--> Abstract: Applications of Image Log Data in the Characterization of a Jurassic Carbonate Reservoir, Saudi Arabia; #90063 (2007)
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Applications of Image Log Data in the Characterization of a Jurassic Carbonate Reservoir, Saudi Arabia

 

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 Previous HitstratigraphicNext Hit Previous HitinterpretationTop. 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