Study On The Fine Geological Model Of Low Permeability Reservoir

Qiananâ… area is a low permeability petroleum reservoir, which gets into the late stage of high water cut development with grave reservoir heterogeneity and poor development effect. Therefore, the resolution is to establish higher precisely three-dimensional geological model in the process of exploratory development and also give accurate and fine reservoir evaluation and identification to characteristic reservoir in the model. Those have important impact on reducing the development risk and enhancing the economic efficiency. The focal and difficult point in this article is how to utilize effectively the combination of geology, well logging and seismic data to set up accurate geological model.This research uses the data such as geology, well logging, oil-production test and production performance and also exercises the three-dimensional geological model in the study area. After that, the facies model is built up and the phase-controlled modeling used to create the petrophysical model. In addition, the model is selected and tested as well. The following is the achieved outcome and understanding:Firstly, Regarding to the low permeability reservoir's depositional feature, the precise three-dimensional structural model is set up, which takes comprehensive consideration including well network, well spacing and source direction from the plane and the impaction of sand shale interbed from vertical.Secondly, Microfaiees model is established by stochastic model methods (sequential indicator simulation) and artificially modified and improved with the combination of sedimentary rule. Deterministic modeling approach is used to establish the lithofacies and dry layer distribution model.Thirdly, The combination method of certainty and random modeling is adopted to limit uncertainty that generated in random model by using certainty information as much as possible. The previous geological knowledge(such as porosity distribution in surface) act as co-variation, which adopt the combination of Co-Kriging and SGS to proceed phase-controlled quality parameter modeling. Those avoid uncertainty information's accumulation created by homogeneous certainty model and show the certainty simulation's prediction to interwell unknown area at the same time. Lastly, Dominant channel identification is processed by research on constraint factores such as permeability, log character ,sedimentary facies and sandbody thickness and create the large pore's probability model, which is tested by geological practice to optimize and detect in order to establish the correspondent dominant channel prediction model.