张君龙, 汪爱云, 何香香. 古城地区碳酸盐岩岩性及微相测井识别方法[J]. 石油钻探技术, 2016, 44(3): 121-126. DOI: 10.11911/syztjs.201603022
引用本文: 张君龙, 汪爱云, 何香香. 古城地区碳酸盐岩岩性及微相测井识别方法[J]. 石油钻探技术, 2016, 44(3): 121-126. DOI: 10.11911/syztjs.201603022
ZHANG Junlong, WANG Aiyun, HE Xiangxiang. Carbonate Lithology and Microfacies Logging Identification in the Gucheng Area[J]. Petroleum Drilling Techniques, 2016, 44(3): 121-126. DOI: 10.11911/syztjs.201603022
Citation: ZHANG Junlong, WANG Aiyun, HE Xiangxiang. Carbonate Lithology and Microfacies Logging Identification in the Gucheng Area[J]. Petroleum Drilling Techniques, 2016, 44(3): 121-126. DOI: 10.11911/syztjs.201603022

古城地区碳酸盐岩岩性及微相测井识别方法

Carbonate Lithology and Microfacies Logging Identification in the Gucheng Area

  • 摘要: 碳酸盐岩沉积相系统刻画及相关研究受到岩石样品有限的制约,为了充分发挥测井曲线高分辨率、信息量丰富的优势,开展了古城地区碳酸盐岩岩性及微相测井识别方法研究。在利用岩样确定的微相类型对测井曲线进行标定的基础上,依据常规测井参数与碳酸盐岩岩性、微相的响应关系,优选出DEN、DT、PE和U、Th、K等敏感测井曲线,进行新的参数组合,建立了岩性识别及微相识别图版,符合率分别为85.4%和81.4%。另外,建立函数关系将各微相类型按照沉积能量进行量化分类,并给出微相能量参数曲线。该方法识别出的微相及其能量参数曲线在相带及沉积旋回的空间划分对比的应用中,符合典型碳酸盐岩沉积模式中的相序组合及沉积能量分布特征,与岩石薄片典型相标志所确定的沉积相带一致。该识别方法的应用效果较好,可以作为沉积相精细研究的重要补充手段。

     

    Abstract: Due to limited availability of rock samples, it was difficult to conduct systematic characterization and other relevant studies on carbonate sedimentary facies. In order to take advantage of high-resolution logging tool which yields a curve rich with information, petrophysicists implemented a new method to identify carbonate lithology and microfacies. To accomplish their goal, they utilized well log data and resulting curves in the Gucheng Area. After the logging curve was calibrated with of the types of microfacies derived from the rock samples, and correlated with the relationships of response between conventional logging parameters and carbonate lithology and microfacies. Then,optimal sensitive logging curves such as DEN, DT, PE, U, Th and K were selected, and a new parameter combination was proposed. The next step involved preparing two charts for identifying carbonate lithology and sedimentary microfacies, and they had a coincidence rate of 85.4% and 81.4%, respectively. Moreover, the function relationship was defined to quantitatively classify the sedimentary microfacies types according to energy within the depositional environment, and the energy parameter curves for microfacies were provided. Microfacies identified with this technique and their energy parameter curves were applied in the space division and correlation of facies belts and sedimentary cycles. Results showed that the microfacies identified and sedimentary energy distribution characteristics were consistent with that of sedimentary facies belts that had been determined previously by identifying patterns in of slices of core. Because of the positive results from the application of the technique, the results suggest that thethe technique can be used as an essential complement of fine-grained sedimentary facies study.

     

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