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Focused ion beam (FIB) milling techniques have been used for more than a decade to prepare organic-rich shale samples for electron microscopy. Nano- and micro-scale imaging of organic pores is used to assess pore volumes and hence estimate gas-in-place. Ion milling natural composites is particularly challenging due to drastic extremes in the physical properties of individual phases such as minerals and organics. Damage to the organic-rich phases occurs due to the large differences in thermal conductivities of minerals and organics that could reach an order of magnitude and the resulting buildup of heat in the organics. Furthermore, radiation damage via ion implantation may also alter the structural characteristics of the shale. Herein, the damage associated with preparing electron-transparent kerogen specimen using low kV FIB, cryo-FIB, and cryomicrotome, a new technique for shale kerogen, is quantified using experimental and modeling techniques. The degree of gallium implantation is quantified using scanning transmission electron microscopy (STEM), selected area electron diffraction (SAED), and energy dispersive X-ray spectroscopy (EDX) along with the stopping range of ions in matter (SRIM) model. Interestingly, although the use of cryogenic temperature removes the thermal effect, Ga+ ion implantation is observed in the specimen prepared by cryo-FIB. Furthermore, the magnitude of the thermal damage at a highly localized level was determined using nano-beam electron diffraction (NBED) performed at −196 °C. Time-resolved diffraction patterns indicate that despite the fact kerogen is among the most stable geopolymers, the aromatic components still degraded due to the local temperature increases. On the other hand, the cryomicrotome technique operating at liquid nitrogen temperature is demonstrated as a suitable method to prepare thin kerogen specimen while minimizing structural damage and preserving its native porosity and chemical composition.

High-speed impact loading has a crucial effect on pore compaction and microscopic crack evolution for shale at different confining pressure (Pc). In this study, we selected the shales from Jiangxi (JX) and Sichuan Province (SC) in China, and then performed Split Hopkinson pressure bar (SHPB) experiments at Pc = 0, 5, 15, and 25 MPa. Further, the impacted shales were tested by low temperature nitrogen adsorption (LTNA), mercury intrusion porosimetry (MIP) and environmental scanning electron microscope (ESEM). The results showed that confining pressure could cause different degrees of pore compaction and crack blockage: total pore volume (TPV) based on MIP of the JX and SC shales at different confining pressures decreased by 24.3 ~ 69.2% and 54.1 ~ 66.5%, respectively; total pore volume based on LTNA decreased by 36.2 ~ 49.0% and 49.9 ~ 58.2%, respectively; total specific surface area (TSSA) based on BET model decreased 68.3 ~ 75.8% and 39.5 ~ 60.0%, respectively. It was found that the confining pressure had a more significant effect on macropores relative to mesopores. Confining pressure also changed the failure patterns of shales. The shales at low confining pressure (Pc = 0, 5, and 15 MPa) showed a marked characteristic of brittle shear damage. However, the shales at high confining pressure (Pc = 25 MPa) showed a brittle-ductile transition (BDT) phenomenon. Additionally, high confining pressure resulted in a tiny ductile damage and a significant increase in elastic modulus. Besides, the effect of different mineral compositions and grain sizes on crack extension was discussed. This study is meaningful for understanding and controlling pore compaction and crack extension, thus improving production processes of dynamic shale gas production technology. [ABSTRACT FROM AUTHOR]

(SCFs) have disclosed a record of organically preserved faunas from Cambrian epeiric seas. Their phylogenetically and functionally derived components, including probable crown-group crustaceans and molluscs, are absent from the 'exceptional' palaeoenvironmental settings captured by Burgess Shale-type (BST) macrofossil biotas. This apparent segregation of SCF and BST-macrofossil deposits has led to contrasting hypotheses on whether their faunal differences reflect genuine ecological patterns or overriding taphonomic controls. We report a new, exceptionally diverse SCF biota from the Cambrian Hess River Formation of the Northwest Territories (Canada), which occupied an offshore slope setting. The Hess River biota, hosted by a single shale sample, rivals the Burgess Shale in its disparity of bilaterian body plans, providing a microfossil counterpoint to the regional record of BST-macrofossil faunas from similar deeper-water palaeoenvironments. The Hess River SCFs comprise exceptionally preserved ecdysozoan and spiralian sclerites, arthropod mouthparts, semi-articulated wiwaxiids, problematica and pterobranchs, but no recognizable crown molluscs or crustaceans. The similarities between the Hess River fauna and classic deeper-water BST-macrofossil biotas suggest significant palaeoecological overlap, robust to their distinct taphonomic expressions. This upholds the existence of comparatively modern communities in Cambrian epeiric settings, distinct from the faunas populating both BST-macrofossil biotas and SCF assemblages sampling similar palaeoenvironments. [ABSTRACT FROM AUTHOR]

AbstractThis study addresses the challenges of characterising hydrocarbon reservoirs in the complex depositional environment of the “Ik” field, Niger Delta Basin, Nigeria, through well log and seismic attribute analyses. Well log analysis identified three reservoirs across five wells with distinct properties. Reservoir 3 showed the most promising characteristics, including high porosity (0.22), substantial net pay thickness (73.8 m), and a favourable net pay-to-gross ratio (NpTG) (0.916), indicating excellent hydrocarbon potential. Reservoir 1 exhibited high permeability (1481.6 mD) and low shale content (0.02), despite higher water saturation (0.45), suggesting productive potential under proper management. Reservoir 2 displayed intermediate characteristics. Seismic interpretation involved synthetic seismogram generation, seismic-to-well ties, and horizon delineation corresponding to the reservoirs. Key seismic attributes, including root mean square (RMS) amplitude and sweetness, effectively delineated reservoir facies. These attributes addressed the heterogeneity of the complex geological setting in the Niger Delta by providing high-resolution lithological detail and extensive spatial coverage. High RMS amplitude and sweetness values identified interconnected sand channels and hydrocarbon-rich zones. This study demonstrates the utility of combining well log and seismic data for enhanced reservoir characterization. The findings underscore the significant hydrocarbon potential of the “Ik” field and offer valuable insights for optimizing exploration and production strategies. [ABSTRACT FROM AUTHOR]

The dynamic and static elastic parameters of rocks exhibit differences. It is of great practical significance to carry out experiments on dynamic and static elastic parameters of rocks under reservoir conditions and determine the conversion relationship between dynamic and static elastic parameters. In this study, shale oil samples from the second member of Kongdong sag in Dagang Oilfield were analyzed by triaxial compression experiments at different bedding angles and longitudinal and shear wave velocity tests. Dynamic and static stiffness coefficient, elastic modulus and acoustic wave velocity change under different directions of pressure and pressure relief. The results indicate that the P-wave velocity, fast shear wave velocity, slow shear wave velocity, dynamic and static Young's modulus exhibit an increase as the confining pressure rises, and the parameters are greater during the unloading process than during loading process. At identical confining pressures, the dynamic Young's modulus measured by cores with parallel bedding plane is greater than that measured by cores with vertical bedding plane. The dynamic and static elastic mechanical parameters of different bedding angles can be transformed under varying pressures, and the dynamic elastic mechanical parameters measured under varying levels of confining pressure can be transformed into static elastic mechanical parameters under equivalent confining pressures, which offer fundamental parameters for examining rock mechanics properties and serving as a reference for developing fracturing construction plans for oil and gas reservoirs. [ABSTRACT FROM AUTHOR]

In-situ conversion technology is a sustainable and effective method of recovering medium-low maturity shale, which can be produced with oil resources expected to exceed global total proven oil reserves. Nevertheless, criteria and procedures for grading such shale oil resources are lacking. We present a combination of distinct faceis and theoretical economic index (I e ) to grade the in-situ conversion shale oil resources of Chang 7 Member in the Ordos Basin and Nenjiang Formation in the Songliao Basin. This shale oil resource was categorized into four classes: invalid, valid, sweet-spot and core resource. For the shale dominated by type II kerogen (Chang 7), total organic carbon (TOC) values at 6%, 9%, and 12%, hydrocarbon generation potential (S1+S2) values at 15 mg/g, 30 mg/g, and 50 mg/g, and I e at 2, 3, and 4, respectively, represent the boundary of the four resource grades. For the shale dominated by type Ⅰ kerogen (Nenjiang), TOC values at 4%, 6%, and 8%, S1+S2 values at 19 mg/g, 32 mg/g, 48 mg/g, and I e at 2, 3, and 4, respectively, represent the boundary of the four resource grades. Our research provides a feasible practical strategy for evaluating and predicting in-situ conversion shale oil resources in lacustrine basins. [ABSTRACT FROM AUTHOR]

The oil content of shale oil reservoirs is a key parameter for reserve evaluation and "sweet spot" selection. However, discrepancies in the oil contents obtained by different methods have led to considerable disparities in the selection of exploration well locations and development strategies for shale oil. This study focuses on low to moderately mature sealed coring samples from the Dongying Depression in the Bohai Bay Basin. Three methods—NMR, Dean–Stark, and Rock-Eval—were employed to measure the oil content of shale. The results indicate that the oil content obtained by NMR is the highest, followed by the Dean–Stark distillation extraction method, while the pyrolysis method yields the lowest value. The study found that (1) the efficiency of the solvent extraction effect on moderately to low-mature shale is low since the occurrence of numerous closed pores leads to a lower yield when using the Dean–Stark method. (2) The exposure of shale samples to the air, sample crushing, and lag time for temperature increase cause a significant loss of light hydrocarbon components, resulting in the lowest oil content when measured by the Rock-Eval method. The NMR method, with its advantages of a short analysis time and non-destructive nature, appears to be the most advantageous method for shale oil content evaluation. [ABSTRACT FROM AUTHOR]

Total organic carbon (TOC) content, indicative of organic richness, serves as a pivotal metric for evaluating the hydrocarbon generative capacity of source rocks. A well-defined correlation exists between well-logging parameters and TOC content. However, conventional TOC prediction models, such as multiple linear regression and the ΔlogR method, often exhibit lower prediction accuracy in complex geological settings. This study aims to introduce an advanced TOC content prediction approach using the Extreme Gradient Boosting (XGBoost) decision tree model, validated through application to the Cambrian Qiongzhusi formation shale in the central Sichuan Basin. Initially, the characteristics of the dataset were delineated, and XGBoost, along with two prevalent machine learning models, was selected and trained using effective training strategies. Subsequently, geological data were normalized using the Gaussian initialization method to compile the dataset, leading to the development of three predictive machine learning models for shale TOC content. Ultimately, a comparative analysis of the prediction accuracies between XGBoost and the other two models was conducted. Experimental findings indicate that the geological dataset is characterized by a limited sample size and an uneven distribution of data. Within this dataset, the training efficacy of the XGBoost algorithm markedly exceeds that of other models. Compared with prevalent models such as the K-Nearest Neighbors (KNN) and backpropagation (BP) neural network, XGBoost demonstrates remarkably superior predictive precision. This is evidenced by a high determination coefficient (R2) of up to 0.81, a comparatively lower mean squared error (MSE), and smaller error fluctuations, indicating greater accuracy and reliability of the model. Conversely, both the KNN and BP neural networks exhibit inferior predictive accuracy. The KNN model is substantially impacted by data imbalance. Moreover, disparities in distance metrics and inappropriate selections of the K-value can significantly degrade the predictive accuracy of the model. Concurrently, the BP neural network may suffer from local optima during its initialization phase due to unstable connection weights and thresholds, thereby diminishing the model’s overall predictive efficacy. The findings of this study are crucial for developing an intelligent TOC content forecasting model, promoting further innovation and development of oil exploration technologies, and reducing human labor costs in oilfield exploration. [ABSTRACT FROM AUTHOR]