Methods of calculating porosity without logging porosity data
Su Jing
Abstract
Su Jing
Abstract
Aiming at the well fields without logging porosity data, we can use type log data to establish porosity interpretation model through core scaling method. There are two common porosity models which are established by SP reduction factor and apparent resistivity. After comparing these two models with the model established by shale content parameters, we found that porosity calculated by shale content porosity model is relatively more coincided with the porosity that calculated by core analysis and its mean absolute deviation is 0.162, while the mean relative deviation is 5.934%. So it is believed that applying shale content porosity interpretation model to calculate reservoir porosity is relatively more accurate in the study area. Thereby, a feasible method is supplied to evaluate reservoir and quantitatively calculate reservoir parameters by using type log data.
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Aiming at the well fields without logging porosity data, we can use type log data to establish porosity interpretation model through core scaling method. There are two common porosity models which are established by SP reduction factor and apparent resistivity. After comparing these two models with the model established by shale content parameters, we found that porosity calculated by shale content porosity model is relatively more coincided with the porosity that calculated by core analysis and its mean absolute deviation is 0.162, while the mean relative deviation is 5.934%. So it is believed that applying shale content porosity interpretation model to calculate reservoir porosity is relatively more accurate in the study area. Thereby, a feasible method is supplied to evaluate reservoir and quantitatively calculate reservoir parameters by using type log data.
Key concepts: Porosity, Oil shale, Geology, Effective porosity, Well logging, Mineralogy, Core (optical fiber), Soil science