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Different parameters obtained through well-logging geophysical sensors such as SP, resistivity, gamma–gamma, neutron, natural gamma and acoustic, help in identification of strata and estimation of the physical, electrical and acoustical properties of the subsurface lithology. Strong and conspicuous changes in some of the log parameters associated with any particular stratigraphy formation, are function of its composition, physical properties and help in classification. However some substrata show moderate values in respective log parameters and make difficult to identify or assess the type of strata, if we go by the standard variability ranges of any log parameters and visual inspection. The complexity increases further with more number of sensors involved.An attempt is made to identify the type of stratigraphy from borehole geophysical log data using a combined approach of neural networks and fuzzy logic, known as Adaptive Neuro-Fuzzy Inference System. A model is built based on a few data sets (geophysical logs) of known stratigraphy of in coal areas of Kothagudem, Godavari basin and further the network model is used as test model to infer the lithology of a borehole from their geophysical logs, not used in simulation. The results are very encouraging and the model is able to decipher even thin cola seams and other strata from borehole geophysical logs. The model can be further modified to assess the physical properties of the strata, if the corresponding ground truth is made available for simulation. 相似文献
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塔河油田碳酸盐岩缝洞型储层的测井识别与评价方法研究 总被引：12，自引：4，他引：12
塔河油田奥陶系以碳酸盐岩为主，油气的主要储渗空间为裂缝和溶蚀孔洞，具有很强的非均质性．本文利用常规及成像测井资料，对碳酸盐岩缝洞型储层的识别与评价方法进行研究．为了综合各种测井方法识别裂缝，建立了综合裂缝概率模型，计算综合裂缝概率指示裂缝的发育程度．利用地层微电阻率扫描成像测井资料进行裂缝和溶蚀孔洞的定性、定量解释．定量计算的裂缝参数为：裂缝密度、裂缝长度、裂缝平均宽度、平均水动力宽度、裂缝视孔隙度；定量计算的溶蚀孔洞参数有：面孔率、孔洞密度．根据缝洞型储层孔隙空间类型及其中子孔隙度、补偿密度、声波、双侧向电阻率的测井响应物性特征，建立缝洞型碳酸盐岩储层复杂孔隙介质解释模型，用于确定裂缝、溶蚀孔洞孔隙度和评价储层． 相似文献
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伽马射线与地层介质的康普顿（Ｃｏｍｐｔｏｎ）效应是密度测井的理论基础，介质对伽马射线的康普顿吸收系数取决于介质的原子核性质及其体积密度．（超热或热）中子测井主要反映地层介质的减速性质，而后者主要取决于介质的含氢量．介质含氢量是由介质的组分及其体积密度决定的．本文从上述两种测井方法的测量原理出发，从理论上证明了这两种测井方法并非两种互相独立的测量手段．对于含油气盆地常见沉积岩石及矿物，两种测井测量结果具有相关性．这一结论为密度、中子测井方法组合地质应用提供了理论依据，利用密度－中子测井的相关性可有效地识别轻质油气层特别是天然气层．实例表明，无论水层还是油气层，两种测井曲线均具有良好的相关性．利用这种相关性明显改善了识别天然气层和划分油－气界面的精度． 相似文献
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伽马射线与地层介质的康普顿（Ｃｏｍｐｔｏｎ）效应是密度测井的理论基础，介质对伽马射线的康普顿吸收系数取决于介质的原子核性质及其体积密度．（超热或热）中子测井主要反映地层介质的减速性质，而后者主要取决于介质的含氢量．介质含氢量是由介质的组分及其体积密度决定的．本文从上述两种测井方法的测量原理出发，从理论上证明了这两种测井方法并非两种互相独立的测量手段．对于含油气盆地常见沉积岩石及矿物，两种测井测量结果具有相关性．这一结论为密度、中子测井方法组合地质应用提供了理论依据，利用密度－中子测井的相关性可有效地识别轻质油气层特别是天然气层．实例表明，无论水层还是油气层，两种测井曲线均具有良好的相关性．利用这种相关性明显改善了识别天然气层和划分油－气界面的精度． 相似文献
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Fuzzy logic has been used for lithology prediction with remarkable success. Several techniques such as fuzzy clustering or linguistic reasoning have proven to be useful for lithofacies determination. In this paper, a fuzzy inference methodology has been implemented as a MATLAB routine and applied for the first time to well log data from the German Continental Deep Drilling Program (KTB). The training of the fuzzy inference system is based on the analysis of the multi-class Matthews correlation coefficient computed for the classification matrix. For this particular data set, we have found that the best suited membership function type is the piecewise linear interpolation of the normalized histograms; that the best combination operator for obtaining the final lithology degrees of membership is the fuzzy gamma operator; and that all the available properties are relevant in the classification process. Results show that this fuzzy logic-based method is suited for rapidly and reasonably suggesting a lithology column from well log data, neatly identifying the main units and in some cases refining the classification, which can lead to a better interpretation. We have tested the trained system with synthetic data generated from property value distributions of the training data set to find that the differences in data distributions between both wells are significant enough to misdirect the inference process. However, a cross-validation analysis has revealed that, even with differences between data distributions and missing lithologies in the training data set, this fuzzy logic inference system is able to output a coherent classification. 相似文献
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针对塔里木盆地库车坳陷北部侏罗系烃源岩受泥浆污染、分析数据少、样品分布不连续及类型多样等问题突出,利用测井资料来对有机地球化学参数进行评价难度大,无法满足勘探需求.本文阐述了不同类型烃源岩的有机质级别、测井响应特征、有机地球化学参数定量计算及品质评价等多种方法,来研究富集区烃源岩对致密气储层的持续供气能力.文中介绍了煤层、碳质泥岩、暗色泥岩等3种类型烃源岩的有机质级别和测井响应特征.首先,提出分不同岩性烃源岩的ΔlogR法,其计算结果与铀曲线相关法、多元回归法对比,效果最好;再次建立了生烃潜率、氯仿沥青“A”及镜质体发射率等多个有机质地球化学参数的测井评价模型;最终,考虑能够反映烃源岩性质的参数来综合定义烃源岩品质指数,形成了完善的烃源岩测井综合评价方法研究技术.研究表明,利用这套地球物理技术提供了烃源岩定量评价和品质分类研究方法及实际应用案例. 相似文献
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By substituting rock skeleton modulus expressions into Gassmann approximate fluid equation, we obtain a seismic porosity inversion equation. However, conventional rock skeleton models and their expressions are quite different from each other, resuling in different seismic porosity inversion equations, potentially leading to difficulties in correctly applying them and evaluating their results. In response to this, a uniform relation with two adjusting parameters suitable for all rock skeleton models is established from an analysis and comparison of various conventional rock skeleton models and their expressions including the Eshelby-Walsh, Pride, Geertsma, Nur, Keys-Xu, and Krief models. By giving the two adjusting parameters specific values, different rock skeleton models with specific physical characteristics can be generated. This allows us to select the most appropriate rock skeleton model based on geological and geophysical conditions, and to develop more wise seismic porosity inversion. As an example of using this method for hydrocarbon prediction and fluid identification, we apply this improved porosity inversion, associated with rock physical data and well log data, to the ZJ basin. Research shows that the existence of an abundant hydrocarbon reservoir is dependent on a moderate porosity range, which means we can use the results of seismic porosity inversion to identify oil reservoirs and dry or water-saturated reservoirs. The seismic inversion results are closely correspond to well log porosity curves in the ZJ area, indicating that the uniform relations and inversion methods proposed in this paper are reliable and effective. 相似文献
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Compressional-wave (Vp) data are key information for estimation of rock physical properties and formation evaluation in hydrocarbon reservoirs. However, the absence of Vp will significantly delay the application of specific risk-assessment approaches for reservoir exploration and development procedures. Since Vp is affected by several factors such as lithology, porosity, density, and etc., it is difficult to model their non-linear relationships using conventional approaches. In addition, currently available techniques are not efficient for Vp prediction, especially in carbonates. There is a growing interest in incorporating advanced technologies for an accurate prediction of lacking data in wells. The objectives of this study, therefore, are to analyze and predict Vp as a function of some conventional well logs by two approaches; Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multiple Linear Regression (MLR). Also, the significant impact of selected input parameters on response variable will be investigated. A total of 2156 data points from a giant Middle Eastern carbonate reservoir, derived from conventional well logs and Dipole Sonic Imager (DSI) log were utilized in this study. The quality of the prediction was quantified in terms of the mean squared error (MSE), correlation coefficient (R-square), and prediction efficiency error (PEE). Results show that the ANFIS outperforms MLR with MSE of 0.0552, R-square of 0.964, and PEE of 2%. It is posited that porosity has a significant impact in predicting Vp in the investigated carbonate reservoir. 相似文献
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Predicting reservoir parameters, such as porosity, lithology, and saturations, from geophysical parameters is a problem with non‐unique solutions. The variance in solutions can be extensive, especially for saturation and lithology. However, the reservoir parameters will typically vary smoothly within certain zones—in vertical and horizontal directions. In this work, we integrate spatial correlations in the predicted parameters to constrain the range of predicted solutions from a particular type of inverse rock physics modelling method. Our analysis is based on well‐log data from the Glitne field, where vertical correlations with depth are expected. It was found that the reservoir parameters with the shortest depth correlation (lithology and saturation) provided the strongest constraint to the set of solutions. In addition, due to the interdependence between the reservoir parameters, constraining the predictions by the spatial correlation of one parameter also reduced the number of predictions of the other two parameters. Moreover, the use of additional constraints such as measured log data at specific depth locations can further narrow the range of solutions. 相似文献
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A parameter-estimation technique based on existing hydrological, geophysical, and geological data was developed to approximate transmissivity values for use in a ground-water flow model of the Animas Valley, southwest New Mexico. Complete Bouguer gravity anomaly maps together with seismic-refraction profiles, geologic maps, geologic, geophysical, and drillers' logs, water levels, and pumping-test data provide insight into the transmissivity of bolson deposits throughout the basin. The transmissivity distribution was primarily based on reported pumping and specific-capacity tests in conjunction with complete Bouguer gravity anomaly maps and well log data. Reported transmissivity values were characterized by gravity values and well log data. In grid blocks lacking pumping and specific-capacity tests, transmissivity values were assigned based on the relationship of gravity values and well log data within the grid block to gravity values and well log data within other grid blocks for which transmissivity values are available. A two-dimensional, finite-difference, ground-water flow computer code was used to evaluate the effectiveness of the parameter-estimation technique. Although the trial-and-error method of calibration was employed, the actual computer time necessary for model calibration was minimal. The conceptually straightforward approach for parameter estimation utilizing existing hydrological, geophysical, and geological data provides realistic parameter estimates. 相似文献
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在定向井及水平井钻井过程中,常采用地质导向技术;地质导向的关键在于实时确定地层界面和产状、实现地层模型的实时更新和井眼轨迹的及时调整,从而最大限度地提高油层的钻遇率.利用基于地层模型的测井响应正演曲线与随钻测井曲线进行对比是确定地层界面的有效方法;本文基于伽马射线在地层中的衰减规律,导出了不同地层模型中随钻伽马测井响应快速正演算法,克服了目前难以将蒙特卡罗算法用于实时随钻伽马测井正演的困难.应用实例表明该方法可以有效地辅助实时判定实际地层界面,更好地实现地质导向. 相似文献
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Free fluid porosity and rock permeability, undoubtedly the most critical parameters of hydrocarbon reservoir, could be obtained by processing of nuclear magnetic resonance (NMR) log. Despite conventional well logs (CWLs), NMR logging is very expensive and time-consuming. Therefore, idea of synthesizing NMR log from CWLs would be of a great appeal among reservoir engineers. For this purpose, three optimization strategies are followed. Firstly, artificial neural network (ANN) is optimized by virtue of hybrid genetic algorithm-pattern search (GA-PS) technique, then fuzzy logic (FL) is optimized by means of GA-PS, and eventually an alternative condition expectation (ACE) model is constructed using the concept of committee machine to combine outputs of optimized and non-optimized FL and ANN models. Results indicated that optimization of traditional ANN and FL model using GA-PS technique significantly enhances their performances. Furthermore, the ACE committee of aforementioned models produces more accurate and reliable results compared with a singular model performing alone. 相似文献
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The saturation in water or hydrocarbon is an important petrophysical parameter used for the evaluation of oil and gas reservoirs. It represents the amount of hydrocarbons in a reservoir. There are many relations to determine the water saturation from well logs by using the physical properties of rocks. The accurate determination of the hydrocarbon formation or the water saturation is given by the accuracy of the parameters used for calculating and by the relations used. 相似文献
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洪泽地区由于沉积的特点，储层横向变化快，油藏受构造、岩性、油源多因素控制。在对该区三维AVO属性体解释中，利用多元回归方法求取了横波曲线，分岩性和含油气性统计了纵、横波、泊松比参数分布规律，建立了本区的含油砂岩的正演模型，从而降低了AVO解释的多解性。通过井-震结合对四种AVO属性数据体进行了标定，并确定了各属性体应用范围，进而进行了储层和含油气检测。实践表明，该方法能有效地利用AVO属性数据体进行储层预测及油气检测，具有一定的推广价值。 相似文献
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James T. Mickam Benjamin S. Levy George W. Lee Jr. 《Ground Water Monitoring & Remediation》1984,4(4):167-171
Ground water flow in karst terranes generally occurs in the solution channels of carbonate aquifers. A hydrogeologist may utilize borehole geophysical methods to identify these solution channels in aquifers. Two specific methods that are applicable in karst terrains are:
1. Natural gamma ray logging
2. Borehole caliper logging.
Gamma ray logging can detect the presence of inter-bedded strata in the main limestone unit, such as shale, which emit high levels of gamma radiation. Gamma ray logging can also detect clay deposits in solution channels that may act to restrict the flow of ground water. The areal extent of these rock strata or clay-filled solution channels can be determined when gamma ray logs are conducted at several borehole locations across the site of investigation.
Borehole caliper logging can be employed to determine the presences of solution channels within the aquifer when penetrated by a borehole. In addition, since shale layers and clay filling are less resistant than the surrounding limestone, the caliper log may detect both the presence and the thickness of shale or clay layers in the aquifer.
Gamma ray logs can be used in conjunction with caliper logs to provide data on the stratigraphic location and thickness of solution channels and clay and shale layers within a limestone aquifer. This information is valuable to the hydrogeologist performing investigations at sites located in limestone terranes because ground water flow preferentially occurs along solution channels. 相似文献
1. Natural gamma ray logging
2. Borehole caliper logging.
Gamma ray logging can detect the presence of inter-bedded strata in the main limestone unit, such as shale, which emit high levels of gamma radiation. Gamma ray logging can also detect clay deposits in solution channels that may act to restrict the flow of ground water. The areal extent of these rock strata or clay-filled solution channels can be determined when gamma ray logs are conducted at several borehole locations across the site of investigation.
Borehole caliper logging can be employed to determine the presences of solution channels within the aquifer when penetrated by a borehole. In addition, since shale layers and clay filling are less resistant than the surrounding limestone, the caliper log may detect both the presence and the thickness of shale or clay layers in the aquifer.
Gamma ray logs can be used in conjunction with caliper logs to provide data on the stratigraphic location and thickness of solution channels and clay and shale layers within a limestone aquifer. This information is valuable to the hydrogeologist performing investigations at sites located in limestone terranes because ground water flow preferentially occurs along solution channels. 相似文献
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Estimating thermal conductivity from core and well log data 总被引：1，自引：1，他引：0
The aim of the presented work was to introduce a method of estimating thermal conductivity using well log data. Many petrophysical properties of rocks can be determined both by laboratory measurements and well-logs. It is thus possible to apply geophysical data to empirical models based on relationships between laboratory measured parameters and derive continuous thermal conductivity values in well profiles. Laboratory measurements were conducted on 62 core samples of Meso-Paleozoic rocks from the Carpathian Foredeep. Mathematical models were derived using multiple regression and neural network methods. Geophysical data from a set of seven well logs: density, sonic, neutron, gamma ray, spectral gamma ray, caliper and resistivity were applied to the obtained models. Continuous thermal conductivity values were derived in three well profiles. Analysis of the obtained results shows good consistence between laboratory data and values predicted from well log data. 相似文献
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基于频变AVO技术对多尺度裂缝内流体属性反演与识别（英文） 总被引：5，自引：3，他引：2
通过地震数据获取裂缝储藏中流体的性质并对流体类型进行识别,是地震勘探岩性反演的重要问题之一。由于地震波的速度、储层的密度等弹性参数对某些流体不具有很强的敏感性,使只依赖振幅信息进行流体识别的传统AVO方法面临困境。作为传统叠前振幅反演的一个拓展,频变AVO（FDAVO）技术进一步考虑了振幅对频率的依赖关系,将这种依赖关系与地下裂缝结构、流体填充对应起来,能带来更丰富的流体信息。利用该技术,本文提出了一种基于地震数据参数化Chapman模型的贝叶斯反演新方法（BIDCMP）,它包含两步算法,即,FDAVO反演储层的非弹性属性和贝叶斯框架下的流体识别。首先,通过匹配观测数据和模型数据,构造差函数反演裂缝储层非弹性参数。随后,在贝叶斯框架下,使用马尔科夫随机场（MRF）作为先验模型,联合多参数场识别流体。本方法在计算过程中,除综合考虑了弹性参数场、测井资料等常规信息外,还特别地加人了第一步中反演得的非弹性参数的约束,从而充分利用了流体粘性差异,最后在最大后验概率（MAP）准则下输出最佳岩性一流体识别结果。分别对合成地震记录和模拟岩性—流体剖面验证本文方法的有效性,结果证明本文方法获得的流体识别结果准确可信。 相似文献