Correcting Errors Due to Borehole and Formation Factors during Azimuthal Gamma Spectrum Logging While Drilling
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摘要:
在不同井眼环境和地层条件下，随钻方位伽马能谱响应会有一定差异，从而影响后续的测井解释及地质导向结果，因此，有必要研究井眼和地层因素对随钻方位伽马能谱的影响规律，以消除其带来的不利影响。对比分析了现有随钻方位伽马能谱测井仪器结构，选择了其中一种结构作为研究对象，建立了相应的MCNP计算模型；采用蒙特卡罗方法模拟了随钻方位伽马能谱测井在不同井眼、地层条件下的响应，得到了钻井液密度、钻井液中KCl含量、地层骨架，以及倾斜放射性地层的倾角、方位角、厚度对随钻方位伽马能谱测井的影响规律，在此基础上，给出了非地层因素影响的校正方法。研究结果表明：计数率与钻井液中KCl含量和地层倾角及厚度正相关，与钻井液密度、地层骨架密度和地层倾斜界面方位角负相关；KCl能改变能谱形状，其他因素不改变能谱形状。研究表明，利用井眼影响因素校正后的计数率或能谱计算的泥质含量及K，U和Th的含量更接近真实值，可为测井解释及地质导向提供更可靠的指导。
Abstract:Under different borehole and formation conditions, there are some differences in the response of azimuthal gamma spectrum logging while drilling which can affect the subsequent logging interpretation and geosteering results. Therefore, it is necessary to study the influence of borehole and formation factors on the LWD azimuthal gamma spectrum, so as to eliminate the adverse effects and errors. First of all, the instrument structure of SAGR tool was compared and analyzed, and one of the structures was selected to be the study objective to establish the corresponding MCNP model. The response of LWD SAGR tool under different wellbore and formation conditions was simulated with the Monte Carlo method. The degree of influence for each of the following factors was obtained: mud density, KCl content, formation matrix and the dip angle, azimuth and thickness of inclined radioactive formation on the LWD SAGR Tool. Using the derived results it was possible to develop an appropriate, correction method for the influence of each of the non-stratigraphic factors. The results showed that the counting rate was positively correlated with KCl, dip angle and the formation thickness, and negatively correlated with mud density, the formation matrix density and azimuth. Only KCl rather than other factors can change the shape of energy spectrum. The study found that the counting rate after being corrected by the borehole influencing factors or the shale content, K, U, Th calculated by energy spectrum were closer to the true values, which could provide more accurate guidance for logging interpretation and geosteering.
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图 2 不同钻井液密度、井眼间隙下的计数率
Figure 2. Total count rate at different mud densities and wellbore gaps
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图 5 不同KCl含量、井眼间隙下的计数率
Figure 5. Counting rate at different KCl contents and wellbore gaps
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图 10 探测器穿过不同倾角界面时的计数率
Figure 10. Counting rate when the detector passes through interfaces with different dip angles
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图 11 原点处不同界面倾角下的计数率
Figure 11. Counting rate at different interface dips at the origin
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图 14 原点处不同旋转角度下的计数率
Figure 14. Counting rate at different rotating angles at the origin
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图 16 倾斜地层厚度的MCNP计算模型
Figure 16. MCNP calculation model of inclined formation with a certain thickness
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图 17 倾斜地层不同厚度下的计数率
Figure 17. Counting rate at different inclined formation thicknesses
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图 18 原点处倾斜地层不同厚度下的计数率
Figure 18. Counting rate at different inclined formation thicknesses at the origin
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图 19 倾斜地层不同厚度下的能谱响应
Figure 19. Energy spectrum response at different inclined formation thicknesses
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图 21 校正前后泥质含量计算值对比
Figure 21. Comparison of the calculated values of muddy content before and after correction
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