An Application Study Of Reservoir Fracture Detection Technology In Qi Jiagu

It’s considered that the development degree and scope of distribution of the buried hill belt in the fracture directly affects the reservoir of the buried hill reservoir potential and scale. The crack is not only a key factor of low permeability reservoir capacity, but also directly controls the formation and distribution of fractured reservoirs. Identifying and evaluating fractured reservoir has been the emphasis and difficulty in reservoir exploration. At present, both at home and abroad there are many distinctive ways to predict and evaluate the cracks in oil and gas basin in the low permeability reservoir. But because of the complexsity of the fracture and the development stage, those methods have their limitations, we also make it difficult to use a method to solve all of the problem in fracture identification and evaluation. For example, the fracture identification is able to achieve quantitative logging levels, but it’s only a small and partial range. The seismic data is large, but the resolution for the stratum is low. Therefore,the integrated application of various data description and predict fracture distribution is to find the basic ideas of fracture reservoir exploration. This paper puts the Liaohe oilfield Qijia Guqian Hill’s rock reservoir as an example, using reservoir fracture forecast technology to make a comprehensive study of this area.Qijia Guqian Hill is composed of three local hills, namely southern mountain, middle mountain and north mountain, the three mountains distribute to the north east. On the lithology of them, the north mountain is composed of andesite, basalt and tuff volcanic rocks mainly, and the middle and southern montain is composed of mix granite. The focus of this study is the middle montain’s reservoir granite.Firstly logging, drilling and oil testing data for statistical analysis, understand the change of the lithology in the purpose of each well point layer, and the seismic response characteristics of oil and gas. Then the seismic attributes extracted from target layer in objective interval after the post-stack wave impedance inversion; On the basis of various seismic attributes, worked on prediction of oil and gas by the artificial neural network. By means of inversion, seismic attribute and comprehensive analysis of oil and gas prediction data, mastered the sensitive seismic attributes and oil and gas distribution. Secondly extracted from objective interval multiple attribute of curvature, Through the comparison and analysis, it’s concluded from several seismic curvature that the minimum nagative and the maximum positive curvature have the best effect of fracture characterization. Based on the fault is the macroscopic fracture performance, crack is the prototype of the fault. Basing on body of variance data we can have fault and the spatial distribution of fracture system in this area, By adjusting the parameters of the ant tracking software technology can get the spatial distribution of the fracture site. Finally using of the conventional log data and stratigraphic dip data for crack identification and evaluation, The logging and seismic fracture prediction results are compared, it has the higher tallies, The results show that curvature and ants body attribute have certain effect for fracture prediction.