澳大利亚昆士兰州Surat盆地致密Walloons煤层压裂增产面临的挑战

T. Flottmann, V. Pandey, S. Ganpule, Elliot Kirk-Burnnand, Massoud Zadmehr, N. Simms, J. Jenkinson, Tristan Renwick-Cooke, M. Tarenzi, Ashok Mishra
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引用次数: 2

摘要

澳大利亚昆士兰州Surat盆地的Walloons煤系含有世界级的煤层气(CSG)储层,由于高斯曲率相关的天然裂缝连通性,其渗透率从高(>1达西)到低(300米),渗透率从<1mD - ~30mD不等。在煤炭脱水过程中,当(不可压缩)水被(可压缩)气取代时,产能指数(PI)会下降。2010年之前,Surat盆地的早期增产措施遵循了页岩行业的“标准”高速率水/砂设计。然而,高处理压力和速率导致了几次套管剪切(Johnson et al. 2003),特别是在与应力状态变化相关的深度。随后的设计(2010-12)重复出现了水裂缝,尽管包括了大量的诊断(Johnson et al . 2010;Flottmann et al . 2013),表明水力压裂在开采Walloons煤方面似乎是无效的。2015年的设计优化(Kirk-Burnnand et al. 2015)基于大量的建模工作(Pandey and Flottmann 2015),确定了低速率凝胶裂缝是开采具有“延展性”walloons特定煤性岩石的最佳选择。然而,为了优化高度增长,既要连接煤,又要避免高度增长进入非储层,处理率受到限制。最初的生产数据表明,一些压裂煤的产能下降(Busetti et al. 2017)。因此,在2016年底对增产设计进行了修改,以解决产能下降的问题,同时最大限度地提高流体采收率。增产后的早期降压策略也进行了现场测试,以减轻由于过度降压可能导致部分或全部裂缝关闭(特别是在井筒附近),并导致储层与井之间失去联系而造成的井产能损失。致密Walloons煤中确定的地下驱动因素控制着任何增产措施的有效性。这些驱动因素以多种方式影响刺激的有效性。首先,这些驱动因素可能导致井与油藏之间的连通性不佳,从而导致产能低下和边际采收率。其次,驱动因素可能会影响作业者选择昂贵的增产方案,这些方案可能会提供更好的井与油藏连通性,但由于涉及的高成本而降低了经济价值。因此,如本文所述,在选择增产设计时考虑地下驱动因素是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fracture Stimulation Challenges in Tight Walloons Coal Measures: Surat Basin Queensland, Australia
Walloons Coals of the Surat Basin, Queensland (Australia) contain world class Coal Seam Gas (CSG) plays, where permeability varies from high (>1Darcy), due to Gaussian curvature-related natural fracture connectivity, to low (<1mD) due to unidirectional fracture-systems attributed to regional unidirectional flexure. The low permeability Walloons Coals require stimulation to unlock their gas resources. This contribution describes the design evolution of stimulation concepts in the Surat Basin in context of five key subsurface drivers Coal net to gross: Surat Basin coals contain 30 coal seams with a cumulative thickness of 20-35m in a gross rock column of >300m Permeability of coals requiring stimulation for economic flow rates varies from <1mD - ~30mD Varying stress regimes, both vertically and laterally Ductile rock properties in Walloons coal reservoirs Productivity Index drop (PI drop) can occur when (incompressible) water is replaced by (compressible) gas during coal dewatering Early stimulation treatments in Surat Basin (pre-2010) followed ‘standard’ high rate water/sand designs adapted from the shale industry. However, high treating pressure and rates resulted in several instances of casing shear (Johnson et al. 2003) particularly at depths associated with stress regime transitions. Subsequent designs (2010-12) repeated water fracs albeit including ample diagnostics (Johnson et al 2010; Flottmann et al 2013), showing that water fracs appear to be ineffective in stimulating Walloons Coals. Design optimizations in 2015 (Kirk-Burnnand et al. 2015) based on extensive modeling work (Pandey and Flottmann 2015), identified low rate gel fracs as optimal to stimulate rocks with ‘ductile’ Walloons-specific coal properties. However, treatment rates were limited to optimize height growth, both to connect coals and to avoid height growth into non-reservoir. Initial production data indicated a drop in well productivity in some fracture stimulated coals (Busetti et al. 2017). Consequently, stimulation designs were modified in late 2016 to account for such productivity drops while maximizing the fluid recovery. Early time post stimulation drawdown strategy was also field-tested to mitigate loss of well productivity due to excessive drawdown which could cause partial or full fracture closure (especially near the wellbore region), and lead to loss of communication between reservoir and well. Sub-surface drivers identified in tight Walloons Coals control the effectiveness of any stimulation option deployed. These drivers influence the effectiveness of stimulation in multiple ways. First, these drivers can lead to a sub-optimal connectivity between well and reservoir resulting in poor productivity and marginal recovery. Second, the drivers may influence an operator towards expensive stimulation options which may provide better well to reservoir connectivity but diminish the economic value due to the high costs involved. Hence the inclusion of sub-surface drivers in selecting stimulation design is paramount as demonstrated in this paper.
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