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  2. 地质与地球物理研究所
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  4. 深部资源勘探装备研发
"Geology-geophysics-data mining" integration to enhance the identification of deep fault-controlled paleokarst reservoirs in the Tarim Basin

文献类型：期刊论文

作者Tian, Fei4,5,6; Zhang, Jiangyun4,5,6; Zheng, Wenhao4,5,6; Zhou, Hui3; Ma, Qihao2; Shen, Chunguang1; Ma, Qingyou7; Lan, Mingjie7; Liu, Yunchen5,6
刊名MARINE AND PETROLEUM GEOLOGY
出版日期2023-12-01
卷号158页码:15
ISSN号0264-8172
关键词Fault-controlled paleokarst reservoirs Machine learning algorithm Reservoir identification Tarim basin
DOI10.1016/j.marpetgeo.2023.106498
英文摘要Large-scale strike-slip faults play a dual role as conduits for fluid flow, channeling both atmospheric freshwater and deep hydrothermal fluids, thereby creating porous carbonate reservoirs at significant depths. Moreover, these faults serve as vertical conduits, connecting deep source rocks to oil and gas reservoirs capable of generating substantial hydrocarbon fields. In recent years, the Tarim Basin has yielded numerous high-yield reservoirs along large-scale strike-slip faults, exhibiting exceptional hydrocarbon potential. Nevertheless, the intricate heterogeneity of deep-seated traps engendered by these faults presents a formidable challenge in accurately determining reservoir geometry, consequently complicating the drilling of high-yield wells. Currently, enhancing the precision of reservoir identification stands as a paramount issue within the Tarim Basin.This paper introduces an innovative solution termed the "Geology-Geophysics-Data Mining" workflow, designed to enhance the resolution of multiscale geophysics data through the lens of geological insights. Drawing inspiration from the geological model of "fault-controlled paleokarst," and utilizing a fusion of well logs and seismic data, we elect seismic impedance as a discerning parameter to differentiate between porous reservoirs and impermeable host rocks. The proposed methodology unfolds through several steps.Primarily, noise reduction and frequency domain extension of the original seismic data are achieved through spectral shaping and diffusion filtering algorithms. Subsequently, the impedance curve of the logging wave is computed, establishing a non-linear correlation with seismic waveforms using a waveform indication inversion algorithm, ultimately yielding inverse impedance data. In the subsequent phase, the impedance originating from stable sedimentary features is quantified and subsequently extracted from the inversely derived seismic data. This step accentuates the high-quality reservoirs formed via fault-controlled karstification. Ultimately, we validate the identification of reservoir geometry using interpretations from well log data and drilling outcomes. Furthermore, this paper employs the seismic impedance obtained from wellbore logging data as "hard data" and deploys machine learning algorithms to map this information to three-dimensional high-precision seismic data. Following the removal of sedimentary features' influence, we extract the longitudinal connectivity and transverse mutation characteristics inherent in fault-controlled paleokarst reservoirs. This extraction enables the capture of geometric structural information related to fault-controlled paleokarst reservoirs, further substanti-ating the geological distribution of effective reservoirs controlled by strike-slip faults. These findings establish a dependable foundation for directional drilling and studies focused on hydrocarbon accumulation. Notably, the "Geology-Geophysics-Data Mining" approach is extendable to analogous strongly heterogeneous reservoirs.
WOS关键词TAHE OIL-FIELD ; ORDOVICIAN CARBONATE RESERVOIRS ; HYDROCARBON ACCUMULATION ; SYSTEM ; AREA ; ATTRIBUTES ; ORIGIN ; UPLIFT ; DAMAGE ; GAS
资助项目Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences[2021063] ; Chinese National key research and development program[2019YFA0708301] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA14050101] ; Chinese National Natural Science Foundation[41502149] ; Chinese National Natural Science Foundation[U1663204] ; China National Petroleum Corporation (CNPC) Scientific research and technology development project[2021DJ05] ; China National Petroleum Corporation (CNPC) Scientific research and technology development project[H2020009]
WOS研究方向Geology
语种英语
出版者ELSEVIER SCI LTD
WOS记录号WOS:001088774700001
资助机构Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Youth Innovation Promotion Association Foundation of the Chinese Academy of Sciences ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Chinese National key research and development program ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; Chinese National Natural Science Foundation ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project ; China National Petroleum Corporation (CNPC) Scientific research and technology development project
源URL[http://ir.iggcas.ac.cn/handle/132A11/110728]  
专题地质与地球物理研究所_深部资源勘探装备研发
通讯作者Zhang, Jiangyun
作者单位1.PetroChina Tarim Oilfield Co, Korla 841000, Xinjiang, Peoples R China
2.Bohai Drilling Corp, Sinopec Shengli Petr Engn Co Ltd, Dongying 257200, Peoples R China
3.PetroChina, Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
4.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R China
5.Chinese Acad Sci, Innovat Acad Earth Sci, Beijing 100029, Peoples R China
6.Chinese Acad Sci, Inst Geol & Geophys, CAS Engn Lab Deep Resources Equipment & Technol, Beijing 100029, Peoples R China
7.SINOPEC, Northwest Oilfield Co, Urumqi 830011, Xinjiang, Peoples R China
推荐引用方式
GB/T 7714		 Tian, Fei,Zhang, Jiangyun,Zheng, Wenhao,et al. "Geology-geophysics-data mining" integration to enhance the identification of deep fault-controlled paleokarst reservoirs in the Tarim Basin[J]. MARINE AND PETROLEUM GEOLOGY,2023,158:15.
APA Tian, Fei.,Zhang, Jiangyun.,Zheng, Wenhao.,Zhou, Hui.,Ma, Qihao.,...&Liu, Yunchen.(2023)."Geology-geophysics-data mining" integration to enhance the identification of deep fault-controlled paleokarst reservoirs in the Tarim Basin.MARINE AND PETROLEUM GEOLOGY,158,15.
MLA Tian, Fei,et al.""Geology-geophysics-data mining" integration to enhance the identification of deep fault-controlled paleokarst reservoirs in the Tarim Basin".MARINE AND PETROLEUM GEOLOGY 158(2023):15.

入库方式： OAI收割

来源：地质与地球物理研究所

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