基于模糊逻辑控制的页岩气井智能化调产预警

doi:10.13809/j.cnki.cn32-1825/te.2025.01.019

Abstract

Abstract:

Against the backdrop of continuously advancing big data technology, digitization and intelligent production management of oil and gas fields have become an inevitable trend. Shale gas wells face challenges such as liquid accumulation, sand production, and high stress sensitivity, necessitating the consideration of numerous factors during production adjustment. Traditional methods, which require extensive manual labor and exhibit low efficiency in production adjustment warnings, fail to consider multiple factors for optimal adjustment. To address this issue, considering the typical lifecycle characteristics of shale gas wells, the study divided the lifecycle into three stages: liquid unloading and gas transportation, stable production and pressure reduction, and fixed pressure and production reduction. Specific production adjustment rules tailored to different lifecycle stages were defined and six types of production adjustment indicators were proposed, including pressure drop method in stable production period, gas production per unit pressure drop method, critical sand-carrying flow rate method, critical liquid-carrying flow rate method, empirical chart method, and intermittent well-switching method. Based on these production adjustment rules and indicators, combined with field experience, an intelligent production adjustment early warning model for shale gas wells using fuzzy logic control was established. Implemented in Python, this model allows for real-time calculation of all production adjustment indicators and the fuzzy logic control algorithm as the well production dynamics change. This method has been applied in over a hundred wells in the Weirong shale gas field, reducing early warning times for production adjustments to just 30 seconds, compared to the traditional methods that require at least 5 days. The timely early warning of production adjustment needs has achieved good application results. In the future, combining remote control of oil nozzles or choke valves to adjust the production regime can provide technical support for intelligent oil and gas fields.

Key words: shale gas wells, fuzzy logic, intelligent, early warning production adjustment, Python

CLC Number:

TE33.2

HE Chunyan,ZHAO Yong,LI Nanying, et al. Intelligent production adjustment early warning for shale gas wells based on fuzzy logic control[J]. Petroleum Reservoir Evaluation and Development, 2025, 15(1): 152-160.

Figures/Tables 8

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References 25

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参数	低配	中低配	合适	中高配	高配
临界携液流量法（排液输气阶段）	S(-0.7,-40.0)	G(0.2,5.0,-0.6)	S(-0.4,40.0)
临界携液流量法（其他阶段）	S(-0.4,-100.0)	G(0.2,15.0,-0.2)	S(0,100.0)
临界出砂流量法			S(0,-100.0)	G(0.2,15.0,0.2)	S(0.4,100.0)
稳产期压降法（排液输气阶段）	S(-0.9,-40.0)	G(0.3,5.0,-0.6)	G(0.3,5.0,0)	G(0.3,5.0,0.6)	S(0.9,40.0)
稳产期压降法（其他阶段）	S(-0.5,-60.0)	G(0.2,5.0,-0.3)	G(0.2,5.0,0)	G(0.2,5.0,0.3)	S(0.5,60.0)
单位压降产气法	S(-0.5,-60.0)	G(0.2,5.0,-0.3)	G(0.2,5.0,0)	G(0.2,5.0,0.3)	S(0.5,60.0)
经验图版法	S(-0.5,-60.0)	G(0.2,5.0,-0.3)	G(0.2,5.0,0)	G(0.2,5.0,0.3)	S(0.5,60.0)
间歇开关井法	S(-0.2,-10.0)		G(0.2,20.0,0)		S(0.2,10.0)
调产预警输出	S(-0.5,-60.0)	G(0.2,5.0,-0.3)	G(0.2,5.0,0)	G(0.2,5.0,0.3)	S(0.5,60.0)

生产阶段	稳产期压降法	临界携液流量法	临界出砂流量法	间歇开关井法	调产结论
排液输气		低配			大幅上调
		中低配			小幅上调
		合适	高配		大幅下调
		合适	中高配		小幅下调
	高配	合适	合适		大幅下调
	中高配	合适	合适		小幅下调
	合适	合适	合适		不调
	中低配	合适	合适		小幅上调
	低配	合适	合适		大幅上调
稳产降压		低配			大幅上调
		中低配			小幅上调
		合适	高配		大幅下调
		合适	中高配		小幅下调
	2个及以上高配	合适	合适		小幅下调
	2个及以上中高配	合适	合适		大幅下调
	2个及以上合适	合适	合适		不调
	2个及以上中低配	合适	合适		小幅上调
	2个及以上低配	合适	合适		大幅上调
间歇开关井		合适	合适	合适	不调
				关井	大幅下调（关井）
				开井	大幅上调（开井）

生产天数/ d	经验图版法	临界携液流量法	临界出砂流量法	稳产期压降法	单位压降产气法	间歇开关井法	模型输出值	调产输出	目前产气量/ （10⁴m³/d）	调产幅度参考值
45		-0.12	-0.71	-0.31	0.57		-0.17	小幅上调	10	10%
90	0.86	0.04	-0.62	0.32	0.07		0.20	小幅下调	12	-10%
200	0.69	-0.25	-0.65	-0.03	-0.09		0	不调	9	0
2 340		0.04	-0.63			0.5	0.68	大幅下调	1	关井

Intelligent production adjustment early warning for shale gas wells based on fuzzy logic control

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