A geological characterization method for the stimulated volume of shale reservoirs

Abstract

The invention discloses a geological characterization method of a transforming volume of a shale gas reservoir. The method comprises the following steps: acquiring reservoir physical properties and rock mechanical parameters; calculating brittleness factors Brit, novel brittleness factors Bn, reservoir breaking tenacity indexes Kn, natural fracture open difficulty indexes Pn and crack through evaluation indexes Cn corresponding to logging points; establishing novel evaluation factors En corresponding to logging data points and judging the novel evaluation factors; and finally, acquiring the transforming volume of the reservoir through a crack propagation wave and length Lo, wave and height Ho and wave and width Wo. The method disclosed by the invention has the beneficial effects that by means of static production data, the transforming volume of the reservoir is pre-evaluated by adopting dynamic geological data such as logging, so that the deployment of a well toil and a beneficial fracture section are formulated and selected before fracture construction, and the method is of relatively high practicality.

Description

technical field [0001] The invention relates to a geological characterization method for the reformed volume of shale reservoirs, belonging to the technical field of oil field development. Background technique [0002] The stimulated volume (SRV) of shale reservoirs is an evaluation index for high production of a single well, and it is of great significance to the prediction and characterization of the stimulated volume (SRV) of shale reservoirs. The characterization and calculation methods of reservoir stimulated volume have developed from qualitative to quantitative, and currently mainly include production fitting method, semi-empirical formula method, discrete network model method, microseismic monitoring method and semi-analytical method. The production fitting method adopts the mean model without considering the anisotropy caused by the development of natural fractures in shale reservoirs, and the single-stage productivity data cannot be obtained due to the staged fract...

AI Technical Summary

Problems solved by technology

For the prediction of reservoir fracturability and fracturing scale, the focus should be on the analysis of shale reservoir geology and mechanical characteristics of fracturing process, while the existing research focuses more on the construction conditions of lateral fracturing. This may be because the geological analysis of the reservoir is neglected, so that the construction process consumes a lot of financial and material resources and may damage the shale reservoir

However, evaluating the compressibility of shale reservoirs only through geological and mechanical characteristics cannot quantitatively describe the approximate extension scale of complex fracture networks.

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