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A Core Logging, Machine Learning and Geostatistical Modeling Interactive Approach for Subsurface Imaging of Lenticular Geobodies in a Clastic Depositional System, SE Pakistan
Natural Resources Research ( IF 5.4 ) Pub Date : 2021-03-16 , DOI: 10.1007/s11053-021-09849-x
Umar Ashraf , Hucai Zhang , Aqsa Anees , Hassan Nasir Mangi , Muhammad Ali , Xiaonan Zhang , Muhammad Imraz , Saiq Shakeel Abbasi , Ayesha Abbas , Zaheen Ullah , Jar Ullah , Shucheng Tan

Facies models are essential tools for imaging subsurface geobodies and for reducing exploration and development risks efficiently. The Lower Goru Formation is one of the principal formations in the Lower Indus Basin, Pakistan. Its substantial hydrocarbon potential is unexplored, as most of the wells within the Sawan gas field are facing relatively low production yields. This study aimed to delineate subsurface geobodies by developing a facies model to study the depositional processes and facies distributions that have been neglected previously. The interactive approaches used in this research consisted of petrophysical, mineral composition, well-log facies, and horizon attribute analyses, as well as an unsupervised vector quantizer artificial neural network (UVQ–ANN) and sequential indicator simulation (SIS) modeling. A series of E–W-oriented lenticular geobodies were delineated. These geobodies had variable thicknesses, and they pinch out to the NW and prograde to the NE. The results of the SIS, UVQ–ANN, petrographic analysis, and attribute analysis show a fluvial fan-delta sedimentary system. The reservoir sands were deposited in distributary mouth bars and deltaic channels in proximal delta front settings. The coarse- to very fine-grained reservoir sands prograde toward the NE. Thinly laminated beds of fine-grained black shales and lime muddy siltstones were deposited under low-energy conditions in mid-shelf marine settings. The adopted methodology for the generated facies model can be extended to different basins within Pakistan with the same geological settings, and it can be used for prospect evaluation, future drilling, and development plans within the Sawan gas field in the Lower Indus Basin.



中文翻译:

巴基斯坦东南部碎屑沉积系统中透镜状地物地下成像的核心测井,机器学习和地统计学建模交互式方法

相模型是用于对地下地质体进行成像并有效降低勘探与开发风险的重要工具。下古鲁组是巴基斯坦下印度河流域的主要组群之一。由于沙旺气田内的大多数井都面临相对较低的产量,因此尚未开发其大量的烃潜力。这项研究旨在通过开发相模型研究以前被忽略的沉积过程和相分布来描述地下地质体。本研究中使用的交互式方法包括岩石物理,矿物成分,测井相和层位属性分析,以及无监督矢量量化器人工神经网络(UVQ-ANN)和顺序指示符模拟(SIS)建模。描绘了一系列面向EW的透镜状地体。这些地体的厚度各不相同,它们会伸向西北,然后过渡到东北。SIS,UVQ-ANN,岩相分析和属性分析的结果显示了河流扇三角洲沉积系统。储层砂沉积在三角洲前缘近端的分布口条和三角洲河道中。粗粒至极细的储层砂向东北方向发展。在低能量条件下,在中层海洋环境中沉积了细颗粒的黑色页岩和石灰泥质粉砂岩的薄层床。生成的相模型所采用的方法可以扩展到巴基斯坦境内具有相同地质背景的不同盆地,并且可以用于前景评估,未来钻探,

更新日期:2021-04-27
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