Sea surface temperature observation by Global Imager (GLI)/ADEOS-II: Algorithm and accuracy of the product

A sea surface temperature (SST) retrieval algorithm for Global Imager (GLI) aboard the ADEOS-II satellite has been developed. The algorithm is used to produce the standard SST product in the Japan Aerospace Exploration Agency (JAXA). The algorithm for cloud screening is formed by combinations of various types of tests to detect cloud-contaminated pixels. The combination is changed according to the solar zenith angle, which enables us to detect clouds even in the sun glitter region in daytime. The parameters in the cloud-detection tests have been tuned using the GLI global observations. SST is calculated by the Multi-Channel SST (MCSST) technique from the detected clear pixels. Using drifting buoy measurements, match-up data are produced to derive the coefficients of the MCSST equations and to examine their performance. The bias and RMSE of the GLI SST are 0.03 K and 0.66 K for daytime and, −0.01 K and 0.70 K for nighttime, respectively.     

广义线性反演初至折射静校技术在金属矿区的应用

在复杂地表地区,近地表速度构造模型的确定在地震资料处理和成像过程中是一个至关重要的工作.针对传统方法只能解决静校正中的部分问题,精度不高,本文采用的广义线性反演折射法,利用初至时间对大量数据进行统计,用交互、迭代的方法计算静校正量.该法在土屋斑岩铜矿区的应用,表明在提高信噪比方面比较传统方法有明显的提高.     

Verification of vertically generalized production model and estimation of primary production in Sagami Bay,Japan

The Vertically Generalized Production Model (VGPM) was verified by the primary production data of the Sagami Bay, Japan. The VGPM with open ocean parameters including P ^B _opt , maximum primary production per unit of chlorophyll a in the water column, explained only 40% of the variability of integrated primary production. Formulations of the open ocean P ^B _opt showed no correlation with in situ P ^B _opt . Adjustment of the parameters of chlorophyll a and temperature dependent P ^B _opt improved the estimation of integrated primary production to 47% of the variation. Vertical integration parameters of VGPM also have to be adjusted to improve the estimation. Integrated primary production calculated with a stronger light dependency and with the adjusted P ^B _opt model can explain 74% of the variation. This model was used to estimate primary production of the Sagami Bay during 2003 with satellite data. In situ measurements on cloudy days indicate that the use of satellite data from sunny days only overestimates primary production.     

Validation of ADEOS-II GLI ocean color products using in-situ observations

The Global Imager (GLI) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) made global observations from 2 April 2003 to 24 October 2003. In cooperation with several institutes and scientists, we obtained quality controlled match-ups between GLI products and in-situ data, 116 for chlorophyll-a concentration (CHLA), 249 for normalized water-leaving radiance (nLw) at 443 nm, and 201 for aerosol optical thickness at 865 nm (Tau_865) and Angstrom exponent between 520 and 865 nm (Angstrom). We evaluated the GLI ocean color products and investigated the causes of errors using the match-ups. The median absolute percentage differences (MedPD) between GLI and in-situ data were 14.1–35.7% for nLws at 380–565 nm, 52.5–74.8% nLws at 625–680 nm, 47.6% for Tau_865, 46.2% for Angstrom, and 46.6% for CHLA, values that are comparable to the ocean-color products of other sensors. We found that some errors in GLI products are correlated with observational conditions; nLw values were underestimated when nLw at 680 nm was high, CHLA was underestimated in absorptive aerosol conditions, and Tau_865 was overestimated in sunglint regions. The error correlations indicate that we need to improve the retrievals of the optical properties of absorptive aerosols and seawater and sea surface reflection for further applications, including coastal monitoring and the combined use of products from multiple sensors.     

Prestack amplitude versus angle inversion for Young's modulus and Poisson's ratio based on the exact Zoeppritz equations

Elastic parameters such as Young's modulus, Poisson's ratio, and density are very important characteristic parameters that are required to properly characterise shale gas reservoir rock brittleness, evaluate gas characteristics of reservoirs, and directly interpret lithology and oil‐bearing properties. Therefore, it is significant to obtain accurate information of these elastic parameters. Conventionally, they are indirectly calculated by the rock physics method or estimated by approximate formula inversion. The cumulative errors caused by the indirect calculation and low calculation accuracy of the approximate Zoeppritz equations make accurate estimation of Young's modulus, Poisson's ratio, and density difficult in the conventional method. In this paper, based on the assumption of isotropy, we perform several substitutions to convert the Zoeppritz equations from the classical form to a new form containing the chosen elastic constants of Young's modulus, Poisson's ratio, and density. The inversion objective function is then constructed by utilising Bayesian theory. Meanwhile, the Cauchy distribution is introduced as a priori information. We then combine the idea of generalised linear inversion with an iterative reweighed least squares algorithm in order to solve the problem. Finally, we obtain the iterative updating formula of the three elastic parameters and achieve the direct inversion of these elastic parameters based on the exact Zoeppritz equations. Both synthetic and field data examples show that the new method is not only able to obtain the two elastic parameters of Young's modulus and Poisson's ratio stably and reasonably from prestack seismic data but also able to provide an accurate estimation of density information, which demonstrates the feasibility and effectiveness of the proposed method. The proposed method offers an efficient seismic method to identify a “sweet spot” within a shale gas reservoir.     

基于基追踪-BI_Zoeppritz方程广义线性脆性指数直接反演方法

非常规油气资源的勘探开发在能源领域越来越受到重视.针对页岩油气、致密砂岩气储层的脆性指数预测,对突破"甜点区"、指导后续水力压裂等都具有重要的意义.针对常规叠前AVO反演技术预测脆性指数存在的问题:(1)稀疏脉冲反演垂向分辨率不高;(2)基于AVO近似公式的常规叠前反演,需要假设常背景纵横波速度比以及弱弹性参数反射率等条件,会影响到三参数反演的精度;(3)通常需要借助反演获取的纵横密三参数转换为杨氏模量和泊松比,再进一步转换才能获取脆性指数,在参数转换的过程中会将误差累积放大,影响最终的脆性指数预测精度.本文从精确Zoeppritz方程出发,通过对其进行重新推导,将其表达为脆性指数、P波速度和S波速度的函数(BI_Zoeppritz方程),并借助广义线性AVO反演,对基追踪反演获取的高分辨率角度反射系数进行迭代反演,直接提取高分辨率、高精度的脆性指数.通过模型和实际资料验证了该算法相对常规叠前反演获取的脆性指数有了进一步的改善.