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裂缝识别对碳酸盐岩储层测井评价至关重要,传统的测井仪器由于探测深度浅(小于3米)而无法对井壁外围(大于3米)裂缝发育情况进行评价,远探测声波测井仪器釆用相控阵发射、同时加大源距,有效提升了测井仪器的探测深度。但由于缺少正演模拟研究,目前对于裂缝的解释往往是基于经验而缺乏理论依据,导致很多现象难以解释。本文利用髙阶有限差分方法对远探测声反射波测井裂缝识别进行了正演模拟及叠前逆时偏移成像研究,首先在理论研究的基础上构建正演模型,重点研究不同裂缝离井壁距离、裂缝张开度和倾角的响应特征;其次在单因素变化基础上提取成像区域的能量强度,分析确定出在实际地层速度有波动变化时远探测声反射波测井方法能够识别裂缝的条件;最后通过对裂缝识别的影响因素定量化分析,确定裂缝识别的最大距离、最小张开度和最小倾角,降低了裂缝识别与评价中的多解性。研究成果对远探测声反射波测井仪器的发展、数据处理方法的改进,以及后续的测井解释工作都有一定的借鉴意义。
Fracture identification is very important for carbonate reservoir well logging evaluation. Traditional logging tools can not evaluate the development of cracks in the periphery (more than 3 meters) due to the shallow exploration depth (less than 3 meters) Logging instruments preclude the use of phased array emission, while increasing the source spacing, effectively enhance the logging depth of logging tools. However, due to the lack of forward simulation research, the current interpretation of cracks is often based on experience and lack of theoretical basis, resulting in many phenomena difficult to explain. In this paper, the 髙 order finite difference method is used to carry out forward modeling and prestack inverse time migration imaging of far-sounding acoustic logging. First, based on the theoretical research, a forward model is constructed, focusing on different fractures Wall distance, crack opening degree and dip angle. Secondly, the energy intensity of the imaging area was extracted based on the single-factor change, and the condition that the remote sounding acoustic logging method can recognize the crack when the actual formation velocity fluctuated was analyzed. Finally, by quantitative analysis of the influencing factors of the fracture identification, the maximum distance, the minimum opening degree and the minimum inclination of the fracture identification are determined, which reduces the multi-solution in the identification and evaluation of the fracture. The research results have some reference to the development of far-sounding acoustic reflection logging tools, the improvement of data processing methods and the subsequent logging interpretation.