Integrated rock-typing approach considering petrophysics, geology and diagenesis / I. I. Churochkin

Уровень набора: (RuTPU)RU\TPU\prd\225573, 2312-2978, Journal of Economics and Social Sciences, electronic scientific journal = 2012-Основной Автор-лицо: Churochkin, I. I., geophysicist, Research Engineer, Tomsk Polytechnic University, 1993-, Iljya IgorevichКоллективный автор (вторичный): School of Earth Sciences & Engineering, National Research Tomsk Polytechnic UniversityЯзык: английский.Страна: Россия.Описание: 1 файл (369 Кб)Серия: Социологические наукиРезюме или реферат: Development of oil and gas field with carbonate reservoirs is quite challenging due to its high heterogeneity (diagenesis, fractures, wetting, leaching, recrystallization etc.). There is no universal rock-typing methodology in order to define groups of rocks in petrophysics, geology and diagenesis. This work proposed integrated approach of rock-typing by using clustering algorithms. At the first stage three homogeneous groups were defined by using well logs. Then the groups were confirmed by lithological description of the core data and capillary pressure curves. For further development, it is better to try different clustering algorithms and use data from several wells simultaneously. This will help to construct geological model..Примечания о наличии в документе библиографии/указателя: [References: 2 tit.].Тематика: труды учёных ТПУ | электронный ресурс | carbonates | rock typing | machine learning Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: 2 tit.]

Development of oil and gas field with carbonate reservoirs is quite challenging due to its high heterogeneity (diagenesis, fractures, wetting, leaching, recrystallization etc.). There is no universal rock-typing methodology in order to define groups of rocks in petrophysics, geology and diagenesis. This work proposed integrated approach of rock-typing by using clustering algorithms. At the first stage three homogeneous groups were defined by using well logs. Then the groups were confirmed by lithological description of the core data and capillary pressure curves. For further development, it is better to try different clustering algorithms and use data from several wells simultaneously. This will help to construct geological model.

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