The estimated ultimate recovery(EUR)of shale gas wells is influenced by many factors,and the accurate prediction still faces certain challenges.As an artificial intelligence algorithm,deep learning yields notable adva...The estimated ultimate recovery(EUR)of shale gas wells is influenced by many factors,and the accurate prediction still faces certain challenges.As an artificial intelligence algorithm,deep learning yields notable advantages in nonlinear regression.Therefore,it is feasible to predict the EUR of shale gas wells based on a deep-learning algorithm.In this paper,according to geological evaluation data,hydraulic fracturing data,production data and EUR evaluation results of 282 wells in the WY shale gas field,a deep-learning-based algorithm for EUR evaluation of shale gas wells was designed and realized.First,the existing EUR evaluation methods of shale gas wells and the deep feedforward neural network algorithm was systematically analyzed.Second,the technical process of a deep-learning-based algorithm for EUR prediction of shale gas wells was designed.Finally,by means of real data obtained from the WY shale gas field,several different cases were applied to testify the validity and accuracy of the proposed approach.The results show that the EUR prediction with high accuracy.In addition,the results are affected by the variety and number of input parameters,the network structure and hyperparameters.The proposed approach can be extended to other shale fields using the similar technic process.展开更多
This paper presents the development and application of a production data analysis software that can analyze and forecast the production performance and reservoir properties of shale gas wells.The theories used in the ...This paper presents the development and application of a production data analysis software that can analyze and forecast the production performance and reservoir properties of shale gas wells.The theories used in the study were based on the analytical and empirical approaches.Its reliability has been confirmed through comparisons with a commercial software.Using transient data relating to multi-stage hydraulic fractured horizontal wells,it was confirmed that the accuracy of the modified hyperbolic method showed an error of approximately 4%compared to the actual estimated ultimate recovery(EUR).On the basis of the developed model,reliable productivity forecasts have been obtained by analyzing field production data relating to wells in Canada.The EUR was computed as 9.6 Bcf using the modified hyperbolic method.Employing the Pow Law Exponential method,the EUR would be 9.4 Bcf.The models developed in this study will allow in the future integration of new analytical and empirical theories in a relatively readily than commercial models.展开更多
Although carbon isotope reversal and its reasons in shale gas reservoirs have been widely recognized,the application of the reversal is yet to be investigated.A study on high-maturity shale from Wufeng and Longmaxi Fo...Although carbon isotope reversal and its reasons in shale gas reservoirs have been widely recognized,the application of the reversal is yet to be investigated.A study on high-maturity shale from Wufeng and Longmaxi Formations in the Sichuan Basin not only reveals the relationship between the degree of isotopes inversion and the production capacity(e.g.,estimated ultimate recovery(EUR))of the gas well but also indicates the preservation conditions of shale gas reservoirs.(1)Although there are differences in gas isotopes in different shale gas reservoirs,the isotope fractionation of shale gas is small during the production stage of gas wells,even when the wellbore pressure drops to zero.The main cause of the difference in carbon isotopes and their inversion degree can be the uplift time during the Yanshan period and the formation pressure relief degree of shale gas reservoirs in distinct structural positions.Thus,carbon isotope inversion is a good indicator of shale gas preservation condition and EUR of shale gas wells.(2)The degree of carbon isotope inversion correlates strongly with shale gas content and EUR.The calculation formula of shale-gas recoverable reserves was established using△δ^(13)C(δC_(1)-δC_(2))and EUR.(3)The gas loss rate and total loss amount can be estimated using the dynamic reserves and isotopic difference values of gas wells in various shale gas fields,which also reflects the current methane loss,thereby demonstrating great potential for evaluating global methane loss in shales.展开更多
基金supported by the funding of National Science and Technology Major Projects of China(2016ZX05037-006-005,2016ZX05037-006,2016ZX05035-004)。
文摘The estimated ultimate recovery(EUR)of shale gas wells is influenced by many factors,and the accurate prediction still faces certain challenges.As an artificial intelligence algorithm,deep learning yields notable advantages in nonlinear regression.Therefore,it is feasible to predict the EUR of shale gas wells based on a deep-learning algorithm.In this paper,according to geological evaluation data,hydraulic fracturing data,production data and EUR evaluation results of 282 wells in the WY shale gas field,a deep-learning-based algorithm for EUR evaluation of shale gas wells was designed and realized.First,the existing EUR evaluation methods of shale gas wells and the deep feedforward neural network algorithm was systematically analyzed.Second,the technical process of a deep-learning-based algorithm for EUR prediction of shale gas wells was designed.Finally,by means of real data obtained from the WY shale gas field,several different cases were applied to testify the validity and accuracy of the proposed approach.The results show that the EUR prediction with high accuracy.In addition,the results are affected by the variety and number of input parameters,the network structure and hyperparameters.The proposed approach can be extended to other shale fields using the similar technic process.
基金supported by the Energy Efficiency&Resources Core Technology Program of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)granted financial resource from the Ministry of Trade,Industry&Energy,Republic of Korea(No.20172510102090).
文摘This paper presents the development and application of a production data analysis software that can analyze and forecast the production performance and reservoir properties of shale gas wells.The theories used in the study were based on the analytical and empirical approaches.Its reliability has been confirmed through comparisons with a commercial software.Using transient data relating to multi-stage hydraulic fractured horizontal wells,it was confirmed that the accuracy of the modified hyperbolic method showed an error of approximately 4%compared to the actual estimated ultimate recovery(EUR).On the basis of the developed model,reliable productivity forecasts have been obtained by analyzing field production data relating to wells in Canada.The EUR was computed as 9.6 Bcf using the modified hyperbolic method.Employing the Pow Law Exponential method,the EUR would be 9.4 Bcf.The models developed in this study will allow in the future integration of new analytical and empirical theories in a relatively readily than commercial models.
基金supported by the National Natural Science Foundation of China(Grant No.41872124,42202175&No.42130803)。
文摘Although carbon isotope reversal and its reasons in shale gas reservoirs have been widely recognized,the application of the reversal is yet to be investigated.A study on high-maturity shale from Wufeng and Longmaxi Formations in the Sichuan Basin not only reveals the relationship between the degree of isotopes inversion and the production capacity(e.g.,estimated ultimate recovery(EUR))of the gas well but also indicates the preservation conditions of shale gas reservoirs.(1)Although there are differences in gas isotopes in different shale gas reservoirs,the isotope fractionation of shale gas is small during the production stage of gas wells,even when the wellbore pressure drops to zero.The main cause of the difference in carbon isotopes and their inversion degree can be the uplift time during the Yanshan period and the formation pressure relief degree of shale gas reservoirs in distinct structural positions.Thus,carbon isotope inversion is a good indicator of shale gas preservation condition and EUR of shale gas wells.(2)The degree of carbon isotope inversion correlates strongly with shale gas content and EUR.The calculation formula of shale-gas recoverable reserves was established using△δ^(13)C(δC_(1)-δC_(2))and EUR.(3)The gas loss rate and total loss amount can be estimated using the dynamic reserves and isotopic difference values of gas wells in various shale gas fields,which also reflects the current methane loss,thereby demonstrating great potential for evaluating global methane loss in shales.
