Oil and gas shows are rich in drilling wells in Kaiping sag,however,large oilfield was still not found in this area.For a long time,it is thought that source rocks were developed in the middle-deep lacustrine facies i...Oil and gas shows are rich in drilling wells in Kaiping sag,however,large oilfield was still not found in this area.For a long time,it is thought that source rocks were developed in the middle-deep lacustrine facies in the Eocene Wenchang Formation,while there is no source rocks that in middle-deep lacustrine facies have been found in well.Thickness of Wenchang Formation is big and reservoirs with good properties could be found in this formation.Distribution and scale of source rock are significant for further direction of petroleum exploration.Distribution characterization of middle-deep lacustrine facies is the base for source rock research.Based on the sedimentary background,fault activity rate,seismic response features,and seismic attributes were analyzed.No limited classification method and multi-attributes neural network deep learning method were used for predicting of source rock distribution in Wenchang Formation.It is found that during the deposition of lower Wenchang Formation,activity rate of main fault controlling the sub sag sedimentation was bigger than 100 m/Ma,which formed development background for middle-deep lacustrine facies.Compared with the seismic response of middle-deep lacustrine source rocks developed in Zhu I depression,those in Kaiping sag are characterized in low frequency and good continuity.Through RGB frequency decomposition,areas with low frequency are main distribution parts for middle-deep lacustrine facies.Dominant frequency,instantaneous frequency,and coherency attributes of seismic could be used in no limited classification method for further identification of middle-deep lacustrine facies.Based on the limitation of geology knowledge,multi-attributes of seismic were analyzed through neural network deep learning method.Distribution of middle-deep lacustrine facies in the fourth member of Wenchang Formation is oriented from west to east and is the largest.Square of the middle-deep lacustrine facies in that member is 154 km^(2)and the volume is 50 km^(3).Achievements could be bases for hydrocarbon accumulation study and for exploration target optimization in Kaiping sag.展开更多
An analysis of the influencing factors and mechanism of tourist revisiting willingness by adopting the multiple regressionmodel based on the survey data obtained from 581 valid questionnaires concerning Kaiping Diaolo...An analysis of the influencing factors and mechanism of tourist revisiting willingness by adopting the multiple regressionmodel based on the survey data obtained from 581 valid questionnaires concerning Kaiping Diaolou and Villages reveals that the maininfluencing factors of revisit intention are ： tourist spot image, cognitive attitude, tourists＇ expectation and satisfaction. Of the fourmain factors, tourists＇ cognitive attitude is the direct influence factor, and the image of the sites and tourists＇ expectation indirectlyinfluence the revisit intention through tourists＇ satisfaction. This research result provides a new approach to the market developmentfor the heritage villages.展开更多
文摘Oil and gas shows are rich in drilling wells in Kaiping sag,however,large oilfield was still not found in this area.For a long time,it is thought that source rocks were developed in the middle-deep lacustrine facies in the Eocene Wenchang Formation,while there is no source rocks that in middle-deep lacustrine facies have been found in well.Thickness of Wenchang Formation is big and reservoirs with good properties could be found in this formation.Distribution and scale of source rock are significant for further direction of petroleum exploration.Distribution characterization of middle-deep lacustrine facies is the base for source rock research.Based on the sedimentary background,fault activity rate,seismic response features,and seismic attributes were analyzed.No limited classification method and multi-attributes neural network deep learning method were used for predicting of source rock distribution in Wenchang Formation.It is found that during the deposition of lower Wenchang Formation,activity rate of main fault controlling the sub sag sedimentation was bigger than 100 m/Ma,which formed development background for middle-deep lacustrine facies.Compared with the seismic response of middle-deep lacustrine source rocks developed in Zhu I depression,those in Kaiping sag are characterized in low frequency and good continuity.Through RGB frequency decomposition,areas with low frequency are main distribution parts for middle-deep lacustrine facies.Dominant frequency,instantaneous frequency,and coherency attributes of seismic could be used in no limited classification method for further identification of middle-deep lacustrine facies.Based on the limitation of geology knowledge,multi-attributes of seismic were analyzed through neural network deep learning method.Distribution of middle-deep lacustrine facies in the fourth member of Wenchang Formation is oriented from west to east and is the largest.Square of the middle-deep lacustrine facies in that member is 154 km^(2)and the volume is 50 km^(3).Achievements could be bases for hydrocarbon accumulation study and for exploration target optimization in Kaiping sag.
文摘An analysis of the influencing factors and mechanism of tourist revisiting willingness by adopting the multiple regressionmodel based on the survey data obtained from 581 valid questionnaires concerning Kaiping Diaolou and Villages reveals that the maininfluencing factors of revisit intention are ： tourist spot image, cognitive attitude, tourists＇ expectation and satisfaction. Of the fourmain factors, tourists＇ cognitive attitude is the direct influence factor, and the image of the sites and tourists＇ expectation indirectlyinfluence the revisit intention through tourists＇ satisfaction. This research result provides a new approach to the market developmentfor the heritage villages.
