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基于最小二乘逆时偏移的场声反射成像测井模拟

Modeling of Acoustic Reflection Imaging Logging Based on Least-square Reverse Time Migration

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【作者】 邹强黄建平刘定进魏巍郭旭

【Author】 ZOU Qiang;HUANG Jianping;LIU Dingjin;WEI Wei;GUO Xu;School of Geosciences, China University of Petroleum;SINOPEC Geophysical Research Institute;

【通讯作者】 黄建平;

【机构】 中国石油大学(华东)地球科学与技术学院中国石油化工股份有限公司石油物探技术研究院中国石化胜利油田分公司物探研究院

【摘要】 近年来,声反射成像测井技术(ARILT)在井旁裂缝、孔洞性储层评价中成为研究热点。常规ARILT的探测深度一般在20 m以内,且对复杂构造边界刻画能力不足。本文基于测井观测系统及采集参数,将最小二乘逆时偏移(LSRTM)地震成像技术引入ARILT中,以提高井旁区域有效成像范围和成像精度。本文在实现偏移算法及处理流程基础上,将算法用于典型模型和实际资料,重点分析不同频率、深度和偏移方法成像效果的差异。成像结果对比发现:(1)偏移算法影响ARILT成像精度,LSRTM具有较高分辨率,并能揭示构造体横向变化特征;(2)激发源频率也影响成像分辨率,提高频率会改善分辨率,但会降低探测深度;(3)在给定的测井观测参数下,LSRTM能有效探测23 m范围内的井旁构造。

【Abstract】 In recent years, the acoustic reflection imaging logging technique(ARILT) has become a research hotspot in evaluation of fractures and holes reservoirs close to borehole. The conventional ARILT can generally detect structures within 20 meters, and has certain limitations on describing complex structural boundaries. In this paper, the least-square reverse time migration(LSRTM) is introduced into ARILT on the premise of matching logging observation systems and calculation parameters, which will improve the effective imaging range and imaging precision nearby the well area. Based on the realization of migration algorithms and processing flows, the article applies the algorithms to typical models and one actual data, and focuses on analyzing the imaging effects of different frequencies, depths and migration methods. It is found by comparing the imaging results that(1) the effective imaging algorithms are the key to the imaging accuracy of ARILT. LSRTM not only has a high resolution, but also can reveal the horizontal change of the structures;(2) Excitation source’s frequency is an important factor affecting the resolution of imaging as the result that the higher the frequency, the higher the image resolution, but the high frequency will lose detecting depth;(3) LSRTM can effectively detect structures within 23 meters under the given logging observation parameters in this paper.

【基金】 中国科学院战略性先导科技专项(A)(XDA14010303);国家自然基金重点项目(41720104006);国家油气重大专项(2016ZX05014-001-008HZ)
  • 【文献出处】 CT理论与应用研究 ,Computerized Tomography Theory and Applications , 编辑部邮箱 ,2019年01期
  • 【分类号】P631.81
  • 【网络出版时间】2019-03-01 10:48
  • 【下载频次】143
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