青西油田碳酸盐岩裂缝性储层地球物理预测技术的应用

白云岩成岩收缩晶间孔、洞、缝与构造网状缝相互沟通可以组成良好的油气储层，但是这种复杂裂缝—孔隙型储层分布随机性强、发育程度和差异性大，储层预测难度大。本文以中国西部酒泉盆地青西油田下白垩统下沟组湖相白云岩裂缝—孔隙型储层为例，提出地球物理综合预测碳酸盐岩裂缝的方法。本文描述了综合地球物理方法预测碳酸盐岩裂缝储层的实施和应用效果。     

关于数字化记录中前兆信号的分析

介绍了如何用MATLAB工具软件—小波分析的基本理论对数字信号进行数字滤波,着重分析和研究了呼和浩特地震台形变观测资料出现各种信号,提出了小波分析理论对台站实际工作的重要性。     

Wavelet analysis and interpretation of gravity data in Sichuan-Yunnan region, China

Introduction Sichuan-Yunnan region, located in the east margin of Qinghai-Xizang (Tibetean) Plateau, is a transitional zone between the rapidly upheaving Tibetean Plateau and relatively steady Yangtze Platform. Under the pressure exerted by the northward movement of Indian Plate, Sichuan-Yunnan region has been undergone strong deformation and regmagenesis, becoming one of the regions with the most intensive seismicity in the world. The research on the tectonics and seismicity there is alw…     

Magnetotelluric data inversion with seismic data constraint

Introduction The research on the structure and physical property of ancient hidden hill, igneous rocks and basement is relatively difficult by using seismic data only. If we combine seismic data, magneto-telluric (MT) data and geophysical data together, better results can be obtained for the above problem. A number of geophysicists at home and abroad, such as CHEN and WANG (1990), Siri-punvarapor and Egbert (2000) have tried many methods to solve the problem by the inversion of seismic da…     

Numerical simulation for 1975 Haicheng and 1999 Xiuyan earthquake processes by DDA+FEM

Introduction The Xiuyan earthquake(MS=5.4)on Nov.29,1999,occurred between Hushan town and Pi-anling town at the southeast end of the aftershocks of Haicheng earthquake(MS=7.3).These two earthquakes′sequences are highly similar in the way that the foreshocks are very frequent,focal mechanisms of the main shocks are about the same and fault strikes are approximately in the same direction.It is important to study these earthquakes for further research on seismogenesis to fore-cast earthquake…     

Primary component analysis method and reduction of seismicity parameters

Introduction Data mining (SHAO and YU, 2003) is a new kind of technique developed with database and artificial intelligence in recent years, which processes the data in the database to abstract the im- plied and pre-unknown, but potentially useful information and knowledge from large amounts of incomplete, noisy, blurring and stochastic data. For data mining, data purging is an important link beforehand that includes eliminating noise, making up lost domain, and deleting ineffective data, as…     

Multifield coupling model and its applications for pile foundation in permafrost

In the construction of Qinghai-Tibet railway,to avoid diseases caused by frost heave and thaw col-lapse of frozen ground,besides the normal bridges over the rivers,a lot of dry bridge structures have been built to replace subgrade in the regions of high tem-perature and high ice content frozen soil.So,the problems on forming mechanism of bearing capacity of pile foundation in cold regions already become one of hot spot problems in frozen soil engineering.Freezing force and frost heave force ar…     

Converted-wave seismology in anisotropic media revisited,Part I: Basic theory

We have developed new basic theories for calculating the conversion point and the travel time of the P-SV converted wave (C-wave) in anisotropic, inhomogeneous media. This enables the use of conventional procedures such as semblance analysis, Dix-type model building and Kirchhoff summation, to implement anisotropic processing, and makes anisotropic processing affordable. Here we present these new developments in two parts: basic theory and application to velocity analysis and parameter estimation. This part deals with the basic theory, including both conversion-point calculation and moveout analysis. Existing equations for calculating the PS-wave (C-wave) conversion point in layered media with vertical transverse isotropy (VTI) are strictly limited to offsets about half the reflector depth (an offset-depth ratio, xlz, of 0.5), and those for calculating the C-wave traveltimes are limited to offsets equal to the reflector depth (x/z=l.0). In contrast, the new equations for calculating the conversion-point extend into offsets about three-times the reflector depth (x/z=3.0), those for calculating the C-wave traveltimes extend into offsets twice the reflector depth (x/z=2.0). With the improved accuracy, the equations can help in C-wave data processing and parameter estimation in anisotropic, inhomogeneous media. This work is funded by the Edinburgh Anisotropy Project (EAP) of the British Geological Survey. First author: Xiangyang Li, Mr. Li is currently a professorial research seismologist (Grade 6) and technical director of the Edinburgh Anisotropy Project in the British Geological Survey. He also holds a honorary professorship in multicomponent seismology at the School of Geosciences, University of Edinburgh. He received his BSc(1982) in Geophysics from Changchun Geological Institute, China, an MSc (1984) in applied geophysics from East China Petroleum Institute (now known as the China University of Petroleum), and a PhD (1992) in seismology from the University of Edinburgh. During 1984–1987, he worked as a lecturer with the East China Petroleum Institute. Since 1991, he has been employed by the British Geological Survey. His research interests include seismic anisotropy and multicomponent seismology.     

Assessing the Comparability of Ammonium,Nitrate and Sulfate Concentrations Measured by Three Air Quality Monitoring Networks

Airborne fine particulate matter across the United States is monitored by different networks, the three prevalent ones presently being the Clean Air Status and Trend Network (CASTNet), the Interagency Monitoring of PROtected Visual Environment Network (IMPROVE) and the Speciation and Trend Network (STN). If combined, these three networks provide speciated fine particulate data at several hundred locations throughout the United States. Yet, differences in sampling protocols and samples handling may not allow their joint use. With these concerns in mind, the objective of this study is to assess the spatial and temporal comparability of the sulfate, nitrate and ammonium concentrations reported by each of these networks. One of the major differences between networks is the sampling frequency they adopted. While CASTNet measures pollution levels on seven-day integrated samples, STN and IMPROVE data pertain to 24-hour samples collected every three days. STN and IMPROVE data therefore exhibit considerably more short-term variability than their CASTNet counterpart. We show that, despite their apparent incongruity, averaging the data with a window size of four to six weeks is sufficient to remove the effects of differences in sampling frequency and duration and allow meaningful comparison of the signals reported by the three networks of concern. After averaging, all the sulfate and, to a lesser degree, ammonium concentrations reported are fairly similar. Nitrate concentrations, on the other hand, are still divergent. We speculate that this divergence originates from the different types of filters used to collect particulate nitrate. Finally, using a rotated principal component technique (RPCA), we determined the number and the geographical organization of the significant temporal modes of variation (clusters) detected by each network for the three pollutants of interest. For sulfate and ammonium, the clusters’ geographical boundaries established for each network and the modes of variations within each cluster seem to correspond. RPCA erformed on nitrate concentrations revealed that, for the CASTNet and IMPROVE networks, the modes of variation do not correspond to unified geographical regions but are found more sporadically. For STN, the clustered areas are unified and easily delineable. We conclude that the possibility of jointly using the data collected by CASTNet, IMPROVE and STN has to be weighed pollutant by pollutant. While sulfate and ammonium data show some potential for joint use, at this point, combining the nitrate data from these monitoring networks may not be a judicious choice.     

Observed Evolution of Linear and Nonlinear Effects at the Dahan Downhole Array,Taiwan: Analysis of the September 21, 1999 M 7.3 Chi-Chi Earthquake Sequence

— In this paper, the site characteristics of the Dahan downhole array are studied by analyzing the September 21, 1999 M 7.3 Chi-Chi earthquake sequence including the main shock and some aftershocks. The four-level array (0 m, 50 m, 100 m and 200 m) is located to the north of Hualien City in eastern Taiwan. Polarization analysis is used to check the orientation errors of the seismometers at different levels of depth. If the surface instrument is chosen as reference, the angle between the major polarization axes of the surface and any downhole records is the orientation error that must be corrected for the downhole accelerographs. The orientation errors at depths of 50 m, 100 m and 200 m are 32°, 120° and –84°. After the corrections, the coherency between the surface and downhole records is substantially improved. Spectral ratio analysis shows that the predominant frequency of the Chi-Chi main shock shifts to a lower frequency. We also simulate ground motions at different depths by using the Haskell method with a linear velocity structure model. The record at surface is chosen as the input motion. Compared with the observed data, ground acceleration can be well reproduced for the aftershocks (weak-motion events) of the September 21, 1999 M 7.3 Chi-Chi earthquake. However, for the Chi-Chi main shock, the synthetic waveform cannot match well with the observation neither in amplitude nor in phase. This indicates that large ground shaking probably induced the nonlinear site effect at that time, and the model used cannot support it.Acknowledgement. The authors would like to express their thanks to Dr. L.F. Bonilla and one anonymous reviewer for their valuable suggestions. This research was supported by the National Science Council under grant number NSC 89-2921-M-194-007. The Institute of Earth Sciences, Academia Sinica supplied the strong-motion data. The support of these organizations is gratefully acknowledged.