The Xiangxi Au–Sb–W deposit, the largest of its type in northwestern Hunan, China, is a sulfide-dominated ore body hosted by low grade metamorphic red slates of the Neoproterozoic Madiyi Formation. Three stages of mineralization, quartz–scheelite, quartz–gold–pyrite, quartz–gold–stibnite, and one metal-barren stage of veining, quartz–calcite, are recognized. Arsenopyrite occurs only as a minor mineral phase in the second stage. Analyses for 21 trace elements show that the enrichment factors of As in the metal deposit (EC [=element concentration of sample/average content of an element in the upper crust]: 190; 43 samples) in ore veins and in the Guanzhuang and Yuershan reference sections (3.7 km and 2.7 km away from the Xiangxi mine, EC: 3.5; 96 samples) are much smaller than those of Sb (52855 [in ore veins], 117 [in the sections]), W (5665, 7.5) and Au (2727, 5.3). The background concentrations of Au and As in the two sections were 1.4 ppb and 1.4 ppm, respectively. Arsenic (with an anomaly coefficient [AC = number of anomalous samples/total number of samples] of 76%) forms a larger geochemical halo than W (AC: 8%) and Au (AC: 32%). Gold and As in the deposit were transported mainly as metal complexes such as Au(HS)−2, HnAs3S−(3−n)6 (n=1, 2 or 3) and HAsS02. Au(HS)−2 is rapidly precipitated by a geochemical oxidation barrier — the red slates of the Madiyi Formation. As–S complexes in the stratigraphic horizon can be transformed into As–O complexes (e.g., H3AsO03) under oxidizing conditions, and are continuously transported. Therefore, they can be widely distributed in the red slate units, thus forming extensive geochemical haloes, so that As can be used as an indicator element for Au exploration in the Xiangxi region. 相似文献
Inversion for seismic impedance is an inherently complicated problem. It is ill‐posed and band‐limited. Thus the inversion results are non‐unique and the process is unstable. Combining regularization with constraints using sonic and density log data can help to reduce these problems. To achieve this, we developed an inversion method by constructing a new objective function, including edge‐preserving regularization and a soft constraint based on a Markov random field. The method includes the selection of proper initial values of the regularization parameters by a statistical method, and it adaptively adjusts the regularization parameters by the maximum likelihood method in a fast simulated‐annealing procedure to improve the inversion result and the convergence speed. Moreover, the method uses two kinds of regularization parameter: a ‘weighting factor’λ and a ‘scaling parameter’δ. We tested the method on both synthetic and field data examples. Tests on 2D synthetic data indicate that the inversion results, especially the aspects of the discontinuity, are significantly different for different regularization functions. The initial values of the regularization parameters are either too large or too small to avoid either an unstable or an over‐smoothed result, and they affect the convergence speed. When selecting the initial values of λ, the type of the regularization function should be considered. The results obtained by constant regularization parameters are smoother than those obtained by adaptively adjusting the regularization parameters. The inversion results of the field data provide more detailed information about the layers, and they match the impedance curves calculated from the well logs at the three wells, over most portions of the curves. 相似文献
Mathematic modeling, established on the basis of physical experiments, is becoming an increasingly important tool in oil and gas migration studies. This technique is based on the observation that hydrocarbon migration tends to take relative narrow pathways. A mathematical model of hydrocarbon migration and accumulation is constructed using the percolation theory. It is then calibrated using physical experimental results, and is tested under a variety of conditions, to understand the applicability of the model in different migration cases. Through modeling, dynamic conditions of large-scale migration pathways within homogeneous formations can be evaluated. Basin-scale hydrocarbon migration pathways and their characteristics are analyzed during the model application to the Chang-8 Member of the Triassic Yanchang Formation in Longdong area of Ordos Basin. In heterogeneous formations, spatial changes in fluid potential determine the direction of secondary migration, and heterogeneity controls the characteristics and geometry of secondary migration pathways.