Integrated Assessment of Pilot Performance of Surface to In-Seam Wells to De-Risk and Quantify Subsurface Uncertainty for a Coalbed Methane Project: An Example from the Bowen Basin in Australia

Abstract

AbstractThis paper presents a detailed case study of using surface to in-seam wells to develop a major coalbed methane (CBM) field in the Bowen Basin of Australia. This study was novel in that special emphasis was given to quantification of subsurface property uncertainty and modeling of dynamic uncertainty. The result was the generation of recovery factor versus depth correlations which can be used to calculate the estimated ultimate recoverable.In this work, a 3D box model around three pilot wells was extracted from the regional static model. To quantify key subsurface uncertainties such as permeability, both the Percentile and Confidence Interval Methods were used. Trends of laboratory-measured parameters like gas content, ash, Langmuir volume, permeability were established. Reservoir properties without measurements such as cleat porosity, desorption time and relative permeability were estimated based on rules-of-thumb, basin-wide analogue or educated guesses. A reservoir simulation model was built and production data from pilot wells were manually history matched. Parametric analysis was conducted to determine key parameters that significantly affect model history matching and forecasting results. Given the complexities of the coal reservoir and the non-uniqueness of the history match, Experimental Design was used to generate a population of simulation models that sampled the uncertainty range of key reservoir properties. This ensemble was reduced to include only those that matched the pilot wells’ production. With different combinations of reservoir properties thus obtained, recovery factor versus depth correlations were generated.This study is a good example of early resource assessment critical to the field development planning of a major CBM field. It presents a systematic method to handle uneven distribution of often sparse subsurface data over a large geographic area which often confounds the CBM industry. Furthermore, this method may be extended to assess other well architectures like vertical, slant, horizontal, multi-branch, multi-lateral and hydraulically fractured vertical and horizontal wells.