This paper presents an overview of petrophysical research and exploration achievements of low resistivity pay (LRP) zone by well logs in China. It includes geological characteristics and characteristics of well log ...This paper presents an overview of petrophysical research and exploration achievements of low resistivity pay (LRP) zone by well logs in China. It includes geological characteristics and characteristics of well log response of the low resistivity pay zones discovered and evaluated in recent years, as well as the problems in recognizing and evaluating low resistivity pay zones by well logs. The research areas mainly include the Neogene formations in the Bohai Bay Basin, the Triassic formations in the northern Tarim Basin and the Cretaceous formations in the Junggar Basin, The petrophysical research concerning recognition and evaluation of the low resistivity pays, based on their genetic types, is introduced in this paper.展开更多
In recent years, as the exploration practices extend into more complicated formations, conventional well log interpretation has often shown its inaccuracy and limitations in identifying hydrocarbons. The Permian Wuton...In recent years, as the exploration practices extend into more complicated formations, conventional well log interpretation has often shown its inaccuracy and limitations in identifying hydrocarbons. The Permian Wutonggou Formation hosts typical clastic reservoirs in the Eastern Junggar Basin. The sophisticated lithology characteristics cause complex pore structures and fluid properties. These all finally cause low well testing agreement rate using conventional methods. Eleven years' recent statistics show that 12 out of 15 water layers have been incorrectly identified as being oil or oil/water layers by conventional well log interpretation. This paper proposes a methodology called intelligent prediction and identification system (IPIS). Firstly, parameters reflecting lithological, petrophysical and electrical responses which are greatly related to reservoir fluids have been selected carefully. They are shale content (Vsh), numbered rock type (RN), porosity (φ), permeability (K), true resistivity (RT) and spontaneous-potential (SP). Secondly, Vsh, φ and K are predicted from well logs through artificial neural networks (ANNs). Finally, all the six parameters are input into a neuro-fuzzy inference machine (NFIM) to get fluids identification results. Eighteen new layers of 145.3 m effective thickness were examined by IPIS. There is full agreement with well testing results. This shows the system's accuracy and effectiveness.展开更多
In the early exploration of many oilfields,low-resistivity-low-contrast(LRLC)pay zones are easily overlooked due to the resistivity similarity to the water zones.Existing identification methods are model-driven and ca...In the early exploration of many oilfields,low-resistivity-low-contrast(LRLC)pay zones are easily overlooked due to the resistivity similarity to the water zones.Existing identification methods are model-driven and cannot yield satisfactory results when the causes of LRLC pay zones are complicated.In this study,after analyzing a large number of core samples,main causes of LRLC pay zones in the study area are discerned,which include complex distribution of formation water salinity,high irreducible water saturation due to micropores,and high shale volume.Moreover,different oil testing layers may have different causes of LRLC pay zones.As a result,in addition to the well log data of oil testing layers,well log data of adjacent shale layers are also added to the original dataset as reference data.The densitybased spatial clustering algorithm with noise(DBSCAN)is used to cluster the original dataset into 49 clusters.A new dataset is ultimately projected into a feature space with 49 dimensions.The new dataset and oil testing results are respectively treated as input and output to train the multi-layer perceptron(MLP).A total of 3192 samples are used for stratified 8-fold cross-validation,and the accuracy of the MLP is found to be 85.53%.展开更多
The Silk Road Economic Belt and the 21st-Century Maritime Silk Road Initiative, abbreviated as the Belt and Road Initiative, is a primary development strategy of China's future international cooperation. Especially, ...The Silk Road Economic Belt and the 21st-Century Maritime Silk Road Initiative, abbreviated as the Belt and Road Initiative, is a primary development strategy of China's future international cooperation. Especially, the energy resource cooperation, including oil and gas resources cooperation, is an important part of this initiative. The Belt and Road has undergone complicated geological evolution, and contains abundant mineral resources such as oil, gas, coal, uranium, iron, copper, gold and manganese ore resources. Among these, Africa holds 7.8% of the world's total proven oil reserves. The oil and gas resources in Africa are relatively concentrated, with an overall low exploration degree and small consumption demand. Nigeria and Libya contain the most abundant oil resources in Africa, accounting for 2.2% and 2.9% of the world's total reserves, respectively. Nigeria and Algeria hold the richest natural gas resources in Africa, occupying 2.8% and 2.4% of the world's total reserves, respectively. Africa's oil and gas resources are mainly concentrated in Egypt, Sultan and Western Sahara regions in the northern Africa, and the Gulf of Guinea, Niger River and Congo River area in the western Africa. The Russia--Central Asia area holds rich petroleum resources in Russia, Kazakhstan, Turkmenistan and Uzbekistan. The potential oil and gas areas include the West Siberia Basin, East Siberia Basin and sea continental shelf in Russia, the northern and central Caspian Basin in Kazakhstan, the right bank of the Amu-Darya Basin, the East Karakum uplift and the South Caspian Basin in Turkmenistan, and the Amu-Daria Basin, Fergana Basin, Afghan-Tajik Basin and North Ustyurt Basin in Uzbekistan. The Middle East oil and gas resources are mainly distributed in the Zagros foreland basin and Arabian continental margin basin, and the main oil-producing countries include Saudi Arabia, Iran and Iraq. The Asia Pacific region is a new oil and gas consumption center, with rapid growth of oil and gas demand. In 2012, this region consumed about 33.6% of the world's total oil consumption and 18.9% of the world's total natural gas consumption, which has been ranked the world's largest oil and gas consumption center. The oil and gas resources are concentrated in China, Indosinian, Malaysia, Australia and India. The abundant European proven crude oil reserves are in Norway, Britain and Denmark and also rich natural gas resources in Norway, Holland and Britain. Norway and Britain contain about 77.5% of European proven oil reserves, which accounts for only 0.9% of the world's proven reserves. The Europe includes main petroliferous basins of the Voring Basin, Anglo-Dutch Basin, Northwest German Basin, Northeast German-Polish Basin and Carpathian Basin. According to the analysis of source rocks, reservoir rocks, cap rocks and traps for the main petroliferous basins, the potential oil and gas prospecting targets in the Belt and Road are mainly the Zagros Basin and Arabic Platform in the Middle East, the East Barents Sea Basin and the East Siberia Basin in Russia-Central Asia, the Niger Delta Basin, East African rift system and the Australia Northwest Shelf. With the development of oil and gas theory and exploration technology, unconventional petroleum resources will play an increasingly important role in oil and gas industry.展开更多
Well control techniques are used in oil and gas drilling operations to control bottom hole pressure and avoid any fluid influx from formation to the well. These techniques are highly important near the pay zone in ter...Well control techniques are used in oil and gas drilling operations to control bottom hole pressure and avoid any fluid influx from formation to the well. These techniques are highly important near the pay zone in term of time. Controlling formation fluid pressure and thereby the formations behavior in a predictable fashion will help toward more optimized environmental friendly drilling operation. Time consumed to control the formation fluid pressure will range between few hours to many days. This paper discusses hydrostatic pressure distribution and changes near the pay zone for one oil blocks in Kurdistan, in the northern part of Iraq. Obtaining homogeneous increase in some drilling fluid properties will help the engineer to better interpret sampling of the lithological columns and reduce potential hole problems and operation time.展开更多
The main focus of study is to characterize lower and upper cretaceous carbonate deposits with Low Resistivity Pay, in Persian Gulf. Four oil reservoirs in the Cretaceous including the Zubair, Buwaib, Shuaiba and Khati...The main focus of study is to characterize lower and upper cretaceous carbonate deposits with Low Resistivity Pay, in Persian Gulf. Four oil reservoirs in the Cretaceous including the Zubair, Buwaib, Shuaiba and Khatiyah Formations of Southern fields have been analyzed. Here is a look at that to determine main factors on decreasing resistivity in pay zone. In some intervals resistivity responses reach less than 6 to 1 ohm·m. Significant hydrocarbon accumulations are “hidden” in low resistivity Pay zone, (LRPZ). LRPZ reservoirs have been found in some formations in Persian Gulf. Causes of LRPZ reservoirs on the basis of experimental analysis include clay-coated grains, carbonate with interstitial dispersed clay. On the other side Smectite and Kaolinite of main clays types have high CEC and greater impact on lowering resistivity. Micritization and Pyritization of digenetic process have noticeable impact on LRPZ. It is mentioned that Lønøy method applied to address pore throat sizes which contain Inter crystalline porosity, Chalky Limestone, Mudstone micro porosity. Pore systems are classified at class 2 and 3 Lucia and pore size varies from 0.5 to 4 micron. NMR Core and Log results show different pore size distribution. NMR core and MRIL results explain that decreasing of resistivity in pay zone is related to texture and grain size variation not being existence of moved water. Irreducible water estimate for this reservoir was between 30% and 50%. T2 cut off estimates, for defining irreducible water saturation, 115 ms.展开更多
基金Supported by CNPC Innovation Foundation,Research Projects of PetroChina,Xinjiang and Tarim Oil Companies
文摘This paper presents an overview of petrophysical research and exploration achievements of low resistivity pay (LRP) zone by well logs in China. It includes geological characteristics and characteristics of well log response of the low resistivity pay zones discovered and evaluated in recent years, as well as the problems in recognizing and evaluating low resistivity pay zones by well logs. The research areas mainly include the Neogene formations in the Bohai Bay Basin, the Triassic formations in the northern Tarim Basin and the Cretaceous formations in the Junggar Basin, The petrophysical research concerning recognition and evaluation of the low resistivity pays, based on their genetic types, is introduced in this paper.
基金financially supported by the National Science and Technology Major Demonstration Project 19 (2011ZX05062-008)
文摘In recent years, as the exploration practices extend into more complicated formations, conventional well log interpretation has often shown its inaccuracy and limitations in identifying hydrocarbons. The Permian Wutonggou Formation hosts typical clastic reservoirs in the Eastern Junggar Basin. The sophisticated lithology characteristics cause complex pore structures and fluid properties. These all finally cause low well testing agreement rate using conventional methods. Eleven years' recent statistics show that 12 out of 15 water layers have been incorrectly identified as being oil or oil/water layers by conventional well log interpretation. This paper proposes a methodology called intelligent prediction and identification system (IPIS). Firstly, parameters reflecting lithological, petrophysical and electrical responses which are greatly related to reservoir fluids have been selected carefully. They are shale content (Vsh), numbered rock type (RN), porosity (φ), permeability (K), true resistivity (RT) and spontaneous-potential (SP). Secondly, Vsh, φ and K are predicted from well logs through artificial neural networks (ANNs). Finally, all the six parameters are input into a neuro-fuzzy inference machine (NFIM) to get fluids identification results. Eighteen new layers of 145.3 m effective thickness were examined by IPIS. There is full agreement with well testing results. This shows the system's accuracy and effectiveness.
基金funded by the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX2020-03)
文摘In the early exploration of many oilfields,low-resistivity-low-contrast(LRLC)pay zones are easily overlooked due to the resistivity similarity to the water zones.Existing identification methods are model-driven and cannot yield satisfactory results when the causes of LRLC pay zones are complicated.In this study,after analyzing a large number of core samples,main causes of LRLC pay zones in the study area are discerned,which include complex distribution of formation water salinity,high irreducible water saturation due to micropores,and high shale volume.Moreover,different oil testing layers may have different causes of LRLC pay zones.As a result,in addition to the well log data of oil testing layers,well log data of adjacent shale layers are also added to the original dataset as reference data.The densitybased spatial clustering algorithm with noise(DBSCAN)is used to cluster the original dataset into 49 clusters.A new dataset is ultimately projected into a feature space with 49 dimensions.The new dataset and oil testing results are respectively treated as input and output to train the multi-layer perceptron(MLP).A total of 3192 samples are used for stratified 8-fold cross-validation,and the accuracy of the MLP is found to be 85.53%.
基金financially supported by the National Natural Science Foundation of China(grant No.41402219)
文摘The Silk Road Economic Belt and the 21st-Century Maritime Silk Road Initiative, abbreviated as the Belt and Road Initiative, is a primary development strategy of China's future international cooperation. Especially, the energy resource cooperation, including oil and gas resources cooperation, is an important part of this initiative. The Belt and Road has undergone complicated geological evolution, and contains abundant mineral resources such as oil, gas, coal, uranium, iron, copper, gold and manganese ore resources. Among these, Africa holds 7.8% of the world's total proven oil reserves. The oil and gas resources in Africa are relatively concentrated, with an overall low exploration degree and small consumption demand. Nigeria and Libya contain the most abundant oil resources in Africa, accounting for 2.2% and 2.9% of the world's total reserves, respectively. Nigeria and Algeria hold the richest natural gas resources in Africa, occupying 2.8% and 2.4% of the world's total reserves, respectively. Africa's oil and gas resources are mainly concentrated in Egypt, Sultan and Western Sahara regions in the northern Africa, and the Gulf of Guinea, Niger River and Congo River area in the western Africa. The Russia--Central Asia area holds rich petroleum resources in Russia, Kazakhstan, Turkmenistan and Uzbekistan. The potential oil and gas areas include the West Siberia Basin, East Siberia Basin and sea continental shelf in Russia, the northern and central Caspian Basin in Kazakhstan, the right bank of the Amu-Darya Basin, the East Karakum uplift and the South Caspian Basin in Turkmenistan, and the Amu-Daria Basin, Fergana Basin, Afghan-Tajik Basin and North Ustyurt Basin in Uzbekistan. The Middle East oil and gas resources are mainly distributed in the Zagros foreland basin and Arabian continental margin basin, and the main oil-producing countries include Saudi Arabia, Iran and Iraq. The Asia Pacific region is a new oil and gas consumption center, with rapid growth of oil and gas demand. In 2012, this region consumed about 33.6% of the world's total oil consumption and 18.9% of the world's total natural gas consumption, which has been ranked the world's largest oil and gas consumption center. The oil and gas resources are concentrated in China, Indosinian, Malaysia, Australia and India. The abundant European proven crude oil reserves are in Norway, Britain and Denmark and also rich natural gas resources in Norway, Holland and Britain. Norway and Britain contain about 77.5% of European proven oil reserves, which accounts for only 0.9% of the world's proven reserves. The Europe includes main petroliferous basins of the Voring Basin, Anglo-Dutch Basin, Northwest German Basin, Northeast German-Polish Basin and Carpathian Basin. According to the analysis of source rocks, reservoir rocks, cap rocks and traps for the main petroliferous basins, the potential oil and gas prospecting targets in the Belt and Road are mainly the Zagros Basin and Arabic Platform in the Middle East, the East Barents Sea Basin and the East Siberia Basin in Russia-Central Asia, the Niger Delta Basin, East African rift system and the Australia Northwest Shelf. With the development of oil and gas theory and exploration technology, unconventional petroleum resources will play an increasingly important role in oil and gas industry.
文摘Well control techniques are used in oil and gas drilling operations to control bottom hole pressure and avoid any fluid influx from formation to the well. These techniques are highly important near the pay zone in term of time. Controlling formation fluid pressure and thereby the formations behavior in a predictable fashion will help toward more optimized environmental friendly drilling operation. Time consumed to control the formation fluid pressure will range between few hours to many days. This paper discusses hydrostatic pressure distribution and changes near the pay zone for one oil blocks in Kurdistan, in the northern part of Iraq. Obtaining homogeneous increase in some drilling fluid properties will help the engineer to better interpret sampling of the lithological columns and reduce potential hole problems and operation time.
文摘The main focus of study is to characterize lower and upper cretaceous carbonate deposits with Low Resistivity Pay, in Persian Gulf. Four oil reservoirs in the Cretaceous including the Zubair, Buwaib, Shuaiba and Khatiyah Formations of Southern fields have been analyzed. Here is a look at that to determine main factors on decreasing resistivity in pay zone. In some intervals resistivity responses reach less than 6 to 1 ohm·m. Significant hydrocarbon accumulations are “hidden” in low resistivity Pay zone, (LRPZ). LRPZ reservoirs have been found in some formations in Persian Gulf. Causes of LRPZ reservoirs on the basis of experimental analysis include clay-coated grains, carbonate with interstitial dispersed clay. On the other side Smectite and Kaolinite of main clays types have high CEC and greater impact on lowering resistivity. Micritization and Pyritization of digenetic process have noticeable impact on LRPZ. It is mentioned that Lønøy method applied to address pore throat sizes which contain Inter crystalline porosity, Chalky Limestone, Mudstone micro porosity. Pore systems are classified at class 2 and 3 Lucia and pore size varies from 0.5 to 4 micron. NMR Core and Log results show different pore size distribution. NMR core and MRIL results explain that decreasing of resistivity in pay zone is related to texture and grain size variation not being existence of moved water. Irreducible water estimate for this reservoir was between 30% and 50%. T2 cut off estimates, for defining irreducible water saturation, 115 ms.