Search

Your search keyword '"Zhikun, Wei"' showing total 10 results
Start Over Author "Zhikun, Wei"
10 results on '"Zhikun, Wei"'

6. Characteristics of lacustrine organic-rich shale: A case study of the Chang 7 member, Triassic Yanchang Formation, Ordos Basin, China

Author

Chuang Er, Yangyang Li, Jingzhou Zhao, Rui Wang, and Zhikun Wei

Subjects
Organic-rich shale, Shale oil and gas, Depositional environment, Shale distribution, Yanchang Formation, Gas industry, TP751-762
Abstract

This paper presents a case study of lacustrine organic-rich shale from the Yanchang Formation, Ordos Basin, China. Sedimentary and geochemical analyses were performed on shale acquired from the Chang 7 member through its outcrop, core and thin section data indicate that depositional environments have a great impact on the distribution and quality of shale reservoirs. Shale in the Chang 7 member was interpreted to have been deposited mainly in delta-front and deep-lake environments. Delta-front shale is 2–10 m thick (average ∼5 m), laterally discontinuous and commonly interbedded with equally thick layers of sandstone. In contrast, deep-lake shale is 5–74 m thick (average ∼21 m), laterally continuous and locally interbedded with thin layers of sandstone. Delta-front shale was mostly massive without obvious sedimentary structures while deep-lake shale was characterized by abundant horizontal laminations. More importantly, delta-front shale primarily contains Type Ⅱ1 and Ⅲ kerogen, with TOC commonly less than 2%. In comparison, deep-lake shale primarily contains Type Ⅰ and Ⅱ1 kerogen, with TOC mostly higher than 2%. Based on the analysis and comparison between shales deposited in two types of environments, it is suggested that deep-lake shales in the Chang 7 member were favorable exploration target for hydrocarbons.

Published
2016
Full Text
View/download PDF

8. Cooperative Fraud Detection Model With Privacy-Preserving in Real CDR Datasets

Author

Zhikun Wei, Jienan Liu, and Na Ruan

Subjects
General Computer Science, Cover (telecommunications), Computer science, business.industry, General Engineering, data mining, security, computer.software_genre, Latent Dirichlet allocation, real-world scenario, Privacy preserving, symbols.namesake, symbols, Differential privacy, General Materials Science, Mobile telephony, Data mining, lcsh:Electrical engineering. Electronics. Nuclear engineering, Roaming, spam detection, business, computer, Data privacy, lcsh:TK1-9971
Abstract

The researchers have shown broad concern about detection and recognition of fraudsters since telecommunication operators and the individual user are both suffering significant losses from fraud activities. Researchers have proposed various solutions to counter fraudulent activity. However, those methods may lose effectiveness in fraud detection because fraudsters always tend to cover their tracks by roaming among different telecommunication operators. What is more, due to the lack of real data, researchers have to do simulations in a virtual scenario, which makes their models and results less persuasive. In our previous paper, we proposed a novel strategy with high accuracy and security through cooperation among mobile telecommunication operators. In this manuscript, we will validate it in a real-world scenario using real Call Detail Records(CDR) data. We apply the Latent Dirichlet Allocation (LDA) model to profile users. Then we use a method based on Maximum Mean Discrepancy (MMD) to compare the distribution of samples to match roaming fraudsters. Cooperation between telecommunication operators may boost the accuracy of detection while the potential risk of privacy leakage exists. A strategy based on Differential Privacy(DP) is used to address this problem. We demonstrate that it can detect the fraudsters without revealing private data. Our model was validated using simulated dataset and showed its effectiveness. In this manuscript, experiments are performed on real CDRs data, and the result shows that our method has impressive performance in the real-world scenario as well.

Published
2019

10. Potential and trend prediction of unconventional oil and gas resources based on combination forecasting model of variable weight for multi-factor.

Author

Yu, Hu, Rui, Lv, Zhikun, Wei, Jie, Zuo, Tingshan, Zhang, Ran, Chen, and Yiqiao, Xu

Subjects
PETROLEUM industry, SIMULATION methods & models
Abstract

In order to increase the potential and trend prediction accuracy of unconventional oil and gas resources, a potential and trend prediction method of unconventional oil and gas resources based on combination forecasting model of variable weight for multi-factor is proposed. First of all, the present situation and trend of oil and gas resources development are analyzed and introduced. It is pointed out that it is influenced and restricted by many factors and external environment, which shows the characteristics of its complexity and non-linear historical evolution trend. Secondly, the optimal variable weights are determined by using the variable weight combination forecasting model and then the potential and trend prediction accuracy of unconventional oil and gas resources is realized to be increased. Finally, the validity of the proposed method is verified by the simulation experiment. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results