An integrated approach to defining well placement strategies for heterogeneous CSG reservoirs
Operators developing the vast CSG resources held in the Surat and Bowen basins of Queensland, Australia, face significant challenges. Given the heterogeneous nature of CSG reservoirs, and often sparse data from wells and 2D seismic, there are significant uncertainties regarding reservoir quality and productivity. The prolific number of wells required to extract the economic reserves (more than 30,000) requires workflows that can efficiently integrate information for rapid development planning. Traditionally, most of the efforts dedicated to assessing uncertainties in CSG reservoirs focus on the estimation of the gas-in-place (GIP), and how it varies laterally. Variations in productivity (mainly dependent on permeability) are usually more abrupt, have a larger impact on project economics, and are far less understood than the GIP. Authors such as Chopra and Marfurt (2012) have recently developed analytical methods using 3D seismic attributes to identify fractured areas with higher permeability. As well as permeability, other factors influencing productivity, such as GIP, thickness, depth and saturation, must be combined to define a complete well placement strategy. In this study, the authors propose a holistic approach for the assessment and integration of the uncertainties in CSG reservoirs, using the Baralaba Coal Measures in the Bowen Basin as a case study to demonstrate the workflow. Various seismic attributes are used to identify fracture drivers associated with faulting and folding around the Burunga Anticline structure, and map areas predicted to have higher permeability, calibrated against well production. Chance-of-success mapping is used to integrate the permeability heterogeneities with traditional well-derived maps of coal properties, such as gas content, to isolate sweet spots in the CSG reservoir. The integrated model is transformed into geological pseudo-cost and combined with surface development costs and restraints to automatically generate potential well placement scenarios.