安太堡矿露井联采边坡稳定性研究及其边界参数优化

安太堡露天矿为我国最早合资开发的大型露天煤矿,近年来,该矿实施露井联采模式,给安太堡矿东南帮和南帮的边坡稳定性的保证和露井边界的确定带来了困难,严重影响安太堡矿的正常生产。通过综合研究,指出露井联采模式下的边坡主要存在两种破坏模式,其井工开采开切眼的位置是确定边坡稳定的关键因素。首次提出了以两种开采方法之间的垂直安全高度为判断依据,并以此依据确定了露井边界参数,为保证安太堡矿南帮的安全开采提供了依据。     

粒子滤波非线性AVO反演方法

提出一种新的AVO非线性反演方法,即利用粒子滤波器来求解AVO非线性贝叶斯反演问题,利用随机带权样本逼近后验概率.论文首先论述了粒子滤波器的基本原理,包括状态转移模型与观测模型,权值预测与更新,重要性密度采样等粒子滤波器应用中的关键技术.然后建立了适合于AVO反演的粒子滤波器状态转移模型和观测模型.最后,利用该方法分别对模型数据和实际资料进行了反演计算.反演结果表明,该方法具有较好的稳定性,在AVO反演中具有的一定的应用潜力.同时对地球物理反演的其他问题求解也提供了一条新的途径.     

基于贝叶斯理论的AVO三参数波形反演

在实际的AVO反演问题中,叠前数据体中的噪声或其他因素严重影响了AVO反演问题的适定性,而采用先验地质信息作为AVO反演问题的约束条件是解决AVO反演问题不适定的一种可行方法. 文中的似然函数采用了[WTBX]ι[WTBX]p范数的解,并用Cauchy分布表示先验模型参数的分布. 以此为基础,在反演中建立了测井数据的参数协方差矩阵对反演过程进行约束,并采用了共轭梯度算法实现多参数非线性的反演过程. 同时,为了提高反演精度,避免动校正拉伸及依赖于炮检距的调谐效应对参数估计的影响,反演采用动校前地震数据进行参数估计. 从应用效果分析来看,即使叠前道集的信噪比不高,反演的结果也能较好地与实际情况相匹配,为识别储层流体性质提供了新的手段.     

不同方法计算的气温平均值差异分析

利用1961～2002年699个国家基本（基准）站的时值气温观测资料,分析了我国不同方法计算的气温平均值的差异。结果表明：平均气温计算值由于受4次观测、3次观测不同的计算方法的影响,造成4次、3次观测记录平均值产生一定差异。其差异在空间分布中具有明显的特征,西部、北部地区3次平均值偏高;东南部地区3次平均值偏低。中西部地区4次、3次气温平均值的差异具有扩大的趋势,是由于最低气温的升高引起的。因此,在使用气温平均值时,要充分重视平均气温值的计算方法,避免误差。     

云母分子式计算方案的选择

本文借助主成分分析证明了花岗岩类中黑云母的Fe~(3+)、Fe~(2+)和(OH+F)主要的数量关系不表现为氧羟铁云母置换,还讨论了水不足和水过剩对云母分子式计算结果的影响,进而提出了当处理一批未受明显脱羟基氧化的云母,尤其是当其中包括明显水过剩云母时,宜优先采用O=22计算分子式方案等建议。     

黑云母成分-f_(H_2O)方程的推导及其在福州和鼓山花岗岩体的应用

利用Wones等(1965;1972)提出的黑云母成分和fH_2O、fO_2方程式对福州和鼓山花岗岩体的成岩温度和压力反复进行估算,发现其结果与地质现象不符。因此才考虑对其方程的Δμ°/2.303RT的数值重新进行热力学推导并应用于上述两岩体的估算,计算结果与地质现象较为吻合。     

承压水体上煤柱留设的理论与实践

华盖山煤矿主要可采Ⅱ号煤层下存在强岩溶含水层,为划定安全开采范围,综合应用国内相关科研成果,成功地留设防水煤柱,划定可采区域。经矿井建设检验,满足安全开采需要。     

Parameter evaluation and optimization for multi-resolution segmentation in object-based shadow detection using very high resolution imagery

Object-based shadow detection in urban areas is an important topic in very high resolution remote sensing image processing. Multi-resolution segmentation (MRS) is an effective segmentation method, and is used for object-based shadow detection. However, several input parameters within MRS may result in unstable performance for final shadow detection; thus, the evaluation and optimization for the parameters upon the final shadow detection accuracy cannot be overlooked. In this paper, the three parameters in MRS (scale s, weight of colour w_color and weight of compactness w_compact) upon the final result of a recently proposed method, object-based shadow detection with Dempster–Shafer theory, were evaluated and optimized by sensitivity analysis and Taguchi’s method with three experimental data. Experiments show that scale s is the most sensitive parameter among the three parameters within MRS. More importantly, according to the Taguchi’s method theory, there is a very significant interaction effect between s and w_color, which cannot be overlooked. The shadow detection accuracy yielded by the optimum parameter combination in consideration of the interaction effect is higher than that only optimized by covering the main effect of single parameter in most cases.     

Parameter identification of nonlinear roll motion equation for floating structures in irregular waves

In order to predict the roll motion of a floating structure in irregular waves accurately, it is crucial to estimate the unknown damping coefficients and restoring moment coefficients in the nonlinear roll motion equation. In this paper, a parameter identification method based on a combination of random decrement technique and support vector regression (SVR) is proposed to identify the coefficients in the roll motion equation of a floating structure by using the measured roll response in irregular waves. Case studies based on the simulation data and model test data respectively are designed to validate the applicability and validity of the identification method. Firstly, the roll motion of a vessel is simulated by using the known coefficients from literature, and the simulated data are used to identify the coefficients in the roll motion equation. The identified coefficients are compared with the known values to validate the applicability of the identification method. Then the roll motion is predicted by using the identified coefficients. The prediction results are compared with the simulated data, and good agreement is achieved. Secondly, the model test data of a FPSO are used to identify the coefficients in the roll motion equation. Then the random decrement signature of the roll motion is predicted by using the identified coefficients and compared with that obtained from the model test data, and satisfactory agreement is achieved. From this study, it is shown that the identification method can be effectively applied to identify the coefficients in the nonlinear roll motion equation in irregular waves.