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1. 中国地质大学(武汉)资源学院
2. 中国地质大学(武汉)海洋学院
Online First:22 September 2025,
Published:22 September 2025
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邵志远, 何杰, 廖远涛, et al. 基于常规测井曲线的火山岩裂缝预测:以渤海湾盆地渤南地区中生界为例[J]. Bulletin of Geological Science and Technology, 2025, 44(5): 82-94.
邵志远, 何杰, 廖远涛, et al. 基于常规测井曲线的火山岩裂缝预测:以渤海湾盆地渤南地区中生界为例[J]. Bulletin of Geological Science and Technology, 2025, 44(5): 82-94. DOI: 10.19509/j.cnki.dzkq.tb20250144.
构造成因裂缝对改善深层火山岩潜山储层物性和提高油气产能具有重要意义,由于其非均质性较强,需要对断裂带不同部位的裂缝发育密度进行精细刻画。实际生产中由于岩心和成像测井资料获取成本较高,因此引入基于常规测井曲线计算的综合裂缝指数,据此划分断裂带内部结构,定量识别裂缝发育密度,为火山岩裂缝型储层勘探提供依据。通过声波时差(AC)、中子孔隙度(CN)、密度(DEN)、井径(CAL)、深侧向电阻率(RD)、浅侧向电阻率(RS)和微侧向电阻率(RMLL)7种测井参数,构建了渤海湾盆地渤南地区中生界火山岩综合裂缝指数(CFI)模型;利用累计CFI曲线斜率变化定量划分了裂缝发育密集段边界,将断裂带内部分别划分为断核、损伤带和围岩,裂缝在损伤带内发育密度最大,其次为围岩,在断核内几乎不发育。研究区中生界火山岩中7种常见测井曲线在裂缝发育带中分别表现为AC、CN和CAL值增大,DEN、RD、RS和RMLL值减小的响应特征,CFI值在裂缝发育位置出现明显上升。结合成像测井和岩心资料表明,CFI曲线高值区与裂缝发育段呈对应关系。结合地震解释确定断核后,可以明确损伤带及围岩分布范围并进一步对渤南地区中生界火山岩中的裂缝进行有效预测。基于测井曲线计算的CFI模型能有效量化火山岩裂缝发育强度,定位裂缝发育密集带的井下空间位置,通过累计CFI曲线可实现断裂带内部结构的有效识别。
ObjectiveTectonic fractures play a significant role in enhancing the physical properties and hydrocarbon productivity of deep volcanic buried-hill reservoirs. Due to their strong heterogeneity
precise characterization of fracture density across different parts of the fault zone is required. In practical production
the high cost of core acquisition and imaging logging data motivates the use of a comprehensive fracture index (CFI) calculated from conventional logging curves to delineate the internal structure of fault zones and quantitatively identify fracture density
providing a basis for exploring fractured volcanic reservoirs. MethodsA CFI model was constructed for Mesozoic volcanic rocks in the Bonan area of the Bohai Bay Basin using seven logging parameters: Acoustic travel time (AC)
neutron porosity (CN)
bulk density (DEN)
caliper (CAL)
deep lateral resistivity (RD)
shallow lateral resistivity (RS)
and micro-lateral resistivity (RMLL). The cumulative CFI curve slope was used to define the boundaries of fracture-dense zones
partitioning the fault zone into the fault core
damage zone
and host rock. The damage zone exhibits the highest fracture density
followed by the host rock
while the fault core is nearly fracture-free. ResultsIn the Mesozoic volcanic rocks of the study area
the seven conventional logging curves show distinct responses in fracture-developed zones: AC
CN
and CAL increase
whereas DEN
RD
RS
and RMLL decrease. The CFI curve shows a pronounced rise in fracture-rich intervals. Comparison with imaging logs and core data confirms that high CFI values correlate with fracture zones. By integrating seismic interpretation to identify the fault core
the distribution of the damage zone and host rock can be delineated
enabling effective fracture prediction in Mesozoic volcanic rocks in the Bonan area. ConclusionThe CFI model
derived from logging curves
can effectively quantify the intensity of fracture development in volcanic rocks
locate the downhole spatial distribution of fracture-dense zones
and enable the reliable identification of internal-zone structures via cumulative CFI curve analysis.
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