Parameter optimization for multistage horizontal well fracturing based on multi-cluster perforation for deep coal measure gas: A case study of the Jurassic Baijiahai area in the Junggar Basin
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摘要:目的
水平井多簇射孔分段压裂已成为深层煤系气效益开发的有效途径之一。然而，深层煤特有的岩石力学性质、储层滤失特性和微裂缝发育特征与非常规页岩、致密砂岩及浅层煤等差异显著，现有压裂经验无法照搬，需要开展针对性压裂参数优化研究。
方法以准噶尔盆地白家海地区深层煤系气储层为对象，建立了顶底板−夹矸−煤复合地质构造的水平井多簇射孔分段压裂模型，模型考虑煤的层理、割理对裂缝扩展和储层滤失的影响，利用小压测试数据对储层关键参数进行修正，综合表征深层煤系气储层的物理力学特性。建立了多目标条件下最优泵注参数组合设计方法，获微地震监测数据验证。
结果和结论结果表明，变黏滑溜水体系相较低黏滑溜水体系、冻胶体系更适合深层煤系气压裂，兼具缝长、缝宽和裂缝均衡性的优势；获得目标区块压裂最优参数组合：3簇+簇间距19 m+每米加砂量2.8 m3+排量16 m3/min。试验井微地震监测结果表明，优化后裂缝半长和改造体积分别增加了57.2%和12.3%。对隔层遮挡严重的深层煤系储层，裂缝在缝高方向通常难以突破，因此，需要提高缝长和缝宽。增大砂量和排量可以显著提高缝长和缝宽，是提升改造效果的关键。
Abstract:ObjectiveThe multistage horizontal well fracturing based on multi-cluster perforation has emerged as an effective approach for the efficient production of deep coal-measure gas (CMG). However, deep coals feature unique rock mechanical properties, fluid loss characteristics of reservoirs, and microfracture developmental characteristics, which differ significantly from those of unconventional shales, tight sandstones, and shallow coals. As a result, existing fracturing experience cannot be directly applied, highlighting the investigation of fracturing parameter optimization tailored for deep CMG production.
MethodsFocusing on deep CMG reservoirs in the Baijiahai area within the Junggar Basin, this study constructed a model of multistage horizontal well fracturing based on multi-cluster perforation for a composite geological structure composed of a roof, a floor, gangue, and coals. This model considered the effects of bedding and cleats in coals on fracture propagation and the fluid loss of reservoirs. Furthermore, critical reservoir parameters in the model were corrected using data derived from mini-fracture tests. These contributed to an elevated accuracy of the model, which, therefore, allowed for the comprehensive characterization of the physical and mechanical properties of deep CMG reservoirs. The optimal fracturing fluid system for deep CMG reservoirs was selected through numerical simulation, and a method for designing the optimal pumping parameter combination under multiple objectives was developed. Finally, the simulation results were verified using microseismic data.
Results and ConclusionsThe results indicate that compared to the low-viscosity slickwater and gelled systems, the variable-viscosity slickwater system was more suitable for the fracturing of deep CMG reservoirs while also enjoying advantages in terms of fracture length, fracture width, and fracture equilibrium. The optimal parameter combination for fracturing in the target block was determined to include three clusters per stage, a cluster spacing of 19 m, a proppant volume of 2.8 m3 per meter, and an injection rate of fracturing fluids of 16 m3/min. The microseismic monitoring results of test wells demonstrate that after parameter optimization, the fracture half-length and stimulated reservoir volume (SRV) increased by 57.2 % and 12.3 %, respectively. A comparison of fracture geometries under varying fracturing parameter combinations reveals that in deep CMG reservoirs subjected to severe blocking by barriers, fractures typically cannot propagate in their height directions, necessitating increasing their lengths and widths. Increasing the proppant volume and the injection rate of fracturing fluids can significantly increase fracture lengths and widths, playing a key role in improving reservoir fracturing performance.
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图 3 小压测试曲线及参数修正
Fig. 3 Curves of mini-fracture tests and physical parameter correction
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图 4 数值模拟−微地震监测结果对比
Fig. 4 Comparison of numerical simulation and microseismic monitoring results
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图 5 半缝长、缝宽箱体图
Fig. 5 Box plots of fracture half-lengths and widths under varying fracturing fluids
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图 7 不同参数组合模拟结果对比
Fig. 7 Comparison of simulation results based on varying parameter combinations
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图 8 水平井参数优化前后微地震监测结果对比
Fig. 8 Comparison of microseismic monitoring results for horizontal wells before and after parameter optimization
表 1 压裂模拟泵注程序
Table 1 Pumping schemes for hydraulic fracturing simulation
压裂液体系 泵注阶段 压裂液类型 排量/(m3·min−1) 液量/m3 支撑剂类型 砂质量分数/(kg·m−3) 低黏滑溜水 前置液 低黏滑溜水 12 240 70/140石英砂 100 携砂液 600 40/70、20/40 200 顶替液 60 — — 变黏滑溜水 前置液 高黏转低黏 240 70/140石英砂 100 携砂液 高黏滑溜水 600 40/70、20/40 200 顶替液 低黏滑溜水 60 — — 冻胶 前置液 冻胶 240 70/140石英砂 100 携砂液 600 40/70、20/40 200 顶替液 60 — — 注：70/140、40/70、20/40表示石英砂目数，对应的粒径分别为0.212 mm/0.106 mm、0.425 mm/0.212 mm、0.850 mm/0.425 mm。顶替液阶段不加砂，用“—”表示。 
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表 2 多簇射孔压裂模拟参数组合
Table 2 Parameter combinations for fracturing simulation based on multi-cluster perforation
簇数 簇间距/m 每米加砂量/m3 排量/(m3·min−1) 3 15 1.84 12 4 20 2.30 14 5 25 2.80 16
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表 3 各目标参数所占权重
Table 3 Weights of various target parameters
权重类型 裂缝均衡性 平均半缝长 缝宽 客观 0.70 0.21 0.09 主观 0.16 0.54 0.30 组合 0.40 0.40 0.20
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表 4 各组合类型参数取值
Table 4 Parameter values for each combination type
组合类型 簇数 簇间距/m 每米加砂量/m3 排量/(m3·min−1) 1 5 19 2.80 16 2 3 25 2.80 16 3 3 19 1.84 16 4 3 19 2.80 12 5 3 19 2.80 16
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表 5 X区块A、B井优化前后对比
Table 5 Comparison of wells A and B in block X before and after parameter optimization
类型
(井号)平均半
缝长/m裂缝
均衡系数单段微地震
事件数总改造体积/
106m3优化前(A井) 138 0.88 62 9.79 优化后(B井) 217 0.89 87 10.99
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