Methodology and use of tensor invariants for satellite gravity gradiometry

Although its use is widespread in several other scientific disciplines, the theory of tensor invariants is only marginally adopted in gravity field modeling. We aim to close this gap by developing and applying the invariants approach for geopotential recovery. Gravitational tensor invariants are deduced from products of second-order derivatives of the gravitational potential. The benefit of the method presented arises from its independence of the gradiometer instrument’s orientation in space. Thus, we refrain from the classical methods for satellite gravity gradiometry analysis, i.e., in terms of individual gravity gradients, in favor of the alternative invariants approach. The invariants approach requires a tailored processing strategy. Firstly, the non-linear functionals with regard to the potential series expansion in spherical harmonics necessitates the linearization and iterative solution of the resulting least-squares problem. From the computational point of view, efficient linearization by means of perturbation theory has been adopted. It only requires the computation of reference gravity gradients. Secondly, the deduced pseudo-observations are composed of all the gravitational tensor elements, all of which require a comparable level of accuracy. Additionally, implementation of the invariants method for large data sets is a challenging task. We show the fundamentals of tensor invariants theory adapted to satellite gradiometry. With regard to the GOCE (Gravity field and steady-state Ocean Circulation Explorer) satellite gradiometry mission, we demonstrate that the iterative parameter estimation process converges within only two iterations. Additionally, for the GOCE configuration, we show the invariants approach to be insensitive to the synthesis of unobserved gravity gradients.     

Efficient GOCE satellite gravity field recovery based on least-squares using QR decomposition

We develop and apply an efficient strategy for Earth gravity field recovery from satellite gravity gradiometry data. Our approach is based upon the Paige-Saunders iterative least-squares method using QR decomposition (LSQR). We modify the original algorithm for space-geodetic applications: firstly, we investigate how convergence can be accelerated by means of both subspace and block-diagonal preconditioning. The efficiency of the latter dominates if the design matrix exhibits block-dominant structure. Secondly, we address Tikhonov-Phillips regularization in general. Thirdly, we demonstrate an effective implementation of the algorithm in a high-performance computing environment. In this context, an important issue is to avoid the twofold computation of the design matrix in each iteration. The computational platform is a 64-processor shared-memory supercomputer. The runtime results prove the successful parallelization of the LSQR solver. The numerical examples are chosen in view of the forthcoming satellite mission GOCE (Gravity field and steady-state Ocean Circulation Explorer). The closed-loop scenario covers 1 month of simulated data with 5 s sampling. We focus exclusively on the analysis of radial components of satellite accelerations and gravity gradients. Our extensions to the basic algorithm enable the method to be competitive with well-established inversion strategies in satellite geodesy, such as conjugate gradient methods or the brute-force approach. In its current development stage, the LSQR method appears ready to deal with real-data applications.     

电离层电子浓度总含量梯度对GPS差分定位精度的影响

针对GPS定位测量的信号传播路径误差,分析了电离层电子浓度总含量梯度对差分定位精度的影响,利用L1载波重点讨论了1999年-2000年太阳活动期间低纬度赤道异常地区GPS差分定位精度的问题,同时验证对于长基线采用GPS广域差分技术可以使电离层定位误差得到明显提高。     

Study on Recovering the Earth＇s Potential Field Based on GOCE Gradiometry

Given the second radial derivative Vrr（P） ｜δs of the Earth＇s gravitational potential V（P） on the surface δS corresponding to the satellite altitude, by using the fictitious compress recovery method, a fictitious regular harmonic field rrVrr（P）^＊ and a fictitious second radial gradient field V：（P） in the domain outside an inner sphere Ki can be determined, which coincides with the real field V（P） in the domain outside the Earth. Vrr^＊（P）could be further expressed as a uniformly convergent expansion series in the domain outside the inner sphere, because rrV（P）^＊ could be expressed as a uniformly convergent spherical harmonic expansion series due to its regularity and harmony in that domain. In another aspect, the fictitious field V^＊（P） defined in the domain outside the inner sphere, which coincides with the real field V（P） in the domain outside the Earth, could be also expressed as a spherical harmonic expansion series. Then, the harmonic coefficients contained in the series expressing V^＊（P） can be determined, and consequently the real field V（P） is recovered. Preliminary simulation calculations show that the second radial gradient field Vrr（P） could be recovered based only on the second radial derivative V（P）｜δs given on the satellite boundary. Concerning the final recovery of the potential field V（P） based only on the boundary value Vrr （P）｜δs, the simulation tests are still in process.     

Integration of local–global upscaling and grid adaptivity for simulation of subsurface flow in heterogeneous formations

We propose a methodology, called multilevel local–global (MLLG) upscaling, for generating accurate upscaled models of permeabilities or transmissibilities for flow simulation on adapted grids in heterogeneous subsurface formations. The method generates an initial adapted grid based on the given fine-scale reservoir heterogeneity and potential flow paths. It then applies local–global (LG) upscaling for permeability or transmissibility [7], along with adaptivity, in an iterative manner. In each iteration of MLLG, the grid can be adapted where needed to reduce flow solver and upscaling errors. The adaptivity is controlled with a flow-based indicator. The iterative process is continued until consistency between the global solve on the adapted grid and the local solves is obtained. While each application of LG upscaling is also an iterative process, this inner iteration generally takes only one or two iterations to converge. Furthermore, the number of outer iterations is bounded above, and hence, the computational costs of this approach are low. We design a new flow-based weighting of transmissibility values in LG upscaling that significantly improves the accuracy of LG and MLLG over traditional local transmissibility calculations. For highly heterogeneous (e.g., channelized) systems, the integration of grid adaptivity and LG upscaling is shown to consistently provide more accurate coarse-scale models for global flow, relative to reference fine-scale results, than do existing upscaling techniques applied to uniform grids of similar densities. Another attractive property of the integration of upscaling and adaptivity is that process dependency is strongly reduced, that is, the approach computes accurate global flow results also for flows driven by boundary conditions different from the generic boundary conditions used to compute the upscaled parameters. The method is demonstrated on Cartesian cell-based anisotropic refinement (CCAR) grids, but it can be applied to other adaptation strategies for structured grids and extended to unstructured grids.     

Strain analysis in Jurassic argillites of the Monte Sirino area (Lagonegro Zone,southern Apennines,Italy) and implications for deformation paths in pelitic rocks

Analysis of strain in Jurassic argillites forming part of the folded and thrusted sedimentary succession of the Lagonegro basin (southern Italian Apennines) has been carried out using ellipsoid-shaped reduction spots as strain markers. Most of the determined finite strain ellipsoids are of oblate type and show a peculiar distribution of the maximum extension direction (X), with maxima either subparallel or subperpendicular to the local fold axes. Using the strain matrix method, two different deformation histories have been considered to assist the interpretation of the observed finite strain pattern. A first deformation history involved vertical compaction followed by horizontal shortening (occurring by a combination of true tectonic strain and volume loss), whereby all strain is coaxial and there is no change in the intermediate axis of the strain ellipsoid. By this type of deformation sequence, which produces a deformation path where total strain moves from the oblate to the prolate strain field and back to the oblate field, prolate strain ellipsoids can be generated and may be recorded where tectonic deformation has not been large enough to reverse pretectonic compaction. This type of deformation history may be of local importance within the study area (i.e. it may characterize some fold hinge regions) and, more generally, is probably of limited occurrence in deformed pelitic rocks. A second deformation sequence considered the superposition of pre-tectonic compaction and tectonic strain consisting of initial layer-parallel shortening followed by layer-parallel shear (related to flexural folding). Also in this instance, volume change during tectonic deformation and tectonic plane strain have been assumed. For geologically reasonable amounts of volume loss due to compaction and of initial layer-parallel shortening, this type of deformation history is capable of producing a deformation path entirely lying within the oblate strain field, but still characterized by a changeover, during deformation, of the maximum extension axis (X) from a position parallel to the fold axis to one perpendicular to it. This type of deformation sequence may explain the main strain features observed in the study area, where most of the measured finite strain ellipsoids, determined from the limb regions of flexural folds, display an oblate shape, irrespective of the orientation of their maximum extension direction (X) with respect to the local structural trends. More generally, this type of deformation history provides a mechanism to account for the predominance of oblate strains in deformed pelitic rocks.     

云南大地热流及地热地质问题

本文报道了云南20多个大地热流测试数据。据热流分布特点并参考前人有关资料,结合地球物理测深资料、岩石热物性与放射性生热率测试数据,对各区地壳深度范围的温度、热流配分组成作了粗略分析,划分出各有特征的若干地质-热流区。云南普遍地热偏高(滇东南小范围除外)的主要原因是新构造运动强烈;怒江以西近代岩浆活动亦强烈,具有典型的板块交汇带的基本地热特点     

Reservoir description using dynamic parameterisation selection with a combined stochastic and gradient search

There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm.