Discovered in 1949 with a rate of (195,000) bbl/day from pay zones in Mishrif and Zubair Formation, the expected production of Zubair field is anticipated to be 1125 million bbl/day. Despite this production history, t...Discovered in 1949 with a rate of (195,000) bbl/day from pay zones in Mishrif and Zubair Formation, the expected production of Zubair field is anticipated to be 1125 million bbl/day. Despite this production history, there is a major deficiency in detailed petrophysical analysis of the producing zones. In the present study well log data of 7 wells, selected from numerous wells, are investigated in details to examine the reservoir properties and characterize the reservoir architecture. The petrophysical analysis of Mishrif Formation indicated two or three pay zones. Lithologically, all zones of Mishrif Formation are dominantly clean limestone to dolomitic limestone with zone 2 and 3 reporting higher dolomitic content (20% to 40%) compared to zone 1 (6% to 13%). Mishrif pay zones indicated a relatively good porosity (18% - 24%) with zone 2 predominant in secondary porosity associating dolomitization processes. In Zubair Formation one pay zone is identified but locally could separate into two zones. The clay content is generally low with average content between 2% and 3% while the average porosity showed slightly better values in zone 1 (~0.20) compared to average porosity of zone 2 (0.17) that is rich in silt content associating deposition at a relatively deeper parts of the shelf. The average water saturation shows distinct lower values that vary between 15% and 18.7%. The petrophysical results are statistically analyzed and property histograms and crossplots are constructed to investigate mutual relationships. Such analysis is essential for understanding the reservoir architecture and calculations of reservoir capacity for future development.展开更多
Artificial Intelligence,or AI,is a method of data analysis that learns from data,identify patterns and makes predictions with the minimal human intervention.AI is bringing many benefits to petrophysical evaluation.Usi...Artificial Intelligence,or AI,is a method of data analysis that learns from data,identify patterns and makes predictions with the minimal human intervention.AI is bringing many benefits to petrophysical evaluation.Using case studies,this paper describes several successful applications.The future of AI has even more potential.However,if used carelessly there are potentially grave consequences.A complex Middle East Carbonate field needed a bespoke shaly water saturation equation.AI was used to‘evolve’an ideal equation,together with field specific saturation and cementation exponents.One UKCS gas field had an‘oil problem’.Here,AI was used to unlock the hidden fluid information in the NMR T1 and T2 spectra and successfully differentiate oil and gas zones in real time.A North Sea field with 30 wells had shear velocity data(Vs)in only 4 wells.Vs was required for reservoir modelling and well bore stability prediction.AI was used to predict Vs in all 30 wells.Incorporating high vertical resolution data,the Vs predictions were even better than the recorded logs.As it is not economic to take core data on every well,AI is used to discover the relationships between logs,core,litho-facies and permeability in multi-dimensional data space.As a consequence,all wells in a field were populated with these data to build a robust reservoir model.In addition,the AI predicted data upscaled correctly unlike many conventional techniques.AI gives impressive results when automatically log quality controlling(LQC)and repairing electrical logs for bad hole and sections of missing data.AI doesn’t require prior knowledge of the petrophysical response equations and is self-calibrating.There are no parameters to pick or cross-plots to make.There is very little user intervention and AI avoids the problem of‘garbage in,garbage out’(GIGO),by ignoring noise and outliers.AI programs work with an unlimited number of electrical logs,core and gas chromatography data;and don’t‘fall-over’if some of those inputs are missing.AI programs currently being developed include ones where their machine code evolves using similar rules used by life’s DNA code.These AI programs pose considerable dangers far beyond the oil industry as described in this paper.A‘risk assessment’is essential on all AI programs so that all hazards and risk factors,that could cause harm,are identified and mitigated.展开更多
A considerable effort has been made in the literature for quality assurance (QA) and quality checking (QC) of the petrophysical log data for computation of reservoir rock property parameters. Well log data plays an in...A considerable effort has been made in the literature for quality assurance (QA) and quality checking (QC) of the petrophysical log data for computation of reservoir rock property parameters. Well log data plays an integral role in building a rock physics model for quantitative interpretation (QI) work. A poor-quality rock physics model may lead to significant financial and HSSE implications by drilling wells in undesired locations. Historically, a variety of techniques have been used including histograms and cross plots for reviewing the feasibility of petrophysical logs for QI work. However, no attempt has ever been made to introduce a simplified workflow. This paper serves two-fold. It provides a simplified step by step approach for building a petrophysics/rock physics model. A case study has been presented to compare the synthetic seismogram generated from the simplified workflow with the actual seismic trace at well locations. Secondly, the paper shows how a few key cross plots and rock property parameters provide adequate information to validate petrophysical data, distinguish overburden and reservoir sections, and to help identify fluids and saturation trends within the reservoir sands. In the mentioned case study, the robustness of the simplified rock physics model has helped seismic data to successfully distinguish hydrocarbon bearing reservoir sands from non-reservoir shales.展开更多
Global warming has greatly threatened the human living environment and carbon capture and storage(CCS)technology is recognized as a promising way to reduce carbon emissions.Mineral storage is considered a reliable opt...Global warming has greatly threatened the human living environment and carbon capture and storage(CCS)technology is recognized as a promising way to reduce carbon emissions.Mineral storage is considered a reliable option for long-term carbon storage.Basalt rich in alkaline earth elements facilitates rapid and permanent CO_(2) fixation as carbonates.However,the complex CO_(2)-fluid-basalt interaction poses challenges for assessing carbon storage potential.Under different reaction conditions,the carbonation products and carbonation rates vary.Carbon mineralization reactions also induce petrophysical and mechanical responses,which have potential risks for the long-term injectivity and the carbon storage safety in basalt reservoirs.In this paper,recent advances in carbon mineralization storage in basalt based on laboratory research are comprehensively reviewed.The assessment methods for carbon storage potential are introduced and the carbon trapping mechanisms are investigated with the identification of the controlling factors.Changes in pore structure,permeability and mechanical properties in both static reactions and reactive percolation experiments are also discussed.This study could provide insight into challenges as well as perspectives for future research.展开更多
Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation ...Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.展开更多
The evaluation of reservoir quality was accomplished on the Late Paleocene to Early Eocene Narimba Formation in Bass Basin,Australia.This study involved combination methods such as petrophysical analysis,petrography a...The evaluation of reservoir quality was accomplished on the Late Paleocene to Early Eocene Narimba Formation in Bass Basin,Australia.This study involved combination methods such as petrophysical analysis,petrography and sedimentological studies,reservoir quality and fluid flow units from derivative parameters,and capillary pressure and wetting fluid saturation relationship.Textural and diagenetic features are affecting the reservoir quality.Cementation,compaction,and presence of clay minerals such as kaolinite are found to reduce the quality while dissolution and secondary porosity are noticed to improve it.It is believed that the Narimba Formation is a potential reservoir with a wide range of porosity and permeability.Porosity ranges from 3.1%to 25.4%with a mean of 15.84%,while permeability ranges between 0.01 mD and 510 mD,with a mean of 31.05 mD.Based on the heterogenous lithology,the formation has been categorized into five groups based on permeability variations.Group I showed an excellent to good quality reservoir with coarse grains.The impacts of both textural and diagenetic features improve the reservoir and producing higher reservoir quality index(RQI)and flow zone indicators(FZI)as well as mostly mega pores.The non-wetting fluid migration has the higher possibility to flow in the formation while displacement pressure recorded as zero.Group II showed a fair quality reservoir with lower petrophysical properties in macro pores.The irreducible water saturation is increasing while the textural and digenetic properties are still enhancing the reservoir quality.Group III reflects lower quality reservoir with mostly macro pores and higher displacement pressure.It may indicate smaller grain size and increasing amount of cement and clay minerals.Group IV,and V are interpreted as a poor-quality reservoir that has lower RQI and FZI.The textural and digenetic features are negatively affecting the reservoir and are leading to smaller pore size and pore throat radii(r35)values to be within the range of macro,meso-,micro-,and nano pores.The capillary displacement pressure curves of the three groups show increases reaching the maximum value of 400 psia in group V.Agreement with the classification of permeability,r35 values,and pore type can be used in identifying the quality of reservoir.展开更多
The present research work attempted to delineate and characterize the reservoir facies from the Dawson Canyon Formation in the Penobscot field,Scotian Basin.An integrated study of instantaneous frequency,P-impedance,v...The present research work attempted to delineate and characterize the reservoir facies from the Dawson Canyon Formation in the Penobscot field,Scotian Basin.An integrated study of instantaneous frequency,P-impedance,volume of clay and neutron-porosity attributes,and structural framework was done to unravel the Late Cretaceous depositional system and reservoir facies distribution patterns within the study area.Fault strikes were found in the EW and NEE-SWW directions indicating the dominant course of tectonic activities during the Late Cretaceous period in the region.P-impedance was estimated using model-based seismic inversion.Petrophysical properties such as the neutron porosity(NPHI)and volume of clay(VCL)were estimated using the multilayer perceptron neural network with high accuracy.Comparatively,a combination of low instantaneous frequency(15-30 Hz),moderate to high impedance(7000-9500 gm/cc*m/s),low neutron porosity(27%-40%)and low volume of clay(40%-60%),suggests fair-to-good sandstone development in the Dawson Canyon Formation.After calibration with the welllog data,it is found that further lowering in these attribute responses signifies the clean sandstone facies possibly containing hydrocarbons.The present study suggests that the shale lithofacies dominates the Late Cretaceous deposition(Dawson Canyon Formation)in the Penobscot field,Scotian Basin.Major faults and overlying shale facies provide structural and stratigraphic seals and act as a suitable hydrocarbon entrapment mechanism in the Dawson Canyon Formation's reservoirs.The present research advocates the integrated analysis of multi-attributes estimated using different methods to minimize the risk involved in hydrocarbon exploration.展开更多
The complex pore structure of carbonate reservoirs hinders the correlation between porosity and permeability.In view of the sedimentation,diagenesis,testing,and production characteristics of carbonate reservoirs in th...The complex pore structure of carbonate reservoirs hinders the correlation between porosity and permeability.In view of the sedimentation,diagenesis,testing,and production characteristics of carbonate reservoirs in the study area,combined with the current trends and advances in well log interpretation techniques for carbonate reservoirs,a log interpretation technology route of“geological information constraint+deep learning”was developed.The principal component analysis(PCA)was employed to establish lithology identification criteria with an accuracy of 91%.The Bayesian stepwise discriminant method was used to construct a sedimentary microfacies identification method with an accuracy of 90.5%.Based on production data,the main lithologies and sedimentary microfacies of effective reservoirs were determined,and 10 petrophysical facies with effective reservoir characteristics were identified.Constrained by petrophysical facies,the mean interpretation error of porosity compared to core analysis results is 2.7%,and the ratio of interpreted permeability to core analysis is within one order of magnitude,averaging 3.6.The research results demonstrate that deep learning algorithms can uncover the correlation in carbonate reservoir well logging data.Integrating geological and production data and selecting appropriate machine learning algorithms can significantly improve the accuracy of well log interpretation for carbonate reservoirs.展开更多
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
The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. De...The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. Despite advances in seismic data interpretation using traditional 3D seismic data interpretation, obtaining adequate reservoir characteristics at the finest level had proved very challenging with often disappointing results. A method that integrates the amplitude variation with offfset (AVO) analysis is hereby proposed to better illuminate the reservoir. The Hampson Russell 10.3 was used to integrate and study the available seismic and well data. The reservoir of interest was delineated using the available suite of petrophysical data. This was marked by low gamma ray, high resistivity, and low acoustic impedance between a true subsea vertical depth (TVDss) range of 10,350 - 10,450 ft. The AVO fluid substitution yielded a decrease in the density values of pure gas (2.3 - 1.6 g/cc), pure oil (2.3 - 1.8 g/cc) while the Poisson pure brine increased (2.3 to 2.8 g/cc). Result from FORMAT 26 plots yielded a negative intercept and negative gradient at the top and a positive intercept and positive gradient at the Base which conforms to Class III AVO anomaly. FORMAT 30 plots yielded a negative intercept and positive gradient at the top and a positive intercept and negative gradient at the Base which conforms to class IV AVO anomaly. AVO attribute volume slices decreased in the Poisson ratio (0.96 to - 1.0) indicating that the reservoir contains hydrocarbon. The s-wave reflectivity and the product of the intercept and gradient further clarified that there was a Class 3 gas sand in the reservoir and the possibility of a Class 4 gas sand anomaly in that same reservoir.展开更多
The findings of a study to ascertain and assess the petrophysical characteristics of Cape Three Points reservoirs in the Western basin with a view to describe the reservoir quantitatively using Well Logs, Petrel and T...The findings of a study to ascertain and assess the petrophysical characteristics of Cape Three Points reservoirs in the Western basin with a view to describe the reservoir quantitatively using Well Logs, Petrel and Techlog. The investigated characteristics, which were all deduced from geophysical wire-line logs, include lithology, porosity, permeability, fluid saturation, and net to gross thickness. To characterise the reservoir on the field, a suite of wire-line logs including gamma ray, resistivity, spontaneous potential, and density logs for three wells (WELL_1X, WELL_2X, and WELL_3X) from the Tano Cape Three Point basin were studied. The analyses that were done included lithology delineation, reservoir identification, and petrophysical parameter determination for the identified reservoirs. The tops and bases of the three wells analysed were marked at a depth of 1203.06 - 2015.64 m, 3863.03 - 4253.85 m and 2497.38 - 2560.32 m respectively. There were no hydrocarbons in the reservoirs from the studies. The petrophysical parameters computed for each reservoir provided porosities of 13%, 3% and 11% respectively. The water saturation also determined for these three wells (WELL_1X, WELL_2X and WELL_3X) were 94%, 95% and 89% respectively. These results together with the behaviour of the density and neutron logs suggested that these wells are wildcat wells.展开更多
文摘Discovered in 1949 with a rate of (195,000) bbl/day from pay zones in Mishrif and Zubair Formation, the expected production of Zubair field is anticipated to be 1125 million bbl/day. Despite this production history, there is a major deficiency in detailed petrophysical analysis of the producing zones. In the present study well log data of 7 wells, selected from numerous wells, are investigated in details to examine the reservoir properties and characterize the reservoir architecture. The petrophysical analysis of Mishrif Formation indicated two or three pay zones. Lithologically, all zones of Mishrif Formation are dominantly clean limestone to dolomitic limestone with zone 2 and 3 reporting higher dolomitic content (20% to 40%) compared to zone 1 (6% to 13%). Mishrif pay zones indicated a relatively good porosity (18% - 24%) with zone 2 predominant in secondary porosity associating dolomitization processes. In Zubair Formation one pay zone is identified but locally could separate into two zones. The clay content is generally low with average content between 2% and 3% while the average porosity showed slightly better values in zone 1 (~0.20) compared to average porosity of zone 2 (0.17) that is rich in silt content associating deposition at a relatively deeper parts of the shelf. The average water saturation shows distinct lower values that vary between 15% and 18.7%. The petrophysical results are statistically analyzed and property histograms and crossplots are constructed to investigate mutual relationships. Such analysis is essential for understanding the reservoir architecture and calculations of reservoir capacity for future development.
文摘Artificial Intelligence,or AI,is a method of data analysis that learns from data,identify patterns and makes predictions with the minimal human intervention.AI is bringing many benefits to petrophysical evaluation.Using case studies,this paper describes several successful applications.The future of AI has even more potential.However,if used carelessly there are potentially grave consequences.A complex Middle East Carbonate field needed a bespoke shaly water saturation equation.AI was used to‘evolve’an ideal equation,together with field specific saturation and cementation exponents.One UKCS gas field had an‘oil problem’.Here,AI was used to unlock the hidden fluid information in the NMR T1 and T2 spectra and successfully differentiate oil and gas zones in real time.A North Sea field with 30 wells had shear velocity data(Vs)in only 4 wells.Vs was required for reservoir modelling and well bore stability prediction.AI was used to predict Vs in all 30 wells.Incorporating high vertical resolution data,the Vs predictions were even better than the recorded logs.As it is not economic to take core data on every well,AI is used to discover the relationships between logs,core,litho-facies and permeability in multi-dimensional data space.As a consequence,all wells in a field were populated with these data to build a robust reservoir model.In addition,the AI predicted data upscaled correctly unlike many conventional techniques.AI gives impressive results when automatically log quality controlling(LQC)and repairing electrical logs for bad hole and sections of missing data.AI doesn’t require prior knowledge of the petrophysical response equations and is self-calibrating.There are no parameters to pick or cross-plots to make.There is very little user intervention and AI avoids the problem of‘garbage in,garbage out’(GIGO),by ignoring noise and outliers.AI programs work with an unlimited number of electrical logs,core and gas chromatography data;and don’t‘fall-over’if some of those inputs are missing.AI programs currently being developed include ones where their machine code evolves using similar rules used by life’s DNA code.These AI programs pose considerable dangers far beyond the oil industry as described in this paper.A‘risk assessment’is essential on all AI programs so that all hazards and risk factors,that could cause harm,are identified and mitigated.
文摘A considerable effort has been made in the literature for quality assurance (QA) and quality checking (QC) of the petrophysical log data for computation of reservoir rock property parameters. Well log data plays an integral role in building a rock physics model for quantitative interpretation (QI) work. A poor-quality rock physics model may lead to significant financial and HSSE implications by drilling wells in undesired locations. Historically, a variety of techniques have been used including histograms and cross plots for reviewing the feasibility of petrophysical logs for QI work. However, no attempt has ever been made to introduce a simplified workflow. This paper serves two-fold. It provides a simplified step by step approach for building a petrophysics/rock physics model. A case study has been presented to compare the synthetic seismogram generated from the simplified workflow with the actual seismic trace at well locations. Secondly, the paper shows how a few key cross plots and rock property parameters provide adequate information to validate petrophysical data, distinguish overburden and reservoir sections, and to help identify fluids and saturation trends within the reservoir sands. In the mentioned case study, the robustness of the simplified rock physics model has helped seismic data to successfully distinguish hydrocarbon bearing reservoir sands from non-reservoir shales.
基金funding support from the National Key R&D Program of China(Grant No.2022YFE0115800)the Creative Groups of Natural Science Foundation of Hubei Province(Grant No.2021CFA030)Shanxi Provincial Key Research and Development Project(Grant No.202102090301009).
文摘Global warming has greatly threatened the human living environment and carbon capture and storage(CCS)technology is recognized as a promising way to reduce carbon emissions.Mineral storage is considered a reliable option for long-term carbon storage.Basalt rich in alkaline earth elements facilitates rapid and permanent CO_(2) fixation as carbonates.However,the complex CO_(2)-fluid-basalt interaction poses challenges for assessing carbon storage potential.Under different reaction conditions,the carbonation products and carbonation rates vary.Carbon mineralization reactions also induce petrophysical and mechanical responses,which have potential risks for the long-term injectivity and the carbon storage safety in basalt reservoirs.In this paper,recent advances in carbon mineralization storage in basalt based on laboratory research are comprehensively reviewed.The assessment methods for carbon storage potential are introduced and the carbon trapping mechanisms are investigated with the identification of the controlling factors.Changes in pore structure,permeability and mechanical properties in both static reactions and reactive percolation experiments are also discussed.This study could provide insight into challenges as well as perspectives for future research.
文摘Flow units(FU)rock typing is a common technique for characterizing reservoir flow behavior,producing reliable porosity and permeability estimation even in complex geological settings.However,the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study.This paper proposes a workflow to generate numerous possible 3D volumes of flow units,porosity and permeability below the seismic resolution limit,respecting the available seismic data at larger scales.The methodology is used in the Mero Field,a Brazilian presalt carbonate reservoir located in the Santos Basin,who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history.We generated metric flow units using the conventional core analysis and transposed to the well log data.Then,given a Markov chain Monte Carlo algorithm,the seismic data and the well log statistics,we simulated acoustic impedance,decametric flow units(DFU),metric flow units(MFU),porosity and permeability volumes in the metric scale.The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios,without losing the seismic lateral control.In other words,every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area,even in the metric scale.The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow.
文摘The evaluation of reservoir quality was accomplished on the Late Paleocene to Early Eocene Narimba Formation in Bass Basin,Australia.This study involved combination methods such as petrophysical analysis,petrography and sedimentological studies,reservoir quality and fluid flow units from derivative parameters,and capillary pressure and wetting fluid saturation relationship.Textural and diagenetic features are affecting the reservoir quality.Cementation,compaction,and presence of clay minerals such as kaolinite are found to reduce the quality while dissolution and secondary porosity are noticed to improve it.It is believed that the Narimba Formation is a potential reservoir with a wide range of porosity and permeability.Porosity ranges from 3.1%to 25.4%with a mean of 15.84%,while permeability ranges between 0.01 mD and 510 mD,with a mean of 31.05 mD.Based on the heterogenous lithology,the formation has been categorized into five groups based on permeability variations.Group I showed an excellent to good quality reservoir with coarse grains.The impacts of both textural and diagenetic features improve the reservoir and producing higher reservoir quality index(RQI)and flow zone indicators(FZI)as well as mostly mega pores.The non-wetting fluid migration has the higher possibility to flow in the formation while displacement pressure recorded as zero.Group II showed a fair quality reservoir with lower petrophysical properties in macro pores.The irreducible water saturation is increasing while the textural and digenetic properties are still enhancing the reservoir quality.Group III reflects lower quality reservoir with mostly macro pores and higher displacement pressure.It may indicate smaller grain size and increasing amount of cement and clay minerals.Group IV,and V are interpreted as a poor-quality reservoir that has lower RQI and FZI.The textural and digenetic features are negatively affecting the reservoir and are leading to smaller pore size and pore throat radii(r35)values to be within the range of macro,meso-,micro-,and nano pores.The capillary displacement pressure curves of the three groups show increases reaching the maximum value of 400 psia in group V.Agreement with the classification of permeability,r35 values,and pore type can be used in identifying the quality of reservoir.
文摘The present research work attempted to delineate and characterize the reservoir facies from the Dawson Canyon Formation in the Penobscot field,Scotian Basin.An integrated study of instantaneous frequency,P-impedance,volume of clay and neutron-porosity attributes,and structural framework was done to unravel the Late Cretaceous depositional system and reservoir facies distribution patterns within the study area.Fault strikes were found in the EW and NEE-SWW directions indicating the dominant course of tectonic activities during the Late Cretaceous period in the region.P-impedance was estimated using model-based seismic inversion.Petrophysical properties such as the neutron porosity(NPHI)and volume of clay(VCL)were estimated using the multilayer perceptron neural network with high accuracy.Comparatively,a combination of low instantaneous frequency(15-30 Hz),moderate to high impedance(7000-9500 gm/cc*m/s),low neutron porosity(27%-40%)and low volume of clay(40%-60%),suggests fair-to-good sandstone development in the Dawson Canyon Formation.After calibration with the welllog data,it is found that further lowering in these attribute responses signifies the clean sandstone facies possibly containing hydrocarbons.The present study suggests that the shale lithofacies dominates the Late Cretaceous deposition(Dawson Canyon Formation)in the Penobscot field,Scotian Basin.Major faults and overlying shale facies provide structural and stratigraphic seals and act as a suitable hydrocarbon entrapment mechanism in the Dawson Canyon Formation's reservoirs.The present research advocates the integrated analysis of multi-attributes estimated using different methods to minimize the risk involved in hydrocarbon exploration.
基金funded by the Science and Technology Project of Changzhou City(Grant No.CJ20210120)the Research Start-up Fund of Changzhou University(Grant No.ZMF21020056).
文摘The complex pore structure of carbonate reservoirs hinders the correlation between porosity and permeability.In view of the sedimentation,diagenesis,testing,and production characteristics of carbonate reservoirs in the study area,combined with the current trends and advances in well log interpretation techniques for carbonate reservoirs,a log interpretation technology route of“geological information constraint+deep learning”was developed.The principal component analysis(PCA)was employed to establish lithology identification criteria with an accuracy of 91%.The Bayesian stepwise discriminant method was used to construct a sedimentary microfacies identification method with an accuracy of 90.5%.Based on production data,the main lithologies and sedimentary microfacies of effective reservoirs were determined,and 10 petrophysical facies with effective reservoir characteristics were identified.Constrained by petrophysical facies,the mean interpretation error of porosity compared to core analysis results is 2.7%,and the ratio of interpreted permeability to core analysis is within one order of magnitude,averaging 3.6.The research results demonstrate that deep learning algorithms can uncover the correlation in carbonate reservoir well logging data.Integrating geological and production data and selecting appropriate machine learning algorithms can significantly improve the accuracy of well log interpretation for carbonate reservoirs.
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.
文摘The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. Despite advances in seismic data interpretation using traditional 3D seismic data interpretation, obtaining adequate reservoir characteristics at the finest level had proved very challenging with often disappointing results. A method that integrates the amplitude variation with offfset (AVO) analysis is hereby proposed to better illuminate the reservoir. The Hampson Russell 10.3 was used to integrate and study the available seismic and well data. The reservoir of interest was delineated using the available suite of petrophysical data. This was marked by low gamma ray, high resistivity, and low acoustic impedance between a true subsea vertical depth (TVDss) range of 10,350 - 10,450 ft. The AVO fluid substitution yielded a decrease in the density values of pure gas (2.3 - 1.6 g/cc), pure oil (2.3 - 1.8 g/cc) while the Poisson pure brine increased (2.3 to 2.8 g/cc). Result from FORMAT 26 plots yielded a negative intercept and negative gradient at the top and a positive intercept and positive gradient at the Base which conforms to Class III AVO anomaly. FORMAT 30 plots yielded a negative intercept and positive gradient at the top and a positive intercept and negative gradient at the Base which conforms to class IV AVO anomaly. AVO attribute volume slices decreased in the Poisson ratio (0.96 to - 1.0) indicating that the reservoir contains hydrocarbon. The s-wave reflectivity and the product of the intercept and gradient further clarified that there was a Class 3 gas sand in the reservoir and the possibility of a Class 4 gas sand anomaly in that same reservoir.
文摘The findings of a study to ascertain and assess the petrophysical characteristics of Cape Three Points reservoirs in the Western basin with a view to describe the reservoir quantitatively using Well Logs, Petrel and Techlog. The investigated characteristics, which were all deduced from geophysical wire-line logs, include lithology, porosity, permeability, fluid saturation, and net to gross thickness. To characterise the reservoir on the field, a suite of wire-line logs including gamma ray, resistivity, spontaneous potential, and density logs for three wells (WELL_1X, WELL_2X, and WELL_3X) from the Tano Cape Three Point basin were studied. The analyses that were done included lithology delineation, reservoir identification, and petrophysical parameter determination for the identified reservoirs. The tops and bases of the three wells analysed were marked at a depth of 1203.06 - 2015.64 m, 3863.03 - 4253.85 m and 2497.38 - 2560.32 m respectively. There were no hydrocarbons in the reservoirs from the studies. The petrophysical parameters computed for each reservoir provided porosities of 13%, 3% and 11% respectively. The water saturation also determined for these three wells (WELL_1X, WELL_2X and WELL_3X) were 94%, 95% and 89% respectively. These results together with the behaviour of the density and neutron logs suggested that these wells are wildcat wells.
