
TY  - JOUR
A1  - Chipperfield, S.T. 
A1  - Wong, J.R. 
A1  - Warner, D.S. 
A1  - Cipolla, C.L. 
A1  - Mayerhofer, M.J. 
A1  - Lolon, E.P. 
A1  - Warpinski, N.R. 
T1  - SHEAR DILATION DIAGNOSTICS&#x2014;A NEW APPROACH FOR EVALUATING TIGHT GAS STIMULATION TREATMENTS
JF  - The APPEA Journal
JO  - The APPEA Journal
Y1  - 2007
VL  - 47
IS  - 1
SP  - 221
EP  - 238
KW  - 
UR  - https://doi.org/10.1071/AJ06014 
N2  - Many tight gas reservoirs require fracture stimulation to achieve commercial outcomes. These reservoirs can often be characterised geologically and geomechanically by high deviatoric stresses and hard, naturally fractured rock. Stimulation treatments in such reservoirs may create complex fracture networks from a combination of shear and tensile failures. Water fracs can be used where shear failure is anticipated to dominate; however, in these environments few practical modelling tools exist to determine: the level of permeability enhancement; the degree of permeability retainment during draw-down; and, the stimulated rock volume (SRV). This paper seeks to provide the engineer with a suite of tools capable of achieving these goals.This paper presents a dual porosity, pressure-dependent permeability reservoir simulation model that was devised to honour shear failure mechanisms (also called shear dilation) using basic geological characterisation. The assumptions of this model and the pragmatic selection of first-order effects are discussed. Using the results of this simulation model, three families of diagnostic tools are presented. The first category is that of treatment diagnostics, which includes bottom hole pressure evaluation, injectivity and fall-off analysis. The second approach is called seismic-based reservoir characterisation (SBRC), which uses the microseismic to determine the SRV as well as provide estimates of the initial and stimulated fracture network properties. The third category is post-treatment diagnostics, which incorporates the evaluation of pressure draw-down characteristics.Finally, this paper compares these individual approaches and provides a workflow to evaluate data on future wells. 
ER  -

