Since the ocean bottom is a sedimentary environment wherein stratification is well developed, the use of an anisotropic model is best for studying its geology. Beginning with Maxwell＇s equations for an anisotropic mo...Since the ocean bottom is a sedimentary environment wherein stratification is well developed, the use of an anisotropic model is best for studying its geology. Beginning with Maxwell＇s equations for an anisotropic model, we introduce scalar potentials based on the divergence-free characteristic of the electric and magnetic （EM） fields. We then continue the EM fields down into the deep earth and upward into the seawater and couple them at the ocean bottom to the transmitting source. By studying both the DC apparent resistivity curves and their polar plots, we can resolve the anisotropy of the ocean bottom. Forward modeling of a high-resistivity thin layer in an anisotropic half-space demonstrates that the marine DC resistivity method in shallow water is very sensitive to the resistive reservoir but is not influenced by airwaves. As such, it is very suitable for oil and gas exploration in shallowwater areas but, to date, most modeling algorithms for studying marine DC resistivity are based on isotropic models. In this paper, we investigate one-dimensional anisotropic forward modeling for marine DC resistivity method, prove the algorithm to have high accuracy, and thus provide a theoretical basis for 2D and 3D forward modeling.展开更多
WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this pape...WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.展开更多
基金financially supported by the National Hi-tech Research and Development Program of China(863 Program)(No.2012AA09A20103)
文摘Since the ocean bottom is a sedimentary environment wherein stratification is well developed, the use of an anisotropic model is best for studying its geology. Beginning with Maxwell＇s equations for an anisotropic model, we introduce scalar potentials based on the divergence-free characteristic of the electric and magnetic （EM） fields. We then continue the EM fields down into the deep earth and upward into the seawater and couple them at the ocean bottom to the transmitting source. By studying both the DC apparent resistivity curves and their polar plots, we can resolve the anisotropy of the ocean bottom. Forward modeling of a high-resistivity thin layer in an anisotropic half-space demonstrates that the marine DC resistivity method in shallow water is very sensitive to the resistive reservoir but is not influenced by airwaves. As such, it is very suitable for oil and gas exploration in shallowwater areas but, to date, most modeling algorithms for studying marine DC resistivity are based on isotropic models. In this paper, we investigate one-dimensional anisotropic forward modeling for marine DC resistivity method, prove the algorithm to have high accuracy, and thus provide a theoretical basis for 2D and 3D forward modeling.
文摘WindSat/Coriolis is the first satellite-borne polarimetric microwave radiometer, which aims to improve the potential of polarimetric microwave radiometry for measuring sea surface wind vectors from space. In this paper, a wind vector retrieval algorithm based on a novel and simple forward model was developed for WindSat. The retrieval algorithm of sea surface wind speed was developed using multiple linear regression based on the simulation dataset of the novel forward model. Sea surface wind directions that minimize the difference between simulated and measured values of the third and fourth Stokes parameters were found using maximum likelihood estimation, by which a group of ambiguous wind directions was obtained. A median filter was then used to remove ambiguity of wind direction. Evaluated with sea surface wind speed and direction data from the U.S. National Data Buoy Center （NDBC）, root mean square errors are 1.2 rn/s and 30~ for retrieved wind speed and wind direction, respectively. The evaluation results suggest that the simple forward model and the retrieval algorithm are practicable for near-real time applications, without reducing accuracy.
