The evaluation of permeability in reservoir assessment is a complex problem. Thus, it is difficult to perform direct evaluation permeability with conventional well-logging methods. Considering that reservoir permeabil...The evaluation of permeability in reservoir assessment is a complex problem. Thus, it is difficult to perform direct evaluation permeability with conventional well-logging methods. Considering that reservoir permeability significantly affects mud invasion during drilling, we derive a mathematical model to assess the reservoir permeability based on mud invasion. A numerical model is first used to simulate the process of mud invasion and mud cake growth. Then, based on Darcy＇s law, an approximation is derived to associate the depth of mud invasion with reservoir permeability. A mathematical model is constructed to evaluate the reservoir permeability as a function of the mud invasion depth in time-lapse logging. Sensitivity analyses of the reservoir porosity, permeability, and water saturation are performed, and the results suggest that the proposed model and method are well suited for oil layers or oil-water layers of low porosity and low permeability. Numerical simulations using field logging and coring data suggest that the evaluated and assumed permeability data agree, validating the proposed model and method.展开更多
According to Cubic law and incompressible fluid law of mass conservation, the seepage character of the fracture surface was simulated with the simulation method of fractal theory and random Brown function. Furthermore...According to Cubic law and incompressible fluid law of mass conservation, the seepage character of the fracture surface was simulated with the simulation method of fractal theory and random Brown function. Furthermore, the permeability coefficient of the single fracture was obtained. In order to test the stability of the method, 500 simulations were conducted on each different fractal dimension. The simulated permeability coefficient was analyzed in probability density distribution and probability cumulative distribution statistics. Statistics showed that the discrete degree of the permeability coefficient increases with the increase of the fractal dimension. And the calculation result has better stability when the fractal dimension value is relatively small. According to the Bayes theory, the characteristic index of the permeability coefficient on fractal dimension P（Dfi｜ Ri） is established. The index, P（Dfi｜ Ri）, shows that when the simulated permeability coefficient is relatively large, it can clearly represent the fractal dimension of the structure surface, the probability is 82%. The calculated results of the characteristic index verify the feasibility of the method.展开更多
基金financially supported by the Open Fund(No.PLC201103) of the State Key Laboratory of Oil and Gas Reservoir Geology and Exploration(Chengdu University of Technology)Open Fund(No.PRP/OPEN-1302) of the State Key Laboratory of Petroleum Resources and Prospecting(China University of Petroleum,Beijing)+2 种基金PetroChina Innovation Foundation(No.2015D-5006-0304)National Natural Science Foundation of China(No.41304078)Sinopec Foundation(No.P14136)
文摘The evaluation of permeability in reservoir assessment is a complex problem. Thus, it is difficult to perform direct evaluation permeability with conventional well-logging methods. Considering that reservoir permeability significantly affects mud invasion during drilling, we derive a mathematical model to assess the reservoir permeability based on mud invasion. A numerical model is first used to simulate the process of mud invasion and mud cake growth. Then, based on Darcy＇s law, an approximation is derived to associate the depth of mud invasion with reservoir permeability. A mathematical model is constructed to evaluate the reservoir permeability as a function of the mud invasion depth in time-lapse logging. Sensitivity analyses of the reservoir porosity, permeability, and water saturation are performed, and the results suggest that the proposed model and method are well suited for oil layers or oil-water layers of low porosity and low permeability. Numerical simulations using field logging and coring data suggest that the evaluated and assumed permeability data agree, validating the proposed model and method.
基金Project(50934006) supported by the National Natural Science Foundation of ChinaProject(CX2012B070) supported by Hunan Provincial Innovation Foundation for Postgraduate,ChinaProject(1343-76140000024) Supported by Academic New Artist Ministry of Education Doctoral Post Graduate in 2012,China
文摘According to Cubic law and incompressible fluid law of mass conservation, the seepage character of the fracture surface was simulated with the simulation method of fractal theory and random Brown function. Furthermore, the permeability coefficient of the single fracture was obtained. In order to test the stability of the method, 500 simulations were conducted on each different fractal dimension. The simulated permeability coefficient was analyzed in probability density distribution and probability cumulative distribution statistics. Statistics showed that the discrete degree of the permeability coefficient increases with the increase of the fractal dimension. And the calculation result has better stability when the fractal dimension value is relatively small. According to the Bayes theory, the characteristic index of the permeability coefficient on fractal dimension P（Dfi｜ Ri） is established. The index, P（Dfi｜ Ri）, shows that when the simulated permeability coefficient is relatively large, it can clearly represent the fractal dimension of the structure surface, the probability is 82%. The calculated results of the characteristic index verify the feasibility of the method.
