A genetic algorithm–driven support vector machine to discriminate the kerogen type using conventional geophysical logging data

IF 2.7 3区地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY

AAPG Bulletin Pub Date : 2023-11-01 DOI:10.1306/08022320102

Jier Zhao, Xinmin Ge, Yiren Fan, Jianyu Liu, Yiguo Chen, Lei Xing

引用次数: 0

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基于遗传算法的支持向量机在常规地球物理测井资料中识别干酪根类型

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

AAPG Bulletin 工程技术-地球科学综合

CiteScore

6.60

自引率

11.40%

发文量

审稿时长

4.8 months

期刊介绍： While the 21st-century AAPG Bulletin has undergone some changes since 1917, enlarging to 8 ½ x 11” size to incorporate more material and being published digitally as well as in print, it continues to adhere to the primary purpose of the organization, which is to advance the science of geology especially as it relates to petroleum, natural gas, other subsurface fluids, and mineral resources. Delivered digitally or in print monthly to each AAPG Member as a part of membership dues, the AAPG Bulletin is one of the most respected, peer-reviewed technical journals in existence, with recent issues containing papers focused on such topics as the Middle East, channel detection, China, permeability, subseismic fault prediction, the U.S., and Africa.