深层超深层钻井地质信息测井拾取与评价^*

Well logging evaluation and characterization of geological information for deep and ultra-deep drilling wells

摘要

顺应国家深海、深地、深空和深蓝战略部署,陆地钻井不断向深层超深层进军,但深部极端环境测井资料获取困难,采集新技术(核磁共振、成像测井和阵列声波)测井少,导致测井资料多解性强,亟需利用有限的地球物理测井信息挖掘深层超深层钻井蕴含的地质信息。经过大量的文献调研,论述了深层超深层测井评价的重点,通过对典型研究案例的分析,系统地梳理测井地质学在深层超深层领域的应用,包括利用测井资料实现对井旁构造地质现象解读、沉积学信息拾取、储集层评价与预测、储集层裂缝评价和对地应力评价。最后探讨了深层超深层领域发展趋势: 重视多角度数据的融合(岩心、实验资料和地震资料等数据),并根据深层超深层环境的差异,发展适应深层超深层环境因素的先进岩石物理模型。同时在大数据、人工智能的发展背景下,利用新技术测井的优势,推进深层超深层领域测井地质学突破技术瓶颈。

Abstract

In accordance with the strategic deployment of deep-sea,deep-earth,deep-space and deep-blue initiatives,land drilling is continuously entering towards deep and ultra-deep reservoirs. However, the collection of advanced well log series are limited for the deep and ultra-deep strata, and will result in interpretation ambiguity of well log data. Therefore,it is urgent to use the limited geophysical logging information to fully interpret on the geological information contained in deep and ultra-deep drilling. This paper firstly discusses the focus of logging evaluation in deep and ultra-deep reservoirs based on extensive literature retrieval. Through the analysis of typical research cases,it systematically reviews the application of logging geology in deep and ultra-deep fields,including using logging data to interpret structural geological phenomena,pick up sedimentary information,evaluate and predict reservoir characteristics,and evaluate in-situ stress using logging data. Finally,the development trend of deep and ultra-deep fields is discussed: paying attention to the integration of multi-data source(such as core,experimental data,and seismic data),and developing advanced rock physical models that adapt to the environmental factors of deep and ultra-deep environments based on their differences. At the same time,in the context of the development of big data and artificial intelligence,the advantages of new technology logging are utilized to promote breakthroughs in the field of logging geology in deep and ultra-deep fields,thus breaking through technical bottlenecks.

关键词

深层超深层 / 地球物理测井 / 地质信息 / 拾取与刻画 / 测井地质学 / 人工智能

Key words

deep and ultra-deep / geophysical well logs / geological information / extraction and characterization / well logging geology / artificial intelligence

基金资助

*国家自然科学基金(编号: 42002133)、中国石油大学(北京)科研启动基金(编号: 2462023QNXZ010)与中国石油—中国石油大学(北京)战略合作协议(编号: ZLZX2020-01)联合资助