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A New Method of Characterizing the Stimulated Reservoir Volume Using Tiltmeter-Based Surface Microdeformation Measurements

机译:一种新方法,使用基于TILTMETER的表面微码测量来表征刺激的储存量

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Unlocking shale gas has been extremely successful during the last decade. Nevertheless, new challenges will continuously arise. One of the most pressing current issues is to know the stimulated reservoir volume (SRV), the part of the reservoir that actually received fracturing fluid. The most widely used technology for estimating SRV is downhole microseismic mapping. Under many conditions, it yields reasonably accurate/reliable information about SRV (Mayerhofer et al. 2008). Unfortunately, it requires an observation well in close proximity to the treatment well in which to place the geophone string used to sense the small seismic signals. This requirement often makes it impossible to provide an SRV estimate for many of the hydraulic-fracture treatments that could benefit from this information. This paper presents an alternative to the downhole-microseismic SRV mapping. A new method, stimulated reservoir characterization (SRC), is based on surface microdeformation measurements obtained with a precision surface tiltmeter array. Tiltmeter-based hydraulic-fracture diagnostics have been successfully used for more than two decades on more than 10,000 hydraulic-fracture treatments. SRV is typically calculated for highly jointed shale reservoirs or coal seams in which injected fluids can inflate a myriad of interconnected hydraulic fractures in two or more dominant orientations. The measured surface deformation is the superposition of all the deformation fields resulting from the inflation of each individual fracture. This makes the deformation-based approach for SRV estimation a convoluted process and requires much more complex tilt-data analysis than does a simple planar hydraulic fracture. This paper describes a new technique for tilt-based SRV estimation, which is capable of resolving spatial distribution, orientations, and volume percentages of the major components of a fracture network. Hence, the new technique allows not only an insight into the areal penetration of treatment fluids into the reservoir, but also an understanding of how multiple joint sets, each with unique orientations, are actually accepting the injected fluids and proppant. This paper includes synthetic data examples and SRV results derived by applying the new technique to a hydraulic-fracture-stimulation project in the lower Eagle Ford shale formation.
机译:在过去十年中,解锁页岩气体已经非常成功。尽管如此,将不断出现新的挑战。最紧迫的当前问题之一是要知道刺激的储层体积(SRV),实际接受压裂液的储层的一部分。最广泛使用的估算SRV技术是井下微震映射。在许多条件下,它产生了关于SRV的合理准确/可靠的信息(Mayerhofer等,2008)。不幸的是,它需要良好的观察,其靠近处理井,在其上放置用于感测小地震信号的地震弦串。这种要求通常使得不可能为许多可以从这些信息中受益的液压破裂处理提供SRV估计。本文提出了井下微震SRV测绘的替代品。一种新的方法,刺激的储存器表征(SRC),基于用精密表面倾斜计阵列获得的表面微码测量。基于TILTMETER的液压骨折诊断已成功地用于超过10,000个液压骨折治疗的二十多年。 SRV通常计算用于高度关节的页岩储存器或煤层,其中注入的流体可以以两个或更多个主导取向膨胀互连的液压骨折。测得的表面变形是由每个单独骨折的膨胀产生的所有变形场的叠加。这使得SRV估计基于变形的方法是卷积过程,并且需要比简单的平面液压骨折更复杂的倾斜数据分析。本文介绍了一种基于倾斜的SRV估计的新技术,其能够解决骨折网络主要部件的空间分布,方向和体积百分比。因此,新技术不仅可以深入了解处理流体进入储存器的面积渗透,还可以理解多个关节套,每个接头套是如何具有独特取向的,实际上是接受注入的流体和支撑剂。本文包括通过将新技术应用于下鹰福特页岩形成的液压 - 断裂刺激项目来源的合成数据示例和SRV结果。

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