Sensitivity and inversion of borehole flexural dispersions for formation parameters

Propagation characteristics of borehole flexural waves are functions of five borehole, fluid and formation parameters. Uncertainties in any of these model parameters may introduce errors in the estimate of formation shear-wave speed. Other sources of error in the estimate may be caused by deviations from the assumed circular borehole cross-section or heterogeneity in the material properties of formation in the vicinity of a borehole from the usually assumed homogeneous properties. The influence of uncertainties in model parameters on borehole flexural dispersion has been calculated from a general perturbation model based on Hamilton's principle. A sensitivity analysis of the flexural dispersion to small variations in the model parameters shows that the formation shear speed has by far the most dominant influence in a slow formation. In contrast, the flexural dispersion in a fast formation is significantly influenced by three of the five model parameters: the formation shear speed, the borehole fluid compressional speed and the borehole diameter. The frequency dependence of these sensitivity functions indicates that the inversion of flexural dispersion for formation shear speed is optimal in the range 2–4 kHz for a borehole of diameter 25.4 cm. The range of validity of the perturbation model has been estimated by comparing results of concentric annuli of different thicknesses, and shear-wave speeds different from that of the formation with those from exact numerical solutions from a modal search program. Generally, the perturbation results for altered annuli of thicknesses up to 15 cm are accurate to within 1 per cent for a shear-wave speed 10 per cent lower than that of the formation. This difference between the perturbation and exact results increases to approximately 1 to 3 per cent for a shear-wave speed 20 per cent lower than that of the formation.     

Inference of past climate from borehole temperature data using Bayesian Reversible Jump Markov chain Monte Carlo

Estimates of past climate derived from borehole temperatures are assuming a greater importance in context of the millennial temperature variation debate. However, recovery of these signals is usually performed with regularization which can potentially lead to underestimation of past variation when noise is present. In this work Bayesian inference is applied to this problem with no explicit regularization. To achieve this Reversible Jump Markov chain Monte Carlo is employed, and this allows models of varying complexity (i.e. variable dimensions) to be sampled so that it is possible to infer the level of ground surface temperature (GST) history resolution appropriate to the data. Using synthetic examples, we show that the inference of the GST signal back to more than 500 yr is robust given boreholes of 500 m depth and moderate noise levels and discuss the associated uncertainties. We compare the prior information we have used with the inferred posterior distribution to show which parts of the GST reconstructions are independent of this prior information. We demonstrate the application of the method to real data using five boreholes from southern England. These are modelled both individually and jointly, and appear to indicate a spatial trend of warming over 500 yr across the south of the country.     

Diurnal surface temperature difference index derived from ground-based meteorological measurements for assessment of moisture availability

Droughts have become widespread in the Northern Hemisphere, including in China, where they have affected farmland resources on the Loess Plateau. Given this background, we proposed a new index, the Normalized Day-Night Surface Temperature Index (NTDI), to estimate moisture availability (m_a), defined as the ratio of actual to reference evapotranspiration. The NTDI is defined as the ratio of the difference between the maximum daytime surface temperature and the minimum nighttime surface temperature, to the difference between the maximum and minimum surface temperatures estimated from meteorological data by applying energy balance equations.To calculate the index, we used data of 20 clear-sky meteorological observations made during the 2005 growing season at a natural grassland station in the Liudaogou River basin on the Loess Plateau. The NTDI showed a significant inverse exponential correlation with m_a (R² = 0.97, p < 0.001), whereas the numerator of the index (the maximum daytime surface temperature minus the minimum nighttime surface temperature) was only weakly correlated with m_a (R² = 0.24, p = 0.03). This result indicates that normalization relative to the index denominator (maximum surface temperature − minimum surface temperature) dramatically improved the accuracy of the estimate.     

基于反射率和亮度温度的锡林郭勒积雪深度估算

积雪是我国西北干旱半干旱区重要的水资源,也是影响全球气候变化的重要因子之一。目前光学影像反射率和雷达亮温数据是积雪遥感领域的主要数据,本文首次结合两类遥感数据估算积雪深度,并比较偏最小二乘法和机器学习算法(人工神经网络、支持向量机和随机森林算法)在积雪深度估算方面的表现。以锡林郭勒盟2012—2015年积雪深度数据为例,基于反射率和亮度温度相结合的积雪深度估算精度优于单个数据源,且随机森林算法表现最好,均方根误差为2.93cm,满足实际应用的需求。研究结果对我国西北地区水资源分布、生态环境评估等研究具有重要意义。     

Shear-wave anisotropy and the stress field from borehole recordings at 2.5 km depth at Cajon Pass

53 local earthquakes recorded at 2.5 km depth in the Cajon Pass scientific borehole are analysed for shear-wave splitting. The time delays between the split shear waves can be positively identified for 32 of the events. Modelling these observations of polarizations and time delays using genetic algorithms suggests that the anisotropic structure near Cajon Pass has orthorhombic symmetry. The polarization of the shear waves and the inferred strike of the stress-aligned fluid-filled intergranular microcracks and pores suggests that the maximum horizontal compressional stress direction is approximately N13°W. This is consistent with previous results from earthquake source mechanisms and the right-lateral strike-slip motion on the nearby San Andreas Fault, but not with stresses measured within the uppermost 3 km of the borehole. This study suggests that the San Andreas Fault is driven by deeper tectonic stresses and the present understanding of a weak and frictionless San Andreas Fault may need to be modified. The active secondary faulting and folding close to the fault are probably driven by the relatively shallow stress as measured in the 3.5 km deep borehole.