Determining Q of near-surface materials from Rayleigh waves

High-frequency (≥2 Hz) Rayleigh wave phase velocities can be inverted to shear (S)-wave velocities for a layered earth model up to 30 m below the ground surface in many settings. Given S-wave velocity (V_S), compressional (P)-wave velocity (V_P), and Rayleigh wave phase velocities, it is feasible to solve for P-wave quality factor Q_P and S-wave quality factor Q_S in a layered earth model by inverting Rayleigh wave attenuation coefficients. Model results demonstrate the plausibility of inverting Q_S from Rayleigh wave attenuation coefficients. Contributions to the Rayleigh wave attenuation coefficients from Q_P cannot be ignored when Vs/V_P reaches 0.45, which is not uncommon in near-surface settings. It is possible to invert Q_P from Rayleigh wave attenuation coefficients in some geological setting, a concept that differs from the common perception that Rayleigh wave attenuation coefficients are always far less sensitive to Q_P than to Q_S. Sixty-channel surface wave data were acquired in an Arizona desert. For a 10-layer model with a thickness of over 20 m, the data were first inverted to obtain S-wave velocities by the multichannel analysis of surface waves (MASW) method and then quality factors were determined by inverting attenuation coefficients.     

不同损失条件下的泥石流预报模型

泥石流预报是泥石流减灾的重要手段之一，然而泥石流形成的复杂性使泥石流预报准确度低，误报和漏报率较高。泥石流误报和漏报都会造成损失，但二者造成的损失有很大的差别。为了减少泥石流误报或漏报造成的损失，应当考虑两种错报造成损失的不同。根据使总平均损失达到最小的原则，建立了不同损失条件下的泥石流预报模型，并将该模型应用到云南东川蒋家沟。     

Sensitivity Analysis of a Feedforward Neural Network for Considering Genetic Mechanisms of Kuroko Deposits

Exploration for volcanogenic massive sulfide deposits of the kuroko-type is underway in many places. Clarifying the spatial patterns of the metals in kuroko deposits will be useful for understanding their genetic mechanisms and for future exploration of such types of deposits. This study represents a spatial distribution analysis on the contents of principal metals of kuroko deposits: Cu, Pb, and Zn, in the Hokuroku district, northern Japan, by a feedforward neural network and 1917 sample data at 143 drillhole sites. The network, which consists of three layers, was trained by the principle of SLANS in which the numbers of neurons in the middle layer and training data are changed to improve estimation accuracy. Using the weight coefficients connecting adjacent neurons, sensitivity analysis of the neural network was carried out to identify factors influencing spatial distributions of the three metals. The coordinates depth (z) direction, Bouguer gravity, and specific lithology such as dacite were determined to be influencing factors. The high frequency of the z coordinate signifies that the metal contents differ to a large extent by depth. The sensitivity vector was defined using sensitivity coefficients for x, y, and z coordinates of an estimation point. We determined that the directions of large vectors were different inside and outside of the Hanawa-Ohdate area. This characteristic is considered to originate from the differences in the permeability of fractures that became the paths for rising ore solutions, and the depths that the solutions mixed with sea water.     

Quantitative classification and analysis on plant communities in the middle reaches of the Tarim River

Plant communities were sampled in the lower reaches of the Tarim River, Xinjiang. The results showed that there are 23 species belonging to 21 genera in 11 families, most of which have low occurrence frequency in quadrats. The most common species is Tamarix ramosissima, which occurred in 17 sites accounting for 89.47% of the total 19 sites. Quantitative classification (TWINSPAN) and ordination (CCA) methods were used to study the distribution patterns of 23 plant species in 19 sites in this valley. TWINSPAN results showed that the plant communities in the middle reaches of the Tarim River could be divided into 3 groups and the sampling sites could be divided into 7 types in 3 groups. CCA results were consistent with TWINSPAN results, and showed species distribution patterns correlated with major environmental variables of groundwater level and soil moisture.     

桂西岩溶堆积型铝土矿床成矿作用及控矿因素

桂西岩溶堆积型铝土矿赋存于岩溶洼地中的红土层中，具有矿床规模大、矿石质量优的特点。成矿物质来源于上二叠统底部的古风化壳型铝土矿层，成矿时代为早更新世，矿床成因与岩溶作用、红土化作用有关。成矿受矿源层、地层岩性、气候、构造、地貌等因素控制。     

锦江水库坝址③号断裂构造破碎带地质特征及其对堤坝安全性的影响

通过野外地质调查和地球化学探测成果，结合区域地质发展史，论述锦江水库③号断裂构造破碎带的地质特征及其对建筑物的影响。     

西藏冈底斯东段成矿系列区域地球化学预测

西藏冈底斯乐段优势矿床成矿系列预测是当前需要解决的重要问题。文中研究了成矿系列矿源场特征，以及地球化学靶区与矿床成矿系列的联系，揭示了矿化规模的地球化学控制因素，计算了因素耦合系数。预测冈底斯构造带是4种类型矿床成矿系列的密集区。     

镇安场变形体特征及稳定性评价

镇安场变形体位于长江左岸的重庆市涪陵区镇安场，是我国地质灾害多发地之一，主要表现为崩塌、滑坡、泥石流等地质灾害。该变形体变形的主要影响因素除地形地貌、地层岩性、物质结构外，还有瀑雨、洪水、地震、植被破坏等外在因素。通过野外勘查，运用探槽、浅井、钻探等工程控制，已查明该变形体已发生过局部变形，尚未形成大范围的变形和滑移，处于潜在滑移变形阶段。在三峡库区水位上升后，特别是在水库水位降低和地震作用下，变形体可能失稳而向下滑动。通过对变形体的稳定性的评价，认为该区沿库岸应采用以支挡工程为主、排水为辅的防治方案。     

Z油田低阻油层影响因素分析

通过对Y油田和Z油田电阻率影响因素对电阻率的影响对比，分析了Z油田低阻的原因及各影响因素影响程度。     

盐城市地下水水质控制因素分析

本文采用主因素分析的方法,结合盐城市近几年地下水水质监测资料,对盐城市淡水区和微咸水区地下水水质各监测组分按不同的分类标准分成全体组和离子组进行分析,确定地下水水质控制因素,并将计算结果与盐城市水文地质条件相结合,分析了计算得出的研究区地下水水质控制因素的形成原因及特点。最后根据分析结果制定一套适用于盐城市第Ⅲ承压含水层水质监测方案。为提高治理水环境的综合效益提供了科学依据。