首页> 外文期刊>Petrophysics: The SPWLA Journal of Formation Evaluation and Reservoir Description >Application and Quality Control of Core Data for the Development and Validation of Elemental Spectroscopy Log Interpretation
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Application and Quality Control of Core Data for the Development and Validation of Elemental Spectroscopy Log Interpretation

机译:核心数据在元素光谱测井解释开发和验证中的应用和质量控制

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Core or cuttings samples are often analyzed for chemical and mineral composition to provide ground truth for developing petrophysical or geological applications or for validating log interpretations of elemental concentrations, mineralogy, and matrix properties. Unfortunately, some core data are inaccurate, but they are rarely subjected to quality-control measures and can therefore lead to erroneous conclusions regarding the validity of the log data.For core data, elemental concentrations are generally measured by X-ray fluorescence (XRF) or inductively coupled plasma (ICP) techniques. The best way to validate results from these techniques is to test certified reference materials that are composed of sedimentary minerals similar in composition to samples of interest. Core mineralogy is most commonly analyzed by X-ray diffraction (XRD) or Fourier-transform infrared spectroscopy (FTIR). Laboratory results can be evaluated by analyzing known mixtures of certified minerals.Once it has been established that sources of accurate core elemental concentrations and mineralogy are available, it is advisable to implement routine quality-control monitoring. An example of a quality-control measure is a technique that requires independent analyses for elemental and mineral concentrations. The technique assumes that the minerals have fixed elemental compositions. Measured mineralogy is used to compute elemental concentrations of the major elements, including Si, Al, K, Fe, S, Ca, Mg, and Na. Derived elemental concentrations are compared with the measured elemental concentrations. Deviations between the derived and measured concentrations are used to evaluate the quality of the input data. Examples of both good and poor inputs for elemental and mineral data are shown. Once the quality of the data is proved to be good, it is possible to use the data to validate the accuracy of interpretations developed for elemental spectroscopy logs, such as the closure model to convert concentrations to yields and models to interpret mineralogy.
机译:通常对岩心或岩屑样品进行化学和矿物成分分析,为开发岩石物理或地质应用或验证元素浓度,矿物学和基质性质的对数解释提供地面依据。不幸的是,一些核心数据不准确,但很少接受质量控制措施,因此可能导致关于测井数据有效性的错误结论。对于核心数据,元素浓度通常通过X射线荧光(XRF)测量或电感耦合等离子体(ICP)技术。验证这些技术结果的最佳方法是测试经认证的参考材料,这些材料由与目标样品相似的沉积矿物组成。核心矿物学最常通过X射线衍射(XRD)或傅里叶变换红外光谱(FTIR)进行分析。可以通过分析已知的合格矿物混合物来评估实验室结果。一旦确定可获得准确的核心元素浓度和矿物学来源,建议进行常规质量控制监测。质量控制措施的一个示例是需要对元素和矿物质浓度进行独立分析的技术。该技术假定矿物具有固定的元素组成。测得的矿物学用于计算主要元素的元素浓度,包括Si,Al,K,Fe,S,Ca,Mg和Na。将得出的元素浓度与测得的元素浓度进行比较。导出浓度和测量浓度之间的差异用于评估输入数据的质量。给出了元素和矿物数据的好坏输入示例。一旦证明数据质量良好,就可以使用该数据来验证为元素光谱测井开发的解释的准确性,例如将浓度转换为产率的封闭模型和解释矿物学的模型。

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