Volume 29,Issue 6,2022 Table of Contents
2022, 29(6):1-11.
DOI: 10.13673/j.cnki.cn37-1359/te.202202027
Abstract:
The hot issues of strong heterogeneity，complex distribution and difficult prediction of organic matter exist in shale reservoirs in Chang73 Member of Mesozoic Yanchang Formation in southeast Ordos Basin. Considering this，based on the data of drilling，logging，core，thin section and trace element analysis to explore the development characteristics of organic matter and its enrichment model in shale reservoirs of Chang73 Member. The results indicate that the semi-deep to deep lacustrine shale in Chang73 Member in the sedimentary period has great potential of shale gas，with a high abundance of organic matter，large thickness，and good continuity，and the most organic matter is Ⅱ1 type. Organic matter is widely developed in thick layered shale rocks and enriched along sedimentary laminae. Affected by the Indosinian movement，the basement subsides intensively during Chang73 Member sedimentary period，which forms a large-scale sedimentary center and expands the accommodation space of the lake basin. Moreover，a humid and semi-arid climate is favorable for nutrient minerals to enter the lake basin and promote aquatic organism accumulation，and volcanic events also lead to eutrophication of water bodies and improved organic matter productivity. A long-term and stable anoxic and reductive environment provides key conditions for the preservation of sedimentary organic matter.
The hot issues of strong heterogeneity，complex distribution and difficult prediction of organic matter exist in shale reservoirs in Chang73 Member of Mesozoic Yanchang Formation in southeast Ordos Basin. Considering this，based on the data of drilling，logging，core，thin section and trace element analysis to explore the development characteristics of organic matter and its enrichment model in shale reservoirs of Chang73 Member. The results indicate that the semi-deep to deep lacustrine shale in Chang73 Member in the sedimentary period has great potential of shale gas，with a high abundance of organic matter，large thickness，and good continuity，and the most organic matter is Ⅱ1 type. Organic matter is widely developed in thick layered shale rocks and enriched along sedimentary laminae. Affected by the Indosinian movement，the basement subsides intensively during Chang73 Member sedimentary period，which forms a large-scale sedimentary center and expands the accommodation space of the lake basin. Moreover，a humid and semi-arid climate is favorable for nutrient minerals to enter the lake basin and promote aquatic organism accumulation，and volcanic events also lead to eutrophication of water bodies and improved organic matter productivity. A long-term and stable anoxic and reductive environment provides key conditions for the preservation of sedimentary organic matter.
2022, 29(6):12-21.
DOI: 10.13673/j.cnki.cn37-1359/te.202204044
Abstract:
Recently，a number of drilling wells in the southeast Sichuan Basin have good oil and gas display in eyeballshaped limestones in the First Member of the Middle Permian of Maokou Formation（Mao1），but the genetic mechanism of the eyeball-shaped limestone has been controversial. Based on the observation of key drilling cores and field outcrops，as well as thin sections of rocks，scanning electron microscopy and microelement analysis，the characteristics and genetic mechanism of the eyeball-shaped limestones are explored，combined with the regional geological background. The results show that the eyeball-shaped limestones of Mao1 in the southeastern Sichuan Basin develop curl deformation structure，liquefied diapir，liquefied veins，hydrothermal veins，and biological shell convex-down，which have the characteristics of earthquake vibration modification. In addition，eyeball-shaped limestones are mainly composed of calcite，quartz, dolomite，talc，pyrite and organic matter. Talc exists as metasomatic bioclasts or in the form of star points, agglomerates，fibrous radiations and rock flowage. The microelement analysis results indicate that the“eyelids”were formed in a more anoxic environ ment than the“eyeballs”，which are both influenced by volcanic activities during the deposition period. The Mao1 eyeball shaped limestones were formed through seismic activities and deposition-diagenesis under the geological background of the Emeishan Large Igneous Province. Seismic activities could cause turbulent instantaneous water flow and intermittently destroy steady carbonate deposition conditions，which resulted in different mixing patterns of different components，leading to differences in composition and occurrence of deposits, and thus the eyeball-shaped limestones with special sedimentary structures were formed.
Recently，a number of drilling wells in the southeast Sichuan Basin have good oil and gas display in eyeballshaped limestones in the First Member of the Middle Permian of Maokou Formation（Mao1），but the genetic mechanism of the eyeball-shaped limestone has been controversial. Based on the observation of key drilling cores and field outcrops，as well as thin sections of rocks，scanning electron microscopy and microelement analysis，the characteristics and genetic mechanism of the eyeball-shaped limestones are explored，combined with the regional geological background. The results show that the eyeball-shaped limestones of Mao1 in the southeastern Sichuan Basin develop curl deformation structure，liquefied diapir，liquefied veins，hydrothermal veins，and biological shell convex-down，which have the characteristics of earthquake vibration modification. In addition，eyeball-shaped limestones are mainly composed of calcite，quartz, dolomite，talc，pyrite and organic matter. Talc exists as metasomatic bioclasts or in the form of star points, agglomerates，fibrous radiations and rock flowage. The microelement analysis results indicate that the“eyelids”were formed in a more anoxic environ ment than the“eyeballs”，which are both influenced by volcanic activities during the deposition period. The Mao1 eyeball shaped limestones were formed through seismic activities and deposition-diagenesis under the geological background of the Emeishan Large Igneous Province. Seismic activities could cause turbulent instantaneous water flow and intermittently destroy steady carbonate deposition conditions，which resulted in different mixing patterns of different components，leading to differences in composition and occurrence of deposits, and thus the eyeball-shaped limestones with special sedimentary structures were formed.
2022, 29(6):22-30.
DOI: 10.13673/j.cnki.cn37-1359/te.202109036
Abstract:
The complex micropore structures of tight sandstone reservoirs leads to an unclear understanding of pore space distribution and flow mechanism. Accordingly，taking the high-temperature，high-pressure，and ultra-low permeability tight sandstone reservoir at Ledong 10 area in Yinggehai Basin as an example，the pore space characteristicss of tight sandstone reservoirs with image analysis techniques such as 3D high-precision micro CT scanning and nano electron microscope scanning were quantitatively characterized in this paper. A two-scale 3D pore structure model based on digital cores was constructed and the flow mechanism of tight sandstone reservoirs based on the two-scale pore coupling flow simulation was determined. The results show as following：①The tight sandstone reservoir at Ledong10 area mainly develops three scale ranges of pores，which are respectively 0.070-3 μm，3-40 μm，and 40-300 μm. ②In the micropore scale dominated by feldspar dissolved pores and rock debris intergranular pores，the difference between pore and throat radius is small. The flow space is composed of micropores and throats，which are characterized by small pores and small throats. The water phase permeability decreases rapidly in the process of gas-water two-phase flow. ③In the two-scale pore structure model composed of large intergranular dissolved pores，mold pores，and secondary scale pores，the flow model presents the characteristics of large pores and small throat，and the water phase permeability decreases slowly.
The complex micropore structures of tight sandstone reservoirs leads to an unclear understanding of pore space distribution and flow mechanism. Accordingly，taking the high-temperature，high-pressure，and ultra-low permeability tight sandstone reservoir at Ledong 10 area in Yinggehai Basin as an example，the pore space characteristicss of tight sandstone reservoirs with image analysis techniques such as 3D high-precision micro CT scanning and nano electron microscope scanning were quantitatively characterized in this paper. A two-scale 3D pore structure model based on digital cores was constructed and the flow mechanism of tight sandstone reservoirs based on the two-scale pore coupling flow simulation was determined. The results show as following：①The tight sandstone reservoir at Ledong10 area mainly develops three scale ranges of pores，which are respectively 0.070-3 μm，3-40 μm，and 40-300 μm. ②In the micropore scale dominated by feldspar dissolved pores and rock debris intergranular pores，the difference between pore and throat radius is small. The flow space is composed of micropores and throats，which are characterized by small pores and small throats. The water phase permeability decreases rapidly in the process of gas-water two-phase flow. ③In the two-scale pore structure model composed of large intergranular dissolved pores，mold pores，and secondary scale pores，the flow model presents the characteristics of large pores and small throat，and the water phase permeability decreases slowly.
2022, 29(6):31-38.
DOI: 10.13673/j.cnki.cn37-1359/te.202111012
Abstract:
Micromechanical properties of the shale play a key role in the drilling，completion，and fracturing of reservoirs.In this paper，the marine shale in Sichuan Basin and continental shale in Shiguai Basin of Inner Mongolia were studied by XRD，SEM，and indentation test. The results show that marine shale in Sichuan Basin is mainly composed of authigenic minerals such as quartz，calcite，dolomite，and pyrite，while continental shale is composed of exogenous minerals such as quartz，kaolinite，montmorillonite，and albite. The microscopic structure of marine shale is relatively compact，while the continental shale develops intergranular pores and the structure is relatively loose. The indentation test results show that the average Vickers hardness（Hv）of marine shale is above 2.43 kN/mm2；the rock stiffness is hard and stiff，and the breakdown pressure required for the reservoir is high. The average Hv of continental shale is 0.80 kN/mm2；the rock is relatively weak，and the breakdown pressure of the reservoir is low. Marine shale has a large indentation displacement difference in different directions and is prone to radiation fractures，indicating that the rock brittleness is significant. Continental shale has similar indentation displacement in different directions and is not prone to radiation fractures，indicating that the rock brittleness is relatively weak. Combined with the energy theory，low net fracture pressure is adopted in marine shale reservoir fracturing to reduce the fracture rebound in the later period，while high net fracture pressure can be considered in continental shale reservoir fracturing to ensure fracture residual width.
Micromechanical properties of the shale play a key role in the drilling，completion，and fracturing of reservoirs.In this paper，the marine shale in Sichuan Basin and continental shale in Shiguai Basin of Inner Mongolia were studied by XRD，SEM，and indentation test. The results show that marine shale in Sichuan Basin is mainly composed of authigenic minerals such as quartz，calcite，dolomite，and pyrite，while continental shale is composed of exogenous minerals such as quartz，kaolinite，montmorillonite，and albite. The microscopic structure of marine shale is relatively compact，while the continental shale develops intergranular pores and the structure is relatively loose. The indentation test results show that the average Vickers hardness（Hv）of marine shale is above 2.43 kN/mm2；the rock stiffness is hard and stiff，and the breakdown pressure required for the reservoir is high. The average Hv of continental shale is 0.80 kN/mm2；the rock is relatively weak，and the breakdown pressure of the reservoir is low. Marine shale has a large indentation displacement difference in different directions and is prone to radiation fractures，indicating that the rock brittleness is significant. Continental shale has similar indentation displacement in different directions and is not prone to radiation fractures，indicating that the rock brittleness is relatively weak. Combined with the energy theory，low net fracture pressure is adopted in marine shale reservoir fracturing to reduce the fracture rebound in the later period，while high net fracture pressure can be considered in continental shale reservoir fracturing to ensure fracture residual width.
2022, 29(6):39-48.
DOI: 10.13673/j.cnki.cn37-1359/te.202104033
Abstract:
By quantitative identification technology of well logging facies，this paper rapidly and efficiently identified sedimentary microfacies of a single well and fully compared the sedimentary micro-facies of Neogene Guantao Formation（Ng）in block LZ9 of Linfanjia Oilfield. Furthermore，the boundary of each sand body in the 6th Submember of the 4th Member of Neogene Guantao Formation（Ng46）was finely described through multi-parameter coupling analysis in terms of paleogeomorphy，seismic attributes，and plane distribution characteristics of oil and water. According to the fine description，Ng in block LZ9 belongs to fluvial facies sediments which mainly develop sedimentary microfacies of the channel，natural levee，crevasse splay，and flood plain. The course of the channel in Ng46 is NW-SE，and the sand bodies are widely developed in the channel. These sand bodies have a banding distribution and extend as far as 3-5 km，with a width of more than 600 m.The natural levee is intermittently distributed in a narrow band or pod structure on both sides of the channel，with a width of less than 100 m. The connectivity of sand bodies in the channel is positive，and the injection-production efficiency is high.However，the lateral connectivity of the natural levee reservoir is poor，and the injection-production efficiency is low.
By quantitative identification technology of well logging facies，this paper rapidly and efficiently identified sedimentary microfacies of a single well and fully compared the sedimentary micro-facies of Neogene Guantao Formation（Ng）in block LZ9 of Linfanjia Oilfield. Furthermore，the boundary of each sand body in the 6th Submember of the 4th Member of Neogene Guantao Formation（Ng46）was finely described through multi-parameter coupling analysis in terms of paleogeomorphy，seismic attributes，and plane distribution characteristics of oil and water. According to the fine description，Ng in block LZ9 belongs to fluvial facies sediments which mainly develop sedimentary microfacies of the channel，natural levee，crevasse splay，and flood plain. The course of the channel in Ng46 is NW-SE，and the sand bodies are widely developed in the channel. These sand bodies have a banding distribution and extend as far as 3-5 km，with a width of more than 600 m.The natural levee is intermittently distributed in a narrow band or pod structure on both sides of the channel，with a width of less than 100 m. The connectivity of sand bodies in the channel is positive，and the injection-production efficiency is high.However，the lateral connectivity of the natural levee reservoir is poor，and the injection-production efficiency is low.
2022, 29(6):49-57.
DOI: 10.13673/j.cnki.cn37-1359/te.202109017
Abstract:
Total organic carbon（TOC）is one of the indicators for evaluating the organic matter abundance and hydrocarbon generation potential of hydrocarbon source rock. In this paper，taking the cored well of shale oil reservoir in Niuzhuang Depression，Dongying Sag as an example，the TOC-related sensitive parameters were obtained through cross plots based on the experimental analysis of TOC from core and logging data. The conventional TOC calculation models for continental shale oil reservoir，namely the ΔlogR method and the multiple regression analysis method，were used to predict the TOC of well and lake facies shale oil reservoir in the study area，but the correlation and performance were not good. Therefore，this paper proposed combining machine learning models，i.e.，the principal component analysis（PCA）model and an improved convolutional neural network（CNN）model，to form the PCA-CNN model. In this model，the PCA model was employed to reduce the dimensions of data and remove redundant information and noise information，and then，the CNN model was used to predict the TOC of shale oil reservoir，which could improve sample data quality and prediction accuracy of TOC. The PCACNN model was applied to predict the TOC of six cored wells shale oil reservoir in Niuzhuang Depression，and the results reveal that for continental shale oil reservoir，the proposed model can accurately predict TOC，and the compliance rate is up to 96%.
Total organic carbon（TOC）is one of the indicators for evaluating the organic matter abundance and hydrocarbon generation potential of hydrocarbon source rock. In this paper，taking the cored well of shale oil reservoir in Niuzhuang Depression，Dongying Sag as an example，the TOC-related sensitive parameters were obtained through cross plots based on the experimental analysis of TOC from core and logging data. The conventional TOC calculation models for continental shale oil reservoir，namely the ΔlogR method and the multiple regression analysis method，were used to predict the TOC of well and lake facies shale oil reservoir in the study area，but the correlation and performance were not good. Therefore，this paper proposed combining machine learning models，i.e.，the principal component analysis（PCA）model and an improved convolutional neural network（CNN）model，to form the PCA-CNN model. In this model，the PCA model was employed to reduce the dimensions of data and remove redundant information and noise information，and then，the CNN model was used to predict the TOC of shale oil reservoir，which could improve sample data quality and prediction accuracy of TOC. The PCACNN model was applied to predict the TOC of six cored wells shale oil reservoir in Niuzhuang Depression，and the results reveal that for continental shale oil reservoir，the proposed model can accurately predict TOC，and the compliance rate is up to 96%.
2022, 29(6):58-66.
DOI: 10.13673/j.cnki.cn37-1359/te.202111016
Abstract:
Fault interpretation is one of the basic works of oil & gas exploration and development. In recent years，with its powerful data analysis ability，deep learning has provided a new technical tool for characterizing the spatial distribution of faults in detail. Its application relies on how to obtain a large number of reliable sample data. Compared with the most popular fault data from forward modeling samples at present，fault data from expert interpretation samples of actual data are not only subjective but also focus on target areas，with incomplete labels of fault samples. The improved loss function of incomplete labels of fault samples emphasizes interpreted areas in fault analysis，which improves the availability of fault data from expert interpretation samples. Through the enhancement processing of data from expert fault interpretation samples，the amount of effective sample data is increased. In addition，this paper designs and constructs a network structure of an automatic 3D fault identification method driven by data from expert interpretation samples and forward modeling samples，and it introduces a self-attention mechanism to improve the generalization ability and spatial feature analysis ability of the automatic 3D fault identification network model. Model tests and practical application show that the proposed automatic 3D fault identification method can analyze actual features of the fault development. The identification results are more in line with geological conditions and the accuracy is effectively improved，which verifies the reliability and practicality of this method.
Fault interpretation is one of the basic works of oil & gas exploration and development. In recent years，with its powerful data analysis ability，deep learning has provided a new technical tool for characterizing the spatial distribution of faults in detail. Its application relies on how to obtain a large number of reliable sample data. Compared with the most popular fault data from forward modeling samples at present，fault data from expert interpretation samples of actual data are not only subjective but also focus on target areas，with incomplete labels of fault samples. The improved loss function of incomplete labels of fault samples emphasizes interpreted areas in fault analysis，which improves the availability of fault data from expert interpretation samples. Through the enhancement processing of data from expert fault interpretation samples，the amount of effective sample data is increased. In addition，this paper designs and constructs a network structure of an automatic 3D fault identification method driven by data from expert interpretation samples and forward modeling samples，and it introduces a self-attention mechanism to improve the generalization ability and spatial feature analysis ability of the automatic 3D fault identification network model. Model tests and practical application show that the proposed automatic 3D fault identification method can analyze actual features of the fault development. The identification results are more in line with geological conditions and the accuracy is effectively improved，which verifies the reliability and practicality of this method.
2022, 29(6):67-76.
DOI: 10.13673/j.cnki.cn37-1359/te.202108009
Abstract:
The affecting factors of ultra-tight sandstone reservoir permeability are complex in the Third Member of Xujiahe Formation in Dayi structure of the southern Western Sichuan Depression. Through the analysis and calculation，it is found that the prediction accuracy is not ideal by the various classical permeability prediction models based on the capillary pressure curves，which has certain limitations. This paper analyzed the reasons for the prediction error of six classical models，selected characteristic parameters，and comprehensively considered multiple affecting factors of permeability such as pore throat size and pore throat distribution to improve prediction accuracy of permeability in ultra-tight sandstone reservoirs.On this basis，the method of leave-one-out cross-validation（LooCV）was used to determine the optimal number of latent variables in the models，and the method of partial least squares regression（PLSR）was employed to construct three prediction models for ultra-tight sandstone reservoir permeability，i. e.，Winland-r5（PLSR），Pittman（PLSR），and Swanson （PLSR）. In this way，the problems of the permeability prediction models based on the ordinary least squares（OLS）method can be effectively solved，such as the multicollinearity of many characteristic parameters and the inability of small samples to generalize models. The results reveal that the three permeability prediction models based on PLSR have strong generalization ability，high prediction accuracy，and good applicability in the ultra-tight sandstone reservoirs of the study area.
The affecting factors of ultra-tight sandstone reservoir permeability are complex in the Third Member of Xujiahe Formation in Dayi structure of the southern Western Sichuan Depression. Through the analysis and calculation，it is found that the prediction accuracy is not ideal by the various classical permeability prediction models based on the capillary pressure curves，which has certain limitations. This paper analyzed the reasons for the prediction error of six classical models，selected characteristic parameters，and comprehensively considered multiple affecting factors of permeability such as pore throat size and pore throat distribution to improve prediction accuracy of permeability in ultra-tight sandstone reservoirs.On this basis，the method of leave-one-out cross-validation（LooCV）was used to determine the optimal number of latent variables in the models，and the method of partial least squares regression（PLSR）was employed to construct three prediction models for ultra-tight sandstone reservoir permeability，i. e.，Winland-r5（PLSR），Pittman（PLSR），and Swanson （PLSR）. In this way，the problems of the permeability prediction models based on the ordinary least squares（OLS）method can be effectively solved，such as the multicollinearity of many characteristic parameters and the inability of small samples to generalize models. The results reveal that the three permeability prediction models based on PLSR have strong generalization ability，high prediction accuracy，and good applicability in the ultra-tight sandstone reservoirs of the study area.
LI Zhenquan
,
LI Dongbo
,
BING Shaoxian
,
XIAO Wu
,
ZHANG Haiyan
,
XU Yongchun
,
ZHENG Weibo
,
YANG Xiuli
2022, 29(6):77-84.
DOI: 10.13673/j.cnki.cn37-1359/te.202205007
Abstract:
As high-energy-consumption units，oil enterprises are requested to meet the dual requirements of efficient production and energy saving & carbon reduction. Thus，they urgently need to carry out energy optimization management and control and scientifically and rationally assign energy saving and consumption reduction tasks to oil production units. At present，the commonly used decomposition and allocation method of energy consumption quota is the method of unit consumption per ton of oil and gas. Following the historical trend of unit consumption per ton of oil and gas in oil production units，this method calculates the energy consumption scale for each oil production unit in combination with the deployment of development and production in the next year and decomposes and allocates the energy consumption quota roportionally.Although this method requires few parameters and is simple to operate，it follows the historical law and can neither reflect the difference in energy saving space of different oil production units nor indicate the impact of different reservoir conditions on energy consumption. In view of this，this paper proposes a simple，effective，and highly precise calculation method for reasonable energy consumption and consumption reduction potential of crude oil production systems with the help of reservoir numerical simulation，the mathematical statistical analysis of an oilfield, and grey correlation analysis. It can fully reflect the differences in energy consumption levels under different reservoir conditions. Further, the paper develops a decomposition and allocation method for energy consumption quota，which can provide reference and a basis for energy consumption management departments to allocate the energy consumption quota to oil production units scientifically and rationally.
As high-energy-consumption units，oil enterprises are requested to meet the dual requirements of efficient production and energy saving & carbon reduction. Thus，they urgently need to carry out energy optimization management and control and scientifically and rationally assign energy saving and consumption reduction tasks to oil production units. At present，the commonly used decomposition and allocation method of energy consumption quota is the method of unit consumption per ton of oil and gas. Following the historical trend of unit consumption per ton of oil and gas in oil production units，this method calculates the energy consumption scale for each oil production unit in combination with the deployment of development and production in the next year and decomposes and allocates the energy consumption quota roportionally.Although this method requires few parameters and is simple to operate，it follows the historical law and can neither reflect the difference in energy saving space of different oil production units nor indicate the impact of different reservoir conditions on energy consumption. In view of this，this paper proposes a simple，effective，and highly precise calculation method for reasonable energy consumption and consumption reduction potential of crude oil production systems with the help of reservoir numerical simulation，the mathematical statistical analysis of an oilfield, and grey correlation analysis. It can fully reflect the differences in energy consumption levels under different reservoir conditions. Further, the paper develops a decomposition and allocation method for energy consumption quota，which can provide reference and a basis for energy consumption management departments to allocate the energy consumption quota to oil production units scientifically and rationally.
2022, 29(6):85-94.
DOI: 10.13673/j.cnki.cn37-1359/te.202107002
Abstract:
Shunbei Oilfield contains four types of storage media（i.e.，caves，high-angle fractures，vugs，and rock matrix）.The vertical beads-on-string structure formed by caves and high-angle fractures in series is a common fracture-cavity connection pattern. During drilling，drilling break and mud loss are prone to occur. These complex geological and engineering factors make it difficult for traditional multiple media models to fit the measured well test data. This paper proposes a physical model with multiple cave regions and multiple fracture regions in connection in series to characterize the complex vertical beads-on-string structure. The cave regions only contain caves in which the fluids are assumed to obey free flow. The fracture regions contain high-angle fractures，vugs，and rock matrix in which the flow obeys Darcy’s law. On this basis，the paper constructs a well test model for the beads-on-string structure with a wellbore-cave connection，draws type curves，and conducts a parameter sensitivity analysis. The following results are obtained：the cave storage regime and linear flow regime are the typical flow stages of vertical beads-on-string structure；the caves and conventional multiple media can be distinguished by the slope of pressure derivative curves；the type curves under the influence of gravity show pressure response characteristics similar to a closed boundary，so the measures should be taken to reduce the influence of gravity for improving the development effect of the vertical beads-on-string structure. Finally，the proposed model is applied to interpret the representative wells in Shunbei Oilfield. Besides the conventional reservoir parameters，the parameters that cannot be interpreted by existing well test methods can also be obtained by inversion，such as equivalent cave radius and equivalent cave height.
Shunbei Oilfield contains four types of storage media（i.e.，caves，high-angle fractures，vugs，and rock matrix）.The vertical beads-on-string structure formed by caves and high-angle fractures in series is a common fracture-cavity connection pattern. During drilling，drilling break and mud loss are prone to occur. These complex geological and engineering factors make it difficult for traditional multiple media models to fit the measured well test data. This paper proposes a physical model with multiple cave regions and multiple fracture regions in connection in series to characterize the complex vertical beads-on-string structure. The cave regions only contain caves in which the fluids are assumed to obey free flow. The fracture regions contain high-angle fractures，vugs，and rock matrix in which the flow obeys Darcy’s law. On this basis，the paper constructs a well test model for the beads-on-string structure with a wellbore-cave connection，draws type curves，and conducts a parameter sensitivity analysis. The following results are obtained：the cave storage regime and linear flow regime are the typical flow stages of vertical beads-on-string structure；the caves and conventional multiple media can be distinguished by the slope of pressure derivative curves；the type curves under the influence of gravity show pressure response characteristics similar to a closed boundary，so the measures should be taken to reduce the influence of gravity for improving the development effect of the vertical beads-on-string structure. Finally，the proposed model is applied to interpret the representative wells in Shunbei Oilfield. Besides the conventional reservoir parameters，the parameters that cannot be interpreted by existing well test methods can also be obtained by inversion，such as equivalent cave radius and equivalent cave height.
ZHENG Songqing
,
KANG Zhijiang
,
CHENG Xiaojun
,
LI Xiaobo
,
ZHANG Shiliang
,
CUI Shuyue
,
JIANG Lin
2022, 29(6):95-104.
DOI: 10.13673/j.cnki.cn37-1359/te.202201022
Abstract:
Based on the waterflooding development practice of fracture-cavity carbonate reservoirs in Tahe Oilfield，this paper systematically study waterflooding characteristics with geology，geophysics，tracer test，and production performance data. In addition，the paper constructs low-efficiency waterflooding modes and puts forward technical measures to improve waterflooding technologies. The research results show that the waterflooding fracture-cavity carbonate reservoirs have three characteristics：the single response direction，the low utilization factor of water injection and the most waterflooding failure due to bottom water invasion；and there are three main types and 10 subtypes of the low-efficiency waterflooding modes including the low the percentage of reserves on hold under waterflooding，the low the percentage of producing reserves under waterflooding，and the low displacement efficiency. The measures to improve the waterflooding development are as follows：First，the percentage of reserves on hold under waterflooding could be increased by improving the well pattern，and connectivity based on constructing（or improving）the injection and production relationships around the connected fracture-cavity bodies（or groups）. Second，the percentage of producing reserves under waterflooding can be improved by profile control and flooding，optimizing the injection and production parameters，changing waterflooding direction，and changing water injection intensity. Third，the oil displacement efficiency can be enhanced by improving the properties of the rock and oil-water interface. Finally，the bottom water can be inhibited by improving the bottom hole pressure，blocking the water invasion channel，and reducing bottom water energy. At the same time，the various technologies should be comprehensively used to strengthen the accuracy of reservoir description and the efficiency of technology implementation.
Based on the waterflooding development practice of fracture-cavity carbonate reservoirs in Tahe Oilfield，this paper systematically study waterflooding characteristics with geology，geophysics，tracer test，and production performance data. In addition，the paper constructs low-efficiency waterflooding modes and puts forward technical measures to improve waterflooding technologies. The research results show that the waterflooding fracture-cavity carbonate reservoirs have three characteristics：the single response direction，the low utilization factor of water injection and the most waterflooding failure due to bottom water invasion；and there are three main types and 10 subtypes of the low-efficiency waterflooding modes including the low the percentage of reserves on hold under waterflooding，the low the percentage of producing reserves under waterflooding，and the low displacement efficiency. The measures to improve the waterflooding development are as follows：First，the percentage of reserves on hold under waterflooding could be increased by improving the well pattern，and connectivity based on constructing（or improving）the injection and production relationships around the connected fracture-cavity bodies（or groups）. Second，the percentage of producing reserves under waterflooding can be improved by profile control and flooding，optimizing the injection and production parameters，changing waterflooding direction，and changing water injection intensity. Third，the oil displacement efficiency can be enhanced by improving the properties of the rock and oil-water interface. Finally，the bottom water can be inhibited by improving the bottom hole pressure，blocking the water invasion channel，and reducing bottom water energy. At the same time，the various technologies should be comprehensively used to strengthen the accuracy of reservoir description and the efficiency of technology implementation.
12 Water flooding experiment and law of carbonate reservoir cores with different fracture occurrences
2022, 29(6):105-112.
DOI: 10.13673/j.cnki.cn37-1359/te.202111038
Abstract:
Carbonate reservoirs mostly develop fractures. The influence of different fracture occurrences on the characteristics and law of water flooding needs to be studied. Through the core displacement experiment，the water flooding law with different fracture occurrences was explored by using carbonate cores with five types of fracture occurrences. The results show that the core with horizontal through fractures has a three-stage production law，namely，synchronous production stage，near-fracture matrix production stage，and fracture channeling production stage. The water-free period and the high water-cut period are the main oil displacement stages of the core. The core with the through fractures has an early water breakthrough，but its anhydrous oil displacement efficiency and final oil displacement efficiency are low. As the fracture angles decrease，the relative permeability of oil（water）decreases（increases）rapidly. The residual oil saturation and the water phase relative permeability increase，and the two-phase area gradually narrows. Based on the Hagen-Poiseuille equation，the permeability calculation method that only considers fractures in the fractured core was proposed. The problem that the irreducible water saturation is hard to be unified was solved through experiments involving three aspects，and the liquid production increase time of actual fields was given，which provides theoretical guidance for the development of carbonate reservoirs.
Carbonate reservoirs mostly develop fractures. The influence of different fracture occurrences on the characteristics and law of water flooding needs to be studied. Through the core displacement experiment，the water flooding law with different fracture occurrences was explored by using carbonate cores with five types of fracture occurrences. The results show that the core with horizontal through fractures has a three-stage production law，namely，synchronous production stage，near-fracture matrix production stage，and fracture channeling production stage. The water-free period and the high water-cut period are the main oil displacement stages of the core. The core with the through fractures has an early water breakthrough，but its anhydrous oil displacement efficiency and final oil displacement efficiency are low. As the fracture angles decrease，the relative permeability of oil（water）decreases（increases）rapidly. The residual oil saturation and the water phase relative permeability increase，and the two-phase area gradually narrows. Based on the Hagen-Poiseuille equation，the permeability calculation method that only considers fractures in the fractured core was proposed. The problem that the irreducible water saturation is hard to be unified was solved through experiments involving three aspects，and the liquid production increase time of actual fields was given，which provides theoretical guidance for the development of carbonate reservoirs.
13 A new characterization method for predominant flow field of reservoirs based on oil-to-flux ratio
2022, 29(6):113-120.
DOI: 10.13673/j.cnki.cn37-1359/te.202111044
Abstract:
The predominant flow channels are the root cause of the plane waterflooding imbalance and low sweep coefficient of well patterns in medium and high water cut oilfields. To accurately locate the development positions of dominant flow channels in a reservoir and guide the subsequent stabilizing oil production & controlling water cut in the oilfield，by the time-varying numerical simulation technology of reservoirs，this paper proposed a new flow-field evaluation index，i.e.，“the oil-to-flux ratio（OFR）”，and a flow-field heterogeneity evaluation index，i.e.，“the heterogeneity coefficient of OFR”，from the perspective of oil displacement efficiency by water. According to the shapes of OFR characteristic curves in different water cut stages and the physical background，the flow-field flow area is divided into four levels to achieve the hierarchical evaluation of the reservoir flow field. The verification reveals that the predominant flow channel area of the flow field is completely consistent with the test results of tracers，which proves the reliability of the flow-field evaluation method by OFR. This method was used to evaluate the predominant flow field in the offshore BZ Oilfield of Bohai Sea，formulate the flow-field hierarchical control measures and policies，and guide the deployment of measures for profile control and water shut-off，as well as controlling water cut of horizontal wells. Upon application，the heterogeneity coefficient of OFR is reduced by 5.6%，which means the flow-field heterogeneity is significantly improved. This method realizes the quantitative characterization of the predominant flow channels in high water cut oilfields.
The predominant flow channels are the root cause of the plane waterflooding imbalance and low sweep coefficient of well patterns in medium and high water cut oilfields. To accurately locate the development positions of dominant flow channels in a reservoir and guide the subsequent stabilizing oil production & controlling water cut in the oilfield，by the time-varying numerical simulation technology of reservoirs，this paper proposed a new flow-field evaluation index，i.e.，“the oil-to-flux ratio（OFR）”，and a flow-field heterogeneity evaluation index，i.e.，“the heterogeneity coefficient of OFR”，from the perspective of oil displacement efficiency by water. According to the shapes of OFR characteristic curves in different water cut stages and the physical background，the flow-field flow area is divided into four levels to achieve the hierarchical evaluation of the reservoir flow field. The verification reveals that the predominant flow channel area of the flow field is completely consistent with the test results of tracers，which proves the reliability of the flow-field evaluation method by OFR. This method was used to evaluate the predominant flow field in the offshore BZ Oilfield of Bohai Sea，formulate the flow-field hierarchical control measures and policies，and guide the deployment of measures for profile control and water shut-off，as well as controlling water cut of horizontal wells. Upon application，the heterogeneity coefficient of OFR is reduced by 5.6%，which means the flow-field heterogeneity is significantly improved. This method realizes the quantitative characterization of the predominant flow channels in high water cut oilfields.
2022, 29(6):121-129.
DOI: 10.13673/j.cnki.cn37-1359/te.202111037
Abstract:
Most of the flooded layers in Chengdao oilfield are saline water flooded. Although the formation resistivity decreases monotonically with the increasing flooded degree，the relationship between the decline in formation resistivity and the flooding degree is extremely complex，and there is no effective method to identify the flooded layers and their flooding degree. Therefore，a prediction model of the flooded layer based on probabilistic neural network was proposed in this paper.Firstly，given the actual logging and test results of Chengdao Oilfield，the flooded degree was classified into five levels：unflooded，weak flooded，moderate flooded，strong flooded，and extra-strong flooded. The correlation analysis between logging characteristic parameters and flooding degree was carried out to select the characteristic parameters which could better reflect the flooding degree. Secondly，the extracted logging characteristic parameters and test results were employed to construct a learning sample library of the target probabilistic neural network model. Finally，the probabilistic neural network model was utilized to predict the flooded layers of the identified samples，and comparative analysis was conducted through the Adaboost algorithm that has good deep learning classification effects. The results show that the prediction accuracy of the water flooded layers is improved by10%，which improves the identification accuracy of the saline water flooded layers.
Most of the flooded layers in Chengdao oilfield are saline water flooded. Although the formation resistivity decreases monotonically with the increasing flooded degree，the relationship between the decline in formation resistivity and the flooding degree is extremely complex，and there is no effective method to identify the flooded layers and their flooding degree. Therefore，a prediction model of the flooded layer based on probabilistic neural network was proposed in this paper.Firstly，given the actual logging and test results of Chengdao Oilfield，the flooded degree was classified into five levels：unflooded，weak flooded，moderate flooded，strong flooded，and extra-strong flooded. The correlation analysis between logging characteristic parameters and flooding degree was carried out to select the characteristic parameters which could better reflect the flooding degree. Secondly，the extracted logging characteristic parameters and test results were employed to construct a learning sample library of the target probabilistic neural network model. Finally，the probabilistic neural network model was utilized to predict the flooded layers of the identified samples，and comparative analysis was conducted through the Adaboost algorithm that has good deep learning classification effects. The results show that the prediction accuracy of the water flooded layers is improved by10%，which improves the identification accuracy of the saline water flooded layers.
2022, 29(6):130-137.
DOI: 10.13673/j.cnki.cn37-1359/te.202201009
Abstract:
The ultimate recovery of the conventional waterflooding sandstone reservoir ranges from 35% to 50%. This paper illustrates the feasibility of further improving the displacement efficiency of waterflooding reservoirs at the extra-high water cut development stage based on previous laboratory experiments，field applications，and global oilfield development cases.The economically feasible ideas and methods including long-term and large pore volume（PV）waterflooding and low salinity waterflooding etc. for improving the displacement efficiency are discussed in waterflooding reservoirs after improving sweep efficiency measures，such as the cyclic waterflooding，shut-in old well sidetracking，upward and layered waterflooding in multiple layers，or new infill wells along fault planes. Laboratory experiments and field applications reveal that the wettability of sandstone reservoirs changes from the oil-wet to the water-wet，and the saturation of residual oil reduces after long-term waterflooding，which can improve the displacement efficiency. Mature oilfield development cases indicate that with favorable reservoir and fluid properties，the ultimate recovery can reach 70% when reservoirs with strong natural waterflooding are developed by natural energy，or that with weak natural energy are developed by waterflooding. It has been proven that technologies such as dump flooding，low salinity waterflooding，and injecting and producing through one well are economically feasible. A large number of developed wells and existing facilities in mature field provide a basis for improving the recovery at the extra-high water cut development stage. The application of long-term and large PV waterflooding that is economically feasible is expected to increase the ultimate recovery to 50%-70%.
The ultimate recovery of the conventional waterflooding sandstone reservoir ranges from 35% to 50%. This paper illustrates the feasibility of further improving the displacement efficiency of waterflooding reservoirs at the extra-high water cut development stage based on previous laboratory experiments，field applications，and global oilfield development cases.The economically feasible ideas and methods including long-term and large pore volume（PV）waterflooding and low salinity waterflooding etc. for improving the displacement efficiency are discussed in waterflooding reservoirs after improving sweep efficiency measures，such as the cyclic waterflooding，shut-in old well sidetracking，upward and layered waterflooding in multiple layers，or new infill wells along fault planes. Laboratory experiments and field applications reveal that the wettability of sandstone reservoirs changes from the oil-wet to the water-wet，and the saturation of residual oil reduces after long-term waterflooding，which can improve the displacement efficiency. Mature oilfield development cases indicate that with favorable reservoir and fluid properties，the ultimate recovery can reach 70% when reservoirs with strong natural waterflooding are developed by natural energy，or that with weak natural energy are developed by waterflooding. It has been proven that technologies such as dump flooding，low salinity waterflooding，and injecting and producing through one well are economically feasible. A large number of developed wells and existing facilities in mature field provide a basis for improving the recovery at the extra-high water cut development stage. The application of long-term and large PV waterflooding that is economically feasible is expected to increase the ultimate recovery to 50%-70%.
LI Chunlei
,
CAO Xiaopeng
,
ZHANG Linfeng
,
JIANG Xingxing
,
LIU Jiantao
,
JIN Caixia
,
WANG Feng
,
YANG Heshan
2022, 29(6):138-142.
DOI: 10.13673/j.cnki.cn37-1359/te.202106039
Abstract:
The relative permeability curve is an important basic datum in oil and gas field development research. The traditional experimental method is expensive and time-consuming，and the relative permeability curve obtained by a few test samples is difficult to represent the characteristics of the whole reservoir. The results from the empirical formula method have low precision and large error. To obtain the relative permeability curves of the water-flooding reservoir in real time and accurately，this paper utilizes machine learning algorithms for simulation and prediction. The simulation sample set of the water-flooding reservoir relative permeability curves is constructed by analyzing the sensitivity of logging parameters and integrating the data of the relative permeability curves. On this basis，the machine learning algorithm is selected to optimize the geological factor constraint and the curve endpoint constraint，and the intelligent visualization generation of the relative permeability curves is realized. The results show that this method can realize the prediction of the relative permeability curves for each well and each section，and the prediction accuracy is more than 90%. It can accurately reflect the flow characteristics of reservoir and the variation law of reservoir permeability，possessing high practical application value and a good prospect of popularization and application.
The relative permeability curve is an important basic datum in oil and gas field development research. The traditional experimental method is expensive and time-consuming，and the relative permeability curve obtained by a few test samples is difficult to represent the characteristics of the whole reservoir. The results from the empirical formula method have low precision and large error. To obtain the relative permeability curves of the water-flooding reservoir in real time and accurately，this paper utilizes machine learning algorithms for simulation and prediction. The simulation sample set of the water-flooding reservoir relative permeability curves is constructed by analyzing the sensitivity of logging parameters and integrating the data of the relative permeability curves. On this basis，the machine learning algorithm is selected to optimize the geological factor constraint and the curve endpoint constraint，and the intelligent visualization generation of the relative permeability curves is realized. The results show that this method can realize the prediction of the relative permeability curves for each well and each section，and the prediction accuracy is more than 90%. It can accurately reflect the flow characteristics of reservoir and the variation law of reservoir permeability，possessing high practical application value and a good prospect of popularization and application.
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