The generalized Pareto distribution model is a kind of hydrocarbon pool size probability statistical method for resource assessment. By introducing the time variable, resource conversion rate and the geological variab...The generalized Pareto distribution model is a kind of hydrocarbon pool size probability statistical method for resource assessment. By introducing the time variable, resource conversion rate and the geological variable, resource density, such model can describe not only different types of basins, but also any exploration samples at different phases of exploration, up to the parent population. It is a dynamic distribution model with profound geological significance and wide applicability. Its basic principle and the process of resource assessment are described in this paper. The petroleum accumulation system is an appropriate assessment unit for such method. The hydrocarbon resource structure of the Huanghua Depression in Bohai Bay Basin was predicted by using this model. The prediction results accord with the knowledge of exploration in the Huanghua Depression, and point out the remaining resources potential and structure of different petroleum accumulation systems, which are of great significance for guiding future exploration in the Huanghua Depression.展开更多
针对以相关谱最大值作为统计量对线性调频/二相编码(LFM/BPSK,Linear Frequency Modulation/Binary Phase Shift Keying)混合调制信号盲处理结果进行可信性检验时,存在概率密度函数复杂,难以得到似然比检验闭合表达式的问题,提出了一种...针对以相关谱最大值作为统计量对线性调频/二相编码(LFM/BPSK,Linear Frequency Modulation/Binary Phase Shift Keying)混合调制信号盲处理结果进行可信性检验时,存在概率密度函数复杂,难以得到似然比检验闭合表达式的问题,提出了一种基于极值分布理论(EVT,Extreme Value Theory)的简化处理算法.利用相关谱最大值的极限分布替代其精确分布,基于纽曼-皮尔逊(NP,Neyman-Pearson)准则得到简化的似然比检验,给出了相应判决式及其判决门限的解析表达式.文中给出了不同假设下相关谱最大值的极限分布形式.计算机仿真结果表明:本算法与已有的恒虚警方法相当,但优于基于分组极值模型及超阈值模型的两种分布拟合检验法,且具有较低的计算复杂度.展开更多
文摘The generalized Pareto distribution model is a kind of hydrocarbon pool size probability statistical method for resource assessment. By introducing the time variable, resource conversion rate and the geological variable, resource density, such model can describe not only different types of basins, but also any exploration samples at different phases of exploration, up to the parent population. It is a dynamic distribution model with profound geological significance and wide applicability. Its basic principle and the process of resource assessment are described in this paper. The petroleum accumulation system is an appropriate assessment unit for such method. The hydrocarbon resource structure of the Huanghua Depression in Bohai Bay Basin was predicted by using this model. The prediction results accord with the knowledge of exploration in the Huanghua Depression, and point out the remaining resources potential and structure of different petroleum accumulation systems, which are of great significance for guiding future exploration in the Huanghua Depression.
文摘现有贝叶斯压缩感知(Bayesian Compressed Sensing,BCS)-逆合成孔径雷达(Inverse Synthetic Aperture Radar,ISAR)成像算法中先验分布模型不能很好地满足可压缩性,导致成像精度随脉冲数目的减小、高斯噪声的增强而急剧下降。为此,提出了一种基于广义Pareto分布改进BCS成像方法(Improving BCS imaging based on GPD,IGPCS)。该方法主要在BCS框架下利用广义Pareto先验分布替代传统的广义Gaussian先验分布,以增强模拟信号的稀疏先验和可压缩性。进一步地,为了克服后验概率模型计算困难等问题,采用最大后验(Maximum A Posteriori,MAP)方法对超参数进行估计。通过对Mig-25小型飞机的ISAR模拟实验表明,与传统方法相比,IGPCS方法能够获取极高的成像精度,并且对低脉冲数、强高斯噪声环境具有较强的鲁棒性。
文摘针对以相关谱最大值作为统计量对线性调频/二相编码(LFM/BPSK,Linear Frequency Modulation/Binary Phase Shift Keying)混合调制信号盲处理结果进行可信性检验时,存在概率密度函数复杂,难以得到似然比检验闭合表达式的问题,提出了一种基于极值分布理论(EVT,Extreme Value Theory)的简化处理算法.利用相关谱最大值的极限分布替代其精确分布,基于纽曼-皮尔逊(NP,Neyman-Pearson)准则得到简化的似然比检验,给出了相应判决式及其判决门限的解析表达式.文中给出了不同假设下相关谱最大值的极限分布形式.计算机仿真结果表明:本算法与已有的恒虚警方法相当,但优于基于分组极值模型及超阈值模型的两种分布拟合检验法,且具有较低的计算复杂度.
