Abstract

Advancements in horizontal well drilling and multistage hydraulic fracturing have made gas production from tight formations economically viable. Reservoir simulation models play an important role in the production forecasting and field development planning. To enhance their predictive capabilities and capture the uncertainties in model parameters, stochastic reservoir models should be calibrated to both geologic and flow observations.

In this paper, a novel approach to characterization and history matching of hydrocarbon production from a hydraulic fractured shale gas is presented. This new methodology includes generating multiple discrete fracture network (DFN) models, upscaling the models for numerical multiphase flow simulation, and updating the DFN model parameters using dynamic flow responses. First, measurements from hydraulic fracture treatment, petrophysical interpretation, and in-situ stress data are used to estimate the initial probability distribution of hydraulic and induced micro fractures parameters, and multiple initial DFN models are generated. Next, the DFN models are upscaled into an equivalent continuum dual porosity model using either analytical (Oda) or flow-based techniques. The upscaled models are subjected to the flow simulation, and their production performances are compared to the actual responses. Finally, an assisted history matching algorithm is implemented to assess the uncertainties of the DFN model parameters. Hydraulic fracture parameters including half-length, shape, and conductivity are updated together with the length, conductivity, intensity, and spatial distribution of the induced fractures are optimized in the algorithm.

The proposed methodology is applied to facilitate characterization of fracture parameters of a multi-fractured shale gas well in the Horn River basin. Fracture parameters and stimulated reservoir volume (SRV) derived from the updated DFN models are in agreement with estimates from micro-seismic interpretation and rate transient analysis. The key advantage of this integrated assisted history matching approach is that uncertainties in fracture parameters are represented by the multiple equall-probable DFN models and their upscaled flow simulation models, which honor the hard data and match the dynamic production history. This work highlights the significance of uncertainties in SRV and hydraulic fracture parameters. It also provides insight into the value of micro-seismic data when integrated in a rigorous production history matching workflow.

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