采用PSO算法的页岩气水平井DTS数据反演方法

doi:10.13810/j.cnki.issn.1000-7210.2023.05.017

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Abstract To realize the quantitative interpretation of multidimensional unknown parameters such as production profile, artificial fracture parameters, and permeability of the fracture network for a horizontal well in shale gas reservoirs, this paper proposes an inversion method based on particle swarm optimization (PSO) algorithm to inverse the distributed temperature sensing (DTS) data in the horizontal well.This inversion method consists of a forward prediction model of temperature profile and PSO algorithm.The forward prediction model is employed to simulate the temperature profile in each inversion iteration step.The PSO algorithm is adopted to optimize and update the unknown parameters such as production profile and fracture parameters in each iteration to gradually reduce the error between the simulated temperature profile and the measured DTS data of a horizontal well in shale gas reservoirs until convergence is achieved.The inversion results of a field well indicate that the predicted temperature profile is well fitted with the measured DTS data, and the absolute temperature deviation at each effective artificial fracture location is less than 0.03℃.The inversion results of the production profile are in good agreement with the PLT(Production Logging Tool) test, and the maximum deviation of flow rate in any individual fracturing stage is only 0.291 × 10⁴ m³/d, which verifies the reliability of the proposed method.Finally, a basis is provided for balancing production profiles and improving the productivity of a single well in shale gas reservoirs.

Key words： production profile interpretation artificial fracture parameter inversion method distributed temperature sensing (DTS) particle swarm optimization (PSO) algorithm horizontal wells in shale gas reservoirs

Received: 27 October 2022

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P631

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	LUO Hongwen
	AI Wenbin
	LI Haitao
	XIANG Yuxing
	ZHANG Qin
	LI Ying

Cite this article:

LUO Hongwen,AI Wenbin,LI Haitao等. Inversion method of distributed temperature sensing data for horizontal wells in shale gas reservoirs based on PSO algorithm[J]. OGP, 2023, 58(5): 1202-1210.

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http://www.ogp-cn.com/EN/10.13810/j.cnki.issn.1000-7210.2023.05.017 OR http://www.ogp-cn.com/EN/Y2023/V58/I5/1202

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