A new method for well pattern density optimization and recovery efficiency evaluation of tight sandstone gas reservoirs

Successful exploitation of tight sandstone gas is one of the important means to ensure the “increasing reserves and production” of the oil and gas initiative and also one of the important ways to ensure national energy security. To further improve the accuracy of historical matching of field data such as gas production and bottom-hole pressure during the production process of this type of gas reservoir, in this study, a new expression of wellbore pressure for the uniform flow of vertical fractured wells in Laplace space based on the point sink function model of vertical fractures in tight sandstone gas reservoirs is constructed. This innovation is based on a typical production data analysis plot of the Blasingame type that uses the numerical inversion decoupling mathematical equation. After analyzing the pressure and pressure derivative characteristics of each flow stage in the typical curves, a new technique of type-curve matching was proposed. In order to verify the correctness of the model and the application value of the field, based on the previous production data of Sulige Gas Field in China, a new set of production data diagnostic chart of tight sandstone gas reservoir was formed. A case analysis showed that the application of the production data analysis method and data diagnosis plot in the field accurately evaluated the development effect of the tight sandstone gas reservoirs, clarified the scale of effective sand bodies, and provided technical support for optimizing and improving the well pattern and realizing the efficient development of gas fields.

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Relationship between well pattern density and variation function of stochastic modelling and database establishment

Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles ◽

10.2516/ogst/2020077 ◽

2020 ◽

Vol 75 ◽

pp. 84

Author(s):

Jinkai Wang ◽

Kai Zhao ◽

Zhaoxun Yan ◽

Yuxiang Fu ◽

Jun Xie

Keyword(s):

Oil And Gas ◽

Stochastic Modelling ◽

Gas Reservoirs ◽

Gas Field ◽

Pattern Density ◽

Vertical Range ◽

Variation Function ◽

Well Pattern ◽

Geological Conditions ◽

Degree Of Convergence

For 3D geological modelling of oil and gas reservoirs, well pattern density is directly related to the number of samples involved in the calculation, which determines the variation function of stochastic modelling and has great impacts on the results of reservoir modelling. This paper focuses on the relationship between well pattern density and the variogram of stochastic modelling, selects the large Sulige gas field with many well pattern types as the research object, and establishes a variogram database of stochastic models for different well pattern densities. First, the well pattern in the study area is divided into three different types (well patterns A, B, and C) according to well and row space. Several different small blocks (model samples) are selected from each type of well pattern to establish the model, and their reasonable variogram values (major range, minor range and vertical range) are obtained. Then, the variogram values of all model samples with similar well pattern densities are analysed and counted, and the variogram database corresponding to each type of well pattern is established. Finally, the statistical results are applied to the modelling process of other blocks with similar well pattern density to test their accuracy. The results show that the reservoir model established by using the variation function provided in this paper agrees well with the actual geological conditions and that the random model has a high degree of convergence. This database has high adaptability, and the model established is reliable.

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