Shale gas has been the exploration focus for future energy supply in South Africa in recent time. Specifically, the Permian black shales of the Prince Albert, Whitehill, Collingham, Ripon and Fort Brown Formations are...Shale gas has been the exploration focus for future energy supply in South Africa in recent time. Specifically, the Permian black shales of the Prince Albert, Whitehill, Collingham, Ripon and Fort Brown Formations are considered to be most prospective rocks for shale gas exploration. In this study,outcrop and core samples from the Ecca Group were analyzed to assess their total organic carbon(TOC), organic matter type, thermal maturity and hydrocarbon generation potential. These rocks have TOC ranging from 0.11 to 7.35 wt%. The genetic potential values vary from 0.09 to 0.53 mg HC/g,suggesting poor hydrocarbon generative potential. Most of the samples have Hydrogen Index(HI) values of less than 50 mg HC/g TOC, thus suggesting Type-Ⅳ kerogen. Tmax values range from 318℃ to601℃, perhaps indicating immature to over-maturity of the samples. The vitrinite reflectance values range from 2.22% to 3.93%, indicating over-maturity of samples. Binary plots of HI against Oxygen Index(OI), and HI versus Tmax show that the shales are of Type II and mixed Type Ⅱ-Ⅲ kerogen.Based on the geochemical data, the potential source rocks are inferred as immature to over-matured and having present-day potential to produce gas.展开更多
Gravity modelling was carried out along five profiles that traverse the Eastern Cape Province of South Africa in order to determine the depositional surface and isochore thickness of the Ecca sediments.Gravity models ...Gravity modelling was carried out along five profiles that traverse the Eastern Cape Province of South Africa in order to determine the depositional surface and isochore thickness of the Ecca sediments.Gravity models of the subsurface rock density reveal that the Ecca Group has a maximum vertical thickness of about 3215 ± 160 m.The maximum depositional surface（elevation）above sea level for the Ecca sediments is about 500 m,whilst the depth below sea level reaches about10000 m.Correlation of the isochore thickness maps with the depositional surfaces shows that the sediments in the basement highs were subsided,deformed,eroded and deposited in the basement lows.The basement highs served as the source area（s） for the sediments in the basement lows,thus basement highs are characterized with thin sediment cover whilst the lows have thick sediment cover.展开更多
Brain-computer interfaces(BCI)based on steady-state visual evoked potentials(SSVEP)have attracted great interest because of their higher signal-to-noise ratio,less training,and faster information transfer.However,the ...Brain-computer interfaces(BCI)based on steady-state visual evoked potentials(SSVEP)have attracted great interest because of their higher signal-to-noise ratio,less training,and faster information transfer.However,the existing signal recognition methods for SSVEP do not fully pay attention to the important role of signal phase characteristics in the recognition process.Therefore,an improved method based on extended Canonical Correlation Analysis(eCCA)is proposed.The phase parameters are added from the stimulus paradigm encoded by joint frequency phase modulation to the reference signal constructed from the training data of the subjects to achieve phase constraints on eCCA,thereby improving the recognition performance of the eCCA method for SSVEP signals,and transmit the collected signals to the robotic arm system to achieve control of the robotic arm.In order to verify the effectiveness and advantages of the proposed method,this paper evaluated the method using SSVEP signals from 35 subjects.The research shows that the proposed algorithm improves the average recognition rate of SSVEP signals to 82.76%,and the information transmission rate to 116.18 bits/min,which is superior to TRCA and traditional eCAA-based methods in terms of information transmission speed and accuracy,and has better stability.展开更多
基金the DST-NRF Centre of Excellence for Integrated Mineral and Energy Resource Analysis (CIMERA)the Govan Mbeki Research and Development Centre (GMRDC) at Fort Hare University for financial support
文摘Shale gas has been the exploration focus for future energy supply in South Africa in recent time. Specifically, the Permian black shales of the Prince Albert, Whitehill, Collingham, Ripon and Fort Brown Formations are considered to be most prospective rocks for shale gas exploration. In this study,outcrop and core samples from the Ecca Group were analyzed to assess their total organic carbon(TOC), organic matter type, thermal maturity and hydrocarbon generation potential. These rocks have TOC ranging from 0.11 to 7.35 wt%. The genetic potential values vary from 0.09 to 0.53 mg HC/g,suggesting poor hydrocarbon generative potential. Most of the samples have Hydrogen Index(HI) values of less than 50 mg HC/g TOC, thus suggesting Type-Ⅳ kerogen. Tmax values range from 318℃ to601℃, perhaps indicating immature to over-maturity of the samples. The vitrinite reflectance values range from 2.22% to 3.93%, indicating over-maturity of samples. Binary plots of HI against Oxygen Index(OI), and HI versus Tmax show that the shales are of Type II and mixed Type Ⅱ-Ⅲ kerogen.Based on the geochemical data, the potential source rocks are inferred as immature to over-matured and having present-day potential to produce gas.
基金the National Research Foundation(NRF)(Grant UID:101980)Govan Mbeki Research and Development Centre(GMRDC),University of Fort Hare for financial support
文摘Gravity modelling was carried out along five profiles that traverse the Eastern Cape Province of South Africa in order to determine the depositional surface and isochore thickness of the Ecca sediments.Gravity models of the subsurface rock density reveal that the Ecca Group has a maximum vertical thickness of about 3215 ± 160 m.The maximum depositional surface（elevation）above sea level for the Ecca sediments is about 500 m,whilst the depth below sea level reaches about10000 m.Correlation of the isochore thickness maps with the depositional surfaces shows that the sediments in the basement highs were subsided,deformed,eroded and deposited in the basement lows.The basement highs served as the source area（s） for the sediments in the basement lows,thus basement highs are characterized with thin sediment cover whilst the lows have thick sediment cover.
文摘Brain-computer interfaces(BCI)based on steady-state visual evoked potentials(SSVEP)have attracted great interest because of their higher signal-to-noise ratio,less training,and faster information transfer.However,the existing signal recognition methods for SSVEP do not fully pay attention to the important role of signal phase characteristics in the recognition process.Therefore,an improved method based on extended Canonical Correlation Analysis(eCCA)is proposed.The phase parameters are added from the stimulus paradigm encoded by joint frequency phase modulation to the reference signal constructed from the training data of the subjects to achieve phase constraints on eCCA,thereby improving the recognition performance of the eCCA method for SSVEP signals,and transmit the collected signals to the robotic arm system to achieve control of the robotic arm.In order to verify the effectiveness and advantages of the proposed method,this paper evaluated the method using SSVEP signals from 35 subjects.The research shows that the proposed algorithm improves the average recognition rate of SSVEP signals to 82.76%,and the information transmission rate to 116.18 bits/min,which is superior to TRCA and traditional eCAA-based methods in terms of information transmission speed and accuracy,and has better stability.
