Optimization of micro-electrolysis pretreatment for fracturing flowback fluids based on improved MOGOA

doi:10.16085/j.issn.1000-6613.2024-1837

Abstract

Abstract:

To investigate the efficacy of the micro-electrolysis process in treating fracturing flowback fluid, and to clarify the influence of key parameters on contaminant removal and to optimize the pretreatment technology path, in this study, the effects of reaction time, initial pH, aeration and micro-electrolytic material addition on wastewater viscosity and chemical oxygen demand (COD) removal were firstly investigated by a one-way experiment. Following this, the response surface design was used to optimize the process parameters and fit a second-order response model for COD removal and viscosity reduction. Finally, the improved multi-objective locust optimization algorithm (MOGOA) was used to optimize the parameters and verify the effect. The results showed that the improved algorithm obtained a better Pareto optimal solution, the optimized parameters were: initial pH=2.3, aeration volume 2.3L/min, material dosage 76g/L, and reaction time 73min. Under these conditions, the COD removal rate was 65.92% and the viscosity reduction rate was 56.42%, and the error with the predicted value was less than 2%, which verified the feasibility of the model. The removal efficiencies of chloride ion and bromide ion under this condition were 31.60% and 26.53%, respectively. The "response surface model-algorithm optimization" system constructed in this study improves the accuracy and efficiency of parameter optimization, and provides a quantifiable solution for the pretreatment of fracturing drainback fluid, and the related method is valuable for the optimization of similar processes.

Key words: fracturing flowback fluid, response surface methodology, multi-objective grasshopper optimization algorithm, parameter optimization, multi-objective optimization

摘要：

为探究微电解工艺处理压裂返排液的效能，需明确关键参数对污染物去除的影响并优化预处理技术路径。本文首先通过单因素实验考察反应时间、初始pH、曝气量和微电解材料加量对废水黏度及化学需氧量（COD）去除率的影响；继而利用响应面设计优化工艺参数，拟合COD去除率和降黏率的二阶响应模型；最后采用改进的多目标蝗虫优化算法（MOGOA）优化参数并验证效果。结果显示，改进算法能获得Pareto最优解，优化后参数为初始pH=2.3、曝气量2.3L/min、材料加量76g/L、反应时间73min。在此条件下，COD去除率65.92%、降黏率56.42%，与预测值误差小于2%，验证了模型可行性，该条件下氯离子、溴离子去除率分别为31.60%、26.53%。本文构建的“响应面模型-算法优化”体系提升了参数优化的精准度与效率，为压裂返排液预处理提供了可量化方案，相关方法对同类工艺优化具借鉴价值。

关键词: 压裂返排液, 响应面法, 多目标蝗虫优化算法, 参数优化, 多目标优化

CLC Number:

X741

ZHAO Hanlei, FAN Zheng, LI Zhixiao, GE Xiaodong, HU Kexian, WAN Zhengping, HAN Jie. Optimization of micro-electrolysis pretreatment for fracturing flowback fluids based on improved MOGOA[J]. Chemical Industry and Engineering Progress, 2025, 44(12): 7238-7249.

赵晗蕾, 范峥, 李志潇, 革晓东, 胡科先, 万征平, 韩洁. 基于改进MOGOA的微电解预处理压裂返排液优化[J]. 化工进展, 2025, 44(12): 7238-7249.

Figures/Tables 15

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指标	数值
Ca²⁺/mg·L^-1	564.52
Mg²⁺/mg·L^-1	157.14
Cl^-/mg·L^-1	22856.96
Br^-/mg·L^-1	84.56
CO₃^2-/mg·L^-1	未检出
HCO₃^-/mg·L^-1	462.99
黏度/mPa·s	7.32

指标	数值
Ca²⁺/mg·L^-1	564.52
Mg²⁺/mg·L^-1	157.14
Cl^-/mg·L^-1	22856.96
Br^-/mg·L^-1	84.56
CO₃^2-/mg·L^-1	未检出
HCO₃^-/mg·L^-1	462.99
黏度/mPa·s	7.32

水平编码	因素
水平编码	pH（A）	曝气量（B）/L·min^–1	微电解材料加量（C）/g·L^–1	反应时间（D）/min
-1	2	1.5	60	40
0	3	2.0	80	60
1	4	2.5	100	80

水平编码	因素
水平编码	pH（A）	曝气量（B）/L·min^–1	微电解材料加量（C）/g·L^–1	反应时间（D）/min
-1	2	1.5	60	40
0	3	2.0	80	60
1	4	2.5	100	80

来源	平方和	自由度	均方	F值	P值	显著性
模型	2801.6	14	200.11	123.36	<0.0001	*
A	105.55	1	105.55	65.07	<0.0001	*
B	36.32	1	36.32	22.39	0.0003	*
C	36.74	1	36.74	22.65	0.0003	*
D	6.29	1	6.29	3.88	0.0691
AB	0.9716	1	0.9716	0.599	0.4518
AC	0.4565	1	0.4565	0.2814	0.6041
AD	1.37	1	1.37	0.846	0.3733
BC	0.0003	1	0.0003	0.0002	0.9892
BD	0.7085	1	0.7085	0.4367	0.5194
CD	0.0064	1	0.0064	0.0039	0.951
A²	2477.92	1	2477.92	1527.55	<0.0001	*
B²	201.53	1	201.53	124.24	<0.0001	*
C²	5.82	1	5.82	3.59	0.0791
D²	6.25	1	6.25	3.85	0.0699
残差	22.71	14	1.62
失拟项	20.53	10	2.05	3.76	0.1067
误差	2.18	4	0.5458
总计	2824.31	28
标准偏差	1.27
平均值	69.67
变异系数	1.83
决定系数R²	0.992
校正决定系数	0.9839
预测决定系数	0.9569
信噪比	33.6496