库车坳陷克深2区块白垩系巴什基奇克组裂缝分布及建模
[Abstract]:In the study of low porosity and low permeability or tight fractured sandstone reservoirs, fracture is undoubtedly the most important, and fracture is not only the main passage of oil and gas migration, but also an important reservoir space. Kesheng 2 block in Kuqa depression is a typical low porosity and low permeability tight fractured sandstone gas reservoir with strong heterogeneity and uncertainty in fracture development. The conventional fracture modeling is mostly based on ant tracing, but the precision of seismic data in the study area is difficult to meet the requirement of fracture prediction. This paper is based on the theory of pixel simulation and takes the statistical fracture parameters of imaging logging as hard data. By analyzing the main factors of fracture control, the key points are assigned, and sequential Gao Si random simulation is chosen as the method to realize the fracture modeling of the target block. The model intuitively depicts the distribution characteristics and development trend of fracture parameters in the study area, provides an effective geological model for the later study of seepage behavior and heterogeneity of fractures, and avoids the limitation brought by the lack of seismic data accuracy. It enriches the research methods of reservoir geological modeling. Based on the previous research results and the relevant theory of fracture research, this paper takes the Cretaceous Bashiki formation fracture of Kesheng 2 block in Kuqa depression as the research object, through field outcrop, core, thin slice, imaging logging and so on. The cracks in the study area are identified and described in detail, and the fracture model is established by selecting the relevant algorithms combined with the main control factors. The main achievements of this paper are as follows: (1) an integrated method of fracture parameter identification and calculation is established by using the core and imaging logging. The accuracy of the method is 0.1 mm and the pick up rate of fracture is 80 mm. Through this method, the fine description of fracture parameters and the establishment of database are carried out for 22 single well imaging logging data in the study area. (2) the study area was mainly composed of small joints, which accounted for 89.6, and the middle seams were only 1.8 and 8.6, respectively. The main strike of the fracture is SN and near EW, the tendency of fracture is mainly NE,SW, the angle of inclination is 45 掳-75 掳, the mean of fracture density is 0.53 / m, the width of fracture is 0.1-0.5 mm / m, and the extension length is 0.1-1m. The area of face seam is 0.02 and 0.08. The fracture assemblage is diverse, among which X conjugate joint and reticular joint are the main types. (3) the fractures in the whole area are generally developed, and the whole area shows a strong structural control feature, which is concentrated in the strong deformation areas near faults, anticline wings and nuclei. The longitudinal distribution of fractures is mainly in Ba -, Ba-2 and Ba-3 members, which are lower than that of Ba-2, Ba-2 and Ba-3 member. The distribution of fractures in the upper part of Ba-2 and Ba-3 member is correlated with the location of faults. The lateral fracture has poor development continuity, showing strong heterogeneity. (4) through the analysis of the main controlling factors of fracture development in the study area, the main influence area is determined and the control points are selected in the anticline area and the near fault area. The formula of the relationship between layer thickness and fracture density and fracture ratio is fitted, and the key well points are selected and assigned according to this formula. The fracture density and fracture surface fracture rate models are established by using sequential Gao Si random simulation method, and the dimension fracture distribution prediction is realized for the plane of each layer and any well point in the study area. The new well data is used to verify the model, and the overall accuracy of the model is 80%.
【学位授予单位】:西南石油大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:P618.13
【参考文献】
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