In the past, most of the studies for compressional velocities are based on experimental measurements, which lack the support of field data. The purpose of this study is to estimate the compressional velocities based o...In the past, most of the studies for compressional velocities are based on experimental measurements, which lack the support of field data. The purpose of this study is to estimate the compressional velocities based on well log data of delta front subfacies of Lower Tertiary ages of Ji-Dong oil field, China. At initial stage, we have chosen the well log parameters (effect factors) which strongly influence on compressional velocities and established a new modified equation for compressional velocities, which is based on these effect factors. Then Gardner, De-hua Han and this newly established equation were utilized to calculate the compressional velocities in each well. Finally, Least-square regression was carried out to check the fitting of each equation. Regression results clearly indicate that our purposed equation shows better fitting as compared to Gardner and De-hua Han equations.展开更多
It is always significant for assessing and evaluation of oil bearing layers, especially for well logging data processing and interpretation of non marine oil beds to get more accurate physical properties in thin and i...It is always significant for assessing and evaluation of oil bearing layers, especially for well logging data processing and interpretation of non marine oil beds to get more accurate physical properties in thin and inter thin layers. This paper presents a definition of measures and the measure presents power law relation with the corresponded scale described by fractal theory. Thus, logging curves can be reconstructed according to this power law relation. This method uses the local structure nearby concurrent points to compensate the average effect of logging probes and measurement errors. As an example, deep and medium induced conductivity (IMPH and IDPH) curves in ODP Leg 127 Hole 797C are reconstructed or corrected. Corrected curves are with less adjacent effects through comparison of corrected curves with original one. And also, the power spectra of corrected well logging curve are abounding with more resolution components than the original one. Thus, fractal correction method makes the well logging more resoluble for thin beds.展开更多
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 resp...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
It is very difficult to discriminate natural fractures using conventional well log data, especially for most of the matured oilfields in China, because the raw data were acquired with relatively obsolete tools. The ra...It is very difficult to discriminate natural fractures using conventional well log data, especially for most of the matured oilfields in China, because the raw data were acquired with relatively obsolete tools. The raw data include only GR and SP curves, indicative of lithology, AC curves, used to calculate the porosity of the formation, and a set of logging curves from various electrode length resistivity by laterolog. On the other hand, these oilfields usually have a large amount of core data which directly display the characteristics of the formation, and enough information of injection and production. This paper describes an approach through which logging curves are calibrated in terms of the raw data, and then a prototype model of natural fractures is established based on the investigation of core data from 43 wells, totaling 4 000 m in length. A computer program has been developed according to this method. Through analysis and comparison of the features of logging curves, this paper proposes a new concept, the well logging curve unit. By strictly depicting its shape through mathematical methods, the natural facture can be discriminated. This work also suggests an equation to estimate the probability of fracture occurrence, and finally other fracture parameters are calculated using some experimental expressions. With this methodology, logging curves from 100 wells were interpreted, the results of which agree with core data and field information.展开更多
This paper introduces briefly the tasks and characteristics of China Continent Science Drilling (CCSD) Well Logging Engineering, the logging methods measured with CCSD, the quality control of original logging informat...This paper introduces briefly the tasks and characteristics of China Continent Science Drilling (CCSD) Well Logging Engineering, the logging methods measured with CCSD, the quality control of original logging information, the logging plan of CCSD, the logging engineering management of CCSD, the logging interpretation and the results and reports made with CCSD.展开更多
Electromagnetic Computer Tomography (ECT) is a method to probe the interior of an inhomogeneous medium via surface measurement in a non-linear way. Due to the great differences in conductivity and permittivity between...Electromagnetic Computer Tomography (ECT) is a method to probe the interior of an inhomogeneous medium via surface measurement in a non-linear way. Due to the great differences in conductivity and permittivity between oil and water in the well, Electromagnetic Tomography Well Logging (ETWL), a new flow imaging measurement system, is proposed to describe the distribution and movement of oil/water two-phase flow in the well by scanning the detected region and applying a suitable data processing algorithm. The results of the numerical simulation and physical modeling show that the system could provide a clear image of the flow profile.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
October oil field is one of the largest hydrocarbon-bearing fields which produces oil from the sand section of the Lower Miocene Asl Formation. Two marl (Asl Marl) and shale (Hawara Formation) sections of possible sou...October oil field is one of the largest hydrocarbon-bearing fields which produces oil from the sand section of the Lower Miocene Asl Formation. Two marl (Asl Marl) and shale (Hawara Formation) sections of possible source enrichment are detected above and below this oil sand section, respectively. This study aims to identify the content of the total organic carbon based on the density log and a combination technique of the resistivity and porosity logs (Δlog R Technique). The available geochemical analyses are used to calibrate the constants of the TOC and the level of maturity (LOM) used in the (Δlog R Technique). The geochemical-based LOM is found as 9.0 and the calibrated constants of the Asl Marl and Hawara Formation are found as 11.68, 3.88 and 8.77, 2.80, respectively. Fair to good TOC% content values (0.88 to 1.85) were recorded for Asl Marl section in the majority of the studied wells, while less than 0.5% is recorded for the Hawara Formation. The lateral distribution maps show that most of the TOC% enrichments are concentrated at central and eastern parts of the study area, providing a good source for the hydrocarbons encountered in the underlying Asl Sand section.展开更多
To supplement missing logging information without increasing economic cost, a machine learning method to generate synthetic well logs from the existing log data was presented, and the experimental verification and app...To supplement missing logging information without increasing economic cost, a machine learning method to generate synthetic well logs from the existing log data was presented, and the experimental verification and application effect analysis were carried out. Since the traditional Fully Connected Neural Network(FCNN) is incapable of preserving spatial dependency, the Long Short-Term Memory(LSTM) network, which is a kind of Recurrent Neural Network(RNN), was utilized to establish a method for log reconstruction. By this method, synthetic logs can be generated from series of input log data with consideration of variation trend and context information with depth. Besides, a cascaded LSTM was proposed by combining the standard LSTM with a cascade system. Testing through real well log data shows that: the results from the LSTM are of higher accuracy than the traditional FCNN; the cascaded LSTM is more suitable for the problem with multiple series data; the machine learning method proposed provides an accurate and cost effective way for synthetic well log generation.展开更多
The source rock model used in this project was developed by French Petroleum Research Institute. The total organic carbon content was estimated primarily and directly by using continuous conventional logging curves (s...The source rock model used in this project was developed by French Petroleum Research Institute. The total organic carbon content was estimated primarily and directly by using continuous conventional logging curves (such as sonic and resistivity curves), which are calibrated through the laboratory analysis data of organic carbon of cores, cuttings or sidewall cores. Regional evaluations have been carried out in downwarping basins abroad. The Haila′er Basin is a faulted basin and the evaluation of such a basin is a new subject. On the basis of a regional evaluation method for the downwarping basins, a new method suitable to faulted basins was developed. The effect is satisfactory when this new method is applied to the Wu′erxun Sag and the Bei′er Sag.展开更多
Hydrocarbon reservoir beds have been delineated using direct hydrocarbon indicator on seismic sections as well as well logs data in X field, Onshore Niger Delta. The research methodology involved horizon interpretatio...Hydrocarbon reservoir beds have been delineated using direct hydrocarbon indicator on seismic sections as well as well logs data in X field, Onshore Niger Delta. The research methodology involved horizon interpretation to produce sub-surface structure map. Geophysical well log signatures were employed in identifying hydrocarbon bearing sand. The well-to-seismic tie revealed that the reservoir tied directly with hydrocarbon indicator (bright spot) on the seismic sections. The major structure responsible for the hydrocarbon entrapment is anticline. The crest of the anticline from the depth structural map occurs at 3450 metres.展开更多
The method of sedimentary cycle division is studied based on comprehensive research and activity analysis of well logging, combined with wavelet analysis and characteristics of stratigraphic cycle. Based on the method...The method of sedimentary cycle division is studied based on comprehensive research and activity analysis of well logging, combined with wavelet analysis and characteristics of stratigraphic cycle. Based on the method above, this paper divided stratigraphic cycles and finely classified the tratifigraphic by taking H1518 in HSS oilfield as an example. The result shows that sedimentary cycle can be divided effectively based on key stratum study, activity and wavelet analysis of well log, and the research of sedimentary cycle characteristics. H1 formation can be divided into 1 sand group, 3 sand layers and 7 single layers.展开更多
A complete set of well logs was used to study the sedimentology, structural and depositional environments of the subsurface Cretaceous rocks of northern Sinai, as a promising hydrocarbon province in Egypt. The sedimen...A complete set of well logs was used to study the sedimentology, structural and depositional environments of the subsurface Cretaceous rocks of northern Sinai, as a promising hydrocarbon province in Egypt. The sedimentological interpretations of well logs show sedimentary sequence of the Early Cretaceous, represented by the Neocomian, Aptian and Albian, which is composed mainly of shales and marls with minor carbonate and sandstone intercalations. Based on the Th/K ratios, the argillaceous sediments are composed of illite, montmorillonite and micas with little amounts of glauconite and chlorite. The environmental interpretations revealed sedimentological environments vary from estuarine to lagoonal and backreef of the Barremian-Aptian rocks, and from continental to estuarine in the Aptian-Albian. By contrast, the Late Cretaceous rocks, represented by the Cenomanian, Turonian, Santonian and Maastrichtian, are mainly composed of carbonates with few shale and marl intercalations. This sequence was accumulated under lagoonal to neritic and bathyal environments. The structural interpretations of well logs show that the Cretaceous section attains a wide range of dip magnitudes and dispersed azimuths all over the study area, which is probably attributed to tectonic and sedimentological processes. The inherited structural complexities indicate possible rejuvenations along old fault planes and rotation of the faulted blocks.展开更多
Geochemical parameters are useful properties to enhance hydrocarbon exploration certainty.Though,attaining these parameters,for instance total organic carbon(TOC),volatile and residual hydrocarbon(S1&S2)is a chall...Geochemical parameters are useful properties to enhance hydrocarbon exploration certainty.Though,attaining these parameters,for instance total organic carbon(TOC),volatile and residual hydrocarbon(S1&S2)is a challenge for geologists due to the high cost and time consumption.Therefore,addressing this issue has become an interesting subject for many researchers.As a result,on the ground of conventional well logs,vast kinds of methods,for example,back propagation artificial neural network(BPANN),have been introduced to solve this problem.Implementing these kinds of methods brings scientists tremendous amounts of information related to the richness of organic matter in a meantime.However,the precision of the aforementioned method is inadequate and BPANN is affected negatively by local optimum.Therefore,current study cope with this issue and alleviate the uncertainty,Least Squares Support Vector Machine(LSSVM)and Adaptive-Neuro Fuzzy Inference System(ANFIS)algorithms cooperating with the particle swarm optimization(PSO)were suggested as a suitable method to increase the precision of estimating geochemical factors.The data bank for this research was attained from available sources of Shahejie formation from Bohai bay basin located in China,which consists of geochemical and well logging information.Outputs of this study illustrated that ANFIS-PSO and LSSVMPSO have a great ability to estimate geochemical parameters.The values of R^(2) obtained for these two models in order to predict the output parameters of TOC,S_(1) and S_(2) are equal to 0.6846&0.785,0.6864&0.778,and 0.7343&0.8128,respectively.The statistical comparison between these models shows that LSSVM-PSO shows a better performance compared to another model.Also,a new attempt was implemented to evaluate the impacts of input parameters on the outputs and the results of sensitivity analysis suggest that transit interval time had the greatest effect on the output parameters.展开更多
The authors applied a the combination of Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT) methods to gamma ray well-log data from the Q3, G1 and D2 wells. This high-resolution stratigraphic study wa...The authors applied a the combination of Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT) methods to gamma ray well-log data from the Q3, G1 and D2 wells. This high-resolution stratigraphic study was based on Milankovitch's orbital cycle theory. It was found that the CWT scale factors, ‘a,’ of 12, 24 and 60 match the ratios of the periodicities of precession, obliquity and eccentricity very well. Nine intervals of the Permo-carboniferous strata were recognized to have Milankovitch cycles in them. For example, section A of well Q3 has 29 precession cycles, 15 obliquity cycles and 7 short eccentricity cycles. The wavelengths are 2.7, 4.4 and 7.8 m for precession, obliquity and eccentricity, respectively. Important geological parameters such as the stratigraphic completeness and the accumulation rate were also estimated. These results provide basic information for further cyclostratigraphic correlation studies in the area. They are of great significance for the study of ancient and future climate change.展开更多
The lithologies of the Chinese Continental Scientific Drilling main hole (CCSD-MH) are mainly comprised of orthogneiss,paragneiss,eclogite,amphibolite,and ultramafic rocks.The statistical results of logs of CCSD-MH in...The lithologies of the Chinese Continental Scientific Drilling main hole (CCSD-MH) are mainly comprised of orthogneiss,paragneiss,eclogite,amphibolite,and ultramafic rocks.The statistical results of logs of CCSD-MH indicate that ultramafic rocks are characterized by very high CNL (neutron log) and very low GR (gamma ray log) and RD (resistivity log);eclogites are characterized by high DEN (density),VP (P-wave velocity) and PE (photoelectric absorption capture cross section);orthogneiss and paragneiss are characterized by high GR,U (uranium content),Th (thorium content),K (potassium content) and RD,and low DEN,PE,and CNL;logging values of amphibolite are between the logging values of eclogites and paragneiss.In addition,the logs could reflect the degree of retrograde metamorphism of eclogites.The upper section (100-2 000 m) shows higher DEN,PE,VP,and lower GR,U,Th,K,RD than the lower section (2 000-5 000 m).Most logs of the upper section are more fluctuant than those of the lower section.This indicates that the upper section has more heterogeneities than the lower section.The cross plots of logs indicate that DEN,GR,K,and CNL are more powerful in identifying ultrahigh pressure metamorphic (UHPM) rocks at the CCSD-MH.GR value of the rocks from CCSD-MH shows obviously an increasing trend from ultramafic rock (the most mafic rocks at CCSD-MH) to orthogneiss (the most acid rocks at CCSD-MH).On the contrary,DEN value decreases from the ultramafic rock to the orthogneiss.CNL log is a good indicator of the content of structure water in crystalline rocks.展开更多
文摘In the past, most of the studies for compressional velocities are based on experimental measurements, which lack the support of field data. The purpose of this study is to estimate the compressional velocities based on well log data of delta front subfacies of Lower Tertiary ages of Ji-Dong oil field, China. At initial stage, we have chosen the well log parameters (effect factors) which strongly influence on compressional velocities and established a new modified equation for compressional velocities, which is based on these effect factors. Then Gardner, De-hua Han and this newly established equation were utilized to calculate the compressional velocities in each well. Finally, Least-square regression was carried out to check the fitting of each equation. Regression results clearly indicate that our purposed equation shows better fitting as compared to Gardner and De-hua Han equations.
文摘It is always significant for assessing and evaluation of oil bearing layers, especially for well logging data processing and interpretation of non marine oil beds to get more accurate physical properties in thin and inter thin layers. This paper presents a definition of measures and the measure presents power law relation with the corresponded scale described by fractal theory. Thus, logging curves can be reconstructed according to this power law relation. This method uses the local structure nearby concurrent points to compensate the average effect of logging probes and measurement errors. As an example, deep and medium induced conductivity (IMPH and IDPH) curves in ODP Leg 127 Hole 797C are reconstructed or corrected. Corrected curves are with less adjacent effects through comparison of corrected curves with original one. And also, the power spectra of corrected well logging curve are abounding with more resolution components than the original one. Thus, fractal correction method makes the well logging more resoluble for thin beds.
基金Project supported by National Natural Science Foundation of China （Grant Nos 10534040 and 10272038） and Doctorate Foundation of the State Education Ministry of China （Grant Nos 20040183045 and 20030183052）.
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Supported by the National Basic Research Program of China （2009CB219603, 2010CB226800） the National Natural Science Foundation of China （40874071, 40672104）
文摘It is very difficult to discriminate natural fractures using conventional well log data, especially for most of the matured oilfields in China, because the raw data were acquired with relatively obsolete tools. The raw data include only GR and SP curves, indicative of lithology, AC curves, used to calculate the porosity of the formation, and a set of logging curves from various electrode length resistivity by laterolog. On the other hand, these oilfields usually have a large amount of core data which directly display the characteristics of the formation, and enough information of injection and production. This paper describes an approach through which logging curves are calibrated in terms of the raw data, and then a prototype model of natural fractures is established based on the investigation of core data from 43 wells, totaling 4 000 m in length. A computer program has been developed according to this method. Through analysis and comparison of the features of logging curves, this paper proposes a new concept, the well logging curve unit. By strictly depicting its shape through mathematical methods, the natural facture can be discriminated. This work also suggests an equation to estimate the probability of fracture occurrence, and finally other fracture parameters are calculated using some experimental expressions. With this methodology, logging curves from 100 wells were interpreted, the results of which agree with core data and field information.
文摘This paper introduces briefly the tasks and characteristics of China Continent Science Drilling (CCSD) Well Logging Engineering, the logging methods measured with CCSD, the quality control of original logging information, the logging plan of CCSD, the logging engineering management of CCSD, the logging interpretation and the results and reports made with CCSD.
基金This work was supported by the National Natural Science Foundation of China(60472019).
文摘Electromagnetic Computer Tomography (ECT) is a method to probe the interior of an inhomogeneous medium via surface measurement in a non-linear way. Due to the great differences in conductivity and permittivity between oil and water in the well, Electromagnetic Tomography Well Logging (ETWL), a new flow imaging measurement system, is proposed to describe the distribution and movement of oil/water two-phase flow in the well by scanning the detected region and applying a suitable data processing algorithm. The results of the numerical simulation and physical modeling show that the system could provide a clear image of the flow profile.
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.
文摘October oil field is one of the largest hydrocarbon-bearing fields which produces oil from the sand section of the Lower Miocene Asl Formation. Two marl (Asl Marl) and shale (Hawara Formation) sections of possible source enrichment are detected above and below this oil sand section, respectively. This study aims to identify the content of the total organic carbon based on the density log and a combination technique of the resistivity and porosity logs (Δlog R Technique). The available geochemical analyses are used to calibrate the constants of the TOC and the level of maturity (LOM) used in the (Δlog R Technique). The geochemical-based LOM is found as 9.0 and the calibrated constants of the Asl Marl and Hawara Formation are found as 11.68, 3.88 and 8.77, 2.80, respectively. Fair to good TOC% content values (0.88 to 1.85) were recorded for Asl Marl section in the majority of the studied wells, while less than 0.5% is recorded for the Hawara Formation. The lateral distribution maps show that most of the TOC% enrichments are concentrated at central and eastern parts of the study area, providing a good source for the hydrocarbons encountered in the underlying Asl Sand section.
基金Supported by the National Natural Science Foundation of China(U1663208,51520105005)the National Science and Technology Major Project of China(2017ZX05009-005,2016ZX05037-003)
文摘To supplement missing logging information without increasing economic cost, a machine learning method to generate synthetic well logs from the existing log data was presented, and the experimental verification and application effect analysis were carried out. Since the traditional Fully Connected Neural Network(FCNN) is incapable of preserving spatial dependency, the Long Short-Term Memory(LSTM) network, which is a kind of Recurrent Neural Network(RNN), was utilized to establish a method for log reconstruction. By this method, synthetic logs can be generated from series of input log data with consideration of variation trend and context information with depth. Besides, a cascaded LSTM was proposed by combining the standard LSTM with a cascade system. Testing through real well log data shows that: the results from the LSTM are of higher accuracy than the traditional FCNN; the cascaded LSTM is more suitable for the problem with multiple series data; the machine learning method proposed provides an accurate and cost effective way for synthetic well log generation.
文摘The source rock model used in this project was developed by French Petroleum Research Institute. The total organic carbon content was estimated primarily and directly by using continuous conventional logging curves (such as sonic and resistivity curves), which are calibrated through the laboratory analysis data of organic carbon of cores, cuttings or sidewall cores. Regional evaluations have been carried out in downwarping basins abroad. The Haila′er Basin is a faulted basin and the evaluation of such a basin is a new subject. On the basis of a regional evaluation method for the downwarping basins, a new method suitable to faulted basins was developed. The effect is satisfactory when this new method is applied to the Wu′erxun Sag and the Bei′er Sag.
文摘Hydrocarbon reservoir beds have been delineated using direct hydrocarbon indicator on seismic sections as well as well logs data in X field, Onshore Niger Delta. The research methodology involved horizon interpretation to produce sub-surface structure map. Geophysical well log signatures were employed in identifying hydrocarbon bearing sand. The well-to-seismic tie revealed that the reservoir tied directly with hydrocarbon indicator (bright spot) on the seismic sections. The major structure responsible for the hydrocarbon entrapment is anticline. The crest of the anticline from the depth structural map occurs at 3450 metres.
文摘The method of sedimentary cycle division is studied based on comprehensive research and activity analysis of well logging, combined with wavelet analysis and characteristics of stratigraphic cycle. Based on the method above, this paper divided stratigraphic cycles and finely classified the tratifigraphic by taking H1518 in HSS oilfield as an example. The result shows that sedimentary cycle can be divided effectively based on key stratum study, activity and wavelet analysis of well log, and the research of sedimentary cycle characteristics. H1 formation can be divided into 1 sand group, 3 sand layers and 7 single layers.
文摘A complete set of well logs was used to study the sedimentology, structural and depositional environments of the subsurface Cretaceous rocks of northern Sinai, as a promising hydrocarbon province in Egypt. The sedimentological interpretations of well logs show sedimentary sequence of the Early Cretaceous, represented by the Neocomian, Aptian and Albian, which is composed mainly of shales and marls with minor carbonate and sandstone intercalations. Based on the Th/K ratios, the argillaceous sediments are composed of illite, montmorillonite and micas with little amounts of glauconite and chlorite. The environmental interpretations revealed sedimentological environments vary from estuarine to lagoonal and backreef of the Barremian-Aptian rocks, and from continental to estuarine in the Aptian-Albian. By contrast, the Late Cretaceous rocks, represented by the Cenomanian, Turonian, Santonian and Maastrichtian, are mainly composed of carbonates with few shale and marl intercalations. This sequence was accumulated under lagoonal to neritic and bathyal environments. The structural interpretations of well logs show that the Cretaceous section attains a wide range of dip magnitudes and dispersed azimuths all over the study area, which is probably attributed to tectonic and sedimentological processes. The inherited structural complexities indicate possible rejuvenations along old fault planes and rotation of the faulted blocks.
基金This work was supported by Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry （2006331）, China Postdoctoral Science Foundation （20070411106） and Open Fund of Key Laboratory of Depositional Mineralization ＆ Sedimentary Mineral, Shandong Province （DMSM200802）.
文摘Geochemical parameters are useful properties to enhance hydrocarbon exploration certainty.Though,attaining these parameters,for instance total organic carbon(TOC),volatile and residual hydrocarbon(S1&S2)is a challenge for geologists due to the high cost and time consumption.Therefore,addressing this issue has become an interesting subject for many researchers.As a result,on the ground of conventional well logs,vast kinds of methods,for example,back propagation artificial neural network(BPANN),have been introduced to solve this problem.Implementing these kinds of methods brings scientists tremendous amounts of information related to the richness of organic matter in a meantime.However,the precision of the aforementioned method is inadequate and BPANN is affected negatively by local optimum.Therefore,current study cope with this issue and alleviate the uncertainty,Least Squares Support Vector Machine(LSSVM)and Adaptive-Neuro Fuzzy Inference System(ANFIS)algorithms cooperating with the particle swarm optimization(PSO)were suggested as a suitable method to increase the precision of estimating geochemical factors.The data bank for this research was attained from available sources of Shahejie formation from Bohai bay basin located in China,which consists of geochemical and well logging information.Outputs of this study illustrated that ANFIS-PSO and LSSVMPSO have a great ability to estimate geochemical parameters.The values of R^(2) obtained for these two models in order to predict the output parameters of TOC,S_(1) and S_(2) are equal to 0.6846&0.785,0.6864&0.778,and 0.7343&0.8128,respectively.The statistical comparison between these models shows that LSSVM-PSO shows a better performance compared to another model.Also,a new attempt was implemented to evaluate the impacts of input parameters on the outputs and the results of sensitivity analysis suggest that transit interval time had the greatest effect on the output parameters.
基金supported by the Project Sponsored by the Scientific Research Foundation for the Re-turned Overseas Chinese Scholars, State Education Ministry (2006331) National Basic Research Program of China (2003CB214608)
文摘The authors applied a the combination of Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT) methods to gamma ray well-log data from the Q3, G1 and D2 wells. This high-resolution stratigraphic study was based on Milankovitch's orbital cycle theory. It was found that the CWT scale factors, ‘a,’ of 12, 24 and 60 match the ratios of the periodicities of precession, obliquity and eccentricity very well. Nine intervals of the Permo-carboniferous strata were recognized to have Milankovitch cycles in them. For example, section A of well Q3 has 29 precession cycles, 15 obliquity cycles and 7 short eccentricity cycles. The wavelengths are 2.7, 4.4 and 7.8 m for precession, obliquity and eccentricity, respectively. Important geological parameters such as the stratigraphic completeness and the accumulation rate were also estimated. These results provide basic information for further cyclostratigraphic correlation studies in the area. They are of great significance for the study of ancient and future climate change.
基金supported by the Special Fund for Basic Scientific Research of Central Colleges (No. CUG090106)the National Basic Research Program of China (No. 2003CB716500)
文摘The lithologies of the Chinese Continental Scientific Drilling main hole (CCSD-MH) are mainly comprised of orthogneiss,paragneiss,eclogite,amphibolite,and ultramafic rocks.The statistical results of logs of CCSD-MH indicate that ultramafic rocks are characterized by very high CNL (neutron log) and very low GR (gamma ray log) and RD (resistivity log);eclogites are characterized by high DEN (density),VP (P-wave velocity) and PE (photoelectric absorption capture cross section);orthogneiss and paragneiss are characterized by high GR,U (uranium content),Th (thorium content),K (potassium content) and RD,and low DEN,PE,and CNL;logging values of amphibolite are between the logging values of eclogites and paragneiss.In addition,the logs could reflect the degree of retrograde metamorphism of eclogites.The upper section (100-2 000 m) shows higher DEN,PE,VP,and lower GR,U,Th,K,RD than the lower section (2 000-5 000 m).Most logs of the upper section are more fluctuant than those of the lower section.This indicates that the upper section has more heterogeneities than the lower section.The cross plots of logs indicate that DEN,GR,K,and CNL are more powerful in identifying ultrahigh pressure metamorphic (UHPM) rocks at the CCSD-MH.GR value of the rocks from CCSD-MH shows obviously an increasing trend from ultramafic rock (the most mafic rocks at CCSD-MH) to orthogneiss (the most acid rocks at CCSD-MH).On the contrary,DEN value decreases from the ultramafic rock to the orthogneiss.CNL log is a good indicator of the content of structure water in crystalline rocks.
