Interpreting reservoir properties through log data and logging responses in complex strata is critical for efficient petroleum exploitation,particularly for metamorphic rocks.However,the unsatisfactory accuracy of suc...Interpreting reservoir properties through log data and logging responses in complex strata is critical for efficient petroleum exploitation,particularly for metamorphic rocks.However,the unsatisfactory accuracy of such interpretations in complex reservoirs has hindered their widespread application,resulting in severe inconvenience.In this study,we proposed a multi-mineral model based on the least-square method and an optimal principle to interpret the logging responses and petrophysical properties of complex hydrocarbon reservoirs.We began by selecting the main minerals based on a comprehensive analysis of log data,X-ray diffraction,petrographic thin sections and scanning electron microscopy(SEM)for three wells in the Bozhong 19-6 structural zone.In combination of the physical properties of these minerals with logging responses,we constructed the multi-mineral model,which can predict the log curves,petrophysical properties and mineral profile.The predicted and measured log data are evaluated using a weighted average error,which shows that the multi-mineral model has satisfactory prediction performance with errors below 11%in most intervals.Finally,we apply the model to a new well“x”in the Bozhong 19-6 structural zone,and the predicted logging responses match well with measured data with the weighted average error below 11.8%for most intervals.Moreover,the lithology is dominated by plagioclase,K-feldspar,and quartz as shown by the mineral profile,which correlates with the lithology of the Archean metamorphic rocks in this region.It is concluded that the multi-mineral model presented in this study provides reasonable methods for interpreting log data in complex metamorphic hydrocarbon reservoirs and could assist in efficient development in the future.展开更多
Objective:Cervical disease,a type of chronic pain,can greatly impact quality of life.Traditional Chinese tuina,a form of therapeutic massage and manipulation,has been shown to be effective in relieving pain and other ...Objective:Cervical disease,a type of chronic pain,can greatly impact quality of life.Traditional Chinese tuina,a form of therapeutic massage and manipulation,has been shown to be effective in relieving pain and other symptoms in patients with chronic neck pain.This study applied functional magnetic resonance imaging (fMRI) to explore the features of the resting state network of patients with chronic neck pain caused by cervical radiculopathy,and how tuina affects the causality between intrinsic brain networks.Methods:Using Granger causality analysis,effective connectivity of brain networks of 10 patients with chronic neck pain was compared with 10 healthy control subjects.Resting state fMRI data were using magnetic resonance scanning.Cervical spondylosis symptom scores were evaluated before and after 4 weeks of tuina therapy.Independent component analysis was applied to extract the specific networks related to sensation,execution,and cognition,including sensorimotor network (SMN),visual network (VN),auditory network (AN),anterior and posterior default mode network (aDMN,pDMN),left frontoparietal network and right frontoparietal network.Results:Compared with the control group,data from the treatment group revealed two major findings:before tuina therapy,SMN had a profound influence on aDMN and AN greatly affected pDMN;however,after 4 weeks of tuina therapy,aDMN and SMN showed reversed causality.Conclusion:Chronic neck pain caused by cervical radiculopathy may influence the DMN,which plays an important role in emotion,cognition,and memory,by stimulating the sensory afferent network.Tuina not only significantly relieves pain and discomfort,but also reverses the causality between aDMN and SMN.展开更多
基金funded by Science and Technology Major Project of China National Offshore Oil Corporation(CNOOC-KJ 135 ZDXM36 TJ 08TJ).
文摘Interpreting reservoir properties through log data and logging responses in complex strata is critical for efficient petroleum exploitation,particularly for metamorphic rocks.However,the unsatisfactory accuracy of such interpretations in complex reservoirs has hindered their widespread application,resulting in severe inconvenience.In this study,we proposed a multi-mineral model based on the least-square method and an optimal principle to interpret the logging responses and petrophysical properties of complex hydrocarbon reservoirs.We began by selecting the main minerals based on a comprehensive analysis of log data,X-ray diffraction,petrographic thin sections and scanning electron microscopy(SEM)for three wells in the Bozhong 19-6 structural zone.In combination of the physical properties of these minerals with logging responses,we constructed the multi-mineral model,which can predict the log curves,petrophysical properties and mineral profile.The predicted and measured log data are evaluated using a weighted average error,which shows that the multi-mineral model has satisfactory prediction performance with errors below 11%in most intervals.Finally,we apply the model to a new well“x”in the Bozhong 19-6 structural zone,and the predicted logging responses match well with measured data with the weighted average error below 11.8%for most intervals.Moreover,the lithology is dominated by plagioclase,K-feldspar,and quartz as shown by the mineral profile,which correlates with the lithology of the Archean metamorphic rocks in this region.It is concluded that the multi-mineral model presented in this study provides reasonable methods for interpreting log data in complex metamorphic hydrocarbon reservoirs and could assist in efficient development in the future.
基金This research was supported by the Young Teachers Foundation of Beijing University of Chinese Medicine,No.2013-JYBZZ-JS-047The funders had no role in study design,data collection and analysis,decision to publish,or preparation of the manuscript.
文摘Objective:Cervical disease,a type of chronic pain,can greatly impact quality of life.Traditional Chinese tuina,a form of therapeutic massage and manipulation,has been shown to be effective in relieving pain and other symptoms in patients with chronic neck pain.This study applied functional magnetic resonance imaging (fMRI) to explore the features of the resting state network of patients with chronic neck pain caused by cervical radiculopathy,and how tuina affects the causality between intrinsic brain networks.Methods:Using Granger causality analysis,effective connectivity of brain networks of 10 patients with chronic neck pain was compared with 10 healthy control subjects.Resting state fMRI data were using magnetic resonance scanning.Cervical spondylosis symptom scores were evaluated before and after 4 weeks of tuina therapy.Independent component analysis was applied to extract the specific networks related to sensation,execution,and cognition,including sensorimotor network (SMN),visual network (VN),auditory network (AN),anterior and posterior default mode network (aDMN,pDMN),left frontoparietal network and right frontoparietal network.Results:Compared with the control group,data from the treatment group revealed two major findings:before tuina therapy,SMN had a profound influence on aDMN and AN greatly affected pDMN;however,after 4 weeks of tuina therapy,aDMN and SMN showed reversed causality.Conclusion:Chronic neck pain caused by cervical radiculopathy may influence the DMN,which plays an important role in emotion,cognition,and memory,by stimulating the sensory afferent network.Tuina not only significantly relieves pain and discomfort,but also reverses the causality between aDMN and SMN.
