共查询到20条相似文献，搜索用时 341 毫秒
1.
Well log analysis provides the information on petrophysical properties of reservoir rock and its fluid content. The present study depicts interpretation of well log responses such as gamma ray, resistivity, density and neutron logs from six wells, namely W-1, W-2, W-9, W-12, W-13 and W-14 under the study area of Krishna-Godavari (K-G) basin. The logs have been used primarily for identification of lithology and hydrocarbon-bearing zones. The gamma ray log trend indicates deposition of cleaning upward sediment. Coarsening upward, clayey-silty-sandy bodies have been evidenced from the gamma ray log. Gas-bearing zones are characterised by low gamma ray, high deep resistivity and crossover between neutron and density logs. Total 14 numbers of hydrocarbon-bearing zones are identified from wells W-9, W-12, W-13 and W-14 using conventional log analysis. Crossplotting techniques are adopted for identification of lithology and fluid type using log responses. Crossplots, namely P-impedance vs. S-impedance, P-impedance vs. ratio of P-wave and S-wave velocities (Vp/Vs) and lambda-mu-rho (LMR), have been analysed to discriminate between lithology and fluid types. Vp/Vs vs. P-impedance crossplot is able to detect gas sand, brine sand and shale whereas P-impedance vs. S-impedance crossplot detects shale and sand trends only. LMR technique, i.e. λρ vs. μρ crossplot is able to discriminate gas sand, brine sand, carbonate and shale. The LMR crossplot improves the detectability and sensitivity of fluid types and carbonate lithology over other crossplotting techniques. Petrophysical parameters like volume of shale, effective porosity and water saturation in the hydrocarbon-bearing zones in these wells range from 5 to 37%, from 11 to 36 and from 10 to 50% respectively. The estimated petrophysical parameters and lithology are validated with limited core samples and cutting samples from five wells under the study area. 相似文献
2.
裂缝性碳酸盐岩储层声波时差曲线的波动和增幅分析 总被引：2，自引：2，他引：0
研究了裂缝性碳酸盐岩储层声波时差曲线的波动和增幅现象,认为是裂缝对声波的衰减导致到达远接收器的初至波幅度降低,因而形成3～4μs/ft的时差增幅,从而有效解释了声波时差曲线的波动和增幅现象。利用成像资料和常规测井资料相结合,研究增幅发生条件和规律,发现低角度、较大开度的裂缝导致时差增幅。 相似文献
3.
Source rock potential (TOC + hydrogen index) evaluation by integrating well log and geochemical data 总被引：1，自引：0，他引：1
Evaluation of source rock potential using well log data alone, e.g. density or sonic log, is limited to the assessment of total organic carbon (TOC) content. Well logs that directly measure the most important source quality parameter, the hydrogen content of the kerogen, do not exist. Therefore, a method is proposed that combines log-derived TOC data with calibration schemes relating TOC content to Hydrogen Index and maturity for individual source rock sets. The method has been applied to the compositionally heterogeneous Kimmeridge Clay Formation of the North Sea and the homogeneous Lower Toarcian Shale of N.-Germany. The combination of well log and geochemical data greatly improves the accuracy with which the lateral and vertical distribution of source rocks and their potential can be predicted on a basin and prospect level. 相似文献
4.
Factor analysis of borehole logs for evaluating formation shaliness: a hydrogeophysical application for groundwater studies 总被引：1，自引：1，他引：0
The calculation of groundwater reserves in shaly sand aquifers requires a reliable estimation of effective porosity and permeability; the amount of shaliness as a related quantity can be determined from well log analysis. The conventionally used linear model, connecting the natural gamma-ray index to shale content, often gives only a rough estimate of shale volume. A non-linear model is suggested, which is derived from the factor analysis of well-logging data. An earlier study of hydrocarbon wells revealed an empirical relationship between the factor scores and shale volume, independent of the well site. Borehole logs from three groundwater wells drilled in the northeastern Great Hungarian Plain are analyzed to derive depth logs of factor variables, which are then correlated with shale volumes given from the method of Larionov. Shale volume logs derived by the statistical procedure are in close agreement with those derived from Larionov’s formula, which confirms the validity of the non-linear approximation. The statistical results are in good accordance with laboratory measurements made on core samples. Whereas conventional methods normally use a single well log as input, factor analysis processes all available logs to provide groundwater exploration with reliable estimations of shale volume. 相似文献
5.
利用测井数据与地震数据二者相结合进行综合分析,是地震勘探工作者的重要工作。可以通过分析井位处的地震数据与测井数据,提取地震的多个属性,建立一个与测井属性的统计关系。选取已改进的三层网络结构BP神经网络算法,在应用一个实际例子后表明,该算法的主要特点是收敛速度快、计算简单,同时还具有跳出局部最小的能力。应用此神经网络算法对某油田的二维地震数据进行了处理,提取了多种地震属性,并在井位置建立了地震属性与密度曲线的非线性关系,成功预测了剖面密度曲线,为了解储层状况提供了有益的资料。 相似文献
6.
7.
8.
可压裂性是页岩在水力压裂中具有能够被有效压裂的能力的性质,是页岩开发中最关键的评价参数,影响因素包括页岩脆性、天然裂缝、石英含量、成岩作用及其他因素,目前常利用页岩矿物组成或岩石力学参数来表征,难以全面反映页岩在水力压裂过程中的综合性质。采用极差变换和经验赋值方法将参数标准化,使用层次分析法确定不同因数对可压裂性影响的权重,使用标准化值与权重系数加权得到可压裂系数的数学模型可对页岩可压裂性进行定量评价。可压裂系数越大,页岩可压裂性越强。采用该模型计算渝东南地区渝页1井龙马溪组页岩可压裂系数为0.485 5,Barnett页岩可压裂系数为0.484 4,总体处于同一水平;同时,使用该模型将页岩可压裂性分为3个级别,可压裂系数在0.132 0~0.282 0的页岩可压裂性低,水力压裂效果不佳;可压裂系数在0.282 0~0.456 7的页岩可压裂性中等,水力压裂能够取得较好的效果;可压裂系数在0.456 7~0.784 0的页岩可压裂性高,是优质的可压裂层。水力压裂应选择可压裂系数大于0.360 7的页岩。 相似文献
9.
Vijai Kumar Baskaran Suresh Kumar Govindarajan Kamal Chandra Dani Mandhir Kumar 《Journal of the Geological Society of India》2017,90(3):312-322
A study on the sedimentary facies characterization and depositional environment interpretations for the K#Field (K-Oil Field) in Cambay petroleum basin of western onshore, India was conducted based on the sub-surface data from drilled wells, including well logs, borehole images, cores and the regional knowledge of the basin. In this work, an effort is made to integrate the current data from seismics and well logging, to study and analyze its depositional environments and establish the petroleum systems. The study regions for the present work are K45 and K48 blocks. The target strata includes 2 oil-bearing formations of Paleogene, which is about 3600 ft; they are M#Fm (M-Formation) of the Eocene and N#Fm (N-Formation) of Oligocene, subdivided into 11 zones. The sediment fill is mostly of Tertiary. The research attempts to decipher the oil - depositional source correlation problems of the basin. Sedimentary models were established referring to the core analysis, core photographs and well logs. Reservoir and heterogeneity study included reservoir lithology features, physical properties and pore structure features.Well facies analysis of oil well WELL-0297 and WELL-0129 was done and the results were analyzed for further drilling of new wells for oil and gas exploration. The study found that the Eocene, Oligocene, Miocene and Paleogene are fluviatile facies sand and mud interbed sediment with the thickness 2000-4000 ft, which are main oil-bearing formations in these areas. Studies concluded that the fluvial reservoirs of the K#Field are characterized by large variations from laterally extensive bodies with good interconnectedness and high net-to-gross ratios, multi-storey ribbon bodies with poor interconnections and low net-to-gross ratios. 相似文献
10.
分析了岩石的孔隙和孔隙结构与岩石的成分尤其是泥质和粘土之间的密切联系,并从常规测井、核磁测井反映的孔隙度、泥质含量等参数入手,研究建立了常规测井资料划分三种孔隙组分的理论和实现方法,结合实际测井资料,对这些方法进行了检验。实例表明,根据该理论和方法确定的储层的三孔隙组分——粘土水孔隙、微孔隙水孔隙以及自由水孔隙组分可以取得较好的效果。 相似文献
11.
水平井分段体积压裂是页岩气商业规模开发的重要工艺措施,如何评价页岩储层可压性是该工艺成功的关键。页岩断裂韧性是可压性评价的重要支撑参数,从I型断裂裂纹（裂缝）微观形态入手,结合断裂力学理论和分形理论,建立了页岩I型断裂韧性分形计算方法;借助晶体劈裂功法计算页岩表面能,采用密度、声波时差2种参数获取计算结果,对比分析新的分形方法计算数据、传统方法预测数据与试验测试数据,新的分形方法计算平均误差为3.63%,传统预测方法平均误差为 %,验证了方法的准确性;参考实例水平井测井解释数据,计算了水平段I型断裂韧性指数的全井筒连续性剖面,结合可压性级别与较大储层改造体积概率关系,优选可压性级别为III级及II级改造。建立的页岩I型断裂韧性分形计算方法对定量评价页岩储层可压性具有重要意义。 相似文献
12.
井间断裂构造分析是根据测井资料,以地层分层数据为基础,利用计算机技术实现井间断裂分析的一种计算机自动分析方法.动态波形匹配算法能够很好地建立井间地层之间的对比关系,可以通过曲线拟合、特征提取、匹配代价计算等步骤,自动绘制井间地层对比的路径图解.通过对各种构造的路径图分析,总结出正断层、逆断层、不整合、同沉积断层、犁式断层和地层尖灭等34种情况下的路径图模式,提出路径图模式及相关概念. 相似文献
13.
作为新兴的测井仪器,岩性扫描测井（LithoScanner）通过获取地层元素含量,进一步获得地层矿物含量,帮助地质学家解决复杂岩性识别等地质学难题。为了充分推广其在地质学领域的应用, 笔者等对岩性扫描测井的原理和解释处理流程进行梳理,并对应用过程中出现的典型案例进行分析。LithoScanner测井可直接获取地层岩性特征,帮助识别地层界面,并实现页岩等复杂岩性、岩相的准确识别。而脆性矿物含量、有机碳含量等也可被LithoScanner测井准确获取,从而计算地层中的脆性指数和有机碳的含量。LithoScanner测井可以探测黄铁矿、煤层等特殊矿物组分,因此可以辅助核磁共振测井资料解释评价。最后指出LithoScanner测井与相应的岩芯和实验数据进行比对,提高LithoScanner测井的可靠性。研究有助于将LithoScanner测井中蕴含的大量地质信息进行挖掘与解读,并消除该资料应用中的一些误区,从而推广LithoScanner测井应用领域。 相似文献
14.
一体化地质建模在新近系礁灰岩储层定量表征中的应用 总被引：3，自引：1，他引：2
以LH油田三维地质建模为实例,针对礁灰岩储层内部结构复杂的情况,提出了一种综合应用地震、测井及地质资料进行礁灰岩储层研究和地质建模的方法。LH油田主要含油层段为中新统珠江组礁灰岩,储层为台地边缘生物礁相,储层内部结构复杂。以井震资料为基础,以生物礁沉积过程和成岩作用为指导,对礁体内部结构进行了分析,预测了主力油层内部的差物性层空间展布。在地质模式、井点信息和地震属性约束下,采用随机模拟的手段,建立了地质模型,实现了多学科综合的储层定量表征,对无井区储层特征进行了预测,为开发方案的设计提供了地质依据。 相似文献
15.
Spectral studies of geologic logs demonstrate that automatic well—log correlation can be processed more efficiently in the frequency domain. Cross correlation of the power spectra of well logs identifies the direction and degree of thickening of stratigraphic sequences between two wells. Given the stretch, the displacement between logs is computed by correlation processes without relying on iterative procedures. Beginning with digitized log data of unequal lengths, power spectra are computed. The stretch factor between the two logs is observed as a difference in frequency scaling. A transform to logarithmic frequencies converts the spectra to a form that reduces the scaling effect of the frequencies to a simple displacement between the plots. A Lagrange interpolation procedure permits cross correlation of the two spectra with a variable window size. The peak value of the resultant correlation function identifies the displacement between the spectra and this, in turn, permits calculation of the stretch factor. 相似文献
16.
17.
Ghasem Aghli Bahman Soleimani Sayed Salman Tabatabai Iman Zahmatkesh 《Arabian Journal of Geosciences》2017,10(12):265
Evaluation of fractures and their parameters, such as aperture and density, is necessary in the optimization of oil production and field development. The purpose of this study is the calculation of fracture parameters in the Asmari reservoir using two electrical image logs (FMI, EMI), and the determination of fracture parameters’ effect on the porosity and permeability using thin sections and velocity deviation log (VDL). The results indicate that production in the Asmari reservoir is a combination of fractures and rock matrix. Fracture aperture (VAH) and fracture porosity (VPA) are only measurable with core and image logs directly. However, regarding core limitations, the image log has been recognized as the best method for fracture parameter determination due to their high resolution (2.5 mm). In this study, VDL log and thin sections have been used as auxiliary methods which may be available in all wells. The VDL log provides a tool to obtain downhole information about the predominant pore type in carbonates. Results indicate that between fracture parameters, VAH is considered as the most important parameter for determining permeability. For well No. 3, VAH ranges from minimum 51 × 10?5 mm to maximum 0. 047 mm and VPA changes from min 10?5% to maximum 0.02056%. For well No. 6, VAH varies from 5 × 10?4 to 0.0695 mm and VPA varies from 10?5 to 0.015%. Therefore, due to high fracture density and fracture aperture, it seems that most of effective porosity originates from fractures especially in well No. 3. However, VDL for well No. 6 indicates that intercrystalline and vuggy porosity are the dominant porosity. This result may be an indication for fracture set diversity in the two studied wells. While in well No. 3, they related to the folding and active faults, in well No. 6 they are only of folding type. Furthermore, results indicate the high capability for both of EMI and FMI image logs for calculation of fracture and vug parameters in the carbonate reservoirs. 相似文献
18.
Drought over a period threatens the water resources, agriculture, and socioeconomic activities. Therefore, it is crucial for decision makers to have a realistic anticipation of drought events to mitigate its impacts. Hence, this research aims at using the standardized precipitation index (SPI) to predict drought through time series analysis techniques. These adopted techniques are autoregressive integrating moving average (ARIMA) and feed-forward backpropagation neural network (FBNN) with different activation functions (sigmoid, bipolar sigmoid, and hyperbolic tangent). After that, the adequacy of these two techniques in predicting the drought conditions has been examined under arid ecosystems. The monthly precipitation data used in calculating the SPI time series (SPI 3, 6, 12, and 24 timescales) have been obtained from the tropical rainfall measuring mission (TRMM). The prediction of SPI was carried out and compared over six lead times from 1 to 6 using the model performance statistics (coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE)). The overall results prove an excellent performance of both predicting models for anticipating the drought conditions concerning model accuracy measures. Despite this, the FBNN models remain somewhat better than ARIMA models with R?≥?0.7865, MAE?≤?1.0637, and RMSE?≤?1.2466. Additionally, the FBNN based on hyperbolic tangent activation function demonstrated the best similarity between actual and predicted for SPI 24 by 98.44%. Eventually, all the activation function of FBNN models has good results respecting the SPI prediction with a small degree of variation among timescales. Therefore, any of these activation functions can be used equally even if the sigmoid and bipolar sigmoid functions are manifesting less adjusted R2 and higher errors (MAE and RMSE). In conclusion, the FBNN can be considered a promising technique for predicting the SPI as a drought monitoring index under arid ecosystems. 相似文献
19.
Zhang Tuanfeng McCormick David Nandlal Allan Lefranc Marie 《Mathematical Geosciences》2021,53(5):925-944
Horizontal wells dominate the development of unconventional shale reservoirs. Using real time drilling data to steer in a target zone is the key to economic success. Today structural interpretation in unconventional horizontal wells is a manual process that is time-consuming, tedious, and error-prone, especially because gamma-ray (GR) logs are commonly the only available logging-while-drilling data. For the first time, a method named TST3D is developed to automate interpretation of subsurface structure. TST3D (true stratigraphic thickness in three-dimensional space) automates structural interpretation using pattern recognition. Given an initial structural model, TST3D automatically computes true stratigraphic thickness (TST) as the shortest distance from each wellbore survey location to the initial surface, then matches GR patterns in the horizontal well to those seen in a vertical pilot well in TST domain. TST3D inserts fold hinges, bends the structure, then recomputes the modeled GR response, progressively matching the pilot well log signature, from heel to toe in the horizontal well. There are three assumptions in the current version of TST3D: constant layer thickness across the drilled interval, GR variation follows stratigraphic layering, and no faults are present in the drilled section. Those assumptions are reasonable in most shale plays. The TST3D method can be applied in either a post-drill mode for structural interpretation or real-time mode for aiding geosteering. Field tests in different shale plays and complex well trajectories demonstrate that TST3D runs quickly: a structural model of a 10,000-ft horizontal section can be computed in minutes, and a real-time update of 100 ft of new data takes less than a minute. Automating the geosteering correlation process would allow well placement engineers to cover multiple wells simultaneously, increasing the efficiency of the team while potentially improving service quality.
相似文献20.
准确预测碳酸盐岩储层孔隙度和渗透率对于碳酸盐岩油气藏储层评价具有重要意义。碳酸盐岩储层裂缝与溶孔广泛发育,基于经验公式从测井曲线预测储层孔隙度和渗透率具有较大误差。以中东某碳酸盐岩油藏为研究对象,选取914块取心井岩心,测定孔隙度与渗透率,利用随机森林（RF）、K-近邻（KNN）、支持向量机（SVM）和长短期记忆网络（LSTM）4种不同机器学习方法,通过测井数据进行孔隙度与渗透率预测,优化机器学习参数,筛选出适用于碳酸盐岩油藏的测井孔隙度与渗透率预测方法。研究结果表明：4种机器学习方法预测储层孔隙度结果差异不大,通过调整输入参数种类,可进一步提高孔隙度与渗透率预测效果,当以补偿中子（NPHI）、岩性密度（RHOB）和声波时差（DT）3种测井参数数据作为输入时,基于LSTM的储层孔隙度预测精度最高,孔隙度预测结果均方根误差（RMSE）为4.536 2;由于碳酸盐岩储层的强非均质性,基于机器学习的测井储层渗透率预测效果较差,相对而言,仅以NPHI作为机器学习输入参数时,基于RF的储层渗透率预测精度最高,渗透率预测结果的RMSE为45.882 3。 相似文献