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<jats:p> We systematically analyze the geochemical characteristics of source rocks of the Yan Chang Formation in the Ordos Basin to reveal the influence mechanisms of the volcano on lacustrine organic matter enrichment. Organic matter enrichment is not synchronous with the volcanic eruption in time, but it has a “hysteresis” effect. The evidence of volcanic activity mainly includes two aspects: one is a large amount of volcanic ash in black shale, and the other is a negative shift of organic carbon isotopes of source rocks and finding that black shale was affected by climate events caused by the volcano. The climate event caused by the volcano has three effects on organic matter enrichment in black shale: (1) it brought nutrients for the growth of organisms and released a large amount of greenhouse gases, such as CO<jats:sub>2</jats:sub>, to accelerate photosynthesis and promote the growth of organisms; (2) a large amount of toxic gases, such as SO<jats:sub>2</jats:sub> and H<jats:sub>2</jats:sub>S, were released and O<jats:sub>2</jats:sub> was consumed and diluted in the air, forming a severe anoxic environment and accelerating the preservation of organic matter; and (3) it caused extremely hot weather, resulting in long-time surface runoff and other climate events, increasing input of terrestrial organic matter, and forming light components of hydrocarbons. </jats:p>

<jats:p> The Yan’an gas field is located in the southeastern part of the Ordos Basin of China. After years of research, we have clarified the characteristics of the upper Paleozoic tight sandstone reservoirs: four main sets of intervals, including the Carboniferous Benxi Formation, the Shan second and Shan first members of the Permian Shanxi Formation, and the He eighth member of the Permian Lower Shihezi Formation, are multilayer complex superposed tight sandstone reservoirs that developed under the control of multiple differential sedimentary systems. Compared with the northern gas field, the upper Paleozoic reservoir is characterized by the small-scale effective sand body and poor physical property in the Yan’an gas field; the heterogeneity of the upper Paleozoic tight reservoir varies greatly: the heterogeneity of the He eighth and the Shan first members was increasing from the north to the south of the research area, owing to the intersection of the north and south provenance. The Shan second member indicates an obviously opposite trend: the heterogeneity of the Benxi Formation weakened from the center to both sides; the Yan’an gas field developed four main superposed composite sand bodies types, including the vertical superposed, lateral migration, cut superposed, and isolated types. Due to the existence of the interlayers rich in mudstone and soft debris near the architectural boundary, the reservoir sand body has strong structural heterogeneity under the interaction of differential diagenesis and densification. Aiming at the strong heterogeneity and multilayer complex superposition characteristics of the Yan’an gas field, we have made clear the constraints and matching relationships between control factors and well-pattern elements on the basis of deep analysis. We have formed the hybrid well pattern for 3D recovery technology that unlocked multilayer complex superposed tight sandstone gas reservoirs with strong heterogeneity in the southeastern portion of the Ordos Basin. </jats:p>

<jats:p> Recently, the computation of seismic fault attribute that may be significant in seismic interpretation is that seismic fault detection is treated as an image segmentation problem using different deep-learning (DL) architectures. To do this, researchers have concentrated on applying cutting-edge DL architectures in computing seismic fault attributes. To explore the factors that may affect the accuracy of seismic fault attribute, we compare the computed fault probability using DL architectures under different scenarios. The designed scenarios aim to highlight the leading factors that may affect the accuracy and resolution of seismic image segmentation. The discussed factors include the dimension and size of training data, training data preparation, ensemble learning, and batch size in DL. The proposed comparisons are applied to one marine seismic survey from New Zealand and one land seismic survey from China. The results demonstrate that properly preparing training data is far more important than choosing a cutting-edge DL architecture in computing seismic fault attribute. We also propose a practical workflow that can include real seismic data and corresponding interpreted fault sticks in training data for a specific seismic survey. </jats:p>

<jats:p> To study the features of the gravity and magnetic anomalies and the prospects of iron deposits in the eastern Hebei province, we have collected and arranged gravity data at scales of 1:50,000 and 1:200,000 and aeromagnetic data at scales of 1:25,000 and 1:200,000. Then, we have separated the Bouguer gravity anomaly and the aeromagnetic anomaly by reduction to the pole (RTP) by the moving average method and processed these two anomalies using the total horizontal gradient method and the vertical second derivative method. Combined with existing geologic and geophysical research, we have studied the features of the gravity and magnetic anomalies and investigated the corresponding relationship between the distribution of iron deposits and these anomalies, and then we predicted the favorable areas for iron deposits in the eastern Hebei province. The results find that there is a good corresponding relationship between the distribution of iron deposits and the gravity and magnetic anomalies in the eastern Hebei province. Identification marks of the gravity and magnetic anomalies are determined to find the iron deposits in the eastern Hebei province, including the magnetic highs of the local magnetic anomaly and the vertical second derivative anomaly, the gravity highs of the local gravity anomaly and the vertical second derivative anomaly, the gradient belts of the Bouguer gravity anomaly, the high-value zones of the RTP aeromagnetic anomaly, and the extreme-value zones of the total horizontal gradient of the Bouguer gravity anomaly and the RTP aeromagnetic anomaly. There are 17 favorable areas for iron deposits in the eastern Hebei province, and these favorable areas display complex trends, including east–west-trending, north-northwest-trending, and northeast-east-trending features. </jats:p>

<jats:p> We interpret a region of undulatory sediments adjacent to a major headwall of the Cape Fear submarine landslide system offshore of North Carolina, USA, as sediment waves rather than creep or fault-related deformation. The wave package extends 19 km upslope from the S4 landslide headwall and thickens upslope from approximately 250 to 450 m. The field of undulating sediments displays the continuity of seismic horizons, upslope-migrating crests, downslope thinning, and wave heights and lengths of approximately 26 m and approximately 1 km, respectively, which are consistent with sediment wavefields. The Western Boundary Undercurrent formed contourites on the nearby Blake Ridge and it is possible that these sediment undulations were deposited via similar mechanisms. Ocean Drilling Program (ODP) cores near the sediment undulation field suggest that the turbidity currents also may have played a role in wave formation. Although most of the 19 km long field comprises unaltered sediment waves, we observe an approximately 5 km long zone adjacent to the landslide scarp that expresses evidence of faults that offset and deform the sediment wave strata. We interpret this deformation as the result of reduction in stress following the removal of the landslide mass. Given that the Cape Fear system has generated several episodes of potentially tsunamigenic slope failure, the future stability of the system is pertinent. Redefining these undulatory sediments as sediment waves eliminates a major slope instability mechanism of the system and is important for understanding the future slope stability hazards of Cape Fear. Our analysis highlights the importance of understanding sediment waves in hybrid submarine landslide-sediment wave systems. </jats:p><jats:sec><jats:title /><jats:p> Geological feature: Cape Fear submarine landslide sediment waves Seismic appearance: Continuous undulating horizons Alternative interpretations: Downslope creep or faults Features with similar appearance: Extensional slope failure Formation: Alongslope and downslope currents Age: Quaternary Location: Cape Fear submarine landslide complex, offshore North Carolina Seismic data: High resolution multichannel seismic data Analysis tools: Multichannel seismic data, multibeam bathymetry, sub-bottom Chirp </jats:p></jats:sec>

<jats:p> Recently, the exploration and development of the Chang 7 shale oil reserves and production have increased in the Ordos Basin. However, the characteristics of the Chang 7 reservoir vary greatly in different areas, which affect the exploration and development of shale oil. We used various analytical methods such as core observation, casting section, high-pressure mercury injection, nuclear magnetic resonance, X-ray diffraction (XRD), and logging interpretation to study characteristics of the reservoir in the Heshui area. The lithology of the Chang 7 member is mainly feldspathic quartz sandstone suggesting that the content of quartz is higher than that of feldspar, and it has relatively low carbonates. In addition, the kinds of feldspar are mainly plagioclase and potassium feldspar, and the concentration of clay minerals is 80%, mainly comprising illite and chlorite. The reservoir of the Chang 7 member is chiefly comprised of submicron pores, such as feldspar dissolved pores, intergranular pores, dissolved pores, microfractures, and intergranular pores. The porosity ranges from 6% to 12%, whereas permeability is less than 0.2 × 10<jats:sup>−3</jats:sup> [Formula: see text]. The Chang 7 reservoir has a strong heterogeneity. Specifically, the heterogeneity of Chang 7<jats:sub>1</jats:sub> is weaker than that of Chang 7<jats:sub>2</jats:sub>. There is a complex diagenesis such as compaction, dissolution, and cementation, and the compaction and cementation are relatively more and the dissolution is dominated by constructive diagenesis of feldspar dissolution. Sedimentary microfacies are one of the main factors controlling reservoir development. The physical properties of the reservoir in the branch channel are better than the edges of the branch channel and the lacustrine. The diagenesis affects the development and distribution of good reservoirs, and destructive diagenesis such as compaction and cementation reduces porosity and permeability. Conversely, dissolution increases the physical properties of the reservoir. Tectonics has no obvious effects on reservoir but plays a positive role in the migration and accumulation of hydrocarbon when microfractures developed. </jats:p>

<jats:p> The dolomite gas reservoir of the Permian Chihsia Formation has recently become the main target of hydrocarbon exploration in the northwest Sichuan Basin. Owing to its substantially low porosity and permeability, the dolomite gas reservoir has become a great challenge for geophysicists in terms of distinguishing gas-filled dolomite thin layers. We have used limestone and dolomite core samples from the Permian in the northwest Sichuan Basin to investigate the physical characteristics of the dolomite gas reservoir in a laboratory. Dolomite has a comparatively higher permeability than limestone due to its higher fracture development. X-ray CT scanning indicates that a few large pore spaces dominate the pore space in limestone that cannot provide good pore connections, whereas small pores and fractures dominate the pore spaces in dolomite. The fracture development in the dolomites provides insignificant porosity that substantially increases the permeability. The [Formula: see text] ratio estimated from well-logging data in the northwest Sichuan Basin indicates significantly lower anomalies. These low [Formula: see text] anomalies validate the rock-physics analysis from the laboratory data and indicate that the [Formula: see text] ratio could be a good indicator of gas reservoirs in dolomite layers. </jats:p>

<jats:p> The offshore part of the Timan-Pechora petroleum basin is one of the most promising areas to search for new petroleum accumulations. The commercial potential of the Carboniferous-Lower Permian play has already been proven by exploratory drilling in the Dolginskoye uplift, whereas the Prirazlomnoye field has been in production since 2013. However, significant petroleum resources in this area may be confined to the Ordovician-Lower Devonian play. The purpose of the study is to evaluate the potential of the Lower Devonian (Ovinparmian) reservoirs within the Pechora Sea shelf based on new geologic and geophysical data. We identified multiple prospects within the Dolginsko-Papaninskaya structural zone and estimated its resources. The potential of the Lower Devonian within the study area is comparable with that of the Carboniferous-Lower Permian play. Based on the new 3D seismic data performed in three offshore license blocks, we identified several unconformities, where the Timanian-Sargaevian regional seal onlaps carbonate rocks of the Ovinparmian horizon (Lochkovian stage, Lower Devonian). We hypothesize that due to the Middle Devonian structural deformations, the Lower Devonian carbonate deposits have been exposed to subaerial erosion and surface and subsurface karst. Diagenetic alterations of the Ovinparmian sediments (i.e., dolomitization, dissolution, and fracturing) are favorable for the development of high-porosity reservoirs. In our study, we consider some sedimentation, diagenesis, and catagenesis models of the Ovinparmian carbonates. Furthermore, we designed an exploration program with a view to further study the Lower Devonian reservoirs. </jats:p>

<jats:p> The BZ-A oilfield is one of the significant discoveries within the Huanghekou Sag, the southern Bohai Sea Basin, China, and the reservoirs of the BZ-A oilfield were deposited in the Paleogene period. Unfortunately, the spatial continuity of the Paleogene clastic reservoirs of the BZ-A oilfield was destroyed by the widely distributed igneous rocks. Characterizing those “isolated” clastic geobodies is the main task in the exploration and production phases. The exploration wells within the BZ-A oilfield demonstrate that the size of the clastic geobodies is one of the main factors that determine if a new drilled well is a commercial oil-producing well. The spatial distribution and the size of igneous rocks are other important factors affecting whether a drilled well is an oil-producing well. Thus, the analysis of 3D geomorphology of igneous rocks is among the most important tasks in well and development planning. We integrate 3D seismic data, well logs, and core data to characterize the Paleogene igneous bodies within the BZ-A oilfield. The analyzing procedure begins with determining the igneous rock types by analyzing the texture of cores and corresponding thin sections. Then, the volcanic/volcaniclastic facies are defined by integrating the well logs and igneous rock. Finally, the volcanic edifices are interpreted by integrating the seismic data, well logs, and core data. The analysis demonstrates that the volcanic edifice usually consists of five facies (volcanic conduit, effusive, explosive, extrusive, volcanic sedimentary, and subvolcanic facies). The overall shape of the edifice and the distribution of each facies are controlled by the volcanic eruption styles. In our study area, the seismic variance attribute can be used to locate the volcanic conduit facies, and the seismic root-mean-square amplitude can characterize the volcanic effusive facies. </jats:p>

<jats:p> Marine exploration and production play a vital role in petroleum industries. It is difficult to acquire sufficient well data in marine settings, so seismic data become the most important interpretation data in research. In general, the seismic data in marine exploration have low quality because of the deep depth from the surface. To partly address this, the support vector regression (SVR) algorithm is proposed to fuse multiple seismic attributes for sand thickness prediction. First, we use forward modeling to establish virtual wells for improving the training data set. Second, we select the optimal attributes by correlation analysis. Third, we apply the SVR algorithm to learn the relationship between seismic attributes and sand thickness. Fourth, we use the SVR model to predict the sand thickness between wells by calculating a fused attribute. The results indicate that the fusion attribute with SVR has a higher correlation coefficient with sand thickness than the original attributes by statistical method. The approach can be widely used for improving the seismic interpretation quality of the research area with few wells. </jats:p>