For deep prospects in the foreland thrust belt,southern Junggar Basin,NW China,there are uncertainties in factors controlling the structural deformation,distribution of paleo-structures and detachment layers,and distr...For deep prospects in the foreland thrust belt,southern Junggar Basin,NW China,there are uncertainties in factors controlling the structural deformation,distribution of paleo-structures and detachment layers,and distribution of major hydrocarbon source rocks.Based on the latest 3D seismic,gravity-magnetic,and drilling data,together with the results of previous structural physical simulation and discrete element numerical simulation experiments,the spatial distribution of pre-existing paleo-structures and detachment layers in deep strata of southern Junggar Basin were systematically characterized,the structural deformation characteristics and formation mechanisms were analyzed,the distribution patterns of multiple hydrocarbon source rock suites were clarified,and hydrocarbon accumulation features in key zones were reassessed.The exploration targets in deep lower assemblages with possibility of breakthrough were expected.Key results are obtained in three aspects.First,structural deformation is controlled by two-stage paleo-structures and three detachment layers with distinct lateral variations:the Jurassic layer(moderate thickness,wide distribution),the Cretaceous layer(thickest but weak detachment),and the Paleogene layer(thin but long-distance lateral thrusting).Accordingly,a four-layer composite deformation sequence was identified,and the structural genetic model with paleo-bulge controlling zonation by segments laterally and multiple detachment layers controlling sequence vertically.Second,the Permian source rocks show a distribution pattern with narrow trough(west),multiple sags(central),and broad basin(east),which is depicted by combining high-precision gravity-magnetic data and time-frequency electromagnetic data for the first time,and the Jurassic source rocks feature thicker mudstones in the west and rich coals in the east according to the reassessment.Third,two petroleum systems and a four-layer composite hydrocarbon accumulation model are established depending on the structural deformation strength,trap effectiveness and source-trap configuration.The southern Junggar Basin is divided into three segments with ten zones,and a hierarchical exploration strategy is proposed for deep lower assemblages in this region,that is,focusing on five priority zones,expanding to three potential areas,and challenging two high-risk targets.展开更多
According to the oversampling imaging characteristics, an infrared small target detection method based on deep learning is proposed. A 7-layer deep convolutional neural network(CNN) is designed to automatically extrac...According to the oversampling imaging characteristics, an infrared small target detection method based on deep learning is proposed. A 7-layer deep convolutional neural network(CNN) is designed to automatically extract small target features and suppress clutters in an end-to-end manner. The input of CNN is an original oversampling image while the output is a cluttersuppressed feature map. The CNN contains only convolution and non-linear operations, and the resolution of the output feature map is the same as that of the input image. The L1-norm loss function is used, and a mass of training data is generated to train the network effectively. Results show that compared with several baseline methods, the proposed method improves the signal clutter ratio gain and background suppression factor by 3–4 orders of magnitude, and has more powerful target detection performance.展开更多
在深层油气藏勘探中,地震波能量屏蔽现象(如煤层、膏盐层等)严重制约了深部目标层反射信号的清晰度,单一地震属性难以全面表征复杂地质条件。时频电磁法(Time Frequency Electromagnetic Method,TFEM)基于电磁波在不同地质体传播差异,...在深层油气藏勘探中,地震波能量屏蔽现象(如煤层、膏盐层等)严重制约了深部目标层反射信号的清晰度,单一地震属性难以全面表征复杂地质条件。时频电磁法(Time Frequency Electromagnetic Method,TFEM)基于电磁波在不同地质体传播差异,可有效穿透高阻、高速屏蔽层,在深部岩石属性探测与储层预测中具有独特的穿透能力。近年来该技术在深层油气勘探方面取得突破:研发了新一代发射系统;创新地提出双侧激发多线同步采集技术和四方位全覆盖同步激发采集技术,显著改善了照明均匀性,降低了阴影效应与各向异性影响。在处理技术方面,创新地提出了一种分步递进反演策略,这种方法核心在于构建多源数据协同约束与分步递进反演策略,通过渐进式优化,实现反演精度的层级提升。理论正反演模拟验证了方法的合理性与有效性,并在中国西部塔里木盆地8000 m超深井储层预测及东部深层火成岩储层评价中取得了显著的应用成效。展开更多
The coal-bearing strata of the deep Upper Paleozoic in the GS Sag have high hydrocarbon potential. Because of the absence of seismic data, we use electromagnetic （MT） and gravity data jointly to delineate the distri...The coal-bearing strata of the deep Upper Paleozoic in the GS Sag have high hydrocarbon potential. Because of the absence of seismic data, we use electromagnetic （MT） and gravity data jointly to delineate the distribution of deep targets based on well logging and geological data. First, a preliminary geological model is established by using three-dimensional （3D） MT inversion results. Second, using the formation density and gravity anomalies, the preliminary geological model is modified by interactive inversion of the gravity data. Then, we conduct MT-constrained inversion based on the modified model to obtain an optimal geological model until the deviations at all stations are minimized. Finally, the geological model and a seismic profile in the middle of the sag is analysed. We determine that the deep reflections of the seismic profile correspond to the Upper Paleozoic that reaches thickness up to 800 m. The processing of field data suggests that the joint MT-gravity modeling and constrained inversion can reduce the multiple solutions for single geophysical data and thus improve the recognition of deep formations. The MT-constrained inversion is consistent with the geological features in the seismic section. This suggests that the joint MT and gravity modeling and constrained inversion can be used to delineate deep targets in similar basins.展开更多
基金Supported by the Science and Technology Special Project of CNPC(2023YQX10111)Key Research and Development Special Project of Xinjiang Uygur Autonomous Region(2024B01015-3)。
文摘For deep prospects in the foreland thrust belt,southern Junggar Basin,NW China,there are uncertainties in factors controlling the structural deformation,distribution of paleo-structures and detachment layers,and distribution of major hydrocarbon source rocks.Based on the latest 3D seismic,gravity-magnetic,and drilling data,together with the results of previous structural physical simulation and discrete element numerical simulation experiments,the spatial distribution of pre-existing paleo-structures and detachment layers in deep strata of southern Junggar Basin were systematically characterized,the structural deformation characteristics and formation mechanisms were analyzed,the distribution patterns of multiple hydrocarbon source rock suites were clarified,and hydrocarbon accumulation features in key zones were reassessed.The exploration targets in deep lower assemblages with possibility of breakthrough were expected.Key results are obtained in three aspects.First,structural deformation is controlled by two-stage paleo-structures and three detachment layers with distinct lateral variations:the Jurassic layer(moderate thickness,wide distribution),the Cretaceous layer(thickest but weak detachment),and the Paleogene layer(thin but long-distance lateral thrusting).Accordingly,a four-layer composite deformation sequence was identified,and the structural genetic model with paleo-bulge controlling zonation by segments laterally and multiple detachment layers controlling sequence vertically.Second,the Permian source rocks show a distribution pattern with narrow trough(west),multiple sags(central),and broad basin(east),which is depicted by combining high-precision gravity-magnetic data and time-frequency electromagnetic data for the first time,and the Jurassic source rocks feature thicker mudstones in the west and rich coals in the east according to the reassessment.Third,two petroleum systems and a four-layer composite hydrocarbon accumulation model are established depending on the structural deformation strength,trap effectiveness and source-trap configuration.The southern Junggar Basin is divided into three segments with ten zones,and a hierarchical exploration strategy is proposed for deep lower assemblages in this region,that is,focusing on five priority zones,expanding to three potential areas,and challenging two high-risk targets.
基金supported by the National Key Research and Development Program of China(2016YFB0500901)the Natural Science Foundation of Shanghai(18ZR1437200)the Satellite Mapping Technology and Application National Key Laboratory of Geographical Information Bureau(KLSMTA-201709)
文摘According to the oversampling imaging characteristics, an infrared small target detection method based on deep learning is proposed. A 7-layer deep convolutional neural network(CNN) is designed to automatically extract small target features and suppress clutters in an end-to-end manner. The input of CNN is an original oversampling image while the output is a cluttersuppressed feature map. The CNN contains only convolution and non-linear operations, and the resolution of the output feature map is the same as that of the input image. The L1-norm loss function is used, and a mass of training data is generated to train the network effectively. Results show that compared with several baseline methods, the proposed method improves the signal clutter ratio gain and background suppression factor by 3–4 orders of magnitude, and has more powerful target detection performance.
文摘在深层油气藏勘探中,地震波能量屏蔽现象(如煤层、膏盐层等)严重制约了深部目标层反射信号的清晰度,单一地震属性难以全面表征复杂地质条件。时频电磁法(Time Frequency Electromagnetic Method,TFEM)基于电磁波在不同地质体传播差异,可有效穿透高阻、高速屏蔽层,在深部岩石属性探测与储层预测中具有独特的穿透能力。近年来该技术在深层油气勘探方面取得突破:研发了新一代发射系统;创新地提出双侧激发多线同步采集技术和四方位全覆盖同步激发采集技术,显著改善了照明均匀性,降低了阴影效应与各向异性影响。在处理技术方面,创新地提出了一种分步递进反演策略,这种方法核心在于构建多源数据协同约束与分步递进反演策略,通过渐进式优化,实现反演精度的层级提升。理论正反演模拟验证了方法的合理性与有效性,并在中国西部塔里木盆地8000 m超深井储层预测及东部深层火成岩储层评价中取得了显著的应用成效。
基金supported by the National Science and Technology Major Project(No.2016ZX05018006)the National Key Research Development Program(No.2016YFC0601104)the National Natural Science Foundation of China(No.41472136)
文摘The coal-bearing strata of the deep Upper Paleozoic in the GS Sag have high hydrocarbon potential. Because of the absence of seismic data, we use electromagnetic （MT） and gravity data jointly to delineate the distribution of deep targets based on well logging and geological data. First, a preliminary geological model is established by using three-dimensional （3D） MT inversion results. Second, using the formation density and gravity anomalies, the preliminary geological model is modified by interactive inversion of the gravity data. Then, we conduct MT-constrained inversion based on the modified model to obtain an optimal geological model until the deviations at all stations are minimized. Finally, the geological model and a seismic profile in the middle of the sag is analysed. We determine that the deep reflections of the seismic profile correspond to the Upper Paleozoic that reaches thickness up to 800 m. The processing of field data suggests that the joint MT-gravity modeling and constrained inversion can reduce the multiple solutions for single geophysical data and thus improve the recognition of deep formations. The MT-constrained inversion is consistent with the geological features in the seismic section. This suggests that the joint MT and gravity modeling and constrained inversion can be used to delineate deep targets in similar basins.
