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Hyperspectral quantitative retrieval of methane content in different concentrations in the seawater background

  • role： First author第一作者
  • Affiliation：

    School of Earth Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China

  • Email：541176500@qq.com
  • Introduction：曾雅琦，1995年生，女，硕士研究生，研究方向为遥感地质与天然气应用。E-mail：541176500@qq.com
ZENG Yaqi1,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Earth Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China

  • Email：wzhengh@mail.sysu.edu.cn
  • Introduction：王正海，1971年生，男，副教授，研究方向为地学信息技术与成矿预测。E-mail: wzhengh@mail.sysu.edu.cn
WANG Zhenghai1*,  
  • Affiliation：

    Research Institute of Petroleum Exploration and Development, Beijing 100083, China

XING Xuewen2,  
  • Affiliation：

    .Hefei Training and Testing Center of SINOPEC Petroleum Exploration and Production Research Institute, Hefei 230022, China

HU Bin3,  
  • Affiliation：

    Research Institute of Petroleum Exploration and Development, Beijing 100083, China

LIU Song2

Resümee

In the remote sensing exploration of oil and gas resources, seabed gas reservoirs are usually detected through the anomaly of methane concentration on the sea surface caused by hydrocarbon seepage. The remote sensing exploration of hydrocarbon seepage in marine gas resources is currently mostly based on methane absorption characteristics and images. Quantitative spectral analysis of methane content on the sea surface is also insufficient. This study designs laboratory spectral response experiments of methane with different concentrations in seawater background to determine the methane anomaly on the sea surface better and improve the accuracy of remote sensing inversion. This study also attempts to establish an inversion model of methane concentration in seawater background.A methane spectra laboratory test platform was designed to obtain hyperspectral data of different methane contents in seawater background. After spectra preprocessing and derivative of ratio spectroscopy, the spectral absorption characteristic parameters (the valley, wave depth, area, wave width, slope, and SAI) were extracted. The correlation between methane content and spectral parameters was analyzed to compare the ability of parameters to distinguish methane content. The correlation between spectral parameters with high correlation of methane content in selected bands was analyzed to further reduce the amount of data. Finally, the spectral parameters that were highly correlated with methane content and lowly correlated with each other were selected as independent variables and methane content was used as dependent variable to construct the methane content inversion model.In the analysis of methane spectra in seawater background, the derivative of ratio spectroscopy can effectively suppress background information of seawater in the spectra and highlight the methane information. Thus, the curve characteristics of the spectra after derivative of ratio spectroscopy are only related to the content of methane. Moreover, higher methane content corresponds to more obvious characteristics. The correlation between spectral parameters in 1650—1664 nm and 2180—2210 nm with methane content is significantly correlated, which is apparently higher than that in 2300—2320 nm and 2350—2380 nm. The valley, wave depth, area, and slope are also significantly correlated with methane content. Meanwhile, wave width is generally correlated with methane content, and SAI is not correlated with methane content. The quadrivariate regression equation (y=-14.356 - 5931.796x1 - 4325.081x2+241.481x3+7531.973x4) in 2180—2210 nm has the best fitting effect, and R2 is 0.9817. The single variable methane inversion model y = 2047.571x - 9.758 is based on wave depth in this band, and R2 is 0.9741, which is better than that of the inversion model based on other spectral characteristic parameters.The corresponding bands of 1650—1664 nm and 2180—2210 nm and corresponding absorption characteristics (valley, wave depth, area, and slope) with significant linear correlation of methane content in sea water background are successfully obtained. The methane content inversion models with good effect and regression significance are established. They can provide theoretical and technical basis for predicting methane concentration on sea surface by multispectral/hyperspectral remote sensing.

Schlüsselwort

remote sensing;hyperspectra;methane content;spectral characteristic parameter;derivative of ratio spectroscopy;inversion model

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