An automatic historical fitting method for a multi-scale fractured medium of a tight oil and gas reservoir

A history-matching, multi-scale technology, applied in the field of automatic history-matching of multi-scale fractured media in tight oil and gas reservoirs, to achieve the effect of improving prediction accuracy and utilization efficiency

Pending Publication Date: 2019-04-02
PEKING UNIV
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Problems solved by technology

[0004] In order to solve the inversion problem of multi-scale fractures in tight oil and gas reservoirs, the present invention proposes an automatic history fitting method for multi-scale fractured media in tight oil and gas reservoirs. The fracture description method and

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  • An automatic historical fitting method for a multi-scale fractured medium of a tight oil and gas reservoir
  • An automatic historical fitting method for a multi-scale fractured medium of a tight oil and gas reservoir
  • An automatic historical fitting method for a multi-scale fractured medium of a tight oil and gas reservoir

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Embodiment Construction

[0028] The present invention will be further elaborated below through specific embodiments in conjunction with the accompanying drawings.

[0029] The automatic history fitting method for multi-scale fractured media in tight oil and gas reservoirs in this embodiment, such as Figure 4 shown, including the following steps:

[0030] 1) Obtain observation data:

[0031] A schematic diagram of a reservoir block containing multi-scale fractures is shown in figure 1 As shown, the oil production rate and water production rate of production wells in tight oil and gas reservoirs are measured by surface separators and volumetric instruments, as observation data, respectively as figure 2 (a) and (b);

[0032] 2) Generate initial guesses for multi-scale fractures:

[0033] Using the Hough space Gaussian random field as the parameter of the large-scale fracture distribution, the initial guess of the large-scale fracture distribution is generated; the level set function is used as the ...

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Abstract

The invention discloses an automatic historical fitting method for a multi-scale fractured medium of a tight oil and gas reservoir. According to the method, differentiated processing is carried out oncracks of different scales, the multi-scale cracks are characterized by combining an explicit large-scale crack description method and an approximate small-scale crack region description method, namely parameterization is achieved, and an iteration minimization algorithm is adopted on the basis of a proposed parameterization method to form an automatic historical fitting method. According to themethod, the utilization efficiency of the dynamic production data of the tight oil and gas reservoir production well can be improved, the prediction precision of future production of the tight oil andgas reservoir production well is improved, and a foundation can be laid for optimization of a development strategy of the tight oil and gas reservoir.

Description

technical field [0001] The invention relates to oil exploitation technology, in particular to an automatic history fitting method for multi-scale fractured media in tight oil and gas reservoirs. Background technique [0002] Due to the extremely low matrix permeability, the development of tight oil and gas reservoirs generally requires fracturing measures. The fracturing process will connect natural fractures to form a complex fracture network while producing fractured fractures. The fracture network provides a high-permeability channel for oil and gas flow, which is the key to the economical development of tight oil and gas reservoirs. Therefore, an accurate understanding of the spatial distribution of fracture networks is the key to predicting future production and optimizing development strategies of tight oil and gas reservoirs. [0003] History matching technology based on production well dynamic production data is the main tool to understand the spatial distribution ...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 常海滨姚梦碧
Owner PEKING UNIV
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