核磁共振谱的岩石孔喉结构分析

岩心核磁共振T2谱和压汞分析数据均在一定程度上反映了岩石的孔喉结构,理论分析表明,这两组数据具有相关性.应用岩心核磁共振T2谱研究岩石孔喉结构,关键是确定T2与Pc的转换系数.但以前的方法在T2与Pc的转化过程中,需要涉及某些岩石特性参数,实用中有一定困难.本次研究,直接利用岩心核磁共振T2谱和压汞分析数据之间的相关性,可以客观地确定T2与Pc之间的转换系数,避免了确定岩石特性参数的困难.应用本方法,对6块岩心的多种核磁共振分析数据进行了对比分析,作出了NMR(nuolearmagneticresonance)T2毛管力曲线和孔喉半径分布,并将这些结果与压汞分析的结果作了对比.研究结果表明,岩心NMRT2谱在实用性和评价精度上均略显有优势;至少是在饱含油的条件下,岩心的NMRT2谱可以用于研究孔喉结构分布,油气的驰豫特性作为影响背景值存在,对于评价结果没有明显的影响;全部6块岩心中,T2与Pc的转换系数位于2500～4000μs·MPa之间.     

Use of a Probabilistic Neural Network to Reduce Costs of Selecting Construction Rock

Rocks used as construction aggregate in temperate climates deteriorate to differing degrees because of repeated freezing and thawing. The magnitude of the deterioration depends on the rock's properties. Aggregate, including crushed carbonate rock, is required to have minimum geotechnical qualities before it can be used in asphalt and concrete. In order to reduce chances of premature and expensive repairs, extensive freeze-thaw tests are conducted on potential construction rocks. These tests typically involve 300 freeze-thaw cycles and can take four to five months to complete. Less time consuming tests that (1) predict durability as well as the extended freeze-thaw test or that (2) reduce the number of rocks subject to the extended test, could save considerable amounts of money. Here we use a probabilistic neural network to try and predict durability as determined by the freeze-thaw test using four rock properties measured on 843 limestone samples from the Kansas Department of Transportation. Modified freeze-thaw tests and less time consuming specific gravity (dry), specific gravity (saturated), and modified absorption tests were conducted on each sample. Durability factors of 95 or more as determined from the extensive freeze-thaw tests are viewed as acceptable—rocks with values below 95 are rejected. If only the modified freeze-thaw test is used to predict which rocks are acceptable, about 45% are misclassified. When 421 randomly selected samples and all four standardized and scaled variables were used to train aprobabilistic neural network, the rate of misclassification of 422 independent validation samples dropped to 28%. The network was trained so that each class (group) and each variable had its own coefficient (sigma). In an attempt to reduce errors further, an additional class was added to the training data to predict durability values greater than 84 and less than 98, resulting in only 11% of the samples misclassified. About 43% of the test data was classed by the neural net into the middle group—these rocks should be subject to full freeze-thaw tests. Thus, use of the probabilistic neural network would meanthat the extended test would only need be applied to 43% of the samples, and 11% of the rocks classed as acceptable would fail early.     

Typing Mineral Deposits Using Their Grades and Tonnages in an Artificial Neural Network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further.Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage).Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag.Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.     

Recent crustal deformation and the earthquake cycle along the Ecuador-Colombia subduction zone

Recent results from Global Positioning System (GPS) measurements show deformation along the coast of Ecuador and Colombia that can be linked to the rupture zone of the earthquake in 1979. A 3D elastic boundary element model is used to simulate crustal deformation observed by GPS campaigns in 1991, 1994, 1996, and 1998. Deformation in Ecuador can be explained best by 50% apparent locking on the subduction interface. Although there have not been any historic large earthquakes (M_w>7) south of the 1906 earthquake rupture zone, 50% apparent elastic locking is necessary to model the deformation observed there. In Colombia, only 30% apparent elastic locking is occurring along the subduction interface in the 1979 earthquake rupture zone (M_w 8.2), and no elastic locking is necessary to explain the crustal deformation observed at two GPS sites north of there. There is no evidence from seismicity or plate geometry that plate coupling on the subduction zone is reduced in Colombia. However, simple viscoelastic models suggest that the apparent reduction in elastic locking can be explained entirely by the response of a viscous upper mantle to the 1979 earthquake. These results suggest that elastic strain accumulation is occurring evenly throughout the study area, but postseismic relaxation masks the true total strain rate.     

Characterization of displacement demand for elastic and inelastic SDOF systems

The results of a research concerning the characterization of elastic and inelastic displacement spectral demand as a function of magnitude, source-to-site distance, and soil type are presented. The displacement spectra were computed for single degree of freedom systems subjected to a large set of strong ground motion records.In the elastic case, design displacement spectra, modeled in a simplified way with a bilinear shape in the period range 0–4 s, are then proposed for the estimation of the displacement demand to structures located on different local soil condition, at different distance from the causative fault, and for different levels of magnitude. In order to evaluate the reliability of the proposed design displacement spectra, probabilistic displacement spectra corresponding to different levels of probability of non-exceedance were also carried out.The inelastic displacement demand to elasto-plastic systems was analyzed through the ratio between inelastic and elastic spectral displacements. Simplified relationships of the inelastic displacement ratio are then proposed as a function of displacement ductility, soil condition and period of vibration. Finally, as a comparison, the inelastic displacement ratios were also estimated considering other constitutive models.     

HF radar-derived origin and destination of surface waters off Bodega Bay, California

As an integral part of the WEST study of the role of wind-driven transport in shelf productivity, HF radar currents are analyzed to determine typical surface flow patterns off Bodega Bay in northern California. Radar-derived surface trajectories and surface velocity divergences are used to determine the proximal origins and destinations of surface waters in the area. Surface trajectory results show a strong bimodality, with water over the entire shelf originating in the north under upwelling conditions and waters over the inner/mid-shelf originating in the south during relaxation conditions. Outer shelf waters have more variable transport patterns during relaxation conditions, with limited equatorward or onshore movements being most typical. The destinations of surface waters starting at the outer shelf are predominantly offshore, with the majority of particles exiting the radar domain west of Pt Reyes along the shelf edge in less than 2 days. Significant proportions of water from the inner/mid-shelf are exported southward and exit the radar domain inshore or within 20 km of the tip of Pt Reyes, creating possibilities for either nearshore retention in the Bodega region or entrainment of water into the Gulf of Farallons. Approximately 15% of all trajectories remained in the radar domain for 6 days, suggesting that a biologically significant percentage of larvae might be retained in the area for time periods approaching typical larval durations. Calculations of surface divergence indicate where vertical flux may be significant. An extensive area of positive divergence is observed off Bodega during upwelling conditions, while weakly convergent flow is observed where upwelling flows approach Pt Reyes. Positive divergence also is observed during relaxation periods when poleward flow separates from the shore just north of Pt Reyes. Estimates of vertical flux in these divergence zones point to a significant contribution of recently upwelled waters to the observed horizontal fluxes at the surface. Determination of the ultimate source and fate of phytoplankton-rich waters requires further analysis of the detailed time dependence of phytoplankton concentration relative to the time dependence of wind-forced currents.     

2022年青海门源MS6.9地震后冷龙岭断裂未来强震的水平位错量评估

2022年1月8日青海门源发生Ｍ_S6.9地震,该地震造成冷龙岭断裂西端错断了兰新铁路大梁隧道,导致铁路长期停运,经济损失巨大。制定隧道修复方案时,需对冷龙岭断裂未来强震的水平位错量进行评估。结合近年来冷龙岭断裂的最新研究进展,同时采用确定性方法和概率断层位错危险性分析方法评估冷龙岭断裂未来强震的水平位错量。考虑不确定因素影响,同时采用3名研究者提供的震级与最大位错量经验关系式进行估算。结果表明,不同经验关系式会对评估结果产生显著影响,其中根据确定性方法得到的冷龙岭断裂未来强震的水平位错量为2.32～4.36 m,均值为3.57 m。概率断层位错危险性分析结果随着超越概率的降低而增大,50年超越概率2%、100年超越概率2%和100年超越概率1%的结果均值分别为1.82 m、3.17 m、4.61 m。相较于确定性方法,概率断层位错危险性分析可提供不同超越概率水平下的位错参数,以供不同抗震设防要求的建筑采用。此外,对于地震活动性强的断裂,可采用低超越概率下的概率断层位错危险性分析结果,该结果可能会大于确定性方法评估结果。     

两次于田M_S7.3地震间应力触发作用及2014年于田地震的发生对周缘断层的影响

基于青藏高原及邻区的三维粘弹性有限元模型,讨论2008年于田MS7.3级地震与2014年于田MS7.3级地震之间的关系,并研究2014年于田MS7.3级地震的发生造成周围断层的库仑破裂应力变化。初步结果表明:1)2008年于田MS7.3级地震在2014年于田MS7.3级地震震中滑动方向上产生的库仑破裂应力变化高于地震触发的阈值0.01 MPa,存在明显的触发作用。在视摩擦系数分别取0.4和0.6时,震源区同震库仑破裂应力变化为0.0167 MPa和0.0170 MPa;而考虑粘弹性松弛作用时产生的库仑应力增加量分别为0.0187 MPa和0.0194 MPa。结合断裂带构造应力年累计速率的结果,2008年于田地震的发生造成2014年于田地震提前21.4~24.9 a;2)在较短的时间尺度内,对于距离相近的两次地震之间,同震产生的应力变化远大于粘弹性松弛效应产生的变化;3)2014年于田MS7.3级地震的发生造成阿尔金断裂中北段、玛尼—玉树断裂中段、东昆仑断裂西段、柴达木北缘断裂东段、西秦岭北缘断裂西段等不同程度的加载效应,地震危险性有所增强。其中阿尔金断裂中段库仑应力增加最为明显,最大达2.8×10–3 MPa;玛尼—玉树断裂中段次之,应力增加量最大达5.6×10–4 MPa;东昆仑断裂西段应力增加量最大达4.75×10–4 MPa。而玛尼—玉树断裂西段库仑破裂应力最大卸载量达3.6×10–3 MPa。     

Muscovite surface structure imaged by fluid contact mode AFM

The surface structure of muscovite was imaged using an atomic force microscope (AFM) in contact mode in water. The following three types of AFM images were observed: (1) those showing clearly the arrangement of hexagonal rings of SiO₄ tetrahedra; (2) those showing a hexagonal array of bright spots separated by a distance of about 5.3 Å; and (3) those changing gradually from image (2) to image (1). Image (1) successfully provides information on the tetrahedral tilt and basal surface corrugation that are particularly characteristic of dioctahedral micas. The mean unit cell dimensions for the muscovite surface measured from Image (1) were slightly longer than those of the bulk structure, due to the rehydration of the tetrahedral sheet and/or surface relaxation. Image (2) was made by varying the scan angles, even on the same surface in which Image (1) was obtained. Image (3) has information on a single plane rather than on two or more planes involving steps, kinks and so on. Therefore, what is depicted in Images (2) and (3) is not the arrangement of interlayer K ions but the basal plane of the tetrahedral sheet. Some structural relaxation of the tetrahedral sheet surface was also observed. Gradual expansion and contraction of hexagonal rings were randomly found on the muscovite surface. The surface relaxation results from a tetrahedral rotation and/or tilting after cleaving, since significant variations of both distances and bond angles between adjacent SiO₄ tetrahedra on the surface were found.