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Study On The 4-Dimensional Reservoir Model And Simulation Of Remaining Oil

Posted on:2011-07-20Degree:DoctorType:Dissertation
Country:ChinaCandidate:S W PanFull Text:PDF
GTID:1100360302984078Subject:Geological Resources and Geological Engineering
Abstract/Summary:PDF Full Text Request
The variation and mechanism of reservoir properties in different stages of development in Z2 block of Jiangsu Oilfield and Shengtuo Oilfield are generally studied by applying synthetically multi-subject theories, methods and technologies and making full use of computer. And the 3 dimensional reservoir model in different stages of development is set up, which can reveal the formation mechanism and distribution of the remaining oil. And the distribution pattern of the remaining oil that will lift the recovery ratio of oilfield is built.The paper achieved some innovational scientific payoffs. Main achievements of the study are summarized as following:(1)The variation of macroscopic parameter is that the porosity and permeability are increasing while the oil saturation is decreasing totally with flood development, which is obtained by counting and analyzing the information of cored well in different stages of development and log interpretation of other wells.(2)A new method of building 4 dimensional reservoir model is proposed. Firstly, the forecasting model of reservoir parameter of well point is built by using the back propagation neural networks improved by the particle swarm optimization, and the forward reservoir parameter is obtained by it, then the 4 dimensional data is set up. Secondly, the precipitation facies model is built by Sequential Indicator Simulation of stochastic modeling, and then the 3 dimensional reservoir model is built with Sequential Gaussian Simulation under the control of the precipitation facies. At last, the 4 dimensional reservoir model is set up by building the 3 dimensional reservoir model in different stages of development.(3)The development history of the production tail oilfield is divided into 3 stages according to the high water content ratio and the complicated water/oil bed. Then the log interpretation model is built in different stages of development with the ample knowledge of core well, and then the 4 dimensional data of reservoir parameter is obtained. At last, the 4 dimensional reservoir model of the production tail oilfield is set up by building the 3 dimensional reservoir model in different stages of development with PETREL.(4)The structural attitude, deposition, reservoir, development history and the changing rule of the reservoir macroscopic parameter of Z2 block of Jiangsu Oilfield and Shengtuo Oilfield are compared. Based on this, it is generally evaluated that the 4 dimensional reservoir model in different area is built with two different methods.(5)The feature of rock and mineral, diagenism, pore and pore structure are generally evaluated, based on which, the changing rule of the rock skeleton, pore throat, clay mineral and infiltrating fluid in different stages of development is analyzed. And it is the acting force of the developing fluid that make the reservoir macroscopic parameter change. At last, the histogram of the radius of pore throat in different stages is built.(6)The composition of microscopic pore of rock specimen is obtained by observing the thin slice, and the realistic models of microscopic pore that are used of physical experiment of microscopic remaining oil are made. During this experiment, the displacement feature of three kinds pore throats is observed.(7) According to the particular development feature of the oilfield, based on the existent technology of imitation, and directed by the Poiseuille's law, the dynamic imitation model of microscopic displacement of oil by water is built by using the advanced technology of computer simulation and 3 dimension display.(8)The back propagation neural networks improved by the particle swarm optimization, the method of Sequential Indicator Simulation and the Sequential Gaussian Simulation are achieved by designing procedure. At last, a software module that can build a 4 dimensional reservoir model is obtained.
Keywords/Search Tags:flood development, the back propagation neural networks, stochastic modeling, the 4 dimensional reservoir model, imitation model
PDF Full Text Request
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