This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large mode...This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.展开更多
Highly accurate observations at various scales on the land surface are urgently needed for the studies of many areas,such as hydrology,meteorology,and agriculture.With the rapid development of remote sensing technique...Highly accurate observations at various scales on the land surface are urgently needed for the studies of many areas,such as hydrology,meteorology,and agriculture.With the rapid development of remote sensing techniques,remote sensing has had the capacity of monitoring many factors of the Earth's land surface.Especially,the space-borne microwave remote sensing systems have been widely used in the quantitative monitoring of global snow,soil moisture,and vegetation parameters with their all-weather,all-time observation capabilities and their sensitivities to the characteristics of land surface factors.Based on the electromagnetic theories and microwave radiative transfer equations,researchers have achieved great successes in the microwave remote sensing studies for different sensors in recent years.This article has systematically reviewed the progresses on five research areas including microwave theoretical modeling,microwave inversion on soil moisture,snow,vegetation and land surface temperatures.Through the further enrichment of remote sensing datasets and the development of remote sensing theories and inversion techniques,remote sensing including microwave remote sensing will play a more important role in the studies and applications of the Earth systems.展开更多
Long-term highly accurate surface soil moisture data of TP(Tibetan Plateau)are important to the research of Asian monsoon and global atmospheric circulation.However,due to the sparse in-situ networks,the lack of soil ...Long-term highly accurate surface soil moisture data of TP(Tibetan Plateau)are important to the research of Asian monsoon and global atmospheric circulation.However,due to the sparse in-situ networks,the lack of soil moisture observations has seriously hindered the progress of climate change researches of TP.Based on the Dual-Channel soil moisture retrieval algorithm and the satellite observation data of AMSR-E(Advanced Microwave Scanning Radiometer for EOS),we have produced the surface soil moisture data of TP from 2003 to 2010 and analyzed the seasonal characteristic of the soil moisture spatial distribution and its multi-year changing trend in area of TP.Compared to the in-situ observations,the accuracy of the soil moisture retrieved by the proposed algorithm is evaluated.The evaluation result shows that the new soil moisture product has a better accuracy in the TP region than the official product of AMSR-E.The spatial distribution of the annual mean values of soil moisture and the seasonal variations of the monthly-averaged soil moisture are analyzed.The results show that the soil moisture variations in space and time are consistent with the precipitation distribution and the water vapor transmission path in TP.Based on the new soil moisture product,we also analyzed the spatial distribution of the changing trend of multi-year soil moisture in TP.From the comparisons with the precipitation changing trend obtained from the meteorological observation sites in TP,we found that the spatial pattern of the changing trend of soil moisture coincides with the precipitation as a whole.展开更多
Microwave radiometers have many applications because of their penetration ability. However, two major problems remain that obstruct the development of microwave research. One factor that limits their commercial applic...Microwave radiometers have many applications because of their penetration ability. However, two major problems remain that obstruct the development of microwave research. One factor that limits their commercial application is the relatively low resolution of microwave radiometers. The other is the non-uniform spatial resolution for each frequency of the radiometer. The resolution mismatch becomes a critical consideration when observations at two or more frequencies must be combined. In this paper, we have used the Backus-Gilbert method to solve these two problems, while AMSR-E is chosen as the research object. First, we derived the Backus-Gilbert method in detail. The simulated data were then used to decide the optimum parameters in the Backus-Gilbert method. To enhance the resolution, the Backus-Gilbert method has been applied to the AMSR-E data, which covered the Mexico Gulf and the Amazon River. After resolution was enhanced, detailed information was obtained and compared with visible high resolution data. To match the resolution, the AMSR-E data from the Oklahoma Little Washed were used to compute the Microwave Vegetation Index (MVI), which was developed by J. C. Shi. Compared to the original MVIs, the information contained in the MVIs that were processed by the Backus-Gilbert method is more reliable.展开更多
基金Supported by the National Natural Science Foundation of China(72088101,42372175)PetroChina Science and Technology Innovation Fund Program(2021DQ02-0904)。
文摘This article elucidates the concept of large model technology,summarizes the research status of large model technology both domestically and internationally,provides an overview of the application status of large models in vertical industries,outlines the challenges and issues confronted in applying large models in the oil and gas sector,and offers prospects for the application of large models in the oil and gas industry.The existing large models can be briefly divided into three categories:large language models,visual large models,and multimodal large models.The application of large models in the oil and gas industry is still in its infancy.Based on open-source large language models,some oil and gas enterprises have released large language model products using methods like fine-tuning and retrieval augmented generation.Scholars have attempted to develop scenario-specific models for oil and gas operations by using visual/multimodal foundation models.A few researchers have constructed pre-trained foundation models for seismic data processing and interpretation,as well as core analysis.The application of large models in the oil and gas industry faces challenges such as current data quantity and quality being difficult to support the training of large models,high research and development costs,and poor algorithm autonomy and control.The application of large models should be guided by the needs of oil and gas business,taking the application of large models as an opportunity to improve data lifecycle management,enhance data governance capabilities,promote the construction of computing power,strengthen the construction of“artificial intelligence+energy”composite teams,and boost the autonomy and control of large model technology.
基金supported by National Natural Science Foundation of China(Grant Nos. 40930530 and 40901180)
文摘Highly accurate observations at various scales on the land surface are urgently needed for the studies of many areas,such as hydrology,meteorology,and agriculture.With the rapid development of remote sensing techniques,remote sensing has had the capacity of monitoring many factors of the Earth's land surface.Especially,the space-borne microwave remote sensing systems have been widely used in the quantitative monitoring of global snow,soil moisture,and vegetation parameters with their all-weather,all-time observation capabilities and their sensitivities to the characteristics of land surface factors.Based on the electromagnetic theories and microwave radiative transfer equations,researchers have achieved great successes in the microwave remote sensing studies for different sensors in recent years.This article has systematically reviewed the progresses on five research areas including microwave theoretical modeling,microwave inversion on soil moisture,snow,vegetation and land surface temperatures.Through the further enrichment of remote sensing datasets and the development of remote sensing theories and inversion techniques,remote sensing including microwave remote sensing will play a more important role in the studies and applications of the Earth systems.
基金supported by the National High-tech R&D Program of China(Grant No.2012AA12A304)the National Natural Science Foundation of China(Grant No.40930530)
文摘Long-term highly accurate surface soil moisture data of TP(Tibetan Plateau)are important to the research of Asian monsoon and global atmospheric circulation.However,due to the sparse in-situ networks,the lack of soil moisture observations has seriously hindered the progress of climate change researches of TP.Based on the Dual-Channel soil moisture retrieval algorithm and the satellite observation data of AMSR-E(Advanced Microwave Scanning Radiometer for EOS),we have produced the surface soil moisture data of TP from 2003 to 2010 and analyzed the seasonal characteristic of the soil moisture spatial distribution and its multi-year changing trend in area of TP.Compared to the in-situ observations,the accuracy of the soil moisture retrieved by the proposed algorithm is evaluated.The evaluation result shows that the new soil moisture product has a better accuracy in the TP region than the official product of AMSR-E.The spatial distribution of the annual mean values of soil moisture and the seasonal variations of the monthly-averaged soil moisture are analyzed.The results show that the soil moisture variations in space and time are consistent with the precipitation distribution and the water vapor transmission path in TP.Based on the new soil moisture product,we also analyzed the spatial distribution of the changing trend of multi-year soil moisture in TP.From the comparisons with the precipitation changing trend obtained from the meteorological observation sites in TP,we found that the spatial pattern of the changing trend of soil moisture coincides with the precipitation as a whole.
基金supported by Chinese Special Funds for National Basic Research Project of China (Grant No. 2007CB714403)National High Technology Research and Development Program of China (Grant Nos. 2007AA12Z135, 2008AA12Z110)Chinese Academy of Sciences (Grant No. KZCX2-YW-Q10-2)
文摘Microwave radiometers have many applications because of their penetration ability. However, two major problems remain that obstruct the development of microwave research. One factor that limits their commercial application is the relatively low resolution of microwave radiometers. The other is the non-uniform spatial resolution for each frequency of the radiometer. The resolution mismatch becomes a critical consideration when observations at two or more frequencies must be combined. In this paper, we have used the Backus-Gilbert method to solve these two problems, while AMSR-E is chosen as the research object. First, we derived the Backus-Gilbert method in detail. The simulated data were then used to decide the optimum parameters in the Backus-Gilbert method. To enhance the resolution, the Backus-Gilbert method has been applied to the AMSR-E data, which covered the Mexico Gulf and the Amazon River. After resolution was enhanced, detailed information was obtained and compared with visible high resolution data. To match the resolution, the AMSR-E data from the Oklahoma Little Washed were used to compute the Microwave Vegetation Index (MVI), which was developed by J. C. Shi. Compared to the original MVIs, the information contained in the MVIs that were processed by the Backus-Gilbert method is more reliable.
