Using population of models to investigate and quantify gas production in a spatially heterogeneous coal seam gas field |
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Affiliation: | 1. School of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia;2. ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, QLD 4000, Australia;3. Institute for Future Environments, Queensland University of Technology, Brisbane, QLD 4000, Australia;4. Visiting Professor, Department of Computer Science, University of Oxford, Oxford OX13QD, UK;5. Australian School of Petroleum, The University of Adelaide, Adelaide SA 5005, Australia;6. Arrow Energy Pty Ltd, Brisbane, QLD 4000, Australia |
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Abstract: |  In this work, we discuss the use of a local model developed previously [1] that describes the multiphase flow of gaseous species and liquid water within a single coal seam to investigate the gas production from a spatially heterogeneous production field. The field is located within the Surat Basin in Queensland, and is composed of a total of 80 production wells spread over a region covering approximately 36 km2. However, not every well is producing gas at any one time and so in this work we take a subset of 42 wells that are the top-producing wells in terms of total gas volume.We utilise a population of models approach to understand the variability in the underlying physical processes, and as a mechanism for dealing with the spatial heterogeneity that arises due to geological variation across the field. We are able to simultaneously obtain a family of parameter sets for each of these wells, in which each set in the family yields a predicted cumulative total gas production curve that matches the measured cumulative production curve for a given well to within an allowable limit of error.By analysing the results of this population of models approach we can identify the similarities between wells based on the parameter distributions, and understand the sensitivity of key model parameters. We show by example that high correlation between wells based on their parameter values may be an indicator of their similarity. A combinatorial sum of the predicted gas production is compared against the individual gas volumes (given in terms of percentage of the total volume) measured at the compression facility as a way of further calibrating a subpopulation of models. |
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