Publications

Shale gas remains one of the most challenging issues in the petroleum industry due to its reservoir ultra-low permeability. This paper works toward delineating sweet spot and distribution of potential shale gas reservoir based on integrated geochemical, geophysical, petrophysical and geomechanical assessments using both surface and subsurface data, focusing on interbedded sandstone-carbonaceous shale in the Eocene interval of the Upper Kutai Basin. Field observation and detailed measuring section are major sources of surface data used in this study. It is combined with 2 key items of well data and 31 2D seismic lines to represent subsurface data. In addition, geochemical data based on representative samples of the outcrop is a beneficial quantitative parameter to support lithology description. Subsequently, subsurface assessment, including facies and depositional environment reconstruction, shale reservoir properties quantification (shaliness, porosity, saturation, TOC, brittleness index) through advanced petrophysical analysis are compelled to identify sweet spots based on 3D static reservoir modeling assisted by seismic attribute comprehension combined with maturity model. By integrating outcrop descriptions and samples of rock eval pyrolysis, carbonaceous shales come up with averaged Total Organic Carbon (TOC) 1% wt, type III kerogen in mature condition (Tmax 450�o C). Electrofacies and stacking pattern analysis illustrate the typical characteristics of fluvio-deltaic deposit trending NW-SE. Conventional gamma ray and neutron-density evaluation reveal high shaliness (>70% shale volume) and low porosity (~5% average) while Passey methods involving sonic and resistivity log combined with level of maturity (LOM) produces TOC (0.7 to 1.2% wt.) matches TOC from surface data. Brittleness index (BI) is defined based on Modulus Young and Poisson; Ratio quantification from a combination of sonic log, effective porosity and shaliness, resulting >0.32 BI, classified as less brittle to brittle shale. All of these reservoir properties are distributed by following Root Mean Square (RMS) amplitude map through 3D reservoir modeling shows NW-SE trend follows regional sedimentation direction.