基于米氏旋回的海相碳酸盐岩低级序不整合面识别——以鄂尔多斯盆地马家沟组五段为例

张斌弛 ,  铁木尔巴特 ,  张月 ,  邵世国 ,  王守志 ,  王林 ,  文慧俭 ,  梅曦 ,  李润民

东北石油大学学报 ›› 2025, Vol. 49 ›› Issue (6) : 57 -69.

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东北石油大学学报 ›› 2025, Vol. 49 ›› Issue (6) : 57 -69. DOI: 10.3969/j.issn.2095-4107.2025.06.005
油气地质与勘探

基于米氏旋回的海相碳酸盐岩低级序不整合面识别——以鄂尔多斯盆地马家沟组五段为例

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Low-order unconformity recognition of marine carbonate rocks based on Milankovitch cycles : an example of fifth member of the Majiagou Formation in the Ordos Basin

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摘要

沉积成因的碳酸盐岩低级序不整合面的分布影响岩溶储层的发育,采用常规方法很难识别和表征。以鄂尔多斯盆地马家沟组五段为例,提出一种基于米氏旋回理论的定量识别方法,融合频谱分析、皮尔逊相关因数法、零假设模型及"暴露时间-溶蚀量"动态模型,结合自然伽马测井曲线与 405 ka 长偏心率周期,定量表征研究区目的层沉积速率 ( 2.5 3.0   c m / k a)、低级序不整合面年代( 468.6 460.1 M a)及溶蚀强度。结果表明:研究区识别四期低级序不整合面,沉积间断总时间为 0.3 Ma ,最大地层缺失厚度为 9 m ;溶蚀强度与相对海平面上升速率呈显著负相关关系,缓慢上升 (0.7 m/Ma ,历时 1.4 Ma)发育直径为 0.20 0.40   m m 的溶洞,快速上升(1.2 m/Ma ,历时 0.9 Ma)发育直径为 0.05 0.10 mm 的微孔。米氏旋回驱动的"气候-海平面耦合"模型实现低级序不整合面定量识别,揭示气候-海平面耦合驱动的滞后响应机制,修正传统层序模型中"海退不整合面"的长期暴露假设。该结果为高频海平面波动区岩溶储层预测、鄂尔多斯盆地及类似克拉通盆地深层勘探提供指导。

Abstract

The spatial distribution of low-order unconformities in sedimentary carbonate rocks exerts a profound influence on the development of karst reservoirs. The identification and characterization pose formidable challenges that traditional geological methods are ill-equipped to address. Confronted with the inherent limitations of conventional approaches, including exorbitant costs, poor spatial continuity, and insufficient quantification, for identifying low-order unconformities in carbonate formations, this study selects the fifth member of the Majiagou Formation in the Ordos Basin as a model system. An innovative, highly efficient quantitative identification method is proposed, which is firmly rooted in the Milankovitch cycle theory. This study integrates multiple analytical techniques, including spectral analysis, the Pearson correlation coefficient method, the null hypothesis model, and the dynamic "exposure time-dissolution amount" model. By correlating gamma-ray logging curves with the 405 ka long eccentricity cycle, we quantitatively characterize key geological parameters, such as the sedimentation rate (ranging from 2.5 to 3.0 cm/ka) of the target formation, the geological age of low-order unconformities (spanning from 468.6 to 460.1 Ma), and the dissolution intensity. The results of this research reveal the presence of four distinct phases of low-order unconformities, with a cumulative sedimentation hiatus of 0.3 million years and a maximum stratigraphic loss of 9 meters. A statistically significant negative correlation is observed between the dissolution intensity and the relative sea-level rise rate. During periods of slow sea-level rise (0.7 m/Ma over 1.4 million years), karst caves with diameters ranging from 0.2 to 0.4 mm are formed. In contrast, rapid sea-level rise events (1.2 m/Ma over 0.9 million years) lead to the development of only micro-pores with diameters of 0.05 to 0.10 mm. This study represents a significant advancement by for the first time elucidating the "lag response" mechanism driven by the coupling of climate change and sea-level fluctuations. It challenges and revises the long-standing assumption of "long-term exposure during regressive unconformities" in traditional sequence stratigraphy models. The proposed method provides essential quantitative technical support for predicting karst reservoirs in regions characterized by high-frequency sea-level fluctuations. The findings of this study have far-reaching implications for both the practical exploration of deep subsurface reservoirs and the theoretical understanding of sedimentary processes in the Ordos Basin and other similar cratonic basins.

关键词

低级序不整合面 / 海相碳酸盐岩 / 米氏旋回 / 台地 / 岩溶储层 / 频谱分析 / 沉积速率 / 海平面变化 / 马家沟组 / 克拉通盆地 / 鄂尔多斯盆地

Key words

low-order unconformity / marine carbonate rocks / Milankovitch cycles / platform / karst reservoir / spectral analysis / sedimentation rate / sea level / Majiagou Formation / Craton Basin / Ordos Basin

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张斌弛,铁木尔巴特,张月,邵世国,王守志,王林,文慧俭,梅曦,李润民. 基于米氏旋回的海相碳酸盐岩低级序不整合面识别——以鄂尔多斯盆地马家沟组五段为例[J]. 东北石油大学学报, 2025, 49(6): 57-69 DOI:10.3969/j.issn.2095-4107.2025.06.005

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黑龙江省自然科学基金联合引导项目(LH2024D010)

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