others. On the test dataset, the BP-AdaBoost model achieved an R² value of 0.77, compared to 0.73 for the BP-Bagging model and only 0.64 for the standard BP model. Variable importance analysis revealed that trap area, sandstone thickness, sedimentary facies type, and distance to faults significantly contribute to HRP. Furthermore, model accuracy is influenced by multiple factors, including the selection and quantification of geological parameters, dataset size and distribution characteristics, and the choice of machine learning algorithm models. In summary, machine learning provides a reliable method for assessing HRP, offering new insights for identifying high-quality exploration blocks and optimizing development strategies.

In tight reservoirs deposited in diverse sedimentary settings, the pore structure governs tight oil enrichment features and sweet-spot distribution. Taking the tight sandstone reservoirs of the lower third member of the Shahejie Formation in the Linnan Subsag of Bohai Bay Basin in China as an example, this study employs XRD to delineate petrological characteristics, while porosity and permeability measurements are used to quantify physical properties. In addition, thin section, SEM, HPMI, NMR, fractal theory, and cathodoluminescence experiments are applied to investigate pore structure characteristics and influencing factors. The results reveal two sedimentary systems: turbidity current and delta front deposits. Turbidite reservoirs exhibit the coarse pore-coarse throats (Type A), medium pore-medium throats (Type B), and fine pore-medium throats (Type C) pore structures. Delta front reservoirs are characterized by medium-pore-coarse-throat (Type D), medium-pore-fine-throat (Type E), and fine-pore-fine-throat (Type F) pore structures. Turbidite reservoirs show more favorable pore structures for oil exploration compared to delta fronts, in which lithofacies and diagenetic facies are the key influences. A genetic model identifies the highest-quality Type A forms in fine sandstone lithofacies under medium compaction–medium cementation–strong dissolution, with pore diameters averaging 10.84 μm in turbidite reservoirs. Conversely, the poorest Type F forms in argillaceous layered siltstone lithofacies under strong compaction, cementation, and weak dissolution diagenetic facies in delta fronts, with pore diameters averaging 0.88 μm. Consequently, the control effect of the pore quality means that Type A has the highest and Type F has the lowest oil-bearing capacity. These findings provide valuable guidance for the classification, evaluation, and exploration of tight oil sweet spots.

Despite the promising exploration potential of the tight bioclastic limestone in the Carboniferous Shiqiantan Formation (Shiqiantan Sag, Junggar Basin), its reservoir characteristics remain poorly constrained. In particular, the macro and microscopic features and the key factors controlling reservoir development are still not well understood. We combined core observation, cast thin-section analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD), high-pressure mercury intrusion, nitrogen adsorption, and nuclear magnetic resonance (NMR) to systematically characterize the Carboniferous bioclastic limestone reservoirs and identify the factors controlling their development in the Shiqiantan Sag. This study develops a multi-scale quantitative framework that integrates mercury intrusion–withdrawal behavior, nitrogen adsorption, and NMR T₂ spectra to constrain pore connectivity and the contribution of microfractures in tight carbonate reservoirs, providing a transferable approach for reservoir evaluation beyond the study area. The results categorize three rock microfacies in the study area: Bioclastic micrite, Micritic bioclastic limestone, and Sparry Bioclastic Limestone. The reservoir space is predominantly composed of secondary pores, including intragranular dissolution pores, intercrystalline clay pores, and microfractures. The pore structures exhibit a marked contrast across the lithofacies: the sparry bioclastic limestone develops the most optimal pore-fracture composite system, The pore structures exhibit a marked contrast across the lithofacies, directly correlating with hydrocarbon accumulation. Specifically, the sparry bioclastic limestone develops a pore-fracture composite system characterized by 25–100 nm pore throats, corresponding to the primary oil-bearing intervals observed in drilling. In contrast, the bioclastic micrite limestone and micritic bioclastic limestone, despite exhibiting localized nanoscale pores, lack effective connectivity (pore throats < 25 nm) and predominantly act as tight, dry layers with poor or no oil and gas shows, which endow them with the anomalous characteristic of relatively low porosity yet high permeability. This study reveals an integrated control on the development of tight bioclastic limestone reservoirs, in which sedimentary microenvironment and paleogeomorphology jointly determine the initial reservoir framework, while subsequent structural fractures and associated diagenetic dissolution play a critical role in modifying pore structures and enhancing reservoir quality. Sedimentary microfacies distribution, controlled by paleogeomorphologic variations, dictated the initial reservoir fabric. Subsequently, fracture systems generated by tectonic uplift, coupled with dissolution from meteoric freshwater leaching and organic acids, facilitated the development of secondary pores. Ultimately, the resulting optimization of the pore structure governs the final reservoir quality. The sparry bioclastic limestone is identified as the most promising exploration target in the study area. Its favorable reservoir quality is mainly attributed to its development on palaeogeomorphic and structural highs, where enhanced hydrodynamic energy and subsequent fracture-related dissolution significantly improved pore connectivity. These high-quality reservoirs are widely developed on gentle slope profiles and similar high-quality reservoirs may also locally occur at isolated palaeogeomorphic highs within steep-slope settings, as demonstrated by individual wells.