In this paper, we propose a hybrid PML （H-PML） combining the normal absorption factor of convolutional PML （C-PML） with tangential absorption factor of Mutiaxial PML （M-PML）. The H-PML boundary conditions can be...In this paper, we propose a hybrid PML （H-PML） combining the normal absorption factor of convolutional PML （C-PML） with tangential absorption factor of Mutiaxial PML （M-PML）. The H-PML boundary conditions can better suppress the numerical instability in some extreme models, and the computational speed of finite-element method and the dynamic range are greatly increased using this HPML. We use the finite-element method with a hybrid PML to model the acoustic reflection of the interface when wireline and well logging while drilling （LWD）, in a formation with a reflector outside the borehole. The simulation results suggests that the PS- and SP- reflected waves arrive at the same time when the inclination between the well and the outer interface is zero, and the difference in arrival times increases with increasing dip angle. When there are fractures outside the well, the reflection signal is clearer in the subsequent reflection waves and may be used to identify the fractured zone. The difference between the dominant wavelength and the model scale shows that LWD reflection logging data are of higher resolution and quality than wireline acoustic reflection logging.展开更多
This study focused on the quantitative analysis of the petrophysical parameters in characterizing the reservoir properties of the Srikail gas field using multi-scale wireline logs.Petrophysical parameters(shale volume...This study focused on the quantitative analysis of the petrophysical parameters in characterizing the reservoir properties of the Srikail gas field using multi-scale wireline logs.Petrophysical parameters(shale volume,porosity,water saturation and hydrocarbon saturation)were estimated from the combination of gamma ray log,resistivity log,density log and neutron log for three hydrocarbon(gas)-bearing zones at well#3.At the first time,log records at 0.1 m and 0.2 m intervals were read for this study.Result showed the average shale volume is 21.07%,53.67%and 51.71%for zone-1,zone-2 and zone-3,respectively.For these zones,the estimated average porosity was 35.89%,29.83%and 28.76%,respectively.The average water saturation of 31.54%,16.83%and 23.39%and average hydrocarbon saturation of 68.46%,83.17%and 76.61%were calculated for zone-1,zone-2 and zone-3,respectively.Thus zone-2 is regarded the most productive zone of well#3.It was found that the values of some parameters(porosity,hydrocarbon saturation and permeability)are higher than the existing results.Therefore,this study confirmed that the log reading at minute/close interval provides better quantitive values of the reservoir’s petrophysical properties.It is expected that this result will contribute to the national gas field development program in future.展开更多
The travel time of rock compressional waves is an essential parameter used for estimating important rock properties,such as porosity,permeability,and lithology.Current methods,like wireline logging tests,provide broad...The travel time of rock compressional waves is an essential parameter used for estimating important rock properties,such as porosity,permeability,and lithology.Current methods,like wireline logging tests,provide broad measurements but lack finer resolution.Laboratory-based rock core measurements offer higher resolution but are resource-intensive.Conventionally,wireline logging and rock core measurements have been used independently.This study introduces a novel approach that integrates both data sources.The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data.By combining machine learning with random field theory,the method allows for probabilistic predictions in regions with sparse data sampling.In this framework,12 parameters from wireline tests are used to predict trends in rock core data.The residuals are modeled using random field theory.The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual.By utilizing unconditional and conditional random field theories,this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates.This integrated approach optimizes the use of existing core and logging data.Its applicability is confirmed in an oil project in West China.展开更多
In this study, an integrated approach for diagenetic facies classification, reservoir quality analysis and quantitative wireline log prediction of tight gas sandstones(TGSs) is introduced utilizing a combination of fi...In this study, an integrated approach for diagenetic facies classification, reservoir quality analysis and quantitative wireline log prediction of tight gas sandstones(TGSs) is introduced utilizing a combination of fit-for-purpose complementary testing and machine learning techniques. The integrated approach is specialized for the middle Permian Shihezi Formation TGSs in the northeastern Ordos Basin, where operators often face significant drilling uncertainty and increased exploration risks due to low porosities and micro-Darcy range permeabilities. In this study, detrital compositions and diagenetic minerals and their pore type assemblages were analyzed using optical light microscopy, cathodoluminescence, standard scanning electron microscopy, and X-ray diffraction. Different types of diagenetic facies were delineated on this basis to capture the characteristic rock properties of the TGSs in the target formation.A combination of He porosity and permeability measurements, mercury intrusion capillary pressure and nuclear magnetic resonance data was used to analyze the mechanism of heterogeneous TGS reservoirs.We found that the type, size and proportion of pores considerably varied between diagenetic facies due to differences in the initial depositional attributes and subsequent diagenetic alterations;these differences affected the size, distribution and connectivity of the pore network and varied the reservoir quality. Five types of diagenetic facies were classified:(i) grain-coating facies, which have minimal ductile grains, chlorite coatings that inhibit quartz overgrowths, large intergranular pores that dominate the pore network, the best pore structure and the greatest reservoir quality;(ii) quartz-cemented facies,which exhibit strong quartz overgrowths, intergranular porosity and a pore size decrease, resulting in the deterioration of the pore structure and reservoir quality;(iii) mixed-cemented facies, in which the cementation of various authigenic minerals increases the micropores, resulting in a poor pore structure and reservoir quality;(iv) carbonate-cemented facies and(v) tightly compacted facies, in which the intergranular pores are filled with carbonate cement and ductile grains;thus, the pore network mainly consists of micropores with small pore throat sizes, and the pore structure and reservoir quality are the worst. The grain-coating facies with the best reservoir properties are more likely to have high gas productivity and are the primary targets for exploration and development. The diagenetic facies were then translated into wireline log expressions(conventional and NMR logging). Finally, a wireline log quantitative prediction model of TGSs using convolutional neural network machine learning algorithms was established to successfully classify the different diagenetic facies.展开更多
Wellbore instability and sand production are all common challenges in the Niger Delta oil province,resulting in high drilling and production cost as well as damage to oil facilities.The vulnerability of lithologic for...Wellbore instability and sand production are all common challenges in the Niger Delta oil province,resulting in high drilling and production cost as well as damage to oil facilities.The vulnerability of lithologic formations to wellbore instability and resultant sand production is investigated in the four delineated reservoirs of the“Areo”field,western part of Niger Delta Basin.The foundation for establishing the geomechanical properties in this study was a 1-dimensional mechanical earth model,using gamma ray(GR),density(RHOB),compressional slowness(DTC),and shear slowness(DTS)logs.Within the Areo oil field,two wells(well 001 and well 002)were correlated.The evaluated formations are still primarily composed of compacted shale and unconsolidated sandstone,with reservoir sand units exhibiting lower elastic and rock strength properties than shale units.High compressibility and porosity make sand more brittle,while low compressibility and porosity make shale stiffer due to high moduli.The maximum force that can be applied to a shale unit without causing it to fail is 17.23 MPa,which is the maximum average rock strength of the shale.It means that shale requires more vertical stress or pressure than sand does in order to deform it(15.06 MPa).The three sand prediction approaches used in the analysis of sand production predictions have cut-off values that are higher than the average values of the formations.The Schlumberger sand production index method(S/I)indicates that the reservoir has potential for sand influx in the two wells,with the average of the four reservoirs studied in wells 001 and 002 being 1.551012 psi and 1.141012 psi respectively.However,when a formation's sand production index is less than 1.241012 psi,as it is in this study,the formation is likely to produce sand.These findings support the notion that the defined sandstone units are highly unconsolidated and have a high potential for producing sands;therefore,sand control techniques must be factored into process optimization and cost reduction plans.展开更多
Porosity is one of the main parameters that should be considered when a gas or an oil field is assessed.Hence,the availability of porosity is crucial in any rock and formation analysis.However,this parameter is not al...Porosity is one of the main parameters that should be considered when a gas or an oil field is assessed.Hence,the availability of porosity is crucial in any rock and formation analysis.However,this parameter is not always available and direct measurement is scarce and usually is confined to appraisal phase of a field.Therefore,in this study it is aimed to find a relationship in order to estimate porosity in afterward phases.The data of 5 appraisal wells of an undeveloped gas field has been gathered to perform this purpose.The full set wireline logging data and drilling data were available.The data inherit high level of fluctuation which is normal with respect to real direct measured data.The smoothed curving was utilized and as a result,the fluctuation was diminished considerably and the feasibility of carrying out the investigation was being established,accordingly.To normalize and gather drilling data in a parameter in order to have a better view and investigation,sigmalog method was employed.It was observed that there is a clear exponential relationship between porosity and drilling data and curve fitting was utilized to conduct a numerical relationship.The curve fitting was established with R^(2)=0.83 and a trustworthy fitting resulted.The results demonstrate the possibility of porosity estimation by using drilling data.Furthermore,a numerical relationship is given for a specific field.The porosity estimation can lead to better analysis of newly drilled rocks and formations leading to more efficient field development strategies.展开更多
基金supported by the National Natural Science Foundation of China(No.41204094)Science Foundation of China University of Petroleum,Beijing(No.2462015YQ0506)
文摘In this paper, we propose a hybrid PML （H-PML） combining the normal absorption factor of convolutional PML （C-PML） with tangential absorption factor of Mutiaxial PML （M-PML）. The H-PML boundary conditions can better suppress the numerical instability in some extreme models, and the computational speed of finite-element method and the dynamic range are greatly increased using this HPML. We use the finite-element method with a hybrid PML to model the acoustic reflection of the interface when wireline and well logging while drilling （LWD）, in a formation with a reflector outside the borehole. The simulation results suggests that the PS- and SP- reflected waves arrive at the same time when the inclination between the well and the outer interface is zero, and the difference in arrival times increases with increasing dip angle. When there are fractures outside the well, the reflection signal is clearer in the subsequent reflection waves and may be used to identify the fractured zone. The difference between the dominant wavelength and the model scale shows that LWD reflection logging data are of higher resolution and quality than wireline acoustic reflection logging.
基金the K.C. Wong Education Foundation (GJTD-2019-04)the Chinese Academy of Sciences as President ’s International Fellowship Initiative (PIFI) for a Postdoctoral fellow to M. Moklesur Rahman (2019PE0025).
文摘This study focused on the quantitative analysis of the petrophysical parameters in characterizing the reservoir properties of the Srikail gas field using multi-scale wireline logs.Petrophysical parameters(shale volume,porosity,water saturation and hydrocarbon saturation)were estimated from the combination of gamma ray log,resistivity log,density log and neutron log for three hydrocarbon(gas)-bearing zones at well#3.At the first time,log records at 0.1 m and 0.2 m intervals were read for this study.Result showed the average shale volume is 21.07%,53.67%and 51.71%for zone-1,zone-2 and zone-3,respectively.For these zones,the estimated average porosity was 35.89%,29.83%and 28.76%,respectively.The average water saturation of 31.54%,16.83%and 23.39%and average hydrocarbon saturation of 68.46%,83.17%and 76.61%were calculated for zone-1,zone-2 and zone-3,respectively.Thus zone-2 is regarded the most productive zone of well#3.It was found that the values of some parameters(porosity,hydrocarbon saturation and permeability)are higher than the existing results.Therefore,this study confirmed that the log reading at minute/close interval provides better quantitive values of the reservoir’s petrophysical properties.It is expected that this result will contribute to the national gas field development program in future.
基金the Australian Government through the Australian Research Council's Discovery Projects funding scheme(Project DP190101592)the National Natural Science Foundation of China(Grant Nos.41972280 and 52179103).
文摘The travel time of rock compressional waves is an essential parameter used for estimating important rock properties,such as porosity,permeability,and lithology.Current methods,like wireline logging tests,provide broad measurements but lack finer resolution.Laboratory-based rock core measurements offer higher resolution but are resource-intensive.Conventionally,wireline logging and rock core measurements have been used independently.This study introduces a novel approach that integrates both data sources.The method leverages the detailed features from limited core data to enhance the resolution of wireline logging data.By combining machine learning with random field theory,the method allows for probabilistic predictions in regions with sparse data sampling.In this framework,12 parameters from wireline tests are used to predict trends in rock core data.The residuals are modeled using random field theory.The outcomes are high-resolution predictions that combine both the predicted trend and the probabilistic realizations of the residual.By utilizing unconditional and conditional random field theories,this method enables unconditional and conditional simulations of the underlying high-resolution rock compressional wave travel time profile and provides uncertainty estimates.This integrated approach optimizes the use of existing core and logging data.Its applicability is confirmed in an oil project in West China.
基金financially supported by the National Natural Science Foundation of China (No. 42272156)research on efficient exploration and development technology for tight stone gas of China United Coalbed Methane Corporation (No. ZZGSECCYWG 2021-322)。
文摘In this study, an integrated approach for diagenetic facies classification, reservoir quality analysis and quantitative wireline log prediction of tight gas sandstones(TGSs) is introduced utilizing a combination of fit-for-purpose complementary testing and machine learning techniques. The integrated approach is specialized for the middle Permian Shihezi Formation TGSs in the northeastern Ordos Basin, where operators often face significant drilling uncertainty and increased exploration risks due to low porosities and micro-Darcy range permeabilities. In this study, detrital compositions and diagenetic minerals and their pore type assemblages were analyzed using optical light microscopy, cathodoluminescence, standard scanning electron microscopy, and X-ray diffraction. Different types of diagenetic facies were delineated on this basis to capture the characteristic rock properties of the TGSs in the target formation.A combination of He porosity and permeability measurements, mercury intrusion capillary pressure and nuclear magnetic resonance data was used to analyze the mechanism of heterogeneous TGS reservoirs.We found that the type, size and proportion of pores considerably varied between diagenetic facies due to differences in the initial depositional attributes and subsequent diagenetic alterations;these differences affected the size, distribution and connectivity of the pore network and varied the reservoir quality. Five types of diagenetic facies were classified:(i) grain-coating facies, which have minimal ductile grains, chlorite coatings that inhibit quartz overgrowths, large intergranular pores that dominate the pore network, the best pore structure and the greatest reservoir quality;(ii) quartz-cemented facies,which exhibit strong quartz overgrowths, intergranular porosity and a pore size decrease, resulting in the deterioration of the pore structure and reservoir quality;(iii) mixed-cemented facies, in which the cementation of various authigenic minerals increases the micropores, resulting in a poor pore structure and reservoir quality;(iv) carbonate-cemented facies and(v) tightly compacted facies, in which the intergranular pores are filled with carbonate cement and ductile grains;thus, the pore network mainly consists of micropores with small pore throat sizes, and the pore structure and reservoir quality are the worst. The grain-coating facies with the best reservoir properties are more likely to have high gas productivity and are the primary targets for exploration and development. The diagenetic facies were then translated into wireline log expressions(conventional and NMR logging). Finally, a wireline log quantitative prediction model of TGSs using convolutional neural network machine learning algorithms was established to successfully classify the different diagenetic facies.
文摘Wellbore instability and sand production are all common challenges in the Niger Delta oil province,resulting in high drilling and production cost as well as damage to oil facilities.The vulnerability of lithologic formations to wellbore instability and resultant sand production is investigated in the four delineated reservoirs of the“Areo”field,western part of Niger Delta Basin.The foundation for establishing the geomechanical properties in this study was a 1-dimensional mechanical earth model,using gamma ray(GR),density(RHOB),compressional slowness(DTC),and shear slowness(DTS)logs.Within the Areo oil field,two wells(well 001 and well 002)were correlated.The evaluated formations are still primarily composed of compacted shale and unconsolidated sandstone,with reservoir sand units exhibiting lower elastic and rock strength properties than shale units.High compressibility and porosity make sand more brittle,while low compressibility and porosity make shale stiffer due to high moduli.The maximum force that can be applied to a shale unit without causing it to fail is 17.23 MPa,which is the maximum average rock strength of the shale.It means that shale requires more vertical stress or pressure than sand does in order to deform it(15.06 MPa).The three sand prediction approaches used in the analysis of sand production predictions have cut-off values that are higher than the average values of the formations.The Schlumberger sand production index method(S/I)indicates that the reservoir has potential for sand influx in the two wells,with the average of the four reservoirs studied in wells 001 and 002 being 1.551012 psi and 1.141012 psi respectively.However,when a formation's sand production index is less than 1.241012 psi,as it is in this study,the formation is likely to produce sand.These findings support the notion that the defined sandstone units are highly unconsolidated and have a high potential for producing sands;therefore,sand control techniques must be factored into process optimization and cost reduction plans.
文摘Porosity is one of the main parameters that should be considered when a gas or an oil field is assessed.Hence,the availability of porosity is crucial in any rock and formation analysis.However,this parameter is not always available and direct measurement is scarce and usually is confined to appraisal phase of a field.Therefore,in this study it is aimed to find a relationship in order to estimate porosity in afterward phases.The data of 5 appraisal wells of an undeveloped gas field has been gathered to perform this purpose.The full set wireline logging data and drilling data were available.The data inherit high level of fluctuation which is normal with respect to real direct measured data.The smoothed curving was utilized and as a result,the fluctuation was diminished considerably and the feasibility of carrying out the investigation was being established,accordingly.To normalize and gather drilling data in a parameter in order to have a better view and investigation,sigmalog method was employed.It was observed that there is a clear exponential relationship between porosity and drilling data and curve fitting was utilized to conduct a numerical relationship.The curve fitting was established with R^(2)=0.83 and a trustworthy fitting resulted.The results demonstrate the possibility of porosity estimation by using drilling data.Furthermore,a numerical relationship is given for a specific field.The porosity estimation can lead to better analysis of newly drilled rocks and formations leading to more efficient field development strategies.
