| 古岩溶油气储层研究进展 |
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| 引用本文： | 张宇,赵伦,李长海,张祥忠.古岩溶油气储层研究进展[J].中国岩溶,2022,41(5):808-824. |
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| 作者姓名： | 张宇 赵伦 李长海 张祥忠 |
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| 作者单位： | 1.中国石油勘探开发研究院, 北京 100083 |
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| 基金项目： | 中亚裂缝孔隙型碳酸盐岩油藏稳油控水及提高采收率技术研究（2022DJ3209） |
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| 摘 要： | 古岩溶对可溶性岩石的改造作用表现为形成溶蚀孔洞等储集空间，特别是对于碳酸盐岩地层，古岩溶发育会极大地改善了地层的储集性能，形成具有良好孔渗性的岩溶储层。作为碳酸盐岩地层中重要储层类型之一，岩溶储层的发育与分布对于碳酸盐岩油气藏的形成具有重要意义。文章系统地总结了前人在不同类型岩溶储层以及断溶体等方面的研究成果，并对古岩溶油气储层研究的最新进展进行了梳理归纳，这对于认识我国含油气盆地中岩溶储层的发育与分布具有重要参考价值。总结认为古岩溶油气储层研究主要存在以下问题:（1）早成岩岩溶储层研究实例较少，且利用测井、地震资料对该类型储层的分布进行预测缺少相应实践；（2）表生岩溶储层的研究主要集中于古地貌恢复以及垂向分带方面。但目前的古地貌恢复方法，均具有一定的局限性，无法对古地貌实现定量恢复。垂向分带的方案众多，尚未形成一个统一的分类方案，且在垂向上带与带之间的界线不明确，无法进行准确地划分；（3）埋藏岩溶储层的研究主要集中在硫酸盐热还原作用以及热液溶蚀方面，对于受有机酸影响的埋藏岩溶储层缺少相应的研究；（4）断溶体的识别、刻画与预测主要依赖于地震资料，受地震资料分辨率影响显著；（5）岩溶储层发育的影响因素众多，仅靠单一地质或者地震资料无法实现对岩溶储层的精准预测。
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| 关 键 词： | 古岩溶 岩溶储层 断溶体 储层预测 |
| 收稿时间： | 2021-12-10 |
Research progress of paleokarst oil and gas reservoirs |
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| Institution: | 1.Research Institute of Petroleum Exploration and Development, Beijing 100083, China;2.School of Earth and Space Sciences, Peking University,Beijing 100871, China |
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| Abstract: | The transformation of soluble rocks by paleokarst can form dissolution pores and other reservoir spaces. Especially for carbonate rocks, the development of paleokarst can greatly improve the reservoir performance of the formation and form karst reservoirs with good porosity and permeability. Paleokarst related oil and gas reservoirs are developed in many large and super-large carbonate oil and gas fields at home and abroad, such as Yurubcheno Oilfield in Russia, Yates Oilfield in the United States, Halfaya Oilfield in Iraq, Renqiu Oilfield, Tahe Oilfield, Maokou formation and Dengying formation in Sichuan Basin and Ordovician formation in Ordos Basin in China. As one of the important reservoir types in carbonate formation, the development and distribution of karst reservoirs are of great significance in the study on carbonate reservoirs. This paper systematically summarizes the previous studies on different types of karst reservoirs and the latest research progress of paleokarst oil and gas reservoirs, which are of important reference value for understanding the development and distribution of karst reservoirs in oil-gas basins in China. The following problems and results can be concluded in the study of paleokarst oil and gas reservoirs. There are few studies on early diagenetic karst reservoirs, and most of them focus on the formation mechanism and development characteristics of eogenetic karst reservoirs. In addition, there is no corresponding practice on how to use logging and seismic data to predict the distribution of this type of reservoir. There are many studies on supergene karst reservoirs, mainly focusing on paleogeomorphology restoration and vertical zonation. Meanwhile, many palaeogeomorphology restoration methods have been proposed, such as impression method, residual thickness method, stripping and filling method, sedimentological analysis method, sequence stratigraphy method, layer leveling method, double-interface method, well-seismic combination method and the new seismic geomorphology method. However, all of the present restoration methods of paleokarst geomorphology have their advantages and disadvantages in certain applicable scope, and can only be used to restore paleokarst geomorphology qualitatively and semi-quantitatively. How to precisely quantify the restoration of paleokarst geomorphology remains further studied. In terms of vertical zonation, many schemes have been proposed from the perspectives of runoff strength, karst space form, karst development intensity, and the characteristics of hydrodynamic action. In particular, a great deal of research and practice has been carried out on the characteristics of hydrodynamic action, and a variety of vertical zonation schemes have been put forward to divide karst vertically into 2-6 zones. But in general, although there are many schemes to divide the vertical zonation of paleokarst, a unified classification has not yet been formed. Besides, the boundary between the vertical zonation and the zonation is not clear, so it is unlikely to distinguish them quantitatively and accurately. From the case study of Sichuan Basin and Tarim Basin in China, buried karst reservoirs have significant identification marks in mineralogy, petrology and geochemistry. In the prediction of buried karst reservoir, the current research is mainly focused on migration channel and fluid distribution. From the perspective of reservoir formation, the research on buried karst reservoirs at present is mainly focused on sulfate thermal reduction and hydrothermal dissolution, but there is a lack of relevant research on buried karst reservoirs affected by organic acids. As a hotspot of karst reservoir research in recent years, the studies on fault-karst reservoirs are mainly focused on the development mechanism and characterization of fault solutions, etc. The recognition, characterization and prediction of fault-karst reservoirs mainly rely on seismic data, and are significantly affected by the resolution of seismic data. There are many internal and external factors affecting the development of paleokarst oil and gas reservoirs. The internal factors include lithology, development degree of primary pores, rock structure, mud and acid insoluble content, fractures, etc. The external factors mainly include sedimentary facies, rise and fall of sea levels, palaeogeomorphology, tectonic movement and paleoclimate. In terms of the prediction of paleokarst oil and gas reservoirs, the accurate prediction of karst reservoirs cannot be achieved with single geological or seismic data, because there are many factors affecting the development of karst reservoirs and many differences in the formation mechanism and development characteristics of different types of karst reservoirs. The comprehensive prediction method based on geology-log-seismic can be adopted as the mainstream of karst reservoir prediction in the future. With the continuous development of geophysics and artificial intelligence of oil and gas, the increasing new methods and technologies will be applied to karst reservoir prediction. |
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