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岩性体边界与断裂异常信息识别研究及应用 被引量:6

Study and application of identification of abnormal information between lithologic body boundaries and fractures
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摘要 岩性和断裂共同控制的油气藏中,岩性体边界和断裂的识别对于油气勘探及开发都具有极其重要的意义。目前,识别岩性体边界和断裂分布主要采用基于地震资料的横向不连续性检测方法,岩性突变和断裂均可导致地震波同相轴在横向上的不连续性,其检测结果难以区分哪些异常信息代表岩性体边界,哪些异常信息代表断裂。层面曲率属性技术对断裂和细微构造特征具有较好的指示作用,对岩性体边界不敏感。基于这2种方法各自的优缺点,提出层面曲率属性技术与地震资料横向不连续性检测技术相结合来识别断裂和岩性体边界异常信息。模型分析表明,提出的方法能对解释工区内断裂和岩性体边界异常进行有效区分,在实际生产应用中已取得良好效果,提高了断裂和岩性体边界识别和区分的精度。 In the oil and gas reservoir that is controlled by both lithology and fracture,the identification of lithologic body boundaries and fracture is of paramount importance for oil and gas exploration and development.At present,identification of lithologic body boundaries and the distribution of fracture are mainly based on the seismic data of lateral discontinuity detection method.As either the lithology mutation or the existence of fracture can lead to event discontinuity,it is very difficult to distinguish which abnormal information can represent lithologic body boundaries and fracture.The curvature attribute technology has a good instruction for fracture and micro structural characteristics,but it is not sensitive to lithology body boundaries.Based on the advantages and disadvantages of both methods,this paper puts forward a new method that combines the curvature attribute with lateral discontinuity detection technology,which is able to identify the abnormal information between lithologic body boundaries and fractures.Model analysis shows that this method can distinguish effectively the abnormal information between lithologic body boundaries and fractures in interpreted work area.Good results have been obtained and the identification accuracy of lithologic body boundaries and fractures has been improved in the actual production application.
出处 《断块油气田》 CAS 北大核心 2010年第3期285-288,共4页 Fault-Block Oil & Gas Field
基金 国家高技术研究发展(863)计划项目"高精度储层结构地震检测分析与流体识别"(2006AA09A102-12)资助
关键词 曲率属性 方差体 岩性体边界 横向不连续性检测 curvature attribute variance cube lithologic body boundaries lateral discontinuity detection.
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