Abstract

Multi-stage fracturing in horizontal wells in shale reservoirs creates a region of stimulated reservoir volume (SRV) around the subject horizontal well. Depending upon the stress state in the reservoir the hydraulic fractures could be planar or form a network near the well. Furthermore, fracture initiation may not take place at every perforation cluster and therefore every perforation cluster may not contribute to production. Wells initially deplete this region of stimulated reservoir rock and with time produce from reservoir beyond the SRV. We attempt to understand depletion in nano darcy reservoirs like the Haynesville Shale by utilizing our state of the art reservoir simulation workflow, Top Down Reservoir Modeling (TDRM™)7 and present a case study on a ten stage Haynesville horizontal well. Following an in-depth analysis of the completion and acquired down hole microseismic data, a subsurface model was built and the SRV extent and equivalent hydraulic fracture parameters were history matched using advanced genetic algorithms. Well production was forecasted to 40 years and this served as a means to calibrate our decline curves used in estimating our recovery. History matching two years of production indicated:

  1. the fracture property estimates in the SRV region are independent of formation permeability;

  2. after around four years of production there is an onset of depletion beyond the SRV and;

  3. higher matrix permeability in the non-stimulated region led to higher recovery.

Simulation indicates higher production could be achieved with greater frac lengths (thereby bigger SRV), higher frac conductivities and better perm in the SRV region. The extent of depletion observed in the reservoir provides valuable insights to spacing future wells in this area. The simulation workflow and the lessons learnt through this study are being applied to our other Haynesville horizontals.

Literature survey

Decline curves have been accepted as a quick and efficient way of estimating recovery of shale and tight gas wells. The transient flow taking place in shale wells throughout well life and the impact of adsorbed gas on production cannot be accounted for by decline curve analysis. Further there exists a need for a basis to support the b-factor (decline exponent) used in decline curve recovery estimation. At early time, drastically different EURs (Estimated Ultimate Recovery) can be calculated due to uncertainty in the b values as shown in Fig 1. In Fig 1 the orange points represent sample production data and hyperbolic decline curves extrapolated from these points for b values from 1.2 to 1.6 are shown in the left logarithmic y axis. The corresponding cumulative gas curves for different b values are plotted in the right y Cartesian axis. A 1.7 Bcf range in 30 year EUR can be observed for b values from 1.2 to 1.6.

Reservoir simulation could be used to model the transient flow and adsorbed gas in shale formations. It should, however, be noted that reservoir simulation does not provide a unique solution but could provide a range of permeability and stimulated reservoir volume (SRV) estimates with reasonable forecasts to support recovery estimation. The business purpose of this study was to address the risk of well performance falling below the reference type curve calculated by decline curve analysis.

URTeC 1581276

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