Numerical Modelling of Multiple Fractured Horizontal Wells in Shale gas Reservoirs

Abstract

Abstract One of today's challenges for shale reservoir developments is to increase the productivity per foot of drilled horizontal section while lowering the production cost to reduce the overall boe/$. Shale gas reservoirs are unconventional resources that need Multifractured Horizontal Wells (MFHW) to produce at commercial rates. Fracking methods have advanced dramatically in the last decade. Technologies are now capable of placing long MFHW with predefined fracs distance with large volumes of fluids injected causing intense formation fracturing. The final goal is to increase the well productivity per foot by increasing the size of the SRV (Stimulated Reservoir Volume) while reducing the cost of production. The objective of this paper is to study and compare the impact on recovery factor, productivity and well performance of different SRV geometries using a dual porosity dual permeability compositional model. This work examines three prolific US gas shale plays, Haynesville, Barnett and Marcellus, having different reservoir and fluid characteristics. Hydraulic fractures properties like half-length, width and density were studied alongside other reservoir properties (matrix and fracture permeability and porosity). These are considered amongst the key parameters influencing MFHW productivity and gas recovery. The chosen approach is a Cartesian grid to mimic the presence of large-scale permeable hydraulic fractures as main flow conduits and enhanced medium scale (equivalent to the grid size) natural fractures in MFHW that contribute to flow in stimulated areas. The method models matrix-fracture interactions, with property-selected refinement to simulate different SRVs geometries demonstrated by Whitson (2016) to be able to history match pressure behavior in shale gas reservoirs for the Haynesville and Marcellus. Numerical modeling of MFHW recovery factors, pressure and production profiles was done using a commercial simulator. Reservoir properties for analyzed shales were extracted from public data. Three different SRV models were studied to represent the enhanced medium scale fractures. The first model, matrix-hydraulic fractures system, is the simplest SRV modeled in this work, and is the base for a subsequent model obtained by adding an enhanced fracture stimulated SRV area around each large scale hydraulic fracture. The most complex SRV geometry modeled was created by adding an additional enhanced stimulated natural fracture area simulating the impact of hydraulic fractures in the medium scale natural fracture network (Whitson, 2016). Results show how relatively moderate increases in the enhanced stimulated SRV's volumes can have a large impact on cumulative gas production and recovery factor, demonstrating the importance of achieving successful large scale hydraulic fractures and/or stimulation of medium scale fractures between and around the major fractures. Changes in SRV geometry, caused by enhanced natural fractures due to hydraulic fracturing stimulation, demonstrated to also have a large impact on recovery factors. A sensitivity analysis was performed to study the impact that different reservoir properties including matrix permeability and fracking parameters (half-length and density) could have on cumulative production and recovery factor. Results can be used to help defining the best strategy to design hydraulic fracturing for different shale gas plays, optimizing the field development plan. This study can be extended to incorporate shale oil plays (Compositional models) and to investigate multiple wells interaction evaluating interferences between wells. This study provides a catalogue of typical cumulative production and pressure profile responses for three US shale gas plays with different characteristics and stimulation areas that can be used to aid practitioners in assessing the extent of the potential stimulated areas contacted by unit wells in modelled SRV's. In addition, sensitivity analysis provides information on key parameters to consider when estimating recovery factors ranges to use for estimating reserves and resources in shales with these characteristics.