P-wave attenuation anisotropy in TI media and its application in fracture parameters inversion

The existence of aligned fractures in fluid-saturated rocks leads to obvious attenuation anisotropy and velocity anisotropy. Attenuation anisotropy analysis can be applied to estimate fracture density and scale, which provide important information for reservoir identification. This paper derives P-wave attenuation anisotropy in the ATI media where the symmetry axis is in the arbitrary direction theoretically and modifies the spectral ratio method to measure attenuation anisotropy in the ATI media, thus avoiding a large measurement error when applied to wide azimuth or full azimuth data. Fracture dip and azimuth can be estimated through attenuation anisotropy analysis. For small-scale fractures, fracture scale and fracture density can be determined with enhanced convergence if velocity and attenuation information are both used. We also apply the modified spectralratio method to microseismic field data from an oilfield in East China and extract the fracture dip through attenuation anisotropy analysis. The result agrees with the microseismic monitoring.     

Enhancement of Seismic Data Processing and Interpretation of Fracture Zones on the Upper Part of Granitic Basement in Cuu Long Basin,Vietnam

The fractured granite basement is the primary oil and gas reservoir in the Cuu Long Basin, Vietnam. Due to the complexity of this nonlayered unconventional target, combined with complicated fault and fracture systems, the seismic data quality near and within the basement section is very low. For this reason, it is important to apply improved seismic data processing workflows, filtering and migration techniques, as wells as attribute processing methods to enhance the imaging quality.Our studies show that applying different types of filters, including the f-k, Radon transform and Tau-P, improves signal to noise ratio, removing multiples, revealing basement’s top and its related fractured and fault zones. In addition, the application of multi-arrival-solution migration algorithms, such as Kirchhoff Migration and Controlled Beam Migration, provides improved imaging for identifying basement top and faults and fractures within the basement. Furthermore, the application of seismic attributes such as curvature, apparent dip, or energy gradient, is important in locating faults and fractures, whereas mapping of intensity and orientation of such structures assists the delineation of “sweet spots” and assists the planning of exploration.     

Gravity anomaly and crustal density structure in Jilantai rift zone and its adjacent region

This paper deals with the interpretation of Bouguer gravity anomalies measured along a 250 km long Suhaitu-Etuokeqi gravity profile located at the transitional zone of the Alxa and Ordos blocks where geophysical characteristics are very complex. The analysis is carried out in terms of the ratio of elevation and Bouguer gravity anomaly, the normalized full gradient of a section of the Bouguer gravity anomaly (G ^h ) and the crustal density structure reveal that (1) the ratio of highs and lows of elevation and Bouguer gravity anomaly is large between Zhengyiguan fault (F4) and Helandonglu fault (F6), which can be explained due to crustal inhomogeneities related to the uplift of the Qinghai-Tibet block in the northeast; (2) the main active faults correspond to the G ^h contour strip or cut the local region, and generally show strong deformation characteristics, for example the Bayanwulashan mountain front fault (F1) or the southeast boundary of Alxa block is in accord with the western change belt of G ^h , a belt about 10 km wide that extends to about 30 km; (3) Yinchuan-Pingluo fault (F8) is the seismogenic structure of the Pingluo M earthquake, and its focal depth is about 15 km; (4) the Moho depth trend and Bouguer gravity anomaly variation indicates that the regional gravity field is strongly correlated with the Moho discontinuity.     

Full moment tensor inversion constrained by double-couple focal mechanism for induced seismicity*

In this study, we propose a new method to determine full moment tensor solution for induced seismicity. This method generalizes the full waveform matching algorithm we have developed to determine the double-couple (DC) focal mechanism based on the neighbourhood algorithm. One major difference between the new method and the former one is that we adopt a new misfit function to constrain the candidate moment tensor solutions with respect to a reference DC solution in addition to other misfit terms characterizing the waveform matching. Through synthetic tests using a real passive seismic survey geometry, the results show the new constraint can help better recover the DC components of inverted moment tensors. We further investigate how errors in the velocity model and source location affect the moment tensor solution. The synthetic test results indicate that the constrained inversion is robust in recovering both the DC and non-DC components. We also test the proposed method on several real induced events in an oil/gas field in Oman using the same observation system as synthetic tests. While it is found that the full moment tensor solutions without using the DC constraints have much larger non-DC components than solutions with the DC constraints, both solutions are able to fit the observed waveforms at similar levels. The synthetic and real test results suggest the proposed DC constrained inversion method can reliably retrieve full moment tensor solutions for the induced seismicity.     

高层建筑荷载引发地面沉降与隆起变形三维数值模拟

针对地下水埋深较浅地区,由高层建筑荷载引起的土体变形问题,以比奥固结理论为基础,结合土体非线性流变理论,将土体本构关系推广到黏弹塑性;同时考虑土体力学参数及水力参数的动态变化关系,建立了高层建筑荷载引发地面沉降与隆起变形的三维有限元数值模型,详细研究了高层建筑荷载影响下的土体变形特征及此过程中土体力学参数及水力学参数的变化特征。结果表明：由高层建筑荷载引起的地面沉降呈现漏斗状,以建筑物中心为漏斗中心,高层建筑荷载施加初期,高层建筑周围出现隆起,到达最大值后隆起逐渐消失;高层建筑底部浅层土体孔隙度、渗透系数及泊松比均呈现缓慢减小趋势,弹性模量呈现缓慢增大趋势;而高层建筑周围浅层土体的孔隙度、渗透系数及泊松比呈现先增大后减小的变化趋势,弹性模量则呈现先减小后增大的变化趋势;高层建筑影响区域浅部土体参数的变化趋势与土体的回弹及压缩有关。     

A comparative study of landslide susceptibility mapping using weight of evidence,logistic regression and support vector machine and evaluated by SBAS-InSAR monitoring: Zhouqu to Wudu segment in Bailong River Basin,China

The determining of landslide-prone areas in mountainous terrain is essential for land planning and hazard mitigation. In this paper, a comparative study using three statistical models including weight of evidence model (WoE), logistic regression model (LR) and support vector machine method (SVM) was undertaken in the Zhouqu to Wudu segment in the Bailong River Basin, Southern Gansu, China. Six conditionally independent environmental factors, elevation, slope, aspect, distance from fault, lithology and settlement density, were selected as the explanatory variables that may contribute to landslide occurrence based on principal component analysis (PCA) and Chi-square test. The relation between landslide distributions and these variables was analyzed using the three models and the results then used to calculate the landslide susceptibility (LS). The performance of the models was then evaluated using both the highly accurate deformation signals produced by using the Small Baseline Subset Interferometric Synthetic Aperture Radar technique and Receiver Operating Characteristic (ROC) curve. Results show more deformation points in areas with high and very high LS levels, and also more stable points in areas with low and very low LS levels for the SVM model. In addition, the SVM has larger area under the ROC curve. It indicates that the SVM has better prediction accuracy and classified ability. For the interpretability, the WoE derives the class of factors that most contributed to landsliding in the study area, and the LR reveals that factors including elevation, settlement density and distance from fault played major roles in landslide occurrence and distribution, whereas the SVM cannot provide relative weights for the variables. The outperformed SVM could be employed to determine potential landslide zones in the study area. Outcome of this research would provide preliminary basis for general land planning such as choosing new urban areas and infrastructure construction in the future, as well as for landslide hazard mitigation in Bailong River Basin.     

基于GIS的证据权重法矿产预测系统(EWM)

探讨了ＧＩＳ的主要功能、ＧＩＳ在矿产预测中的应用、证据权重法的理论基础,并在Ｗｉｎｄｏｗｓ９５环境下,建立了基于ＧＩＳ的证据权重法矿产预测系统———ＥＷＭ。     

Time–frequency characteristics and trend feature of the ENPEMF signal before Lushan $${{\varvec{M}}}_{{\varvec{w}}}$$ M w 6.6 earthquake via DE-DDTFA method

Natural Hazards - The Earth's natural pulse electromagnetic field (ENPEMF) signal, is generally considered to be a nonlinear or nonstationary signal received from our instrument, placed on the...     

The 2010 Yushu earthquake triggered landslide hazard mapping using GIS and weight of evidence modeling

The Yushu County, Qinghai Province, China, April 14, 2010, earthquake triggered thousands of landslides in a zone between 96°20′32.9″E and 97°10′8.9″E, and 32°52′6.7″N and 33°19′47.9″N. This study examines the use of geographic information system (GIS) technology and Bayesian statistics in creating a suitable landslide hazard-zone map of good predictive power. A total of 2,036 landslides were interpreted from high-resolution aerial photographs and multi-source satellite images pre- and post-earthquake, and verified by selected field checking before a final landslide-inventory map of the study area could be established using GIS software. The 2,036 landslides were randomly partitioned into two subsets: a training dataset, which contains 80 % (1,628 landslides), for training the model; and a testing dataset 20 % (408 landslides). Twelve earthquake triggered landslide associated controlling parameters, such as elevation, slope gradient, slope aspect, slope curvature, topographic position, distance from main surface ruptures, peak ground acceleration, distance from roads, normalized difference vegetation index, distance from drainages, lithology, and distance from all faults were obtained from variety of data sources. Landslide hazard indices were calculated using the weight of evidence model. The landslide hazard map was compared with training data and testing data to obtain the success rate and predictive rate of the model, respectively. The validation results showed satisfactory agreement between the hazard map and the existing landslide distribution data. The success rate is 80.607 %, and the predictive rate is 78.855 %. The resulting landslide hazard map showed five classes of landslide hazard, i.e., very high, high, moderate, low and very low. The landslide hazard evaluation map should be useful for environmental recovery planning and reconstruction work.