Taking a geophysical approach to shale gas characterisation
Jo Firth looks at an integrated geophysical approach to characterising shale gas reservoirs.
Jo Firth wirft einen Blick auf einen integrierten geophysikalischen Zugang zur Charakterisierung von Schiefergas-Reservoirs.
Jo Firth analiza una estrategia geofísica integrada para caracterizar los yacimientos de gas de esquisto.
GGVeritas has developed an integrated geophysical approach to characterising shale gas reservoirs,
based on pre-stack azimuthal seismic data analysis calibrated with well log and core measurements to identify sweet spots. Relative production estimates
across the reservoir may be derived by combining seismic estimates of lithological, geomechanical and stress properties, correlated to existing well measurements to predict porosity, volume of shale, carbonate content and water saturation. Tis technique has been applied to the CGGVeritas Tri- Parish multi-client survey in the Haynesville Shale with positive results (Fig. 1). However, all shale plays are different, so the selection of geomechanical and lithological parameters that provide the best correlation with production will vary from one play to another and must be derived for each survey. A quantitative understanding of a host of
Fig.1. Mapping of the predicted first six months of production (calibrated to horizontal well length), based on correlation of calibrated geomechanical and lithological attributes with actual production rates. High-productivity areas are shown in red.
rock properties such as acoustic impedance, Poisson’s ratio, and Young’s modulus can be obtained from prestack seismic. Tese properties are in turn related to quantitative reservoir properties such as porosity, Total
Organic Content (TOC) and mineral content. CGGVeritas combines the elastic rock
properties, derived from seismic inversion, with azimuthal velocity and AVO analysis of conventional 3D seismic data to estimate principal stresses. Te Differential Horizontal Stress Ratio (DHSR) is an important parameter for prediction of hydraulic fractures and can be estimated from seismic data alone. Tese estimated stresses are then calibrated to the stress state of the reservoir, derived from drilling and completion data, microseismic analysis and regional information. Zones with relatively high brittleness (derived from isotropic Young’s Modulus, Lambda-Mu-Rho, etc) and low DHSR (no preferential stress orientation) are more prone to fracturing and tend to produce fracture swarms when completed, potentially increasing production. CGGVeritas has applied this workflow
to its Tri-Parish data. Tis is a high-pressure, high-temperature (HPHT) field with no large structural features and so has a relatively homogeneous stress field. Although there is an east-west regional orientation of the
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