The anisotropy of Leighton Buzzard sand under general stress conditions
A hollow cylinder apparatus was used to investigate the inherent anisotropy and membrane penetration of Leighton Buzzard sand test-specimens. The degree of inherent anisotropy was found to be independent of the mean effective stress but dependent on the initial relative density of the test-specimen. In the vertical-tohorizontal directions, the degree of inherent anisotropy decreases with increasing relative density. A wet-pluviation, sample preparation technique produces cross-anisotropic test-specimens, with the degree of cross anisotropy independent of the initial relative density. The effects of membrane penetration (expressed in terms of the normalized unit membrane penetration) are found to be independent of the initial relative density and the mean effective stress.
Proportional Loading Behaviour of Sand under Multiaxial Stresses.
A study of sand deformation under proportional loading under generalized stress conditions is presented. The loading includes a variety of stress paths in which the principal axes of stresses have a constant inclination to the axes of the vertically water deposited specimens. This was intended to capture the effects of inherent anisotropy in sand during proportional loading. It is shown that under such loading conditions increments of volumetric and maximum shear strains depend both on the initial stress and density state as well as on the inclination of principal stresses to the material axes.
Predicting the gas resource potential in reservoir C-sand interval of Lower Goru Formation, Middle Indus Basin, Pakistan
Abstract The integrated study of seismic attributes and inversion analysis can provide a better understanding for predicting the hydrocarbon-bearing zones even in extreme heterogeneous reservoirs. This study aims to delineate and characterize the gas saturated zone within the reservoir (Cretaceous C-sand) interval of Sawan gas field, Middle Indus Basin, Pakistan. The hydrocarbon bearing zone is well identified through the seismic attribute analysis along a sand channel. The sparse-spike inversion analysis has efficiently captured the variations in reservoir parameter (P-impedance) for gas prospect. Inversion results indicated that the relatively lower P-impedance values are encountered along the predicted sand channel. To further characterize the reservoir, geostatistical techniques comprising multiattribute regression and probabilistic neural network (PNN) analysis are applied to predict the effective porosity of reservoir. Comparatively, the PNN analysis predicted the targeted property more efficiently and applied its estimations on entire seismic volume. Furthermore, the geostatistical estimations of PNN analysis significantly predicted the gas-bearing zones and confirmed the sand channel as a major contributor of gas accumulation in the area. These estimates are in appropriate agreement with each other, and the workflow adopted here can be applied to various South Asian regions and in other parts of the world for improved characterization of gas reservoirs.