Intelligent Fracture Diagnostic Procedure Using Smart Microchip Proppants Data

Vuong Van Pham, Amirmasoud Kalantari Dahaghi, S. Negahban, W. Fincham, A. Babakhani
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Abstract

Unconventional oil and gas reservoir development requires an understanding of the geometry and complexity of hydraulic fractures. The current categories of fracture diagnostic approaches include methods for near-wellbore (production and temperature logs, tracers, borehole imaging) and far-field techniques (micro-seismic fracture mapping). These techniques provide an indirect and/or interpreted fracture geometry. Therefore, none of these methods consistently provides a fully detailed and accurate description of the character of created hydraulic fractures. This study proposes a novel approach that uses direct data from the injected fine size and battery-less Smart MicroChip Proppants (SMPs) to map the fracture geometry. This novel approach enables direct, fast, and smart of the received high-resolution geo-sensor data from the SMPs collected in high pressure and high-temperature environment and maps the fracture network using the proposed Intelligent and Integrated Fracture Diagnostic Platform (IFDP), which is a closed-loop architecture and is based on multi-dimensional projection, unsupervised clustering, and surface reconstruction. Affine transformation and a shallow ANN are integrated to control the stochasticity of clustering. IFDP proves its efficacy in fracture diagnostics for 3 in-house design synthetic fracture networks, with 100% consistency, rated "fairly satisfied" to "highly satisfied" in prediction capability, and between 85-100% in execution robustness. The integration of the couple affine transformation-ANN increases the performance of unsupervised clustering in IFDP.
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使用智能Microchip支撑剂数据的智能裂缝诊断程序
非常规油气储层的开发需要了解水力裂缝的几何形状和复杂性。目前的裂缝诊断方法包括近井方法(产量和温度测井、示踪剂、井眼成像)和远场技术(微地震裂缝作图)。这些技术提供了间接和/或解释裂缝的几何形状。因此,这些方法都不能对水力裂缝的特征提供完整、详细和准确的描述。该研究提出了一种新方法,利用注入的细尺寸和无电池的Smart MicroChip支撑剂(SMPs)的直接数据来绘制裂缝几何形状。这种新方法可以直接、快速、智能地处理高压高温环境下smp采集的高分辨率地理传感器数据,并使用智能综合裂缝诊断平台(IFDP)绘制裂缝网络图。IFDP是一种闭环架构,基于多维投影、无监督聚类和表面重建。结合仿射变换和浅层人工神经网络控制聚类的随机性。IFDP在3个自行设计的合成裂缝网络的裂缝诊断中证明了其有效性,预测能力达到100%的一致性,“相当满意”到“高度满意”,执行稳健性在85-100%之间。耦合仿射变换与人工神经网络的结合提高了IFDP中无监督聚类的性能。
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