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An integrated approach for the identification of lithofacies and clay mineralogy through Neuro-Fuzzy, cross plot, and statistical analyses, from well log data
Journal of Earth System Science ( IF 1.3 ) Pub Date : 2020-03-24 , DOI: 10.1007/s12040-020-1365-5
Muhsan Ehsan , Hanming Gu

Today, researchers face multiple challenges identifying clay mineral types and lithofacies from well log data. This research paper hopes to offer new insight into this particular challenge. Formation evaluation characteristics play a significant role in the exploration and production of future and current oil and gas fields. The proposed methodology in this study uses an integrated approach that includes: (1) numerical equations, (2) Neuro-Fuzzy neural networks, (3) cross plots, and (4) statistical analyses. This proposed integrated approach is capable of dramatically improving the accuracy of the results. Well logging data provide valuable information for identifying lithofacies, clay mineralogy types, as well as other important hydrocarbon reservoir characteristics. Talhar Shale in the Southern Lower Indus Basin, Pakistan, is composed of interbedded shale, sand, and shaly-sand, intervals that have been identified via the lithological interpretation process of well logs. Talhar Shale contains montmorillonite type clay with minor amounts of illite, glauconite, and various micas that can be easily identified by natural gamma ray absorption profiles, as well as through ratio logs, bulk density log, and photoelectric absorption index log. These interpretations can be further confirmed via cross plots and other statistical analyses. This approach consists of a comprehensive study of well logging data and thus can lend itself to be a helpful component in characterizing the hydrocarbon structures of the Talhar Shale.



中文翻译:

一种通过Neuro-Fuzzy,剖面图和统计分析从测井数据中识别岩相和粘土矿物学的综合方法

如今,研究人员面临着从测井数据中识别粘土矿物类型和岩相的多重挑战。这篇研究论文希望为这一特殊挑战提供新的见解。地层评价特征在未来和当前油气田的勘探和生产中起着重要作用。本研究中提出的方法论采用了一种综合方法,包括:(1)数值方程式;(2)Neuro-Fuzzy神经网络;(3)交叉图;以及(4)统计分析。提出的集成方法能够显着提高结果的准确性。测井数据为识别岩相,粘土矿物学类型以及其他重要的油气藏特征提供了有价值的信息。巴基斯坦下印度河南部盆地的Talhar页岩,由层状页岩,沙子和页岩砂组成,这些层段已通过测井的岩性解释过程确定。Talhar页岩含有蒙脱石型粘土,其中含有少量的伊利石,青绿石和各种云母,可以通过自然伽马射线吸收曲线以及比率记录,堆积密度记录和光电吸收指数记录轻松识别。这些解释可以通过交叉图和其他统计分析得到进一步确认。这种方法包括对测井数据的全面研究,因此可以成为表征Talhar页岩烃结构的有用成分。Talhar页岩含有蒙脱石型粘土,其中含有少量的伊利石,青绿石和各种云母,可以通过自然伽马射线吸收曲线以及比率记录,堆积密度记录和光电吸收指数记录轻松识别。这些解释可以通过交叉图和其他统计分析得到进一步确认。这种方法包括对测井数据的全面研究,因此可以成为表征Talhar页岩烃结构的有用成分。Talhar页岩含有蒙脱石型粘土,其中含有少量的伊利石,青绿石和各种云母,可以通过自然伽马射线吸收曲线以及比率记录,堆积密度记录和光电吸收指数记录轻松识别。这些解释可以通过交叉图和其他统计分析得到进一步确认。这种方法包括对测井数据的全面研究,因此可以成为表征Talhar页岩烃结构的有用成分。这些解释可以通过交叉图和其他统计分析得到进一步确认。这种方法包括对测井数据的全面研究,因此可以成为表征Talhar页岩烃结构的有用成分。这些解释可以通过交叉图和其他统计分析得到进一步确认。这种方法包括对测井数据的全面研究,因此可以成为表征Talhar页岩烃结构的有用成分。

更新日期:2020-04-16
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