基于分布温度回温分析的裂缝定量诊断的现场应用

Y. Mao, C. Godefroy, M. Gysen
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引用次数: 0

摘要

多段水力压裂井的裂缝诊断仍然具有挑战性,但对于确定增产作业的质量和未来井的完井策略至关重要。由于注入的增产液的温度与原来的地热不同,因此增产后的热剖面经过了很大的改变,且高度不均匀,这为裂缝诊断提供了巨大的潜力。在这项工作中,提出了一个分析水力压裂后关井期相关温度信号的模型,并对两个数据集进行了试点测试。该模型扩展了传统热注入剖面算法的范围,具有裂缝诊断功能。在开发过程中,我们将现有的常规井回温模型与新开发的增产区热模型结合起来分析关井温度数据。对该模型的两个主要输出,即注入液量和裂缝扩展程度进行了估计和测试。然后,该模型被自动化并在软件包中完全实现。该工作的主要应用是压裂井中各射孔簇的注入液量和裂缝扩展程度。注入剖面和裂缝扩展的空间分辨率可以达到亚米尺度(与分布式感温空间分辨率相同)。与常规的径向回温模型相比,压裂井在注入量较大的情况下,温度信号的升温趋势要快得多。这种行为可以归因于额外的热损失到未受刺激的区域和团簇之间更大的接触面积。另一方面,泄漏流体在裂缝面周围形成了一个较冷的受激区域,与线性流动模式相比,这使得回温趋势变慢。本研究开发的模型考虑了这两种行为来模拟实际数据集。逆模型既估算了受刺激区域的裂缝扩展程度,也估算了裂缝平面的裂缝扩展程度。这两种估计可以共同推断单个簇的泄漏程度。作为一个试点项目,该模型在两个数据集的暖背温度数据上进行了测试。利用该模型获得的注入剖面结果与其他数据源获得的剖面结果一致,而估算的单个簇的裂缝扩展程度呈现出不同类型的裂缝几何形状(对称、不对称、双峰等)。在现场研究中,使用暖回分析对单个簇进行定量注入剖面和裂缝扩展程度估计已被证明是可行和可靠的。这可能是业内第一个应用于压裂井的定量回温分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Field Applications of Quantitative Fracture Diagnostic From Distributed Temperature Warmback Analysis
Fracture diagnostic on a cluster scale of multi-stage hydraulic fracturing wells remains challenging but essential to determine the quality of the stimulation operation and the completion strategies for future wells. Since the stimulation fluid is injected at a different temperature compared to the original geothermal, the considerably modified and highly heterogeneous thermal profile after stimulation presents significant potential to serve for fracture diagnostic purposes. In this work, a model to analyze the temperature signal associated with the shut-in period after hydraulic fracturing is presented, along with the pilot testing of two datasets. The model extends the scope of traditional thermal injection profiling algorithm with fracture diagnostic functions. During the development process, we incorporate the existing warmback model of conventional wells in analyzing shut-in temperature data with a newly developed stimulated region thermal model. Two main outputs of the model, the injection fluid intake and the fracture propagation extent, are estimated and tested. The model is then automated and thoroughly implemented in the software package. The primary applications of this work are injection fluid intake and fracture propagation extent of each perforation cluster in fractured wells. The spatial resolution of the injection profiling and fracture growth can reach the sub-meter scale (same as the distributed temperature sensing spatial resolution). Compared to the conventional radial warmback model, the temperature signals from the fractured well show a much faster warming trend while taking relatively larger amounts of injection fluid. This behavior can be attributed to the additional heat loss to the unstimulated region and larger contact area between clusters. On the other hand, leak-off fluids create a cooler stimulated region around the fracture plane, which makes the warmback trend slower compared to the linear flow regime model. The model developed in this study considers both behaviors to simulate the actual datasets. The inverse model estimates the fracture propagation extent in both the stimulated region as well as the fracture plane. Both estimations can jointly infer the leak-off extent of an individual cluster. As a pilot project, this model is tested on warmback temperature data from two datasets. The injection profiling results using the model are consistent with profiles obtained from other data sources, while the estimated fracture propagation extents of individual clusters present different types of fracture geometry (symmetrical, asymmetrical, double peaks, etc.). Quantitative injection profiling and fracture propagation extent estimations of an individual cluster using warmback analysis have been proven viable and reliable in this field study. It could be the first quantitative warmback analysis applied to fracture wells in the industry.
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