1980 -2021年储层数值岩相识别文献计量学分析

I. S. Ronoatmojo, Muhamad Apriniyadi, R. Nugraheni, C. P. Riyandhani, C. Rosyidan, Y. Sutadiwiria
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引用次数: 1

摘要

“电相”一词由Serra和Abbott于1980年提出,自2009年以来得到了迅速发展。这一发展主要是由有线测井技术和人工智能技术引发的。电相分类是为了便于储层表征的研究。然而,由于沉积环境和地质过程的独特性,涉及到许多物理性质,因此很难确定地表述。至少有369篇文章是在1980 - 2021年期间从Scopus来源获得的。在文献计量学分析中,我们将文章重新分为四组,即“模式识别”、“相分析”、“目标”和“质量”。利用VOSviewer软件采用共现、合著、引文分析和书目耦合等方法进行分组。主题之间的距离和耦合将决定它们之间讨论的质量和数量。物镜的质量在于受运输或成岩事件控制的岩性的确定性值。例如,砂和页岩属硅质碎屑岩性,其确定性程度将高于碳酸盐岩。因此,在人工智能的应用过程中,特别是对于复杂的相和不确定的地质条件,存在较大的差距。不涉及地质分析,人工智能的应用不仅仅是功能性的。这意味着,从这一角度来看,电相的作用还需要进一步的研究,因此,如果不建立成岩过程的模型,电相的作用就不能独立存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BIBLIOMETRIC ANALYSIS ON NUMERICAL LITHOFACIES IDENTIFICATION FOR RESERVOIR CHARACTERIZATION IN THE PERIOD OF 1980 -2021
The term "electrofacies" was introduced in 1980 by Serra and Abbott, it had been developed promptly since 2009. The development was triggered predominantly by wireline logging technology and artificial intelligence technology. The electrofacies categorization  was intended to facilitate the study of reservoir characterization. However, it is difficult to formulate deterministically, due to the uniqueness of the depositional environment and geological processes that involve many physical properties. At least, there are 369 articles which were obtained from Scopus sources in the period of 1980 - 2021. In this bibliometric analysis, we regrouped the articles into four groups, i.e. “pattern recognition” “facies analysis”, “objectives” and “quality”. This grouping was attained on the methods of co-occurences, co-authorship, citation analysis and bibliographic coupling using VOSviewer software. The distance and coupling between themes will determine the level of quality and quantity of discussion between them. The quality of the objective resides in the certainty value of the lithology controlled by transportation or diagenetic events. For example, sand and shale which are siliciclastic lithology will have a higher degree of certainty than carbonate rocks. Therefore, the wide gap occurred during the application of artificial intelligence, especially for complex facies and uncertain geological conditions. The application of artificial intelligence is not solely functional without involving geological analysis. The implication is some researchs are still needed from this point of view, so the electrofacies role cannot be independent without developing models of the diagenetic process.
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