连续型储集层属性分布预测是油气储集层研究的重要内容。定量化的方法有各种插值技术和基于地质统计学的一些随机模拟技术,不同方法各有其优缺点。对基于GMRF(Gaussian Markov Random Fields)模型的随机模拟方法的原理和算法进行了较为...连续型储集层属性分布预测是油气储集层研究的重要内容。定量化的方法有各种插值技术和基于地质统计学的一些随机模拟技术,不同方法各有其优缺点。对基于GMRF(Gaussian Markov Random Fields)模型的随机模拟方法的原理和算法进行了较为详细的介绍,实际模型的运算过程及结果表明,该方法较为简捷,同时连续型属性作为空间随机变量的两个特征———结构性和随机性也得到了很好的反映。展开更多
It has been testified that the Gauss Markov random field model is most suitable for the characterization of fabric texture among a variety of available models because of its approximately constant character and the no...It has been testified that the Gauss Markov random field model is most suitable for the characterization of fabric texture among a variety of available models because of its approximately constant character and the normality of the gray-level distribution found with typical fabric images. However, the general Gauss-Markov random field(GMRF) method for fabric defect detection is not always ideal in practice since in some cases, the estimated model parameters make the Markov error covariance not positively definite, which may render the method to fail thoroughly. In this paper, the use of the GMRF model for defect detection of fabric is discussed and an approach to this problem is proposed. Some detailed texture may be overlooked in this way, but good detection results can still be expected as far as fabric defect detection is concerned.展开更多
为了解海州湾大泷六线鱼时空分布特征及其影响因素,根据2013—2019年秋季在海州湾开展的底拖网渔业资源调查和环境观测数据,构建了时空物种分布模型(spatio-temporal species distribution models),分析其分布与环境因子的关系,通过残...为了解海州湾大泷六线鱼时空分布特征及其影响因素,根据2013—2019年秋季在海州湾开展的底拖网渔业资源调查和环境观测数据,构建了时空物种分布模型(spatio-temporal species distribution models),分析其分布与环境因子的关系,通过残差分析比较其与广义加性模型的残差独立性和异质性,运用交叉验证检验模型预测性能,最终结合delta方法对其分布进行预测并计算栖息地适宜性指数(habitat suitability index,HSI)和资源分布重心。时空模型的偏差解释率为65.50%,模型分析表明,影响大泷六线鱼资源分布最主要的环境因子为水深(22.11%),其次为底层水温(12.98%),底层盐度(0.09%)的影响较小,水深与其分布存在正向相关性,底层水温与其分布存在负向相关性,底层盐度与其分布存在弱正向线性关系。时空模型的残差独立性和异质性较GAM更强,其交叉验证回归线斜率为0.90±0.38。模型预测结果表明,大泷六线鱼主要分布在34.5°N以北,120.0°E以东的海域,其栖息地适宜性指数的高值区域呈现逐年收缩的趋势,资源分布重心呈现向东北海域转移的趋势,这可能是气候变迁以及捕捞压力共同作用的结果。本研究解析了大泷六线鱼在海州湾的时空分布,对于深入了解大泷六线鱼的分布动态和科学的渔业管理具有重要意义。展开更多
文摘连续型储集层属性分布预测是油气储集层研究的重要内容。定量化的方法有各种插值技术和基于地质统计学的一些随机模拟技术,不同方法各有其优缺点。对基于GMRF(Gaussian Markov Random Fields)模型的随机模拟方法的原理和算法进行了较为详细的介绍,实际模型的运算过程及结果表明,该方法较为简捷,同时连续型属性作为空间随机变量的两个特征———结构性和随机性也得到了很好的反映。
文摘It has been testified that the Gauss Markov random field model is most suitable for the characterization of fabric texture among a variety of available models because of its approximately constant character and the normality of the gray-level distribution found with typical fabric images. However, the general Gauss-Markov random field(GMRF) method for fabric defect detection is not always ideal in practice since in some cases, the estimated model parameters make the Markov error covariance not positively definite, which may render the method to fail thoroughly. In this paper, the use of the GMRF model for defect detection of fabric is discussed and an approach to this problem is proposed. Some detailed texture may be overlooked in this way, but good detection results can still be expected as far as fabric defect detection is concerned.
文摘为了解海州湾大泷六线鱼时空分布特征及其影响因素,根据2013—2019年秋季在海州湾开展的底拖网渔业资源调查和环境观测数据,构建了时空物种分布模型(spatio-temporal species distribution models),分析其分布与环境因子的关系,通过残差分析比较其与广义加性模型的残差独立性和异质性,运用交叉验证检验模型预测性能,最终结合delta方法对其分布进行预测并计算栖息地适宜性指数(habitat suitability index,HSI)和资源分布重心。时空模型的偏差解释率为65.50%,模型分析表明,影响大泷六线鱼资源分布最主要的环境因子为水深(22.11%),其次为底层水温(12.98%),底层盐度(0.09%)的影响较小,水深与其分布存在正向相关性,底层水温与其分布存在负向相关性,底层盐度与其分布存在弱正向线性关系。时空模型的残差独立性和异质性较GAM更强,其交叉验证回归线斜率为0.90±0.38。模型预测结果表明,大泷六线鱼主要分布在34.5°N以北,120.0°E以东的海域,其栖息地适宜性指数的高值区域呈现逐年收缩的趋势,资源分布重心呈现向东北海域转移的趋势,这可能是气候变迁以及捕捞压力共同作用的结果。本研究解析了大泷六线鱼在海州湾的时空分布,对于深入了解大泷六线鱼的分布动态和科学的渔业管理具有重要意义。
