Interpretation of transient electromagnetic soundings over three-dimensional structures for the central-loop configuration

Summary. An assessment is made of the bias of fitting constrained layered-earth models to transient electromagnetic data obtained over 3-D structures. In this assessment we use the central-loop configuration and show that accurate estimates of the depth of burial of 3-D structures can be obtained with layered-earth model fitting. However, layered-earth interpretations are not reliable for estimating depth extents and resistivities of 3-D structures. When layered earths are used for interpretation, it is advantageous in some cases to use data based on the magnetic field instead of the voltage. A magnetic-field definition of apparent resistivity, in contrast to a definition based on the voltage, eliminates apparent-resistivity overshoots and undershoots in the data. A resistivity undershoot in the data can produce an extraneous and misleading layer in an interpretation of a 3-D resistive structure. Due to 3-D effects, apparent-resistivity soundings (magnetic field and voltage) may rise so steeply at late times that it may not be possible to fit a sounding to a reasonable layered-earth model. Truncating such a sounding, over a buried conductor, allows for a reasonable layered-earth fit and an accurate estimate of the depth to the conductor. However, the resistivity of the conductor is overestimated.
Measurements of the horizontal field in the central-loop configuration can map 3-D structures, provided the sensor is located accurately at the centre of the transmitting loop. Horizontal-field calculations show that the transients peak on the flanks of a 3-D structure, but are depressed over the structure's centre. Weak transient responses flanked by two large transient responses, which are opposite in sign, locate the structure. The sign reversal is caused by a corresponding reversal in the currents that are channelled through or deflected away from conductive or resistive structures, respectively.     

Fast static correction methods for high-frequency multichannel marine seismic reflection data: A high-resolution seismic study of channel-levee systems on the Bengal Fan

Very high-frequency marine multichannel seismic reflection data generated by small-volume air- or waterguns allow detailed, high-resolution studies of sedimentary structures of the order of one to few metres wavelength. The high-frequency content, however, requires (1) a very exact knowledge of the source and receiver positions, and (2) the development of data processing methods which take this exact geometry into account. Static corrections are crucial for the quality of very high-frequency stacked data because static shifts caused by variations of the source and streamer depths are of the order of half to one dominant wavelength, so that they can lead to destructive interference during stacking of CDP sorted traces. As common surface-consistent residual static correction methods developed for land seismic data require fixed shot and receiver locations two simple and fast techniques have been developed for marine seismic data with moving sources and receivers to correct such static shifts. The first method – called CDP static correction method – is based on a simultaneous recording of Parasound sediment echosounder and multichannel seismic reflection data. It compares the depth information derived from the first arrivals of both data sets to calculate static correction time shifts for each seismic channel relative to the Parasound water depths. The second method – called average static correction method – utilises the fact that the streamer depth is mainly controlled by bird units, which keep the streamer in a predefined depth at certain increments but do not prevent the streamer from being slightly buoyant in-between. In case of calm weather conditions these streamer bendings mainly contribute to the overall static time shifts, whereas depth variations of the source are negligible. Hence, mean static correction time shifts are calculated for each channel by averaging the depth values determined at each geophone group position for several subsequent shots. Application of both methods to data of a high-resolution seismic survey of channel-levee systems on the Bengal Fan shows that the quality of the stacked section can be improved significantly compared to stacking results achieved without preceding static corrections. The optimised records show sedimentary features in great detail, that are not visible without static corrections. Limitations only result from the sea floor topography. The CDP static correction method generally provides more coherent reflections than the average static correction method but can only be applied in areas with rather flat sea floor, where no diffraction hyperbolae occur. In contrast, the average static correction method can also be used in regions with rough morphology, but the coherency of reflections is slightly reduced compared to the results of the CDP static correction method.     

High Precision Geoid Models HKGEOID-2000 for Hong Kong and SZGEOID-2000 for Shenzhen, China

High precision geoid models HKGEOID-2000 for Hong Kong and SZGEOID-2000 for Shenzhen, China, have been developed with a hybrid approach of so-called sequential processing, using high precision GPS/leveling data, land and sea gravity anomalies, and digital terrain models. These two local geoid models have the same 1-km resolution. The estimated accuracy (external accuracy) is better than 1.7 cm for HKGEOID-2000 and 1.4 cm for SZGEOID-2000. Some common areas are covered by HKGEOID-2000 and SZGEOID-2000. So these two geoid models, along with high quality GPS/leveling data collected on the overlapping areas, can be used to detect the systematic bias between HKGEOID-2000 and SZGEOID-2000, as well as the difference between Hong Kong Principal Datum and 1956 yellow sea height datum of China, yielding RMS errors of 1.011 m and 1,003 m, respectively. Moreover, HKGEOID-2000, along with GPS ellipsoidal heights, is employed to determine the errors of the “orthometric heights” from purely trigonometric heighting, yielding an RMS error of 0.102 m. The combination of SZGEOID-2000 and GPS ellipsoidal heights has been used to replace the traditional spirit leveling and mapping, called GPS mapping.     

Nonparametric Estimates of the Sea State Bias for the Jason-1 Radar Altimeter

The Jason-1 sea state bias (SSB) is analyzed in depth from the first year of GDR products. Compared to previous missions, this work benefits from two aspects of the empirical determination of the SSB from the altimetric data themselves. First, from a methodological point of view, a nonparametric technique (NP) has been developed and largely tested on TOPEX/Poseidon 1, GFO and Envisat data. The NP estimator has proven to be a useful tool in the SSB estimation, and it is now mature enough to be used for a refined analysis. On the other hand, the SSB can be extracted from three different data sets (crossovers, collinear data, and residuals) with different characteristics. It is then possible to cross calibrate various estimations of the SSB models and to determine the most accurate one. A systematic comparison is made between these different estimates for the Jason-1 altimeter. The collinear and crossover data sets yield very similar estimates despite their difference of spatial and temporal distributions. These SSB models assure consistency with the TOPEX mission when comparing Jason-1 and TOPEX residuals during the tandem phase. Thanks to the present work, the impact of the short wavelengths filtering on the SSB estimation is evidenced. More generally, our understanding of potential errors affecting the sea surface height and their impact onto the SSB estimation is also improved.     

Effects of detailed soil spatial information on watershed modeling across different model scales

Hydro-ecological modelers often use spatial variation of soil information derived from conventional soil surveys in simulation of hydro-ecological processes over watersheds at mesoscale (10–100 km²). Conventional soil surveys are not designed to provide the same level of spatial detail as terrain and vegetation inputs derived from digital terrain analysis and remote sensing techniques. Soil property layers derived from conventional soil surveys are often incompatible with detailed terrain and remotely sensed data due to their difference in scales. The objective of this research is to examine the effect of scale incompatibility between soil information and the detailed digital terrain data and remotely sensed information by comparing simulations of watershed processes based on the conventional soil map and those simulations based on detailed soil information across different simulation scales. The detailed soil spatial information was derived using a GIS (geographical information system), expert knowledge, and fuzzy logic based predictive mapping approach (Soil Land Inference Model, SoLIM). The Regional Hydro-Ecological Simulation System (RHESSys) is used to simulate two watershed processes: net photosynthesis and stream flow. The difference between simulation based on the conventional soil map and that based on the detailed predictive soil map at a given simulation scale is perceived to be the effect of scale incompatibility between conventional soil data and the rest of the (more detailed) data layers at that scale. Two modeling approaches were taken in this study: the lumped parameter approach and the distributed parameter approach. The results over two small watersheds indicate that the effect does not necessarily always increase or decrease as the simulation scale becomes finer or coarser. For a given watershed there seems to be a fixed scale at which the effect is consistently low for the simulated processes with both the lumped parameter approach and the distributed parameter approach.     

地震静校正全局最优化问题的求解

针对地震静校正存在的非线性和多参数性等问题，本文提出了一种全局优化的剩余静校正方法.在模型更新规则上，把模拟退火方法和均匀优化设计方法结合在一起，使模型的更新更为合理，从而加快了搜寻全局最优解的速度.同时提出了模型的不同分量的温度参数和退火过程的选取方式，把温度参数的选取与地震剖面的能量联系起来，使温度参数的选取具有自适应的特点.该方法克服了常规模拟退火方法所具有的寻优空间不均匀以及退火参数需通过多次试验选取的缺陷.通过实际地震资料的计算证明，本文提出的方法对地震静校正问题合理而有效.     

GPS精密定位中的海潮位移改正

根据海洋负荷潮理论，利用NAO99b全球海潮模型，计算了中国部分IGS站的海潮位移改正，并将海潮位移改正应用到GPS数据处理当中。在GAMIT软件的解算过程中，分别按加入和不加入海潮位移改正，对GPS基线分量和测站坐标分别进行了计算和比较分析。结果表明，海潮位移改正无论是对GPS基线分量还是对测站坐标，都有一定的影响。     

高分辨率厘米级局部大地水准面的典型应用

介绍了香港大地水准面HKGEOID_2 0 0 0和深圳市高分辨率、高精度似大地水准面SZGEOID_2 0 0 0。利用HKGEOID_2 0 0 0和GPS椭球高求得的正常高与香港地区由三角高程测量得到的“正常高 (或本地高 )”进行比较 ,结果表明 ,其差值的均方根为 0 .1 0 2m ,标准差 (STD)为± 3 .4cm。结合HKGEOID_2 0 0 0、SZGEOID_2 0 0 0和这两个大地水准面模型重复覆盖地区的高精度GPS水准数据 ,探测这两个大地水准面模型之间的差异和香港主要高程基准面 (HKPD)与我国 1 95 6黄海高程基准面之间的系统偏差。     

Fitting the Linear Model of Coregionalization by Generalized Least Squares

In geostatistical studies, the fitting of the linear model of coregionalization (LMC) to direct and cross experimental semivariograms is usually performed with a weighted least-squares (WLS) procedure based on the number of pairs of observations at each lag. So far, no study has investigated the efficiency of other least-squares procedures, such as ordinary least squares (OLS), generalized least squares (GLS), and WLS with other weighing functions, in the context of the LMC. In this article, we compare the statistical properties of the sill estimators obtained with eight least-squares procedures for fitting the LMC: OLS, four WLS, and three GLS. The WLS procedures are based on approximations of the variance of semivariogram estimates at each distance lag. The GLS procedures use a variance–covariance matrix of semivariogram estimates that is (i) estimated using the fourth-order moments with sill estimates (GLS₁), (ii) calculated using the fourth-order moments with the theoretical sills (GLS₂), and (iii) based on an approximation using the correlation between semivariogram estimates in the case of spatial independence of the observations (GLS₃). The current algorithm for fitting the LMC by WLS while ensuring the positive semidefiniteness of sill matrix estimates is modified to include any least-squares procedure. A Monte Carlo study is performed for 16 scenarios corresponding to different combinations of the number of variables, number of spatial structures, values of ranges, and scale dependence of the correlations among variables. Simulation results show that the mean square error is accounted for mostly by the variance of the sill estimators instead of their squared bias. Overall, the estimated GLS₁ and theoretical GLS₂ are the most efficient, followed by the WLS procedure that is based on the number of pairs of observations and the average distance at each lag. On that basis, GLS₁ can be recommended for future studies using the LMC.