| Popis: |
Because core porosity versus permeability relationships are often limited for predicting production performance, it is desirable to investigate alternative methodologies to improve permeability estimates. This paper presents a workflow using logging-while-drilling (LWD) sensor measurements, namely laterolog resistivities for permeability derivation and high-resolution microresistivity images for porosity partitioning. High-resolution microresistivity images were used for traditional picks of symmetric features, such as bedding planes and fractures, as well as for identification of asymmetric features, such as vugs or secondary porosity. The estimation of secondary porosity was based on several assumptions. In water water-based mud (WBM) systems, the encountered vugs during drilling will be filled with conductive fluid and hence display dark pixels on the high-resolution image. The determination of these features was based on a histogram of pixels created corresponding to a full azimuthal coverage. Next, an associated mean value and standard deviation were calculated, and any pixel values lower than the average minus a standard deviation was classified as a vug. The number of these pixels was then divided by the total count of all pixels, the fractional value of which then represented the ratio of secondary porosity with respect to total porosity. This ratio could then be converted into porosity units (pu) from any independent source. Permeability transform was based on the average image resistivity and/or conductivity values from button values, which were then normalized to an external permeability value or indicators; in this paper, these were formation tester mobility measurements. The workflow also entailed partitioning of the horizontal section to different intervals based on the derived permeability profiles and petrophysical attributes. Finally, the derived results from microresistivity and mobility measurements were analyzed to provide qualitative estimates of permeability, leading to identification of reservoir flow units. This paper presents a case study where the discussed methodology was applied and provided the derived interpreted results. Multiwell interpretation in this reservoir sector in the vicinity of the case study well, together with further data integration, is desirable to fine-tune this methodology and workflow. |
