THE USE OF WATERJETS IN CUTTING A MULTIPLE PHASE MATERIAL
The University of Missouri-Rolla is carving a new sculpture. This involves shaping 3 rocks, collectively weighing 100 tons, and cutting figures of a man and a woman from two blocks. The three blocks will then be erected to form a Millennium Arch and the Figures will be polished as a second set. A relatively inexpensive X-Y table and cutting head unit were developed. The cutting waterjet was without abrasive at under 100 MPa. One problem in cutting large blocks (5 m x 2 m by 0.75 m) is that the structure changes. A variety of approaches were taken to solve this problem. The process steps required to cut the rock to shape, and then to carve the rock are described in the paper.
THE EFFECT OF ROCK ANISOTROPY ON THE EXCAVATION RATE IN BARRE GRANITE
The variation in the volume of rock removed when a water jet traverses over a sample of Barre Granite is shown to vary with the angle at which the sample is cut relative to the orientation of the main deposit. For example where the jet impacts perpendicular to a microfissure plane a channel up to 10 times the volume is cut as when the jet is traversed along the microfissure plane. A correlation is shown to exist between the dimensions of the rock volume removed and the angle of impact between the water jet and the two microfissure planes of the Barre Granite.
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.