Compressing seismic migration parameters by B-spline surface fitting
Seismic migration needs many kinds of parameters. The parameters are scattered data and have a large amount of data points. In order to improve the numerical efficiency of seismic migration, the enormous parameter files need be compressed. The published methods for compressing scattered data have a few shortcomings, for example, some are not suitable for enormous data, some are time-consuming, and some can't provide high enough numerical precision. I propose a rapid algorithm to compress the enormous scattered migration parameters by B-spline surface fitting: A least surface is fitted by B-spline function which covers all the scattered data according to their coordinate range in 2D plane firstly. Then, on the basis of the linear interpolaton of B-spline smoothing function, the values of all the regular grids can be calculated by solving a liner system equation group with LU decomposition based on the multi-frontal method. Through storing these values of the regular grids, the value of every point from the original data can be estimated. In this way, the aim of scattered data compressing is achieved. The algorithm is practiced successfully in several models. The experiments show that the cubic B-spline function can be the best basal function for surface fitting because it makes the construction surface smooth, as well as has stable and effective compression with high approximate accuracy using regular grids. The compression algorithm has local relative errors as little as 0.0001, compressing ratio up to 300 and faster calculation efficiency than conventional iterative compressing methods. The algorithm is applicable for any seismic data with low gradient.
Fast visualisation of massive data based on viewpoint motion model
To display massive data accurately and in real time, a visualisation algorithm based on the viewpoint motion model is proposed. A Hilbert-R tree is constructed to index massive data. Further, the massive data is divided into a visible area, a potential area, and an unloading area using the viewpoint motion model. According to the index, corresponding data blocks are loaded into the memory, and data blocks of the visible area further transferred into the graphic processing unit (GPU) memory for rendering. When the viewpoint is changed, the data block of the potential area in the memory is directly loaded into the GPU. Experimental results show that under the premise of ensuring the quality of rendering, massive data can be displayed interactively, and the speed of displaying increases by 36–78%.
Pyrite multiple-sulfur isotope evidence for rapid expansion and contraction of the early Paleoproterozoic seawater sulfate reservoir
Abstract Earthʼs oxygenation is often described in terms of two unidirectional steps at the beginning and end of the Proterozoic Eon, separated by a long-lived intermediate redox state. Recent work defines a more complicated path to oxygenation, exemplified by an apparent drop in oxidation state following the early Paleoproterozoic Lomagundi carbon isotope excursion. The timing of this proposed drop in oxidation state is not well constrained, and it is not clear how it relates to redox conditions during the remainder of the Proterozoic. Here we present a study of pyrite multiple-sulfur isotopes, supported by Fe speciation and organic carbon isotopes, from early Paleoproterozoic black shales. We find evidence for the rapid expansion of the seawater sulfate reservoir during the Great Oxidation Event at ca. 2.3 Ga followed by a subsequent contraction in the size of the seawater sulfate reservoir at ca. 2.05 Ga. This scenario is consistent with the emerging view of a rise and fall in surface oxidation state during the early Paleoproterozoic. Comparison of our new data to other records of the seawater sulfate reservoir suggests that the elevated sulfate concentrations that characterize the early Paleoproterozoic did not return until the late Neoproterozoic.