Petroleum resource assessment using reservoir volumetric approach relies on porosity and oil/gas saturation characterization by laboratory tests.In liquid-rich resource plays,the pore fluids are subject to phase chang...Petroleum resource assessment using reservoir volumetric approach relies on porosity and oil/gas saturation characterization by laboratory tests.In liquid-rich resource plays,the pore fluids are subject to phase changes and mass loss when a drilled core is brought to the surface due to volume expansion and evaporation.Further,these two closely related volumetric parameters are usually estimated separately with gas saturation inferred by compositional complementary law,resulting in a distorted gas to oil ratio under the circumstances of liquid hydrocarbon loss from sample.When applied to liquid-rich shale resource play,this can lead to overall under-estimation of resource volume,distorted gas and oil ratio(GOR),and understated resource heterogeneity in the shale reservoir.This article proposes an integrated mass balance approach for resource calculation in liquid-rich shale plays.The proposed method integrates bulk rock geochemical data with production and reservoir parameters to overcome the problems associated with laboratory characterization of the volumetric parameters by restoring the gaseous and light hydrocarbon loss due to volume expansion and evaporation in the sample.The method is applied to a Duvernay production well(14-16-62-21 W5)in the Western Canada Sedimentary Basin(WCSB)to demonstrate its use in resource evaluation for a liquid-rich play.The results show that(a)by considering the phase behavior of reservoir fluids,the proposed method can be used to infer the quantity of the lost gaseous and light hydrocarbons;(b)by taking into account the lost gaseous and light hydrocarbons,the method generates an unbiased and representative resource potential;and(c)using the corrected oil and gas mass for the analyzed samples,the method produces a GOR estimate close to compositional characteristics of the produced hydrocarbons from initial production in 14-16-62-21 W5 well.展开更多
With increasing global demand for energy,the importance of unconventional shale oil and gas research cannot be over-emphasized.The oil and gas industry requires rapid and reliable means of forecasting production.Exist...With increasing global demand for energy,the importance of unconventional shale oil and gas research cannot be over-emphasized.The oil and gas industry requires rapid and reliable means of forecasting production.Existing traditional decline curve analysis(DCA)methods have been limited in their ability to satisfactorily forecast production from unconventional liquid-rich shale(LRS)reservoirs.This is due to several causes ranging from the complicated production mechanisms to the ultra-low permeability in shales.The use of hybrid(combination)DCA models can improve results.However,complexities associated with these techniques can still make their application quite tedious without proper diagnostic plots,correct use of model parameters and some knowledge of the production mechanisms involved.This work,therefore,presents a new statistical data-driven approach of forecasting production from LRS reservoirs called the Principal Components Methodology(PCM).PCM is a technique that bypasses a lot of the difficulties associated with existing methods of forecasting and forecasts production with reasonable certainty.PCM is a data-driven method of forecasting based on the statistical technique of principal components analysis(PCA).In our study,we simulated production of fluids with different compositions for 30 years with the aid of a commercial compositional simulator.We then applied the Principal Components Methodology(PCM)to the production data from several representative wells by using Singular Value Decomposition(SVD)to calculate the principal components.These principal components were then used to forecast oil production from wells with production histories ranging from 0.5 to 3 years,and the results were compared to simulated data.Application of the PCM to field data is also included in this work.展开更多
文摘Petroleum resource assessment using reservoir volumetric approach relies on porosity and oil/gas saturation characterization by laboratory tests.In liquid-rich resource plays,the pore fluids are subject to phase changes and mass loss when a drilled core is brought to the surface due to volume expansion and evaporation.Further,these two closely related volumetric parameters are usually estimated separately with gas saturation inferred by compositional complementary law,resulting in a distorted gas to oil ratio under the circumstances of liquid hydrocarbon loss from sample.When applied to liquid-rich shale resource play,this can lead to overall under-estimation of resource volume,distorted gas and oil ratio(GOR),and understated resource heterogeneity in the shale reservoir.This article proposes an integrated mass balance approach for resource calculation in liquid-rich shale plays.The proposed method integrates bulk rock geochemical data with production and reservoir parameters to overcome the problems associated with laboratory characterization of the volumetric parameters by restoring the gaseous and light hydrocarbon loss due to volume expansion and evaporation in the sample.The method is applied to a Duvernay production well(14-16-62-21 W5)in the Western Canada Sedimentary Basin(WCSB)to demonstrate its use in resource evaluation for a liquid-rich play.The results show that(a)by considering the phase behavior of reservoir fluids,the proposed method can be used to infer the quantity of the lost gaseous and light hydrocarbons;(b)by taking into account the lost gaseous and light hydrocarbons,the method generates an unbiased and representative resource potential;and(c)using the corrected oil and gas mass for the analyzed samples,the method produces a GOR estimate close to compositional characteristics of the produced hydrocarbons from initial production in 14-16-62-21 W5 well.
文摘With increasing global demand for energy,the importance of unconventional shale oil and gas research cannot be over-emphasized.The oil and gas industry requires rapid and reliable means of forecasting production.Existing traditional decline curve analysis(DCA)methods have been limited in their ability to satisfactorily forecast production from unconventional liquid-rich shale(LRS)reservoirs.This is due to several causes ranging from the complicated production mechanisms to the ultra-low permeability in shales.The use of hybrid(combination)DCA models can improve results.However,complexities associated with these techniques can still make their application quite tedious without proper diagnostic plots,correct use of model parameters and some knowledge of the production mechanisms involved.This work,therefore,presents a new statistical data-driven approach of forecasting production from LRS reservoirs called the Principal Components Methodology(PCM).PCM is a technique that bypasses a lot of the difficulties associated with existing methods of forecasting and forecasts production with reasonable certainty.PCM is a data-driven method of forecasting based on the statistical technique of principal components analysis(PCA).In our study,we simulated production of fluids with different compositions for 30 years with the aid of a commercial compositional simulator.We then applied the Principal Components Methodology(PCM)to the production data from several representative wells by using Singular Value Decomposition(SVD)to calculate the principal components.These principal components were then used to forecast oil production from wells with production histories ranging from 0.5 to 3 years,and the results were compared to simulated data.Application of the PCM to field data is also included in this work.
