Publications

Thin bed reservoirs are commonly found in a deltaic depositional environment, such as an alluvial channel, distributary channel, delta front, and shingled turbidite. The formation evaluation and hydrocarbon identification of these thin beds with log data is challenging, as the thickness of the reservoir is less than the vertical resolution of standard logging tools. Sand-shale lamination depresses further resistivity measurements. A new technique has been developed to analyze, evaluate, and interpret thin bed reservoirs using image data combined with standard openhole log data. Thin bed boundary and lithology classification were performed using image data and calibrated by comparison with core photos. From bed boundary and lithology classification, squared synthetic logs were generated from the statistical analysis of standard log data. Afterwards, a formation evaluation was performed using squared synthetic logs with core analysis data for calibration. The results of this new technique yield a better match with core analysis data compared with standard methods. This method not only leads to more accurate computation of shale volume, porosity, and saturation, but is also able to identify new pay zones not identified by standard interpretation methods. This paper shows the application of this new technique in thin bed evaluation in an offshore field in the Mahakam area, East Kalimantan. This technique provides an alternative for thin bed reservoir evaluation that could help to reduce costs for advanced formation evaluation and increase confidence levels in evaluating reservoir properties and potential hydrocarbon zones.