Logging Evaluation Of Sand And Conglomerate Reservoir

With the development of oil prospecting, we pay more and more attention on the complicated oil-gas reservoir which has become an important research to find new oil-gas reservoir in the oil fileds. As one type of favorable area for the conceal oil-gas reservoir, it is difficult to evaluate with well logging data glutenite reservoir, which has strong aeolotropism and complex lithology and low porosity and permeability. It’s hard to identify effectively reservoir and oil-water layer. The reservoir evaluation with well logging data, the discrimination of oil-water and the application of geology are all difficult problems to prospecting at home and aboard, so it requires new theories and advanced technologies to support.The glutenite reservoir of carboniferous in the He gas field is mainly composed of conglomerate, pebbly sandstone and fine sandstone, with high gamma glutenite reservior found in the part of the section. With the constant exploration and development of gas field in recent years, glutenite reservoir gradually be taken seriously. In order to accurately evaluate the reservoir, a detailed study is needed to establish fine logging parameter model.In this paper, we take this glutenite reservoir as the research object and the main research work is as follows. Combining with the geological, well logging, testing and core analysis data of the study area reservoir, we analyze the "four characteristics" relationship, and we then use crossplot method to set a high gamma recognition template which can be used to identify the high gamma glutenite reservoir and correctly divide effective reservoir. Then on the basis of lithology identification, we establish the logging interpretation model of porosity and permeability by using core analysis data calibration logging curve and the saturation model by combining litho-electric experiment data and the analysis data of formation water. And then depending on the test data and logging data, we use crossplot method and mathematical statistics analysis method to identify the fluid and to establish identification standard. Based on the above research work, we eventually determine effective reservoir lower limit logging interpretation standard in the study area.Applying the methods, logging data of eighteen wells in the study area are processed and the results are satisfactory.