Scholarlink

<p>Hydraulic fracturing operations require precise control of friction-reducer dosage to minimize pumping costs, yet the nonlinear coupling between polymer concentration, flow rate, and drag reduction (DR) efficiency remains difficult to predict quantitatively. To address this gap, the present study develops a predictive Response Surface Methodology (RSM) framework for optimizing the DR performance of oxidized polyethylene (1 MDa) in aqueous fracturing fluids. Using a closed-loop pipe flow system (inner diameter 3&#xa0;cm, test length 10&#xa0;m), a central composite design (CCD) was executed over the parameter space of polymer concentration (200–600 ppm) and volumetric flow rate (10–50&#xa0;L/min) at 20 ± 0.5&#xa0;°C. The resulting quadratic regression model correlating DR% with the two factors is statistically highly significant (<i>p</i> &lt; 0.01, R<sup>2</sup> = 0.985, Adj. R<sup>2</sup> = 0.961). The RSM model predicts an optimum DR% of ~ 69.3% at a polymer concentration of ~ 376 ppm and a flow rate of ~ 33&#xa0;L/min (Re ≈ 35 000), which is experimentally bracketed by the center-point confirmation run (400 ppm, 30&#xa0;L/min, measured DR% = 69.0%). Validation experiments confirm a prediction error below 2%, and scale-up analysis via empirical scaling laws projects a DR% of 59% under field-relevant conditions (Re = 100 000, large-diameter pipe). Furthermore, temporal degradation tests reveal that DR performance decays exponentially under continuous circulation (first-order rate constant k = 0.045&#xa0;min<sup>−1</sup>), declining from 70% to 45% within 20&#xa0;min. These findings provide a reproducible, data-driven basis for real-time dosage optimization and operational fluid management in hydraulic fracturing.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Response surface modeling of oxidized polyethylene drag reduction for hydraulic fracturing

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月22日

查看全文
  • Haowen Yuan,
  • Qingli Zhu,
  • Zhiguo Sun,
  • Chao Kang,
  • Xiaolei Zhang,
  • Tao Cheng

摘要

Hydraulic fracturing operations require precise control of friction-reducer dosage to minimize pumping costs, yet the nonlinear coupling between polymer concentration, flow rate, and drag reduction (DR) efficiency remains difficult to predict quantitatively. To address this gap, the present study develops a predictive Response Surface Methodology (RSM) framework for optimizing the DR performance of oxidized polyethylene (1 MDa) in aqueous fracturing fluids. Using a closed-loop pipe flow system (inner diameter 3 cm, test length 10 m), a central composite design (CCD) was executed over the parameter space of polymer concentration (200–600 ppm) and volumetric flow rate (10–50 L/min) at 20 ± 0.5 °C. The resulting quadratic regression model correlating DR% with the two factors is statistically highly significant (p < 0.01, R2 = 0.985, Adj. R2 = 0.961). The RSM model predicts an optimum DR% of ~ 69.3% at a polymer concentration of ~ 376 ppm and a flow rate of ~ 33 L/min (Re ≈ 35 000), which is experimentally bracketed by the center-point confirmation run (400 ppm, 30 L/min, measured DR% = 69.0%). Validation experiments confirm a prediction error below 2%, and scale-up analysis via empirical scaling laws projects a DR% of 59% under field-relevant conditions (Re = 100 000, large-diameter pipe). Furthermore, temporal degradation tests reveal that DR performance decays exponentially under continuous circulation (first-order rate constant k = 0.045 min−1), declining from 70% to 45% within 20 min. These findings provide a reproducible, data-driven basis for real-time dosage optimization and operational fluid management in hydraulic fracturing.