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Applying a stochastic pore-network modelling to obtain refined dependence between porosity and absolute permeability by example of Neocomian deposits of the West Siberian fields

UDK: 622.276.5.1/4(571.1)
DOI: 10.24887/0028-2448-2017-9-96-98
Key words: stochastic network models, porosity, absolute permeability
Authors: I.N. Zhizhimontov, S.V. Stepanov, A.V. Svalov (TNNC LLC, RF, Tyumen)

The paper describes the application of a stochastic porous-network model, as well as the results of testing the developed software application. It was used to justify the porosity/absolute permeability function applied to simulate a group of Neocomian reservoirs in West Siberia poorly covered by core studies.

The discussed stochastic pore-network model of virtual rock samples was built in two stages. The first stage included a stochastic reconstruction of the void space. To do this, statistical data on the pore sizes obtained from capillary pressure curves was used. Due to the lack of detailed data on the microstructure of the pore space, a number of correlation and topological characteristics, such as the maximum connectivity radius (directly affects the coordination number), weight functions, etc., served as the tuning parameters. In the second stage, the absolute permeability was estimated based on the numerical flow simulation of single-phase incompressible fluid in pore channels. For this, the hydraulics equations were used: the equations of mass balance in pores and the equations for fluid flow in channels (the Poiseuille equations).

To appraise the poorly-cored target, a number of stochastic porous-network models were built with a detailed tuning by the available core data, taking into account the sample lithological descriptions. As a result of averaging a large number of model runs, the absolute permeability/porosity correlation function was updated. A new porosity/absolute permeability function was built which characterizes the rock as having the best reservoir properties in comparison with the previously justified function. The improved reservoir properties are also consistent with the logging data.

The use of the new function in a flow simulation model demonstrates a clearly improved match between the estimated and actual development data, which confirms the validity of the new petrophysical function.


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