Abstract
Sweet spots are the areas where reservoir parameters are suitable for maximum production with the least possible footprint and investment. The high complexity of reservoirs, absent or insufficient seismic data and the requirement of a great number of wells are the major challenges and hence, sweet spot identification during the exploration stage is key for the optimized appraisal of a Coal bed Methane (CBM) field. Identifying major controlling parameters that impact production is the first and foremost step towards demarcating the sweet spot.
A unique workflow consisting of reservoir characterization, modelling and simulation was used along with both short- and long-term uncertainty analysis. Different reservoir parameters analysis acquired from different sources like laboratory or field tests are critically analyzed to characterize reservoirs. Data were analyzed to define the range of variation of individual parameters to build reservoir models for uncertainty analysis. The single well models on each of the 50 cases were run in prediction mode in Eclipse as a dual-porosity system. The model results of estimated ultimate recovery (EUR) are plotted in a tornado plot to analyze the relative impact of each parameter.
From the analysis, it is found that Gas content, Permeability, thickness, and gas saturation are the dominant parameters for sweet spot demarcation although a few other parameters like bottom-hole pressure constraint, and relative permeabilities are also impacting the production, especially during early periods of production. As per plots, porosity also plays a role but as its range is very low, it could be ignored. It is interesting to note that the order of impacting parameters changes from long-term to short-term. In the long term, thickness and gas content i.e., resources play a bigger role than saturation, permeability, or relative permeability. But in the short term, which is important for the economic success of the field, permeability, saturation, and relative permeability plays a more important role. This helped in identifying sweet spots in this coal reservoir by shortlisting the areas where these dominant controlling parameters coexist and are well developed. Further, sweet spots are used to plan appraisal or pilot production test wells whose success ultimately leads to field-scale development.
The present study brings uniqueness in the form of an innovative workflow consisting of reservoir characterization, modelling, and simulation. This has been used along with both short and long-term uncertainty analysis that adds considerable value to the existing knowledge. This workflow can be applied in other reservoirs or basins which may help CBM exploitation time and cost effective and optimize the field development.
