The advantage of high-resolution sequence stratigraphy, which takes base-levels as reference, is that it can be applied to continental depositional basins controlled by multiple factors and can effectively improve the...The advantage of high-resolution sequence stratigraphy, which takes base-levels as reference, is that it can be applied to continental depositional basins controlled by multiple factors and can effectively improve the accuracy and resolution of sequential stratigraphic analysis. Moreover, the principles of base-level cycles are also suitable for analyzing sequential stratigraphy in continental coal-bearing basins because of their accuracy in forecasting distribution of coal measures. By taking the Dongsheng coalfield in the Ordos basin as an example, the extensive application of base-level cycles in exploration and exploitation of coal is analyzed. The result shows that the Yan’an formation in the Dongsheng area is a long-term base-level cycle which is bordered by nonconformities and made up of five mid-term cycles and 13 short-term cycles. The long-term cycle and the mid-term cycles are obvious in comparison with a transverse profile. The episodic coal accumulation in the Mesozoic Ordos basin means that the deposition of primary matter (peat bogs) of coalification is discontinuous, periodical and cyclical in the evolution of the basin. The episodic accumulation of coal measures in the Yan’an stage is controlled by ascending-descending changes of a long-term cycle and middle-term cycles. Coal measures formed during the early and late periods of the long-term cycle are characterized by multiple layers, big cumulative thickness and poor continuity. Coal measures formed in the mid-term of the long cycle are dominated by good continuity, fewer layers and a small additive thickness, which is favorable for the accumulation of thick and continuous coal measures in the transition stage of mid term base-level cycles.展开更多
The identification of sequence boundaries is the key point for sequence stratigraphic classification. Both the higher-order sequences and the units within the sequences are bounded with the key sediments or isochronou...The identification of sequence boundaries is the key point for sequence stratigraphic classification. Both the higher-order sequences and the units within the sequences are bounded with the key sediments or isochronous surfaces. Eight sequences can be divided in the whole Permo-Carboniferous strata （the Shiqianfeng Formation is not included）, which is from the Benxi Formation, Taiyuan Formation, Shanxi Formation, Xiashihezi Formation, Wanshan Section, and Kuishan Section to the Xiaofuhe Section. Also, different system tracts （Iowstand system tract, transgression system tract and highstand system tract） and some parasequences can be recognized in each sequence. Parasequence analysis was on the basis of the division of the base-level cycle. The base-level cycle was mainly identified according to the change of the water area, which was reflected by the depositional sequence. The physical characteristic of the strata was reflected by the well log. It was supplied by the test of the minerals and rocks and the analysis of the micro-element in the lab. The paleogeographic characteristic of the Iowstand system tract in the sequence Ⅵ is that the east-north part takes the river system as its feature; the south part is the lake system, the river channel spreads from north to south, and the area of the flooding plain is great. The paleogeographic characteristic of the water-transgressive system tract is that the range of the lake in the south extended distinctively, the range of the river channel in the east reduced. The coastal shallow lake deposit is the main characteristic in the water-transgressive system tract. The paleogeographic characteristic of the highstand system tract is similar to the one of the Iowstand system tract.展开更多
Base-level is a kind of surface which controls sedimentation and erosion. So, it can be concluded that it is base-level change that controls the formation and internal structure of a sequence. A single cycle of base-l...Base-level is a kind of surface which controls sedimentation and erosion. So, it can be concluded that it is base-level change that controls the formation and internal structure of a sequence. A single cycle of base-level change can generate four sets of different stacking patterns. They are two sets of aggradation, one progradation and one retrogradation, which affects the features of the internal structure of a sequence. Lishu fault subsidence of Songliao basin is a typical half-graben lacustrine basin. Comprehensive base-level change analysis indicates that six base-level cycles and their related six sequences can be recognized between T 4 and T 5 seismic reflection surface. The contemporaneous fault is the main controlling factor of the fault lacustrine basin. There are obvious differences exist in the composition of sedimentary systems and all systems tracts between its steep slope (the side that basin control fault existed) and flat slope. Except highstand systems tract is composed of fan delta-lacustrine system, lowstand systems tract, transgressive systems tract and regressive systems tract are all made up of fan delta-underwater fan-lacustrine sedimentary systems in the side of steep slope.展开更多
The authors discussed the method of wavelet neural network （WNN） for correlation of base-level cycle. A new vectored method of well log data was proposed. Through the training with the known data set, the WNN can re...The authors discussed the method of wavelet neural network （WNN） for correlation of base-level cycle. A new vectored method of well log data was proposed. Through the training with the known data set, the WNN can remenber the cycle pattern characteristic of the well log curves. By the trained WNN to identify the cycle pattern in the vectored log data, the ocrrdation process among the well cycles was completed. The application indicates that it is highly efficient and reliable in base-level cycle correlation.展开更多
针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为...针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为降低专家的主观偏差,应用基于层级的模糊权重评估(Fuzzy level based weight assessment,FLBWA)法来计算各评价指标权重;继而结合改进的Borda-全乘比例多目标优化(Borda-multi-objective optimization on the basis of ratio analysis plus full multiplicative form,Borda-MULTIMOORA)法计算开发适宜性指数,从而能够更加准确、高效地得到评价结果;之后,基于灰狼优化算法的反向传播(Grey wolf optimizer with back propagation,GWO-BP)神经网络构建并训练智能模型,将适宜性分析转化为自动化、高效化和智能化的过程;最后,以山东省风浪联合开发区划为例验证该模型的可行性和合理性。根据实例验证,该模型可以实现风浪联合开发区划的智能化,为相关领域的研究和政府规划提供参考。展开更多
近年来,洪涝灾害频发,给社会带来严重影响,而洪涝灾害期间往往伴随着显著的河流水位变化和大气可降水量(precipitable water vapor,PWV)变化.本文以2024年发生在巴西阿雷格里港的洪涝灾害为例,选取GNSS站观测数据,分别开展了洪涝水位和...近年来,洪涝灾害频发,给社会带来严重影响,而洪涝灾害期间往往伴随着显著的河流水位变化和大气可降水量(precipitable water vapor,PWV)变化.本文以2024年发生在巴西阿雷格里港的洪涝灾害为例,选取GNSS站观测数据,分别开展了洪涝水位和PWV监测研究.结果表明,暴雨前SPH4站水位反演与水文站数据的相关系数为0.993,均方根误差(root mean square error,RMSE)为0.02 m;暴雨期间,河流两岸的SPH4站与IDP1站的水位反演结果相关系数达到0.997,RMSE为0.06 m,降雨峰值与水位峰值存在2~5 d不等的时间差.GNSS站反演的PWV与探空站实测PWV的相关系数为0.992,RMSE仅为1.9 mm,PWV值达到峰值的5 h内出现降雨最大值.实验证明,岸基GNSS设备能够准确反演出洪涝水位变化和PWV变化,在洪涝灾害的预防和监测方面具有广阔的应用前景.展开更多
基金Project2003CB214603 supported by Development Plan of the State Key Fundamental Research, China
文摘The advantage of high-resolution sequence stratigraphy, which takes base-levels as reference, is that it can be applied to continental depositional basins controlled by multiple factors and can effectively improve the accuracy and resolution of sequential stratigraphic analysis. Moreover, the principles of base-level cycles are also suitable for analyzing sequential stratigraphy in continental coal-bearing basins because of their accuracy in forecasting distribution of coal measures. By taking the Dongsheng coalfield in the Ordos basin as an example, the extensive application of base-level cycles in exploration and exploitation of coal is analyzed. The result shows that the Yan’an formation in the Dongsheng area is a long-term base-level cycle which is bordered by nonconformities and made up of five mid-term cycles and 13 short-term cycles. The long-term cycle and the mid-term cycles are obvious in comparison with a transverse profile. The episodic coal accumulation in the Mesozoic Ordos basin means that the deposition of primary matter (peat bogs) of coalification is discontinuous, periodical and cyclical in the evolution of the basin. The episodic accumulation of coal measures in the Yan’an stage is controlled by ascending-descending changes of a long-term cycle and middle-term cycles. Coal measures formed during the early and late periods of the long-term cycle are characterized by multiple layers, big cumulative thickness and poor continuity. Coal measures formed in the mid-term of the long cycle are dominated by good continuity, fewer layers and a small additive thickness, which is favorable for the accumulation of thick and continuous coal measures in the transition stage of mid term base-level cycles.
基金Supported by the Nation's National Science Foundation of China(40742010)
文摘The identification of sequence boundaries is the key point for sequence stratigraphic classification. Both the higher-order sequences and the units within the sequences are bounded with the key sediments or isochronous surfaces. Eight sequences can be divided in the whole Permo-Carboniferous strata （the Shiqianfeng Formation is not included）, which is from the Benxi Formation, Taiyuan Formation, Shanxi Formation, Xiashihezi Formation, Wanshan Section, and Kuishan Section to the Xiaofuhe Section. Also, different system tracts （Iowstand system tract, transgression system tract and highstand system tract） and some parasequences can be recognized in each sequence. Parasequence analysis was on the basis of the division of the base-level cycle. The base-level cycle was mainly identified according to the change of the water area, which was reflected by the depositional sequence. The physical characteristic of the strata was reflected by the well log. It was supplied by the test of the minerals and rocks and the analysis of the micro-element in the lab. The paleogeographic characteristic of the Iowstand system tract in the sequence Ⅵ is that the east-north part takes the river system as its feature; the south part is the lake system, the river channel spreads from north to south, and the area of the flooding plain is great. The paleogeographic characteristic of the water-transgressive system tract is that the range of the lake in the south extended distinctively, the range of the river channel in the east reduced. The coastal shallow lake deposit is the main characteristic in the water-transgressive system tract. The paleogeographic characteristic of the highstand system tract is similar to the one of the Iowstand system tract.
文摘Base-level is a kind of surface which controls sedimentation and erosion. So, it can be concluded that it is base-level change that controls the formation and internal structure of a sequence. A single cycle of base-level change can generate four sets of different stacking patterns. They are two sets of aggradation, one progradation and one retrogradation, which affects the features of the internal structure of a sequence. Lishu fault subsidence of Songliao basin is a typical half-graben lacustrine basin. Comprehensive base-level change analysis indicates that six base-level cycles and their related six sequences can be recognized between T 4 and T 5 seismic reflection surface. The contemporaneous fault is the main controlling factor of the fault lacustrine basin. There are obvious differences exist in the composition of sedimentary systems and all systems tracts between its steep slope (the side that basin control fault existed) and flat slope. Except highstand systems tract is composed of fan delta-lacustrine system, lowstand systems tract, transgressive systems tract and regressive systems tract are all made up of fan delta-underwater fan-lacustrine sedimentary systems in the side of steep slope.
基金Supported by Project of Dagang Branch of Petroleum Group Company Ltd,CNPC No TJDG-JZHT-2005-JSDW-0000-00339
文摘The authors discussed the method of wavelet neural network （WNN） for correlation of base-level cycle. A new vectored method of well log data was proposed. Through the training with the known data set, the WNN can remenber the cycle pattern characteristic of the well log curves. By the trained WNN to identify the cycle pattern in the vectored log data, the ocrrdation process among the well cycles was completed. The application indicates that it is highly efficient and reliable in base-level cycle correlation.
文摘针对目前海洋能区划研究中存在的计算复杂、耗时长和成本高等问题,本研究基于改进的多准则决策(Multiple criteria decision making,MCDM)方法和人工神经网络(Artificial neural network,ANN),提出了一种风浪联合开发区划智能模型。为降低专家的主观偏差,应用基于层级的模糊权重评估(Fuzzy level based weight assessment,FLBWA)法来计算各评价指标权重;继而结合改进的Borda-全乘比例多目标优化(Borda-multi-objective optimization on the basis of ratio analysis plus full multiplicative form,Borda-MULTIMOORA)法计算开发适宜性指数,从而能够更加准确、高效地得到评价结果;之后,基于灰狼优化算法的反向传播(Grey wolf optimizer with back propagation,GWO-BP)神经网络构建并训练智能模型,将适宜性分析转化为自动化、高效化和智能化的过程;最后,以山东省风浪联合开发区划为例验证该模型的可行性和合理性。根据实例验证,该模型可以实现风浪联合开发区划的智能化,为相关领域的研究和政府规划提供参考。
