A Core Logging, Machine Learning and Geostatistical Modeling Interactive Approach for Subsurface Imaging of Lenticular Geobodies in a Clastic Depositional System, SE Pakistan

被引:108
作者
Ashraf, Umar [1 ]
Zhang, Hucai [1 ]
Anees, Aqsa [1 ]
Mangi, Hassan Nasir [2 ]
Ali, Muhammad [3 ]
Zhang, Xiaonan [1 ]
Imraz, Muhammad [4 ]
Abbasi, Saiq Shakeel [5 ]
Abbas, Ayesha [6 ]
Ullah, Zaheen [7 ]
Ullah, Jar [3 ]
Tan, Shucheng [8 ]
机构
[1] Yunnan Univ, Inst Ecol Res & Pollut Control Plateau Lakes, Sch Ecol & Environm Sci, Kunming 650504, Yunnan, Peoples R China
[2] Wuhan Inst Technol, Sch XingFa Min Engn, Wuhan 430073, Peoples R China
[3] China Univ Geosci, Inst Geophys & Geomat, Wuhan 430074, Peoples R China
[4] China Univ Geosci, Sch Earth Sci, Wuhan 430074, Peoples R China
[5] Bahria Univ, Dept Earth & Environm Sci, Islamabad 44000, Pakistan
[6] NED Univ Engn & Technol, Dept Petr Engn, Karachi 75270, Pakistan
[7] China Univ Geosci, Fac Earth Resources, Wuhan 430074, Peoples R China
[8] Yunnan Univ, Sch Resource Environm & Earth Sci, Kunming 650500, Yunnan, Peoples R China
基金
中国国家自然科学基金;
关键词
Reservoir facies modeling; Sequential indicator simulation (SIS); Unsupervised machine learning; Facies classification; Sub-surface geobodies; 3D SEISMIC ATTRIBUTES; SOUTHERN INDUS BASIN; SAWAN GAS-FIELD; RESERVOIR CHARACTERIZATION; WELL LOGS; SHALE GAS; FACIES; IDENTIFICATION; SANDSTONES; QUALITY;
D O I
10.1007/s11053-021-09849-x
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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.
引用
收藏
页码:2807 / 2830
页数:24
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