Applicability of existing numerical simulation methodologies to unconventional reservoirs is questionable and requires investigation and research.

We have focused on gas flow simulation of a highly heterogeneous fractured reservoir with extremely low matrix permeability. First of all we have considered the key roadmap components, natural gas composition, rock properties, critical elements and the main features inherent in tight and shale gas reservoir engineering. Using field reference data and a reservoir simulator, different scenarios of gas production have been modelled. This paper presents results from a sensitivity study of the dimension of hydraulic fracturing stimulated reservoir volume (SRV), matrix and propped fracture permeability which is spatially varied as one of the most realistic approaches, and of the bottom hole pressure. The approaches "dual porosity -single permeability", "dual porosity -dual permeability" and key reservoir properties have been reconsidered for specific geological and technological conditions in order to support decision making in unconventional reservoir management. Assuming pseudo-steady state gas flow, the simulation time step and gridblock size have been adjusted with a sector model represented by a logarithmically refined grid. In comparison with previous studies, it has been stated that the proposed approach of discrete fracture network modeling can be used in cases where the dual medium approach is questionable or inappropriate. The simulations of flow that have been performed, showed that the contribution of unstimulated reservoir volume (in the vicinity of the SRV) to gas production is non-negligible and can be a significant part of gas production to be taken into account in some field cases.

The results of this study can be used in unconventional reservoir modeling and flow simulation to identify development, stimulation, and completion strategies aimed at optimization of gas production, reservoir performance and gas recovery. The proposed approach also supports risk and uncertainty analysis, revenue estimation and economic performance evaluation.

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