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本文提出了一种将高分辨率阵列侧向和方位电极系综合在一起的三维侧向测井电极系3D-LS,该电极系具有径向、纵向和周向探测能力。通过有限元数值模拟计算,考察了井眼尺寸、冲洗带电阻率、侵入深度、层厚及围岩电阻率对六种不同探测模式的影响,确定了电极系尺寸和探测特性。分析伪几何因子,低侵时电极系的探测深度最深可达1.5m,其值接近斯伦贝谢双侧向电极系深探测深度,而大于高分辨率方位侧向成像仪深探测深度,并且三维侧向测井电极系可提供多条径向不同深度曲线,可更好地描述地层侵入剖面。无限厚地层条件下,方位电极可识别出厚度0.1m的异常体,利用方位侧向曲线半幅点对应异常体厚度判断,对异常体纵向分层能力可达0.5m。高阻背景下,异常体的电阻率越低,越靠近井眼,方位越大于15度,越易被方位电极探测。数值模拟结果为后续三维侧向测井电极系的研究奠定了基础,对低阻异常评价具有一定的指导意义。
In this paper, we propose a 3D-LSD 3D-LS that integrates high-resolution array lateral and azimuthal electrodes with radial, longitudinal and circumferential probing capabilities. Through the numerical simulation of finite element method, the effects of borehole size, resistivity of wash zone, invasion depth, wall thickness and resistivity of surrounding rock on six different exploration modes were investigated, and the size and detection characteristics of the electrode system were determined. The analysis of the pseudo-geometric factors shows that the detection depth of the electrode system at the time of low invasion is up to 1.5 m, which is close to the deep detection depth of the Schlumberger double lateral electrode system and greater than the deep detection depth of the high resolution azimuth side imaging instrument, and Three-dimensional lateral logging electrode systems provide multiple radial depth profiles to better characterize the formation invasion profile. Under the condition of infinite thickness, the azimuth electrode can identify the abnormal body with the thickness of 0.1m. Judging from the thickness of the anomalous body corresponding to the half-point point of the curve, the longitudinal stratification ability of the anomalous body can reach 0.5m. High resistance background, the lower the resistivity of the abnormal body, the closer the hole, the greater the azimuth of 15 degrees, the more easily detected by the azimuth electrode. The numerical simulation results lay the foundation for the research of the subsequent three-dimensional lateral well electrode system, which is of guiding significance to the low resistance anomaly evaluation.