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The study of fine-grained sedimentation has consistently concentrated on investigating the mechanisms and principles governing the enrichment of organic matter. However, the lack of unified stratigraphic framework has always existed as fine-grained sedimentation covers two distinct grain-size grades, namely, mud and silt, which has impeded the progress of subsequent production research. This study exemplified this issue by analyzing the first member of the Qingshankou Formation in the southern Songliao Basin. We established reconstructed gamma and density curves that mitigated filter noise interference, integrated high-resolution sequence results with astronomical cycle divisions, and created a high-frequency isochronous stratigraphic framework for clastic fine-grained sedimentation by leveraging the weak sensitivity of sandstone density curves and the robust stability in eccentricity cycle extraction. This approach addresses the inconsistencies in stratigraphic division methodologies and mismatched outcomes stemming from the use varying techniques to delineate mud and silt components within clastic fine-grained sedimentary sequences. Furthermore, it elucidates how tectonic-scale variations in sediment supply coupled with potential accommodation changes dictate macroscopic stacking patterns within strata, whereas climate fluctuations on orbital time scales govern sand-mud progradation degrees within these layers, culminating in periodic rhythmic characteristics characterized by vertical sand-mud interbedding. A model for stratigraphic development pertaining to lake delta systems constrained by a “synchronous heterotopy” paradigm is proposed for the southern Songliao Basin. The organic matter enrichment pattern aligns with its filling dynamics, indicating an “overfilling” type developmental pattern at lower strata levels where organic material predominantly originates from terrestrial plant debris external to the basin; this material accumulates primarily within silty zones along layers—with areas exhibiting heightened enrichment values slightly lagging behind short-eccentric maxima positions. In contrast, under an upper “balanced filling” type developmental framework, sources of organic matter are derived both internally and externally relative to the basin—exhibiting substantial heterogeneity—and regions marked by elevated organic matter concentrations are directly associated with locations identified as short-eccentric maxima.

Previous studies show that glycogen synthase kinase 3β (GSK3B) plays an important role in tumorigenesis. However, its role in cervical cancer is unclear. The present study silenced GSK3B with siRNAs and/or chemical inhibitors to determine its role in HeLa cervical cancer cell proliferation and migration as well as in xenograft tumor growth. Cell Counting Kit (CCK)-8 and 5-ethynyl-2'-deoxyuridine (EdU) assays were used to determine cell survival and proliferation. Scratch and Transwell® assays were used to evaluate cell migration. Xenograft tumors were used to evaluate the effect of GSK3B on tumor growth. Transcriptomic sequencing was used to clarify the mechanisms underlying the foregoing processes. Public databases and clinical specimens showed that GSK3B was upregulated in cervical cancer tissues and correlated with poor prognosis. In vitro experiments indicated that GSK3B inhibition reduced cell viability, proliferation, and migration. In vivo experiments demonstrated that GSK3B inhibition slowed xenograft tumor growth. Transcriptomic sequencing revealed that GSK3B inhibition modulated the phosphatidylinositol 3-carboxykinase (PI3K)/protein kinase B (Akt) and extracellular matrix (ECM)-receptor interaction signaling pathways. GSK3B inhibition decreased the protein levels of phosphorylated PI3K and Akt and the levels of mesenchymal markers but increased those of epithelial markers. An activator of the PI3K/Akt signaling pathway counteracted the suppressive effects of GSK3B inhibition on HeLa cell viability and proliferation and on PI3K/Akt signaling. Our data suggested that GSK3B regulated cervical cancer cell proliferation and migration by modulating the PI3K/Akt signaling pathway and epithelial-to-mesenchymal transition (EMT).

The current seismic prediction methods of the shale brittleness index are all based on the pre-stack seismic inversion of elastic parameters, and the elastic parameters are transformed by Rickman and other simple linear mathematical relationship formulas. In order to address the low accuracy of the seismic prediction results for the brittleness index, this study proposes a method for predicting the brittleness index of shale reservoirs based on an error backpropagation neural network (BP neural network). The continuous static rock elastic parameters were calculated by fitting the triaxial test data with well logging data, and the static elastic parameters with good correlation with the brittleness index of shale minerals were selected as the sample data of the BP neural network model. A dataset of 1970 data points, characterized by Young’s modulus, Poisson’s ratio, shear modulus, and the mineral brittleness index, was constructed. A total of 367 sets of data points from well Z4 were randomly retained as model validation data, and 1603 sets of data points from the other three wells were divided into model training data and test data at a ratio of 7:3. The calculation accuracy of the model with different numbers of nodes was analyzed and the key parameters of the BP neural network structure such as the number of input layers, the number of output layers, the number of hidden layers, and the number of neurons were determined. The gradient descent method was used to determine the weight and bias of the model parameters with the smallest error, the BP neural network model was trained, and the stability of the brittleness index prediction model of the BP neural network was verified by posterior data. After obtaining Young’s modulus, Poisson’s ratio, and shear modulus through pre-stack seismic inversion, the BP neural network model established in this study was used to predict the brittleness index distribution of the target layer in the study area. Compared with the conventional Rickman method, the prediction coincidence rate is 69.16%, and the prediction coincidence rate between the prediction results and the real value is 95.79%, which is 26.63% higher. The BP neural network method proposed in this paper provides a reliable new method for seismic prediction of the shale reservoir brittleness index, which has important practical significance for clarifying the shale gas development scheme and improving shale gas exploitation efficiency.

Triboelectric nanogenerator (TENG) can power wireless, real‐time sensing system with hybrid electromagnetic or piezoelectric power, or directly drive commercial LED without battery. However, it is a great challenge to directly drive wireless real‐time sensing system due to low energy density based on environment energy. Here, a self‐powered smart wireless temperature monitoring system that uses machine learning to accurately measure the ambient temperature is developed. A position modulation‐based TENG‐driven transmitter enables wireless communication and real‐time temperature monitoring. This machine learning‐based wireless sensor can accurately monitor the ambient temperature, with a recognition accuracy of up to 96.2%. This sensor architecture could potentially be used in low‐cost distributed sensors for environmental monitoring.

Oil content and the movability of shale oil are important indicators for the evaluation of continental shale oil. In recent years, the sandwiched shale oil in the fourth member of the Shahejie Formation in the Liaohe Western Depression area of the Bohai Bay Basin has shown great exploration potential, while the understanding of shale oil content and the movability of shale oil is weak. In this study, through a combination of core observations and experiments, we clarified the shale lithofacies types in the fourth member of the Shahejie Formation in the Liaohe Western Depression and explored the influencing factors of the characteristics in the oil-bearing and movability of shales in different lithofacies. The results of the study show that the organic matter content of the shale is high (TOC = 2.2–4.3%), but the maturity of thermal evolution is low (Ro = 0.38–0.55%), and the mineral component is dominated by clay minerals (30.3–72.7%), with quartz, feldspar, and other feldspar minerals developing secondarily. According to the content of organic matter, the mineral component, and the sedimentary structure, five types of lithofacies can be classified: organic-rich laminated clay-bearing felsic shale lithofacies (LS1), organic-rich laminated clay felsic mixed shale lithofacies (LS2), organic-rich layered clay felsic mixed shale lithofacies (LS3), organic-containing massive felsic-bearing clay shale lithofacies (LS4), and organic-containing massive clay felsic mixed shale lithofacies (LS5). The oil content of shale is mainly affected by the organic matter. The rate of increase in oil content of shale is fastest when the organic matter content is between 2 and 4%. The movability of shale oil is mainly controlled by the sedimentary structure, mineral component, and microscopic pore structure; the more the shale laminae is developed, the lower the clay content is, and the more the pore space is developed, the better the movability of shale oil is. Combined with the results of the shale oil content and mobility analysis in the study area, LS2 and LS3 are the dominant lithofacies in the fourth member of the Shahejie Formation in the study area, followed by LS1 >LS5 >LS4, so shale oil exploration should focus on the development of LS2 and LS3.

Based on the information of dense cored wells and by analyzing off-surface reservoir data, we determined the type of off-surface reservoirs in the area, the characteristics of off-surface reservoir microfacies (vertical), the planar distribution characteristics of off-surface reservoirs, the off-surface reservoir rocks, facies features, etc., so as to extract the matching pattern of the well pattern and the sand body. Based on the core analysis of the cored well area and the analysis of the matching relationship between injection and production between wells, five typical conventional off-surface and high-quality strip sand body injection and production modes between wells were extracted, and five corresponding core physical models and numerical models were constructed. Through physical simulation displacement experiment and numerical simulation displacement experiment analysis, the research shows that conventional off-surface reservoirs can be exploited separately and can be produced well, with a recovery rate of 40%; conventional off-surface reservoirs are combined with high-quality strip sand bodies (Lu et al., Journal of Xi’an Shiyou University (Natural Science Edition), 2019, 34(4): 60–66 and Cheng et al., Oil and Gas Reservoir Evaluation and Development, 2019, 9(02): 56–59). Under mining conditions, there is serious interlayer interference; under the condition of tandem mining of conventional off-surface reservoirs and high-quality strip sand bodies, the production level of off-surface reservoirs can be effectively improved. Experiments show that the contribution rate of conventional off-surface reservoirs reaches 62% under the conditions of pin-out mining with high-quality sand bodies. The research results lay the foundation for further refined development and improvement of the economic and effective utilization of reserves.

To deepen our understanding of reservoir heterogeneity, seepage barriers in the study area were divided into interlayer, intralayer, and planar levels based on their spatial distribution characteristics and then investigated by taking the third member of the Neogene Guantao Formation in the block M of the Gudao oilfield as an example. Based on their genesis characteristics, the interlayer seepage barriers were divided into the overbank sand-overbank sand type, overbank sand-channel type, isolated channel superposition type, and channel shallow-cut type. The planar seepage barriers were categorized into the channel boundary type, abandoned channel type, channel-overbank sand type, and floodplain mudstone type. The intralayer seepage barriers were classified into the mudstone type and physical property type. Classifying multiple levels of different types of seepage barriers led to the refinement of their spatial characteristics. The strength of seepage barriers was characterized using the “seepage barrier coefficient” and “reservoir quality coefficient,” and the small-valued coefficients of the interlayer and intralayer seepage barriers indicated that these seepage barriers are characterized by large thickness, high mudstone content, poor physical properties, and weak seepage ability. The strength of the planar seepage barriers was dependent on the sedimentary facies types and channel stages, and the difference between planar seepage barriers was characterized using the reservoir quality coefficient. The seepage barriers were described based on the multilevel classification of seepage barrier categories, the intralayer seepage barriers with a lateral accretion pattern in the meandering river point bars were identified and described, and the distribution characteristics of seepage barriers were summarized at multiple levels. The method of “hierarchical analysis, skeleton construction, and category fitting” was used to establish 3D models of different levels of seepage barriers, and a modeling method based on the characteristics of intralayer seepage barriers under the constraint of architecture pattern was used to model intralayer seepage barriers with a lateral accretion pattern. In the monitoring of water injection profiles, it was found that the extent of blockage achieved by seepage barriers affects the water injection volume and thus controls the fluid transport pattern. Due to the development characteristics of the seepage barrier in the formation, there are some differences in injection production efficiency under different well pattern matching modes. The research on the distribution characteristics of different levels of seepage barrier categories provides a reliable geological basis for improving the injection-production relationship.

To clarify the dynamic evolution characteristics of reservoir flow units during water injection development, the upper member of the Neogene Guantao formation in Block M of Gudao Oilfield is taken as a case study. Based on logging data, water injection profile test data, subwell data, and production performance data, among others, the flow zone index (FZI static) was proposed as the static evaluation parameter of the flow unit. The relationship between cumulative water injection (WT) and FZI change (△FZI) was fitted. Hence, the △FZI caused by water injection is combined with the static parameter of flow unit evaluation (FZI static) as the dynamic parameter of flow unit evaluation (FZI dynamic). The comprehensively evaluated reality of flow units in different periods is characterized by formula FZI static+△FZI=FZI dynamic. The study shows that as the division standard of the flow unit, the FZI has a good correlation with the test results of the water absorption profile, such as water absorption intensity and relative water injection volume. Using the FZI as the static parameter of flow unit evaluation, four types of flow units were divided as follows: type I flow unit, FZI≥4.1; type II flow unit, 4.1>FZI≥2.4; type III flow unit, 2.4>FZI≥1.7; type IV flow unit, 1.7>FZI. The reservoir porosity and permeability characteristics of different flow units are highly correlated. Moreover, the relative permeability curve confirms that different flow units have different seepage capacities. Though, comparing characteristic reservoir parameters in different periods, the reservoir’s physical parameters became more conducive to fluid flow with the water injection development. The increase in the same water injection rate for type I and II flow units was greater than that for type III and IV flow units. Furthermore, when type I flow units were continuously distributed in a large area, high water consumption bands were formed, absorbing most of the water injection in the water injection wells. Hence, the waterflood efficiency was low. The change in different flow units was mainly controlled by the injection production well pattern and WT. Combined with the relative change characteristics of interlayer flow units, the changes can be divided into increasing type change and decreasing type changes. Finally, according to the distribution characteristics of different flow units, oil saturation, and water flooding results, strategies for tapping the potential of the remaining oil from three aspects (plane, interlayer, and inner layer) were formulated.