煤层气富集区遥感勘查研究进展与展望

doi:10.6046/zrzyyg.2023193

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煤层气是一种自生自储式非常规清洁能源,它赋存于煤层及其围岩中。传统勘查方法费时费力,而遥感技术提供了煤层气富集区快速勘查的新途径。煤层气富集区遥感勘查的基本原理是基于典型地物波谱特征与富集区烃微渗漏导致的地表物体异常波谱特征,包括岩矿蚀变、植被异常和热异常等波谱特征的对比,结合煤田地质、地震、大地电磁等物探方法获取的数据,进行多源信息提取与综合分析,逐步查明煤层气富集区分布范围与含气特性。文章综述了煤层气富集区烃类物质渗漏与地表岩矿波谱和植被波谱异常的响应机制,以及基于地表岩矿波谱与植被波谱参数反演的多种方法与地物波谱异常反演在煤层气潜在富集区的勘查应用; 阐述了含煤层气地层导致地表热异常的不同解释与提高地表温度反演准确率的主要方法与应用。未来,遥感与煤田地质数据、地震探测和大地电磁探测相结合,开展立体多元信息分析与信息提取,将成为实现煤层气富集区低成本快速勘查的主要途径。

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	秦其明
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	王楠
	韩谷怀

关键词 ：煤层气富集区, 烃微渗漏, 遥感勘查, 多源信息提取

Abstract：

Coalbed methane (CBM), a type of self-sourced unconventional clean energy, occurs in coal seams and their surrounding rocks. Conventional exploration methods for CBM enrichment areas are laborious, while remote sensing provides a new approach to the rapid exploration of such areas. The basic principle behind the remote sensing-based exploration of CBM enrichment areas is as follows: ① The extraction and comprehensive analysis of multi-source data are conducted based on the comparison between the spectral features of typical surface features and those of surface feature anomalies, including rock and mineral alterations, vegetation anomalies, and thermal anomalies, caused by hydrocarbon micro-seepage in CBM enrichment areas, along with data obtained using geophysical prospecting methods like geological, seismic, and magnetotelluric methods; ② The distribution range and gas-bearing properties of CBM enrichment areas are gradually delineated. This paper reviews the hydrocarbon seepage in the CBM enrichment areas and the response mechanisms of spectral anomalies of surface rocks, minerals, and vegetation. It covers the applications of various methods based on the inversion of spectral parameters of surface rocks, minerals, and vegetation, together with the inversion of the spectral anomalies of surface features, in the exploration of potential CBM enrichment areas. Additionally, this paper elucidates the different explanations for surface thermal anomalies caused by CBM-bearing strata, as well as major methods to improve the accuracy of surface temperature inversion and their applications. In the future, the main approach to achieving low-cost, rapid exploration of CBM enrichment areas will be the analysis and information extraction of three-dimensional, multi-source information based on the combination of remote sensing technology with the geological data, seismic exploration, and geomagnetic prospecting of coalfields.

Key words： coalbed methane enrichment area hydrocarbon micro-seepage remote sensing-based exploration multi-source data extraction

收稿日期: 2023-07-03 出版日期: 2024-09-03

ZTFLH:	TP79
	P618.13

基金资助:国家自然科学基金项目“煤层气富集区地表参数遥感反演与综合勘查”(42071314)

作者简介: 秦其明(1955-),男,博士,教授,研究方向为定量遥感。Email: qmqin@pku.edu.cn。

引用本文:

秦其明, 吴自华, 叶昕, 王楠, 韩谷怀. 煤层气富集区遥感勘查研究进展与展望[J]. 自然资源遥感, 2024, 36(3): 1-12.
QIN Qiming, WU Zihua, YE Xin, WANG Nan, HAN Guhuai. Remote sensing-based exploration of coalbed methane enrichment areas:Advances in research and prospects. Remote Sensing for Natural Resources, 2024, 36(3): 1-12.

链接本文:

https://www.gtzyyg.com/CN/10.6046/zrzyyg.2023193 或 https://www.gtzyyg.com/CN/Y2024/V36/I3/1

Fig.1 USGS数据库若干典型矿物波谱特征

指数名称	表达式^①	含义	参考文献
三价铁指数1	$ρ R e d ρ B l u e$	反映土壤中三价铁矿物丰度,也即土壤“红度”	[30-31]
三价铁指数2	$ρ R e d ρ B l u e · ρ R e d + ρ S W I R 1650 ρ N I R$	反映土壤中三价铁矿物丰度,适用于三价铁丰度较高的情形	[30-31]
二价铁指数1	$ρ G r e e n + ρ S W I R 1650 ρ R e d + ρ N I R$	反映土壤中二价铁矿物丰度	[31]
二价铁指数2	$ρ S W I R 2167 ρ N I R + ρ G r e e n ρ R e d$	反映土壤中二价铁矿物丰度	[15]
黏土和碳酸盐矿物指数	$ρ N I R ρ S W I R 1650$	反映土壤中黏土和碳酸盐矿物的丰度	[31-32]

Tab.1 可用于监测烃微渗漏导致岩矿蚀变的常用光谱指数

Tab.2 可用于监测烃微渗漏导致岩矿蚀变的光谱降维方法

指数名称	表达式^①	含义	参考文献
NDVI	$ρ N I R - ρ R e d ρ N I R + ρ R e d$	综合反映植被长势	[48?-50]
绿光归一化差值植被指数(GNDVI)	$ρ N I R - ρ G r e e n ρ N I R + ρ G r e e n$	对叶绿素含量敏感	[47,51]
增强归一化差值植被指数(ENDVI)	$ρ N I R + ρ G r e e n - 2 ρ B l u e ρ N I R + ρ G r e e n + 2 ρ B l u e$	综合反映植被长势,适用于各个生育期	[52-53]
OSAVI	$ρ N I R - ρ R e d ρ N I R + ρ R e d + 0.16$	综合反映植被长势,较好地消除了土壤背景的影响	[47,54]
增强植被指数(EVI)	$2.5 (ρ N I R - ρ R e d) 1 + ρ N I R + 6 ρ R e d - 7.5 ρ B l u e$	对叶面积指数敏感	[52,55]
反转差值植被指数(IDVI)	$1 + (ρ N I R - ρ R e d) 1 - (ρ N I R - ρ R e d)$	综合反映植被长势,在高植被覆盖情况下不易饱和	[56]
红边位置植被指数(RPVI)	$(ρ R e d - b) / k + (ρ N I R - b) / k 2$	对叶绿素含量敏感	[46]

Tab.3 可用于监测烃微渗漏导致植被胁迫的常用光谱指数

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