Unsupervised learning approach for revealing subsurface tectono-depositional environment: A study from NE India

IF 2.2 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY
Priyadarshi Chinmoy Kumar , Heather Bedle , Jitender Kumar , Kalachand Sain , Suman Konar
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Abstract

The present study attempts to explore the efficacy of self-organizing maps (SOMs) in understanding the pattern of seismic reflections and analyze their implications for revealing the subsurface tectono-depositional environment prevailing within the Oligocene-Miocene intervals of the Upper Assam foreland basin, NE India. A series of seismic attributes including geometrical, spectral, amplitude, and GLCM-textures are extracted using high-resolution three-dimensional seismic data acquired from the upper shelf of the basin. These attributes are amalgamated into two different cases to compute the SOM models with an aim to highlight the subsurface structures and reveal sedimentary deposits engulfed within these structures. It is observed that the model SOM Case 1 highlights subsurface fault networks that structurally control the Oligocene-Miocene intervals. However, the model SOM Case 2 not only hints at the presence of these structures but also illuminates different patterns of seismic reflections and geomorphic features associated with sediment entrapped within the fault-bounded structures. Through this research, we envisage that for the SOMs to be optimal, geologically meaningful sets of seismic attributes should be used as an input such that attributes assisting seismic interpreters could successfully identify relations or patterns within the data. The method presented in this study can be applied to similar geologic settings to aid subsurface interpretation.

揭示地下构造沉积环境的无监督学习方法:印度东北部研究
本研究试图探索自组织图(SOM)在理解地震反射模式方面的功效,并分析其对揭示印度东北部上阿萨姆前陆盆地渐新世-中新世时期地下构造沉积环境的影响。利用从盆地上陆架获取的高分辨率三维地震数据,提取了一系列地震属性,包括几何、频谱、振幅和 GLCM 纹理。将这些属性合并为两种不同的情况来计算 SOM 模型,目的是突出地下结构并揭示这些结构中的沉积沉淀。据观察,SOM 模型案例 1 突出了在结构上控制渐新世-中新世区间的地下断层网络。然而,SOM 案例 2 模型不仅暗示了这些构造的存在,还揭示了不同的地震反射模式以及与断层构造内沉积物相关的地貌特征。通过这项研究,我们认为要使 SOM 达到最佳效果,应使用具有地质意义的地震属性集作为输入,以便协助地震解释人员成功识别数据中的关系或模式。本研究提出的方法可用于类似的地质环境,以帮助地下解释。
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来源期刊
Journal of Applied Geophysics
Journal of Applied Geophysics 地学-地球科学综合
CiteScore
3.60
自引率
10.00%
发文量
274
审稿时长
4 months
期刊介绍: The Journal of Applied Geophysics with its key objective of responding to pertinent and timely needs, places particular emphasis on methodological developments and innovative applications of geophysical techniques for addressing environmental, engineering, and hydrological problems. Related topical research in exploration geophysics and in soil and rock physics is also covered by the Journal of Applied Geophysics.
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