Applications of
Image Log Data in the Characterization of a Jurassic Carbonate
Russell, S. Duffy1, Weihua Wang2 (1) Saudi Arabian Oil Company,
Dhahran, Saudi Arabia (2) Schlumberger Middle East, Al-Khobar,
Saudi Arabia
This study demonstrates the use of image
logs for characterizing carbonate reservoirs beyond fracture characterization.
The study will show sedimentary structures, permeability transforms and produce
synthetic production logs. First, the sedimentary parameters of rock fabric and
texture, sedimentary structures and surfaces, and skeletal macrofossils are
observed in image log data. Cladocoropsis floatstones, domal stromatoporoid rudstones, and vuggy dolomites have recognizable fabrics and textures that
are important for the characterization of highly productive intervals. After
calibration with core data, image logs provide accurate estimations of dolomite
percentage in mud-dominated intervals. Key sedimentary structures, such as
cross-bedding in oolitic-peloidal grainstones,
mark cycle tops for sequence stratigraphic
interpretation. The identification of large skeletal macrofossils, such as stromatoporoids and corals, provides unique facies recognition. Second, petrophysical
parameters are quantified for the observed rock textures and facies using image log data. After special processing and
calibration with core data, partitioning of the porosity network into matrix
and vuggy porosity percentages through porosity image
analysis yields an estimation of permeability using modified
porosity-permeability transforms. The image-derived, high-resolution
permeability characterizes thin bed and vuggy
heterogeneity. Third, the spectrum of total porosity and permeability values is
divided into classes of reservoir rock types, which are used to predict trends
in reservoir quality. Image-derived permeability is transformed into
pseudo-production logs. Flow percentage predicted from image-derived
permeability is shown to match actual flow meter data.
AAPG Search and Discover Article #90063©2007 AAPG Annual Convention, Long Beach, California