干旱区生态环境知识资源中心(Arid): Integrated TOC prediction and source rock characterization using machine learning, well logs and geochemical analysis: Case study from the Jurassic source rocks in Shams Field, NW Desert, Egypt

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DOI	10.1016/j.petrol.2019.01.055
	Integrated TOC prediction and source rock characterization using machine learning, well logs and geochemical analysis: Case study from the Jurassic source rocks in Shams Field, NW Desert, Egypt
	Shalaby, Mohamed R.1,2; Jumat, Nurhazwana 1; Lai, Daphne 3,4; Malik, Owais 3,4
通讯作者	Jumat, Nurhazwana
来源期刊	JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
ISSN	0920-4105
EISSN	1873-4715
出版年	2019
卷号	176 页码:369-380
英文摘要	The machine learning methods and well log mathematical models have been used for predicting total organic carbon (TOC) in Jurassic source rock formations in Northwestern Desert, Egypt. Conventional well log data from two wells have been utilized for source rock study of Jurassic source rocks from Khatatba and Ras Qattara formations in the study area. The source rock is first studied based on geochemical parameters, which include assessments on the type and amount of kerogen present within the source rock samples. The Jurassic source rock samples have great generative potential and consist of mixed kerogen type III and kerogen type II-III. TOC content reaches up to 46.90% for Khatatba and 16.80% Ras Qattara. In the second part of this research, we attempt to characterize the Jurassic source rocks by using mathematical well log models and machine learning methods. GR, RHOB and NPHI well log data were used for TOC prediction using both methods. The quantified TOC results show that the R-2 values of well log models are above 0.9 for both formations, whereas the machine learning method using Artificial Neural Network showed R-2 value of 0.4. The results from the well log models suggest that they are applicable in the study area. This study has proven that well log data can be used with confidence to evaluate organic source quantity of Jurassic rocks in Northwestern Desert in the absence of geochemical data.
英文关键词	Machine learning Artificial neural network Geochemical analysis Well log data Source rock Jurassic Egypt
类型	Article
语种	英语
国家	Brunei ; Egypt
收录类别	SCI-E
WOS记录号	WOS:000460395200030
WOS关键词	NORTHERN WESTERN DESERT ; ORGANIC-CARBON CONTENT ; APPALACHIAN DEVONIAN SHALES ; DEPOSITIONAL ENVIRONMENT ; KAZHDUMI FORMATION ; KHATATBA FORMATION ; SHUSHAN BASIN ; WIRELINE LOGS ; GENERATION ; RESERVOIR
WOS类目	Energy & Fuels ; Engineering, Petroleum
WOS研究方向	Energy & Fuels ; Engineering
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/217263
作者单位	1.Univ Brunei Darussalam, Dept Phys & Geol Sci, Jalan Tungku Link, BE-1410 Gadong, Brunei; 2.Tanta Univ, Geol Dept, Fac Sci, Tanta, Egypt; 3.Univ Brunei Darussalam, Dept Math, Jalan Tungku Link, BE-1410 Gadong, Brunei; 4.Univ Brunei Darussalam, Inst Appl Data Analyt, Jalan Tungku Link, BE-1410 Gadong, Brunei
推荐引用方式 GB/T 7714	Shalaby, Mohamed R.,Jumat, Nurhazwana,Lai, Daphne,et al. Integrated TOC prediction and source rock characterization using machine learning, well logs and geochemical analysis: Case study from the Jurassic source rocks in Shams Field, NW Desert, Egypt[J],2019,176:369-380.
APA	Shalaby, Mohamed R.,Jumat, Nurhazwana,Lai, Daphne,&Malik, Owais.(2019).Integrated TOC prediction and source rock characterization using machine learning, well logs and geochemical analysis: Case study from the Jurassic source rocks in Shams Field, NW Desert, Egypt.JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING,176,369-380.
MLA	Shalaby, Mohamed R.,et al."Integrated TOC prediction and source rock characterization using machine learning, well logs and geochemical analysis: Case study from the Jurassic source rocks in Shams Field, NW Desert, Egypt".JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 176(2019):369-380.