The TRU-Vision system,developed by Baker Hughes,analyzes the gas extracted from drilling mud to estimate the hydrocarbons composition in drilled rock formations.Several separation processes had been surveyed in order ...The TRU-Vision system,developed by Baker Hughes,analyzes the gas extracted from drilling mud to estimate the hydrocarbons composition in drilled rock formations.Several separation processes had been surveyed in order to enhance the gas extraction at the gas trap,namely,mechanical stirring,vacuum,air sparging,membrane separation processes,ultrasounds,and cyclones.Mechanical stirring devices(one propeller,one flat-blade turbine,and two baffles sets),a vacuum generator,and an air bubble generator were designed and assembled to increase the efficiency and the response stability of TRU-Vision system.展开更多
This paper presents a debugging system for multi-pole array acoustic logging （MPAL） tools. The debugging system proposed in this study can debug the MPAL tool system, sub-system and local electronics. In the test eq...This paper presents a debugging system for multi-pole array acoustic logging （MPAL） tools. The debugging system proposed in this study can debug the MPAL tool system, sub-system and local electronics. In the test equipment, we have used principal and subordinate structures, and interconnected the host computer and the front-end machine via Ethernet. The front-end machine is based on the ARM7 （advanced reduced instruction set computing （RISC） machine） technique, the processor of which runs an embedded operating system, namely, uClinux OS. We have analyzed the system telecommunication, human-machine interface circuit, transmitter mandrel interface circuit, receiver mandrel interface circuit, and board-level test interface circuit. The software used in the system consists of the embedded front-computer software and the host application software. We have explained in detail the flow chart of the boot loader in the embedded front-computer software. The host application software is composed of four application subroutines, which match with the functional modules of the system hardware. A net communication program based on the server^client mode is implemented by means of socket programming and multi-thread programming. Test results indicate that the data transmission rate of the system is higher than 1 MB/s, which completely meets the current requirements of the data transmission rate between the tool system and the wireline telemetry device. Application of the debugging system, which includes multiple level test methods, shows that the proposed system can fully meet the test requirements of MPAL at various levels.展开更多
In the paper, the problem of storing and replaying of HTTP requests to websites in order to improve their debugging efficiency during development and further support is considered. To solve this problem, the automatic...In the paper, the problem of storing and replaying of HTTP requests to websites in order to improve their debugging efficiency during development and further support is considered. To solve this problem, the automatic HTTP requests logging and replaying subsystem Dagger that provides storage and playback of the requests sent to a website, which is developed by CMS （content management system） Plone means, is offered. The subsystem consists of the three components： Detector, Logger and Player. Detector detects filters user＇s requests, creates a log and sends it to Logger. Logger is a daemon program that stores logs of user＇s work with a website. The logs are stored in the files in one of the supported formats： JSON, CSV, PICKLE. Player replays the GET and POST HTTP requests that users sent to a server.展开更多
Electromagnetic technology used in logging while drilling(LWD) provides the resistivity distribution around a borehole within a range of several tens of meters.However,a blind zone appears in front of the drill bit wh...Electromagnetic technology used in logging while drilling(LWD) provides the resistivity distribution around a borehole within a range of several tens of meters.However,a blind zone appears in front of the drill bit when operating in high-angle wells,limiting the ability to detect formations ahead of the drill bit.Look-ahead technology addresses this issue and substantially enhances the proactive capability of geological directional drilling.In this study,we examine the detection capabilities of various component combinations of magnetic dipole antenna.Based on the sensitivity of each component to the axial information,a coaxial component is selected as a boundary indicator.We investigate the impact of various factors,such as frequency and transmitter and receiver(TR) distance,under different geological models.This study proposes 5 and 20 kHz as appropriate frequencies,and 10-14 and 12-17 m as suitable TR distance combinations.The accuracy of the numerical calculation results is verified via air-sea testing,confirming the instrument's detection capability.A test model that eliminated the influence of environmental factors and seawater depth is developed.The results have demonstrated that the tool can recognize the interface between layers up to 21.6 m ahead.It provides a validation idea for the design of new instruments as well as the validation of detection capabilities.展开更多
Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of th...Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of these data has not been well stored,managed and mined.With the development of cloud computing technology,it provides a rare development opportunity for logging big data private cloud.The traditional petrophysical evaluation and interpretation model has encountered great challenges in the face of new evaluation objects.The solution research of logging big data distributed storage,processing and learning functions integrated in logging big data private cloud has not been carried out yet.To establish a distributed logging big-data private cloud platform centered on a unifi ed learning model,which achieves the distributed storage and processing of logging big data and facilitates the learning of novel knowledge patterns via the unifi ed logging learning model integrating physical simulation and data models in a large-scale functional space,thus resolving the geo-engineering evaluation problem of geothermal fi elds.Based on the research idea of“logging big data cloud platform-unifi ed logging learning model-large function space-knowledge learning&discovery-application”,the theoretical foundation of unified learning model,cloud platform architecture,data storage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storage and processing of data and learning algorithms.The feasibility of constructing a well logging big data cloud platform based on a unifi ed learning model of physics and data is analyzed in terms of the structure,ecology,management and security of the cloud platform.The case study shows that the logging big data cloud platform has obvious technical advantages over traditional logging evaluation methods in terms of knowledge discovery method,data software and results sharing,accuracy,speed and complexity.展开更多
In the Yingdong Oil/Gas Field of the Qaidam Basin,multiple suites of oil-gas-water systems overlie each other vertically,making it difficult to accurately identify oil layers from gas layers and calculate gas-oil rati...In the Yingdong Oil/Gas Field of the Qaidam Basin,multiple suites of oil-gas-water systems overlie each other vertically,making it difficult to accurately identify oil layers from gas layers and calculate gas-oil ratio(GOR).Therefore,formation testing and production data,together with conventional logging,NMR and mud logging data were integrated to quantitatively calculate GOR.To tell oil layers from gas layers,conventional logging makes use of the excavation effect of compensated neutron log,NMR makes use of the different relaxation mechanisms of light oil and natural gas in large pores,while mud logging makes use of star chart of gas components established based on available charts and mathematical statistics.In terms of the quantitative calculation of GOR,the area ratio of the star chart of gas components was first used in GOR calculation.The study shows that:(1)conventional logging data has a modest performance in distinguishing oil layers from gas layers due to the impacts of formation pressure,hydrogen index(HI),shale content,borehole conditions and invasion of drilling mud;(2)NMR is quite effective in telling oil layers from gas layers,but cannot be widely used due to its high cost;(3)by contrast,the star chart of gas components is the most effective in differentiating oil layers from gas layers;and(4)the GOR calculated by using the area ratio of star chart has been verified by various data such as formation testing data,production data and liquid production profile.展开更多
Agricultural machinery typically requires lower limb actuation forces for operations such as treadling,pedaling and tractor based.However,limited systems exist for assessment of such forces that have ergonomic influen...Agricultural machinery typically requires lower limb actuation forces for operations such as treadling,pedaling and tractor based.However,limited systems exist for assessment of such forces that have ergonomic influence.This study,therefore developed and evaluated a single board computer integrated foot transducer(IFT)and autonomous data logging and visualization systemtomonitor dynamic lower limb exerted forces.The systemconsists of custom developed load sensors sandwiched into foot shaped units that fit operator's both feet.Stamped forces at crank angles for operations typical to pedaling while at height(above ground level)for operation representing typical treadling operations were recorded on-board amemory card and displayed on a liquid crystal display.Evaluations were conducted by imposing external loads that significantly increased(p b 0.05)the foot exerted forces.Force trends were periodic with peaks of 73,85,110.5 and 145.4 N for left foot and 41,50,131.7 and 145.4 N for right foot at loads of 10,30,50 and 70 N,respectively during pedaling operations.Similarly,the left lower actuation limb exerted forces of 139,249 and 255 N at 5,10 and 15 N of imposed loads,respectively during treadling operation.System was also evaluated for tractor operations and exerted forces ranged from 92 to 164 and 107–176 N for clutch pedal engagement at lower to higher tractor speeds on farm and tarmacadam roads,respectively.Similarly,for brake pedal engagement,such forces ranged from106 to 173 and 120–204 N on farm and tarmacadamroads.These forces varied significantly at different forward speeds.Results suggest potential of such system for foot exerted force assessments typical to agricultural machinery systems in real field.Designsmay be evaluated or reconsidered tominimizemusculoskeletal disorder risks during prolonged operations.Work-rest schedules protocols can be developed by ergonomists for safe,efficient and comfortable operations.展开更多
A cased well model consists of a coaxial tank and casing,which houses coaxially installed transmitting and receiving coils.The transmitting coil is excited by the current produced by the transmitting circuit,and trans...A cased well model consists of a coaxial tank and casing,which houses coaxially installed transmitting and receiving coils.The transmitting coil is excited by the current produced by the transmitting circuit,and transient electromagnetic responses occur in the casing,including direct coupling and casing responses.As the range between the transmitting and receiving coils increases,direct coupling responses decay rapidly,are less than the casing response at 0.3 m,and disappear at 0.7 m.By contrast,a casing response increases rapidly and then declines slowly after reaching a peak and changes little within a specifi c range.The peak decreases slowly with range.The continuous addition of water to the tank causes slight changes in transient electromagnetic responses,so the diff erence which are subtracted from the response without water is used.Moreover,the diff erences at the time of rapid increase in response and the time of rapid decrease in response are large,forming a peak and a trough.Given that the conductivity of water in a full tank changes after the addition of salt,the diff erence in the peak is linear with the increase in the conductivity of water.This result provides an experimental basis for the design of a transient electromagnetic logging instrument that measures the conductivity of formation in cased well.展开更多
Neutron well logging,using instruments equipped with neutron source and detectors(e.g.,^(3)He-tubes,Nal,BGO),plays a key role in lithological differentiation,porosity determination,and fluid property evaluation in the...Neutron well logging,using instruments equipped with neutron source and detectors(e.g.,^(3)He-tubes,Nal,BGO),plays a key role in lithological differentiation,porosity determination,and fluid property evaluation in the petroleum industry.The growing trend of multifu nctional neutron well logging,which enables simultaneous extraction of multiple reservoir characteristics,requiring high-performance detectors capable of withstanding high-temperature downhole conditions,limited space,and instrument vibrations,while also detecting multiple particle types.The Cs_(2)LiYCl_(6):Ce^(3+)(CLYC)elpasolite scintillator demonstrates excellent temperature resistance and detection efficiency,making it become a promising candidate for leading the development of the novel neutron-based double-particle logging technology.This study employed Monte Carlo simulations to generate equivalent gamma spectra and proposed a pulse shape discrimination simulation method based on theoretical analysis and probabilistic iteration.The performance of CLYC was compared to that of common detectors in terms of physical properties and detection efficiency.A double-particle pulsed neutron detection system for porosity determination was established,based on the count ratio of equivalent gamma rays from the range of 2.95-3.42 MeVee energy bins.Results showed that CLYC can effectively replace ^(3)He-tubes for porosity measurement,providing consistent responses.This study offers numerical simulation support for the design of future neutron well logging tools and the application of double-particle detectors in logging systems.展开更多
China,as the world’s largest coal producer and consumer,faces increasingly severe challenges from coal mine goaf areas formed through decades of intensive mining.These underground voids,resulting from exhausted resou...China,as the world’s largest coal producer and consumer,faces increasingly severe challenges from coal mine goaf areas formed through decades of intensive mining.These underground voids,resulting from exhausted resources or technical limitations,not only cause environmental issues like land subsidence and groundwater contamination but also pose critical safety risks for ongoing mining operations,including water inrushes,gas outbursts,and roof collapses.Conventional geophysical methods such as seismic surveys and electromagnetic detection demonstrate limited effectiveness in complex geological conditions due to susceptibility to electrical heterogeneity,electromagnetic interference,and interpretation ambiguities.This study presents an innovative integrated approach combining the Audio-Frequency Electrical Transillumination(AFET)method with multi-parameter borehole logging to establish a three-dimensional detection system.The AFET technique employs 0.1–10 kHz electromagnetic waves to identify electrical anomalies associated with goafs,enabling extensive horizontal scanning.This is complemented by vertical high-resolution profiling through borehole measurements of resistivity,spontaneous potential,and acoustic velocity.Field applications in Shanxi Province’s typical coal mines achieved breakthrough results:Using a grid-drilling pattern(15 m spacing,300 m depth),the method successfully detected three concealed goafs missed by conventional approaches,with spatial positioning errors under 0.5 m.Notably,it accurately identified two un-collapsed water-filled cavities.This surface-borehole synergistic approach overcomes single-method limitations,enhancing goaf detection accuracy to over 92%.The technique provides reliable technical support for safe mining practices and represents significant progress in precise detection of hidden geological hazards in Chinese coal mines,offering valuable insights for global mining geophysics.展开更多
Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images,this paper integrates the YOLOv8 model with the Convolution Block Attention Module(CBAM).It proposes ...Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images,this paper integrates the YOLOv8 model with the Convolution Block Attention Module(CBAM).It proposes an intelligent method for detecting fractures and holes,as well as segmenting whole-wellbore images.Firstly,we develop a dataset sample of effective reservoir sections by integrating logging data and conducting data augmentation on fracture and hole samples in ultrasonic logging images.A standardized process procedure for the generation of new samples and model training has been proposed effectively.Subsequently,the improved YOLOv8 model undergoes a process of training and validation.The results indicate that the model achieves average accuracies of 0.910 and 0.884 in target detection and image segmentation tasks,respectively.These findings demonstrate a notable performance improvement compared to the original model.Furthermore,a sliding window strategy is proposed to tackle the challenges of high computational demands and insufficient accuracy in the intelligent processing of full-well ultrasonic images.To manage overlapping regions within the sliding window,we employ the Non-Maximum Suppression(NMS)principle for effective processing.Finally,the model has been tested on actual logging images and demonstrates an enhanced capability to identify irregular fractures and holes,which significantly improves the efficiency of geological feature recognition in the wholewell section ultrasonic logging images.展开更多
To improve the accuracy and generalization of well logging curve reconstruction,this paper proposes an artificial intelligence large language model“Gaia”and conducts model evaluation experiments.By fine-tuning the p...To improve the accuracy and generalization of well logging curve reconstruction,this paper proposes an artificial intelligence large language model“Gaia”and conducts model evaluation experiments.By fine-tuning the pre-trained large language model,the Gaia significantly improved its ability in extracting sequential patterns and spatial features from well-log curves.Leveraging the adapter method for fine-tuning,this model required training only about 1/70 of its original parameters,greatly improving training efficiency.Comparative experiments,ablation experiments,and generalization experiments were designed and conducted using well-log data from 250 wells.In the comparative experiment,the Gaia model was benchmarked against cutting-edge small deep learning models and conventional large language models,demonstrating that the Gaia model reduced the mean absolute error(MAE)by at least 20%.In the ablation experiments,the synergistic effect of the Gaia model's multiple components was validated,with its MAE being at least 30%lower than that of single-component models.In the generalization experiments,the superior performance of the Gaia model in blind-well predictions was further confirmed.Compared to traditional models,the Gaia model is significantly superior in accuracy and generalization for logging curve reconstruction,fully showcasing the potential of large language models in the field of well-logging.This provides a new approach for future intelligent logging data processing.展开更多
The development of machine learning and deep learning algorithms as well as the improvement ofhardware arithmetic power provide a rare opportunity for logging big data private cloud.With the deepeningof exploration an...The development of machine learning and deep learning algorithms as well as the improvement ofhardware arithmetic power provide a rare opportunity for logging big data private cloud.With the deepeningof exploration and development and the requirements of low-carbon development,the focus of exploration anddevelopment in the oil and gas industry is gradually shifting to the exploration and development of renewableenergy sources such as deep sea,deep earth and geothermal energy.The traditional petrophysical evaluation andinterpretation model has encountered great challenges in the face of new evaluation objects.To establish a distributedlogging big data private cloud platform with a unified learning model as the key,which realizes the distributed storageand processing of logging big data,and enables the learning of brand-new knowledge patterns from multi-attributedata in the large function space in the unified logging learning model integrating the expert knowledge and the datamodel,so as to solve the problem of geoengineering evaluation of geothermal fields.Based on the research ideaof“logging big data cloud platform---unified logging learning model---large function space---knowledge learning&discovery---application”,the theoretical foundation of unified learning model,cloud platform architecture,datastorage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storageand processing of data and learning algorithms.New knowledge of geothermal evaluation is found in a large functionspace and applied to Geo-engineering evaluation of geothermal fields.The examples show its good application in theselection of logging series in geothermal fields,quality control of logging data,identification of complex lithologyin geothermal fields,evaluation of reservoir fluids,checking of associated helium,evaluation of cementing quality,evaluation of well-side fractures,and evaluation of geothermal water recharge under the remote logging module ofthe cloud platform.The first and second cementing surfaces of cemented wells in geothermal fields were evaluated,as well as the development of well-side distal fractures,fracture extension orientation.According to the well-sidefracture communication to form a good fluid pathway and large flow rate and long flow diameter of the thermalstorage fi ssure system,the design is conducive to the design of the recharge program of geothermal water.展开更多
The numerical dispersion phenomenon in the finite-difference forward modeling simulations of the wave equation significantly affects the imaging accuracy in acoustic reflection logging.This issue is particularly prono...The numerical dispersion phenomenon in the finite-difference forward modeling simulations of the wave equation significantly affects the imaging accuracy in acoustic reflection logging.This issue is particularly pronounced in the reverse time migration(RTM)method used for shear-wave(S-wave)logging imaging.This not only affects imaging accuracy but also introduces ambiguities in the interpretation of logging results.To address this challenge,this study proposes the use of a least-squares difference coefficient optimization algorithm aiming to suppress the numerical dispersion phenomenon in the RTM of S-wave reflection imaging logging.By optimizing the difference coefficients,the high-precision finite-difference algorithm serves as an effective operator for both forward and backward RTM processes.This approach is instrumental in eliminating migration illusions,which are often caused by numerical dispersion.The effectiveness of this optimized algorithm is demonstrated through numerical results,which indicate that it can achieve more accurate forward imaging results across various conditions,including high-and low-velocity strata,and is effective in both large and small spatial grids.The results of processing real data demonstrate that numerical dispersion optimization effectively reduces migration artifacts and diminishes ambiguities in logging interpretations.This optimization offers crucial technical support to the RTM method,enhancing its capability for accurately modeling and imaging S-wave reflections.展开更多
Global forest cover is undergoing significant transformations due to anthropogenic activities and natural disturbances,profoundly impacting hydrological processes.However,the inherent spatial heterogeneity within wate...Global forest cover is undergoing significant transformations due to anthropogenic activities and natural disturbances,profoundly impacting hydrological processes.However,the inherent spatial heterogeneity within watersheds leads to varied hydrological responses across spatiotemporal scales,challenging comprehensive assessment of logging impacts at the watershed scale.Here,we developed multiple forest logging scenarios using the soil and water assessment tool(SWAT)model for the Le'an River watershed,a 5,837 km2 subtropical watershed in China,to quantify the hydrological effects of forest logging across different spatiotemporal scales.Our results demonstrate that increasing forest logging ratios from 1.54% to 9.25% consistently enhanced ecohydrological sensitivity.However,sensitivity varied across spatiotemporal scales,with the rainy season(15.30%-15.81%)showing higher sensitivity than annual(11.56%-12.07%)and dry season(3.38%-5.57%)periods.Additionally,the ecohydrological sensitivity of logging varied significantly across the watershed,with midstream areas exhibiting the highest sensitivity(13.13%-13.25%),followed by downstream(11.87%-11.98%)and upstream regions(9.96%-10.05%).Furthermore,the whole watershed exhibited greater hydrological resilience to logging compared to upstream areas,with attenuated runoff changes due to scale effects.Scale effects were more pronounced during dry seasons((-8.13 to -42.13)×10^(4) m^(3)·month^(-1))than in the rainy season((-11.11 to -26.65)×10^(4) m^(3)·month^(-1)).These findings advance understanding of logging impacts on hydrology across different spatiotemporal scales in subtropical regions,providing valuable insights for forest management under increasing anthropogenic activities and climate change.展开更多
BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive ...BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive lymph node ratio(LNR)and log odds of positive lymph nodes(LODDS)were introduced.AIM To assess the prognostic accuracy and stratification efficacy of three nodal staging systems in GC.METHODS A systematic review identified 12 studies,from which hazard ratios(HRs)for overall survival(OS)were summarized.Sensitivity analyses,subgroup analyses,publication bias assessments,and quality evaluations were conducted.To enhance comparability,data from studies with identical cutoff values for pN,LNR,and LODDS were pooled.Homogeneous stratification was then applied to generate Kaplan-Meier(KM)survival curves,assessing the stratification efficacy of three staging systems.RESULTS The HRs and 95%confidence intervals for pN,LNR,and LODDS were 2.16(1.72-2.73),2.05(1.65-2.55),and 3.15(2.15-4.37),respectively,confirming all three as independent prognostic risk factors for OS.Comparative analysis of HRs demonstrated that LODDS had superior prognostic predictive power over LNR and pN.KM curves for pN(N0,N1,N2,N3a,N3b),LNR(0.1/0.2/0.5),and LODDS(-1.5/-1.0/-0.5/0)revealed significant differences(P<0.001)among all prognostic stratifications.Mean differences and standard deviations in 60-month relative survival were 27.93%±0.29%,41.70%±0.30%,and 26.60%±0.28%for pN,LNR,and LODDS,respectively.CONCLUSION All three staging systems are independent prognostic factors for OS.LODDS demonstrated the highest specificity,making it especially useful for predicting outcomes,while pN was the most effective in homogeneous stratification,offering better patient differentiation.These findings highlight the complementary roles of LODDS and pN in enhancing prognostic accuracy and stratification.展开更多
It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations...It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations. First, we use the plane-wave superposition model containing two plane waves with different velocities and able to change the values of phase velocity and group velocity. The numerical results show that whether phase velocity is higher or lower than group velocity, using the slowness-time coherence （STC） method we can only get phase velocities. Second, according to the results of the dispersion analysis and branch-cut integration, in a rigid boundary borehole model the results of dispersion curves and the waveforms of the first-order mode show that the velocities obtained by the STC method are phase velocities while group velocities obtained by arrival time picking. Finally, dipole logging in a slow formation model is investigated using dispersion analysis and real-axis integration. The results of dispersion curves and full wave trains show similar conclusions as the borehole model with rigid boundary conditions.展开更多
Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play...Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.展开更多
The reservoir pore structure controls the reservoir quality and resistivity response of hydrocarbon-bearing zones and thus, critically affects logging interpretation. We use petrophysical data in three types of reserv...The reservoir pore structure controls the reservoir quality and resistivity response of hydrocarbon-bearing zones and thus, critically affects logging interpretation. We use petrophysical data in three types of reservoir with different pore structure characteristics to show that the complexity of pore structure had a significant effect on the effective porosity and permeability regardless of geological factors responsible for the formation of pore structure. Moreover,, the distribution and content of conductive fluids in the reservoir varies dramatically owing to pore structure differences, which also induces resistivity variations in reservoir rocks. Hence, the origin of low-resistivity hydrocarbon-bearing zones, except for those with conductive matrix and mud filtrate invasion, is attributed to the complexity of the pore structures. Consequently, reservoir-specific evaluation models, parameters, and criteria should be chosen for resistivity log interpretation to make a reliable evaluation of reservoir quality and fluids.展开更多
We designed a new downhole electrokinetic logging tool based on numericalsimulations and petrophysical experiments. Acoustic and electric receivers cannot be arrangedat the same depth, and the proposed composite elect...We designed a new downhole electrokinetic logging tool based on numericalsimulations and petrophysical experiments. Acoustic and electric receivers cannot be arrangedat the same depth, and the proposed composite electrokinetic logging tool offers a solutionto this problem. The sound field characteristics of the detectors were tested in a water tank inthe laboratory. Then, we calculated the sound pressure of the radiated acoustic field and thetransmitting voltage response of the transmitting transducers; in addition, we analyzed thedirectivity and application of the acoustic transmitting probe based on linear phased array.The results suggest that the sound pressure generated at 1500 mm spacing reaches up to 47.2k Pa and decreases with increasing acoustic source frequency. When the excitation signalsdelay time of adjacent acoustic transmitting subarrays increases, the radiation beam of themain lobe is deflected and its energy gradually increases, which presumably enhances theacoustoelectric conversion efficiency.展开更多
文摘The TRU-Vision system,developed by Baker Hughes,analyzes the gas extracted from drilling mud to estimate the hydrocarbons composition in drilled rock formations.Several separation processes had been surveyed in order to enhance the gas extraction at the gas trap,namely,mechanical stirring,vacuum,air sparging,membrane separation processes,ultrasounds,and cyclones.Mechanical stirring devices(one propeller,one flat-blade turbine,and two baffles sets),a vacuum generator,and an air bubble generator were designed and assembled to increase the efficiency and the response stability of TRU-Vision system.
基金supported by National Science Foundation of China (61102102, 11134011, 11204380 and 11374371)Major National Science and Technology Projects (2011ZX05020-002)+2 种基金PetroChina Innovation Foundation (2014D-5006-0307)Science and Technology Project of CNPC (2014A-3912 and 2011B-4001)the Foundation of China University of Petroleum (KYJJ2012-05-07)
文摘This paper presents a debugging system for multi-pole array acoustic logging （MPAL） tools. The debugging system proposed in this study can debug the MPAL tool system, sub-system and local electronics. In the test equipment, we have used principal and subordinate structures, and interconnected the host computer and the front-end machine via Ethernet. The front-end machine is based on the ARM7 （advanced reduced instruction set computing （RISC） machine） technique, the processor of which runs an embedded operating system, namely, uClinux OS. We have analyzed the system telecommunication, human-machine interface circuit, transmitter mandrel interface circuit, receiver mandrel interface circuit, and board-level test interface circuit. The software used in the system consists of the embedded front-computer software and the host application software. We have explained in detail the flow chart of the boot loader in the embedded front-computer software. The host application software is composed of four application subroutines, which match with the functional modules of the system hardware. A net communication program based on the server^client mode is implemented by means of socket programming and multi-thread programming. Test results indicate that the data transmission rate of the system is higher than 1 MB/s, which completely meets the current requirements of the data transmission rate between the tool system and the wireline telemetry device. Application of the debugging system, which includes multiple level test methods, shows that the proposed system can fully meet the test requirements of MPAL at various levels.
文摘In the paper, the problem of storing and replaying of HTTP requests to websites in order to improve their debugging efficiency during development and further support is considered. To solve this problem, the automatic HTTP requests logging and replaying subsystem Dagger that provides storage and playback of the requests sent to a website, which is developed by CMS （content management system） Plone means, is offered. The subsystem consists of the three components： Detector, Logger and Player. Detector detects filters user＇s requests, creates a log and sends it to Logger. Logger is a daemon program that stores logs of user＇s work with a website. The logs are stored in the files in one of the supported formats： JSON, CSV, PICKLE. Player replays the GET and POST HTTP requests that users sent to a server.
基金co-funded by the National Key Research and Development Program of China under Grant (2019YFA0708301)the CAS Project for Young Scientists in Basic Research (Grant No.YSBR-082)Research Instrument and Equipment Development Project of Chinese Academy of Sciences (GJJSTD20210008)。
文摘Electromagnetic technology used in logging while drilling(LWD) provides the resistivity distribution around a borehole within a range of several tens of meters.However,a blind zone appears in front of the drill bit when operating in high-angle wells,limiting the ability to detect formations ahead of the drill bit.Look-ahead technology addresses this issue and substantially enhances the proactive capability of geological directional drilling.In this study,we examine the detection capabilities of various component combinations of magnetic dipole antenna.Based on the sensitivity of each component to the axial information,a coaxial component is selected as a boundary indicator.We investigate the impact of various factors,such as frequency and transmitter and receiver(TR) distance,under different geological models.This study proposes 5 and 20 kHz as appropriate frequencies,and 10-14 and 12-17 m as suitable TR distance combinations.The accuracy of the numerical calculation results is verified via air-sea testing,confirming the instrument's detection capability.A test model that eliminated the influence of environmental factors and seawater depth is developed.The results have demonstrated that the tool can recognize the interface between layers up to 21.6 m ahead.It provides a validation idea for the design of new instruments as well as the validation of detection capabilities.
基金supported By Grant (PLN2022-14) of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University)。
文摘Well logging technology has accumulated a large amount of historical data through four generations of technological development,which forms the basis of well logging big data and digital assets.However,the value of these data has not been well stored,managed and mined.With the development of cloud computing technology,it provides a rare development opportunity for logging big data private cloud.The traditional petrophysical evaluation and interpretation model has encountered great challenges in the face of new evaluation objects.The solution research of logging big data distributed storage,processing and learning functions integrated in logging big data private cloud has not been carried out yet.To establish a distributed logging big-data private cloud platform centered on a unifi ed learning model,which achieves the distributed storage and processing of logging big data and facilitates the learning of novel knowledge patterns via the unifi ed logging learning model integrating physical simulation and data models in a large-scale functional space,thus resolving the geo-engineering evaluation problem of geothermal fi elds.Based on the research idea of“logging big data cloud platform-unifi ed logging learning model-large function space-knowledge learning&discovery-application”,the theoretical foundation of unified learning model,cloud platform architecture,data storage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storage and processing of data and learning algorithms.The feasibility of constructing a well logging big data cloud platform based on a unifi ed learning model of physics and data is analyzed in terms of the structure,ecology,management and security of the cloud platform.The case study shows that the logging big data cloud platform has obvious technical advantages over traditional logging evaluation methods in terms of knowledge discovery method,data software and results sharing,accuracy,speed and complexity.
文摘In the Yingdong Oil/Gas Field of the Qaidam Basin,multiple suites of oil-gas-water systems overlie each other vertically,making it difficult to accurately identify oil layers from gas layers and calculate gas-oil ratio(GOR).Therefore,formation testing and production data,together with conventional logging,NMR and mud logging data were integrated to quantitatively calculate GOR.To tell oil layers from gas layers,conventional logging makes use of the excavation effect of compensated neutron log,NMR makes use of the different relaxation mechanisms of light oil and natural gas in large pores,while mud logging makes use of star chart of gas components established based on available charts and mathematical statistics.In terms of the quantitative calculation of GOR,the area ratio of the star chart of gas components was first used in GOR calculation.The study shows that:(1)conventional logging data has a modest performance in distinguishing oil layers from gas layers due to the impacts of formation pressure,hydrogen index(HI),shale content,borehole conditions and invasion of drilling mud;(2)NMR is quite effective in telling oil layers from gas layers,but cannot be widely used due to its high cost;(3)by contrast,the star chart of gas components is the most effective in differentiating oil layers from gas layers;and(4)the GOR calculated by using the area ratio of star chart has been verified by various data such as formation testing data,production data and liquid production profile.
文摘Agricultural machinery typically requires lower limb actuation forces for operations such as treadling,pedaling and tractor based.However,limited systems exist for assessment of such forces that have ergonomic influence.This study,therefore developed and evaluated a single board computer integrated foot transducer(IFT)and autonomous data logging and visualization systemtomonitor dynamic lower limb exerted forces.The systemconsists of custom developed load sensors sandwiched into foot shaped units that fit operator's both feet.Stamped forces at crank angles for operations typical to pedaling while at height(above ground level)for operation representing typical treadling operations were recorded on-board amemory card and displayed on a liquid crystal display.Evaluations were conducted by imposing external loads that significantly increased(p b 0.05)the foot exerted forces.Force trends were periodic with peaks of 73,85,110.5 and 145.4 N for left foot and 41,50,131.7 and 145.4 N for right foot at loads of 10,30,50 and 70 N,respectively during pedaling operations.Similarly,the left lower actuation limb exerted forces of 139,249 and 255 N at 5,10 and 15 N of imposed loads,respectively during treadling operation.System was also evaluated for tractor operations and exerted forces ranged from 92 to 164 and 107–176 N for clutch pedal engagement at lower to higher tractor speeds on farm and tarmacadam roads,respectively.Similarly,for brake pedal engagement,such forces ranged from106 to 173 and 120–204 N on farm and tarmacadamroads.These forces varied significantly at different forward speeds.Results suggest potential of such system for foot exerted force assessments typical to agricultural machinery systems in real field.Designsmay be evaluated or reconsidered tominimizemusculoskeletal disorder risks during prolonged operations.Work-rest schedules protocols can be developed by ergonomists for safe,efficient and comfortable operations.
基金supported by the National Natural Science Foundation of China (grant nos. 42074137)。
文摘A cased well model consists of a coaxial tank and casing,which houses coaxially installed transmitting and receiving coils.The transmitting coil is excited by the current produced by the transmitting circuit,and transient electromagnetic responses occur in the casing,including direct coupling and casing responses.As the range between the transmitting and receiving coils increases,direct coupling responses decay rapidly,are less than the casing response at 0.3 m,and disappear at 0.7 m.By contrast,a casing response increases rapidly and then declines slowly after reaching a peak and changes little within a specifi c range.The peak decreases slowly with range.The continuous addition of water to the tank causes slight changes in transient electromagnetic responses,so the diff erence which are subtracted from the response without water is used.Moreover,the diff erences at the time of rapid increase in response and the time of rapid decrease in response are large,forming a peak and a trough.Given that the conductivity of water in a full tank changes after the addition of salt,the diff erence in the peak is linear with the increase in the conductivity of water.This result provides an experimental basis for the design of a transient electromagnetic logging instrument that measures the conductivity of formation in cased well.
基金the support of the National Natural Science Foundation of China(42174147,42474155)the Scientific and Technological Innovation Projects of Laoshan Laboratory(LSKJ20220347)。
文摘Neutron well logging,using instruments equipped with neutron source and detectors(e.g.,^(3)He-tubes,Nal,BGO),plays a key role in lithological differentiation,porosity determination,and fluid property evaluation in the petroleum industry.The growing trend of multifu nctional neutron well logging,which enables simultaneous extraction of multiple reservoir characteristics,requiring high-performance detectors capable of withstanding high-temperature downhole conditions,limited space,and instrument vibrations,while also detecting multiple particle types.The Cs_(2)LiYCl_(6):Ce^(3+)(CLYC)elpasolite scintillator demonstrates excellent temperature resistance and detection efficiency,making it become a promising candidate for leading the development of the novel neutron-based double-particle logging technology.This study employed Monte Carlo simulations to generate equivalent gamma spectra and proposed a pulse shape discrimination simulation method based on theoretical analysis and probabilistic iteration.The performance of CLYC was compared to that of common detectors in terms of physical properties and detection efficiency.A double-particle pulsed neutron detection system for porosity determination was established,based on the count ratio of equivalent gamma rays from the range of 2.95-3.42 MeVee energy bins.Results showed that CLYC can effectively replace ^(3)He-tubes for porosity measurement,providing consistent responses.This study offers numerical simulation support for the design of future neutron well logging tools and the application of double-particle detectors in logging systems.
文摘China,as the world’s largest coal producer and consumer,faces increasingly severe challenges from coal mine goaf areas formed through decades of intensive mining.These underground voids,resulting from exhausted resources or technical limitations,not only cause environmental issues like land subsidence and groundwater contamination but also pose critical safety risks for ongoing mining operations,including water inrushes,gas outbursts,and roof collapses.Conventional geophysical methods such as seismic surveys and electromagnetic detection demonstrate limited effectiveness in complex geological conditions due to susceptibility to electrical heterogeneity,electromagnetic interference,and interpretation ambiguities.This study presents an innovative integrated approach combining the Audio-Frequency Electrical Transillumination(AFET)method with multi-parameter borehole logging to establish a three-dimensional detection system.The AFET technique employs 0.1–10 kHz electromagnetic waves to identify electrical anomalies associated with goafs,enabling extensive horizontal scanning.This is complemented by vertical high-resolution profiling through borehole measurements of resistivity,spontaneous potential,and acoustic velocity.Field applications in Shanxi Province’s typical coal mines achieved breakthrough results:Using a grid-drilling pattern(15 m spacing,300 m depth),the method successfully detected three concealed goafs missed by conventional approaches,with spatial positioning errors under 0.5 m.Notably,it accurately identified two un-collapsed water-filled cavities.This surface-borehole synergistic approach overcomes single-method limitations,enhancing goaf detection accuracy to over 92%.The technique provides reliable technical support for safe mining practices and represents significant progress in precise detection of hidden geological hazards in Chinese coal mines,offering valuable insights for global mining geophysics.
基金supported by the National Natural Science Foundation of China(Grant Nos.12334019,12304496).
文摘Aiming to address the demand for intelligent recognition of geological features in whole-wellbore ultrasonic images,this paper integrates the YOLOv8 model with the Convolution Block Attention Module(CBAM).It proposes an intelligent method for detecting fractures and holes,as well as segmenting whole-wellbore images.Firstly,we develop a dataset sample of effective reservoir sections by integrating logging data and conducting data augmentation on fracture and hole samples in ultrasonic logging images.A standardized process procedure for the generation of new samples and model training has been proposed effectively.Subsequently,the improved YOLOv8 model undergoes a process of training and validation.The results indicate that the model achieves average accuracies of 0.910 and 0.884 in target detection and image segmentation tasks,respectively.These findings demonstrate a notable performance improvement compared to the original model.Furthermore,a sliding window strategy is proposed to tackle the challenges of high computational demands and insufficient accuracy in the intelligent processing of full-well ultrasonic images.To manage overlapping regions within the sliding window,we employ the Non-Maximum Suppression(NMS)principle for effective processing.Finally,the model has been tested on actual logging images and demonstrates an enhanced capability to identify irregular fractures and holes,which significantly improves the efficiency of geological feature recognition in the wholewell section ultrasonic logging images.
基金Supported by the National Natural Science Foundation of China(52288101)National Key R&D Program of China(2024YFF1500600)。
文摘To improve the accuracy and generalization of well logging curve reconstruction,this paper proposes an artificial intelligence large language model“Gaia”and conducts model evaluation experiments.By fine-tuning the pre-trained large language model,the Gaia significantly improved its ability in extracting sequential patterns and spatial features from well-log curves.Leveraging the adapter method for fine-tuning,this model required training only about 1/70 of its original parameters,greatly improving training efficiency.Comparative experiments,ablation experiments,and generalization experiments were designed and conducted using well-log data from 250 wells.In the comparative experiment,the Gaia model was benchmarked against cutting-edge small deep learning models and conventional large language models,demonstrating that the Gaia model reduced the mean absolute error(MAE)by at least 20%.In the ablation experiments,the synergistic effect of the Gaia model's multiple components was validated,with its MAE being at least 30%lower than that of single-component models.In the generalization experiments,the superior performance of the Gaia model in blind-well predictions was further confirmed.Compared to traditional models,the Gaia model is significantly superior in accuracy and generalization for logging curve reconstruction,fully showcasing the potential of large language models in the field of well-logging.This provides a new approach for future intelligent logging data processing.
文摘The development of machine learning and deep learning algorithms as well as the improvement ofhardware arithmetic power provide a rare opportunity for logging big data private cloud.With the deepeningof exploration and development and the requirements of low-carbon development,the focus of exploration anddevelopment in the oil and gas industry is gradually shifting to the exploration and development of renewableenergy sources such as deep sea,deep earth and geothermal energy.The traditional petrophysical evaluation andinterpretation model has encountered great challenges in the face of new evaluation objects.To establish a distributedlogging big data private cloud platform with a unified learning model as the key,which realizes the distributed storageand processing of logging big data,and enables the learning of brand-new knowledge patterns from multi-attributedata in the large function space in the unified logging learning model integrating the expert knowledge and the datamodel,so as to solve the problem of geoengineering evaluation of geothermal fields.Based on the research ideaof“logging big data cloud platform---unified logging learning model---large function space---knowledge learning&discovery---application”,the theoretical foundation of unified learning model,cloud platform architecture,datastorage and learning algorithm,arithmetic power allocation and platform monitoring,platform stability,data security,etc.have been carried on analysis.The designed logging big data cloud platform realizes parallel distributed storageand processing of data and learning algorithms.New knowledge of geothermal evaluation is found in a large functionspace and applied to Geo-engineering evaluation of geothermal fields.The examples show its good application in theselection of logging series in geothermal fields,quality control of logging data,identification of complex lithologyin geothermal fields,evaluation of reservoir fluids,checking of associated helium,evaluation of cementing quality,evaluation of well-side fractures,and evaluation of geothermal water recharge under the remote logging module ofthe cloud platform.The first and second cementing surfaces of cemented wells in geothermal fields were evaluated,as well as the development of well-side distal fractures,fracture extension orientation.According to the well-sidefracture communication to form a good fluid pathway and large flow rate and long flow diameter of the thermalstorage fi ssure system,the design is conducive to the design of the recharge program of geothermal water.
基金supported by Scientific Research and Technology Development Project of CNPC(2021DJ4002,2022DJ3908).
文摘The numerical dispersion phenomenon in the finite-difference forward modeling simulations of the wave equation significantly affects the imaging accuracy in acoustic reflection logging.This issue is particularly pronounced in the reverse time migration(RTM)method used for shear-wave(S-wave)logging imaging.This not only affects imaging accuracy but also introduces ambiguities in the interpretation of logging results.To address this challenge,this study proposes the use of a least-squares difference coefficient optimization algorithm aiming to suppress the numerical dispersion phenomenon in the RTM of S-wave reflection imaging logging.By optimizing the difference coefficients,the high-precision finite-difference algorithm serves as an effective operator for both forward and backward RTM processes.This approach is instrumental in eliminating migration illusions,which are often caused by numerical dispersion.The effectiveness of this optimized algorithm is demonstrated through numerical results,which indicate that it can achieve more accurate forward imaging results across various conditions,including high-and low-velocity strata,and is effective in both large and small spatial grids.The results of processing real data demonstrate that numerical dispersion optimization effectively reduces migration artifacts and diminishes ambiguities in logging interpretations.This optimization offers crucial technical support to the RTM method,enhancing its capability for accurately modeling and imaging S-wave reflections.
基金supported by the National Natural Science Foundation of China(No.31660234).
文摘Global forest cover is undergoing significant transformations due to anthropogenic activities and natural disturbances,profoundly impacting hydrological processes.However,the inherent spatial heterogeneity within watersheds leads to varied hydrological responses across spatiotemporal scales,challenging comprehensive assessment of logging impacts at the watershed scale.Here,we developed multiple forest logging scenarios using the soil and water assessment tool(SWAT)model for the Le'an River watershed,a 5,837 km2 subtropical watershed in China,to quantify the hydrological effects of forest logging across different spatiotemporal scales.Our results demonstrate that increasing forest logging ratios from 1.54% to 9.25% consistently enhanced ecohydrological sensitivity.However,sensitivity varied across spatiotemporal scales,with the rainy season(15.30%-15.81%)showing higher sensitivity than annual(11.56%-12.07%)and dry season(3.38%-5.57%)periods.Additionally,the ecohydrological sensitivity of logging varied significantly across the watershed,with midstream areas exhibiting the highest sensitivity(13.13%-13.25%),followed by downstream(11.87%-11.98%)and upstream regions(9.96%-10.05%).Furthermore,the whole watershed exhibited greater hydrological resilience to logging compared to upstream areas,with attenuated runoff changes due to scale effects.Scale effects were more pronounced during dry seasons((-8.13 to -42.13)×10^(4) m^(3)·month^(-1))than in the rainy season((-11.11 to -26.65)×10^(4) m^(3)·month^(-1)).These findings advance understanding of logging impacts on hydrology across different spatiotemporal scales in subtropical regions,providing valuable insights for forest management under increasing anthropogenic activities and climate change.
基金the Clinical Medical Team Introduction Program of Suzhou,No.SZYJTD201804.
文摘BACKGROUND Lymph node status is a critical prognostic factor in gastric cancer(GC),but stage migration may occur in pathological lymph nodes(pN)staging.To address this,alternative staging systems such as the positive lymph node ratio(LNR)and log odds of positive lymph nodes(LODDS)were introduced.AIM To assess the prognostic accuracy and stratification efficacy of three nodal staging systems in GC.METHODS A systematic review identified 12 studies,from which hazard ratios(HRs)for overall survival(OS)were summarized.Sensitivity analyses,subgroup analyses,publication bias assessments,and quality evaluations were conducted.To enhance comparability,data from studies with identical cutoff values for pN,LNR,and LODDS were pooled.Homogeneous stratification was then applied to generate Kaplan-Meier(KM)survival curves,assessing the stratification efficacy of three staging systems.RESULTS The HRs and 95%confidence intervals for pN,LNR,and LODDS were 2.16(1.72-2.73),2.05(1.65-2.55),and 3.15(2.15-4.37),respectively,confirming all three as independent prognostic risk factors for OS.Comparative analysis of HRs demonstrated that LODDS had superior prognostic predictive power over LNR and pN.KM curves for pN(N0,N1,N2,N3a,N3b),LNR(0.1/0.2/0.5),and LODDS(-1.5/-1.0/-0.5/0)revealed significant differences(P<0.001)among all prognostic stratifications.Mean differences and standard deviations in 60-month relative survival were 27.93%±0.29%,41.70%±0.30%,and 26.60%±0.28%for pN,LNR,and LODDS,respectively.CONCLUSION All three staging systems are independent prognostic factors for OS.LODDS demonstrated the highest specificity,making it especially useful for predicting outcomes,while pN was the most effective in homogeneous stratification,offering better patient differentiation.These findings highlight the complementary roles of LODDS and pN in enhancing prognostic accuracy and stratification.
基金supported by the National Natural Science Foundation of China (Grant No. 40774099, 10874202 and 11134011)National 863 Program of China (Grant No. 2008AA06Z205)
文摘It is still argued whether we measure phase or group velocities using acoustic logging tools. In this paper, three kinds of models are used to investigate this problem by theoretical analyses and numerical simulations. First, we use the plane-wave superposition model containing two plane waves with different velocities and able to change the values of phase velocity and group velocity. The numerical results show that whether phase velocity is higher or lower than group velocity, using the slowness-time coherence （STC） method we can only get phase velocities. Second, according to the results of the dispersion analysis and branch-cut integration, in a rigid boundary borehole model the results of dispersion curves and the waveforms of the first-order mode show that the velocities obtained by the STC method are phase velocities while group velocities obtained by arrival time picking. Finally, dipole logging in a slow formation model is investigated using dispersion analysis and real-axis integration. The results of dispersion curves and full wave trains show similar conclusions as the borehole model with rigid boundary conditions.
基金sponsored by the National Science and Technology Major Project(No.2011ZX05023-005-006)
文摘Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.
基金supported by China national petroleum corporation science and technology development projects(No.2011D_4101)
文摘The reservoir pore structure controls the reservoir quality and resistivity response of hydrocarbon-bearing zones and thus, critically affects logging interpretation. We use petrophysical data in three types of reservoir with different pore structure characteristics to show that the complexity of pore structure had a significant effect on the effective porosity and permeability regardless of geological factors responsible for the formation of pore structure. Moreover,, the distribution and content of conductive fluids in the reservoir varies dramatically owing to pore structure differences, which also induces resistivity variations in reservoir rocks. Hence, the origin of low-resistivity hydrocarbon-bearing zones, except for those with conductive matrix and mud filtrate invasion, is attributed to the complexity of the pore structures. Consequently, reservoir-specific evaluation models, parameters, and criteria should be chosen for resistivity log interpretation to make a reliable evaluation of reservoir quality and fluids.
基金supported by the National Science Foundation of China(No.61102102,11134011,11204380 and 11374371)Major National Science and Technology Projects(No.2011ZX05020-009)+1 种基金Science and Technology Project of CNPC(No.2014A-3912 and 2011B-4001)Petro China Innovation Foundation(No.2014D-5006-0307)
文摘We designed a new downhole electrokinetic logging tool based on numericalsimulations and petrophysical experiments. Acoustic and electric receivers cannot be arrangedat the same depth, and the proposed composite electrokinetic logging tool offers a solutionto this problem. The sound field characteristics of the detectors were tested in a water tank inthe laboratory. Then, we calculated the sound pressure of the radiated acoustic field and thetransmitting voltage response of the transmitting transducers; in addition, we analyzed thedirectivity and application of the acoustic transmitting probe based on linear phased array.The results suggest that the sound pressure generated at 1500 mm spacing reaches up to 47.2k Pa and decreases with increasing acoustic source frequency. When the excitation signalsdelay time of adjacent acoustic transmitting subarrays increases, the radiation beam of themain lobe is deflected and its energy gradually increases, which presumably enhances theacoustoelectric conversion efficiency.
