For many decades most oil wells in Iran have produced using their natural flow potential and haven’t needed to be fractured. As time goes by, the reservoir pressure depletes and the need for hydraulic fracturing as a stimulation practice arises. Nonetheless there is no record of successful hydraulic fracturing in Iran.
The Bangestan reservoir with a suitable amount of oil in place and good rock reservoirs, has been selected for the present research work. In this work, the in situ stress profile was calculated by using the available petrophysical data. This is achieved by using poroelastic theory for the stresses, and the Mohr–Coulomb criterion to predict failure. The model leads to easily computed expressions for calculating the pressure required to maintain hydraulic fracturing. Then the appropriate depth for treatment was determined. The results indicate that Ilam and Sarvak formations could be good candidates for hydraulic fracturing. Then, for two layers, a hydraulic fracture was designed and the production was predicted and the Net Present Value (NPV) resulting from the fracture of both layers was investigated. 相似文献
Accurate pesticide exposure estimation is integral to epidemiologic studies elucidating the role of pesticides in human health. Humans can be exposed to pesticides via residential proximity to agricultural pesticide applications (drift). We present an improved geographic information system (GIS) and remote sensing method, the Landsat method, to estimate agricultural pesticide exposure through matching pesticide applications to crops classified from temporally concurrent Landsat satellite remote sensing images in California. The image classification method utilizes Normalized Difference Vegetation Index (NDVI) values in a combined maximum likelihood classification and per-field (using segments) approach. Pesticide exposure is estimated according to pesticide-treated crop fields intersecting 500 m buffers around geocoded locations (e.g., residences) in a GIS. Study results demonstrate that the Landsat method can improve GIS-based pesticide exposure estimation by matching more pesticide applications to crops (especially temporary crops) classified using temporally concurrent Landsat images compared to the standard method that relies on infrequently updated land use survey (LUS) crop data. The Landsat method can be used in epidemiologic studies to reconstruct past individual-level exposure to specific pesticides according to where individuals are located. 相似文献