The design of a drainage system for a roofing slate quarry was implemented by the enhancement of discharge peak estimation, and the uncertainty inevitably associated with the engineering model was reduced.
The development of a topographical, geological, and vegetation cover database developed from a Geographical Information System (GIS) allowed for the definition of the drainage network for a hydraulic system, along with the calculation of the runoff coefficient. This is applied to the digital model of accumulated flow (DMF) as a weight correction coefficient, using a matrix-based model at 5×5 m resolution. The new digital model of corrected accumulated flow (DMCF) is the result of combining the thematic maps with the map of slope <3%, which was previously created from the slope model. It is demonstrated that this new model allows to apply the “Rational Method” on cartographic units defined by the GIS.
The DMCF is compared with other traditional applications of the Rational Method based on the calculation of the discharge peak considering: (1) the drainage basin as a single watershed or (2) defining an average runoff coefficient in each sub-watershed. Both approaches have bigger discharge peaks than those obtained by the DMCF since the slope, lithology, and vegetation cover have average values, and the runoff coefficient is poorly defined, increasing the uncertainty in the discharge peak. 相似文献
A consistent stochastic model for faults and horizons is described. The faults are represented as a parametric invertible deformation operator. The faults may truncate each other. The horizons are modeled as correlated Gaussian fields and are represented in a grid. Petrophysical variables may be modeled in a reservoir before faulting in order to describe the juxtaposition effect of the faulting. It is possible to condition the realization on petrophysics, horizons, and fault plane observations in wells in addition to seismic data. The transmissibility in the fault plane may also be included in the model. Four different methods to integrate the fault and horizon models in a common model is described. The method is illustrated on an example from a real petroleum field with 18 interpreted faults that are handled stochastically. 相似文献