Few attempts have been made to model shale gas reservoirs on a compositional basis. Multiple distinct micro-scale physical phenomena influence the transport and storage of reservoir fluids in shale, including differential desorption, preferential Knudsen diffusion, and capillary critical effects. Concerted, these phenomena cause a measureable compositional change in the produced gas over time.
We developed a compositional numerical model capable of describing the coupled processes of diffusion and desorption in ultra-tight rocks as a function of pore size. The model captures the various fracture configurations believed to be induced by shale gas fracture stimulations. By combining the macro-scale (reservoir-scale fractures) and micro-scale (diffusion through nanopores) physics, we show how gas composition changes spatially and temporally during production.
We compare our numerical model against measured gas composition data obtained at regular intervals from shale gas wells. We utilize the characteristic behavior illustrated in the model results to identify and to define features in the measured data. We present a workflow for the integration of measured gas composition data into production data analysis tools in order to develop a more complete well performance diagnostic process.
The onset of fracture interference in horizontal wells with multiple transverse hydraulic fractures is shown to be uniquely identified by distinct fluctuations in the flowing gas composition. Using these measured composition data, the timescale and durations of the transitional flow regimes in shales are quantified, even for high levels of noise in the rate and pressure data. Reservoir properties are inferred from the integration of the compositional shift analysis of this work with modern production analysis.
This work expands the current understanding of well performance for shale gas to include physical phenomena that lead to compositional change. This may be used to optimize fracture and completion design, improve well performance analysis and provide more accurate reserves estimation.
This work demonstrates a numerical model which captures multicomponent desorption, diffusion, and phase behavior in ultra-tight rocks. We identify and validate diagnostic trends via high-resolution composition, saturation and pressure maps. We provide a workflow for incorporating measured gas composition data into modern production analysis.