Support-vector-regression machine technology for total organic carbon content prediction from wireline logs in organic shale: A comparative study-Reference-Cited by-同舟云学术

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Support-vector-regression machine technology for total organic carbon content prediction from wireline logs in organic shale: A comparative study

Published:2015-09 Issue: Volume:26 Page:792-802
ISSN:1875-5100
Container-title:Journal of Natural Gas Science and Engineering
language:en
Short-container-title:Journal of Natural Gas Science and Engineering

Author:

Tan Maojin^ORCID,Song Xiaodong,Yang Xuan,Wu Qingzhao

Funder

National Natural Science Foundation of China

Development of Major Oil and Gas Fields and Coal Bed Methane

Publisher

Elsevier BV

Subject

Energy Engineering and Power Technology,Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference37 articles.

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2. A Tutorial on Support Vector Regression, NeuroCOLT2 Technical Report NC-TR-98–030;Alex,1998

3. Estimating total organic carbon content and source rock evaluation, applying delta logR and neural network methods: Ahwaz and Marun Oilfields, SW of Iran;Bakhtiar;Petrol. Sci. Technol.,2011

4. Early Toarcian source-rock potential in the central high atlas basin (central morocco): regional distribution and depositional model;Bodin;J. Petrol. Geol.,2011

5. Wireline logging and source rocks estimation of organic carbon by the Carbolog method;Carpentier;Log Anal.,1991

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