Seismic depth imaging of iron‐oxide deposits and their host rocks in the Ludvika mining area of central Sweden
Seismic depth imaging of iron‐oxide deposits and their host rocks in the Ludvika mining area of central Sweden
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DOI：
10.1111/1365-2478.12836
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发表时间：
2019-07
影响因子：
2.6
通讯作者：
L. Bräunig;S. Buske;A. Malehmir;E. Bäckström;M. Schön;P. Marsden
中科院分区：
文献类型：
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作者：
L. Bräunig;S. Buske;A. Malehmir;E. Bäckström;M. Schön;P. Marsden
开发具有成本效益和环境可接受的矿产资源勘探地球物理方法是一项具有挑战性的任务。地震方法有可能以足够高的分辨率在更深处描绘矿床。在硬岩环境中，通常承载大多数金属矿床，地震深度成像工作流程受到陡倾结构，强烈的非均匀性和覆盖层中相关波场散射以及所采集数据的信噪比通常有限的挑战。在这项研究中，我们开发了一种工作流程，用于在深度域的准确位置对主要氧化铁存款进行成像，同时以高分辨率表征近地表冰川覆盖层，包括周围结构，如交叉断层。我们的工作流程已在2016年从瑞典中部卢德维卡矿区采集的二维地表地震遗留数据集上成功展示。我们应用聚焦叠前深度成像技术，获得了1000米以上深度的矿化清晰且分辨率良好的图像。为了在深度成像算法中考虑浅层低速层，我们通过综合方法仔细推导了偏移速度模型。这包括结合层析近地表模型，根据钻孔信息和常规的表面分析将速度向下延伸到主要反射层。在最后一步中，通过研究主要目标反射体的公共图像道集来评估和更新速度。虽然我们的数据集的反射从矿化在地震剖面中表现出很强的相干性和连续性，反射结构在硬岩环境中通常是不连续的。为了对矿化的内部结构进行成像并破译周围的结构，我们将反射图像光谱学的概念应用于数据，这使得反射体内的特定波长特征能够成像。因此，矿化周围的共轭交叉断层可以直接在低频带成像，而内部结构在高频带内获得。
The development of cost‐effective and environmentally acceptable geophysical methods for the exploration of mineral resources is a challenging task. Seismic methods have the potential to delineate the mineral deposits at greater depths with sufficiently high resolution. In hardrock environments, which typically host the majority of metallic mineral deposits, seismic depth‐imaging workflows are challenged by steeply dipping structures, strong heterogeneity and the related wavefield scattering in the overburden as well as the often limited signal‐to‐noise ratio of the acquired data. In this study, we have developed a workflow for imaging a major iron‐oxide deposit at its accurate position in depth domain while simultaneously characterizing the near‐surface glacial overburden including surrounding structures like crossing faults at high resolution. Our workflow has successfully been showcased on a 2D surface seismic legacy data set from the Ludvika mining area in central Sweden acquired in 2016. We applied focusing prestack depth‐imaging techniques to obtain a clear and well‐resolved image of the mineralization down to over 1000 m depth. In order to account for the shallow low‐velocity layer within the depth‐imaging algorithm, we carefully derived a migration velocity model through an integrative approach. This comprised the incorporation of the tomographic near‐surface model, the extension of the velocities down to the main reflectors based on borehole information and conventional semblance analysis. In the final step, the evaluation and update of the velocities by investigation of common image gathers for the main target reflectors were used. Although for our data set the reflections from the mineralization show a strong coherency and continuity in the seismic section, reflective structures in a hardrock environment are typically less continuous. In order to image the internal structure of the mineralization and decipher the surrounding structures, we applied the concept of reflection image spectroscopy to the data, which allows the imaging of wavelength‐specific characteristics within the reflective body. As a result, conjugate crossing faults around the mineralization can directly be imaged in a low‐frequency band while the internal structure was obtained within the high‐frequency bands.