Отправлено: 21.08.18 13:09. Заголовок: Новая (свежая) оценка взаимосвязи проницаемости с пористостью и компонентным составом

Estimating permeability of shale gas reservoirs from porosity and rock compositions
Peiqiang Zhao, Jianchao Cai, Zhenhua Huang, Mehdi Ostadhassan, Fuqiang Ran
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Для нетрадиционных коллекторов с компонентным составом
авторы на 30-ти образцах обосновывают расширенный вариант уравнения Herron-Herron
Расширение подхода за счёт учёта большего числа компонент
Все образцы имеют проницаемость ниже сотых долей миллидарси
Регрессии но на 30 образцов 7 коэффициентов

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It is challenges for effectively estimating the permeability of shale gas reservoirs by
traditional models, however, the study on this area is lacked and deficient. We proposed a
method for predicting permeability of shale gas reservoirs from porosity and rock
compositions including mineralogy and organic matter content, which is applicable to
laboratory data and downhole measurements. First, two sets including 38 samples from the
Longmaxi Formations were tested for porosity, permeability, grain density, total organic
carbon (TOC) content, mineralogical compositions and low temperature nitrogen adsorption.
We used the Kozeny’s equation to calculate the specific surface area, which was viewed as
the effective specific surface in shale formations through comparing with the specific surface
from low temperature nitrogen adsorption. Further, the effective specific surface was found to
be positively correlated with clays, pyrite, and TOC contents, while negatively with quartz,
feldspar and carbonates. Then, an empirical equation between the effective specific surface
area and rock compositions was established via partial least square method which can process
the serious multi collinearity of various mineral contents. Combining with Kozeny’s equation,
this equation enabled a prediction of permeability from porosity and rock composition. The
results showed that the predicted and measured permeability have a reasonable match.
Comparing with other models, this method avoids the correlations between porosity and
minerals, providing a better insight to the influence of minerals and organic matter on
permeability. The influences of rock compositions on the permeability are different, which
are caused by the different types and sizes of pores developed within the minerals and organic
matter. In addition, the new method was successfully applied to the well log data from a shale
gas well for permeability predictions.