Study On Fracture Identification From Conventional Logging Data In Low Porosity And Low Permeability Tight Sandstone Reservoir

Imaging logging data are the most accurate method in identifying fractures so far, but the cost is very expensive and many oil fields don’t have the imaging logging data. Hence the application the imaging logging data is not so widely. However, the conventional logging data have many advantages, such as the low cost, the complete data and the common application. Thus it has very important meanings to identify the fractures with the conventional logging data which are commonly used in most wells.Because the lithology in the study area is sandstone of low-porosity-and-low-permeability, its lithology is more dense and its fractures are less develop. The variation of the conventional logging data is less in the mud-invasion fracture than in the Carbonate formation. In addition, because of the impact of the formation lithology, the oil content and the borehole, it is very difficult to identify the fractures with on one conventional logging curve. The study area has complete conventional logging data. This article makes use of the fracture response characters of many conventional logging curves and extracts the fracture characteristic parameters and then adopts comprehensive probability method, BP neural network, fractal R/S method and the log curve element method respectively to identify fractures in the study area. At last, comparing to the results of the fracture identification with the imaging logging method, the conventional logging method has a better effect.The study area is a big gas field, and its lithology is sandstone of low-porosity-and-low-permeability. Because of the special Tectonic characteristics, this area has many fractures, especially with the medium and high angels. The development of the fractures not only improves the porosity and the permeability of the formation in the study area, but also provides a migration channel for oil and gas. Therefore, the fracture identification in the study area has serious meanings for the Physical property study and the oil field detection.