关键词: 深层油气, 富集机理, 勘探关键技术, 勘探进展及方向

Abstract:

The deep oil and gas exploration area serves as a crucial position for resource development in Subei Basin. However, challenges including generally poor physical properties of deep reservoirs, insufficient understanding of oil and gas enrichment mechanisms, and ineffective reservoir prediction to meet exploration demands have constrained the expansion of deep oil and gas exploration. To understand the enrichment mechanisms of deep oil and gas, develop key exploration technologies, and indicate future research directions, this paper focuses on the deep layers of Gaoyou and Jinhu Sags, which are rich in oil and gas resources. Firstly, by analyzing the exploration development trends and oil and gas resource potential in oil and gas enrichment Sags such as Gaoyou and Jinhu, along with physical characteristics and main controlling factors of deep reservoirs, it was believed that the deep oil and gas reservoirs in Gaoyou and Jinhu Sags were mainly characterized by low to extra-low porosity and permeability. Secondary pore was the main pore type, while primary pore occurred locally. Overall, as burial depth increased, the proportion of primary pores gradually decreased. Subsequently, based on the relationship between pores and pore throats, deep reservoirs were classified into four types of pore-throat structures: large intergranular pores and wide lamellar throats; small intergranular pores and narrow lamellar throats; intragranular dissolution pores and narrow lamellar throats; and micropores and tubular throats. The physical properties of deep reservoirs were generally poor, with locally developed favorable reservoirs. The factors influencing the physical properties of deep reservoirs were complex. Analysis suggests that sedimentary factors, diagenesis, tectonic activity, oil and gas injection, and abnormal formation pressures all significantly affected the physical properties of deep reservoirs, although the controlling factors and their effects varied across different regions. Secondly, investigations were conducted on the occurrence conditions, main controlling factors, and accumulation models of deep oil and gas. The occurrence conditions of oil and gass suggested that oil and gas migration and accumulation were controlled by the pressure systems and physical properties between source rocks and reservoirs, as well as between different reservoirs. Oil and gas accumulation occurred when migration forces overcame migration resistance. Microscopically, pore-throat structure determined the fluid occurrence state and permeability. Larger throat radii, lower pore-throat radius ratios, and smaller tortuosities led to enhanced pore-throat connectivity and higher reservoir permeability. Macroscopically, pressure increase with oil and gas generation provided the driving force for oil and gas migration and accumulation. The magnitude and direction of source-reservoir pressure difference decided the favorable trends for oil and gas migration and accumulation, controlling their favorable areas. In terms of the main controlling factors for oil and gas enrichment, it was believed that oil and gas accumulation and enrichment in deep reservoirs were jointly controlled by source-reservoir configuration, pressure increase with oil and gas generation, fault-sandstone carrier system, and reservoir physical properties. Three accumulation models for deep oil and gas enrichment were established: stepped accumulation driven by combined abnormal overpressure and buoyancy, accumulation via fault-sandstone carrier system driven by abnormal overpressure, and accumulation of early-stage oil and gas injection followed by later-stage compaction. These models elucidated the enrichment mechanisms of deep oil and gass. Based on the above, to address exploration challenges such as unclear reservoir distribution, undefined enrichment zones, and low identification accuracy of effective reservoirs, three breakthrough technologies were developed: (1) A facies-controlled index method for deep reservoir classification was developed based on “facies-controlled index, porosity-permeability characteristics, pore structures, and diagenetic facies”. Reservoir classification criteria were formulated, categorizing reservoirs into four grades. Effective reservoirs in deep layers were mainly grades Ⅱ and Ⅲ. The distribution of effective reservoirs in the deep layers was evaluated across key stratigraphic intervals, revealing the graded distribution of reservoirs in deep zones of the first and third member of Funing Formation, the third submember in the first member of Dainan Formation in Gaoyou Sag, and the second member of Funing Formation in Jinhu Sag. The favorable areas of effective reservoirs in the deep layers of each stratigraphic system in each Sag were finally determined. (2) Through the analysis of deep oil and gas enrichment mechanisms, and according to the dynamic conditions of oil and gas injection, models for calculating reservoir potential energy, fluid potential, and source-reservoir pressure differences were established. Subsequently, a model for calculating the reservoir injection potential energy index were established based on the above models. Finally, the obtained reservoir injection potential energy index was used to assess the probability of oil and gas accumulation, providing technical support for the selection of favorable oil and gas accumulation zones in deep layers. (3) Subaqueous distributary channels and beach-bar sand bodies were effective reservoirs for deep oil and gass. To address the challenge of effective reservoir prediction in thin sandstone-mudstone interbeds within favorable oil and gas accumulation zones in selected deep layers, an integrated technical suite for effective reservoir prediction was developed. This technique, tailored to different sand body types such as channels and beach bars, integrated pre-stack and post-stack multi-attribute analysis. It leveraged geological, petrophysical, seismic, statistical, and other disciplinary theories to provide a comprehensive approach to reservoir prediction. Based on the distinction between sandstone and mudstone, this suite included six techniques for reservoir prediction: effective reservoir modeling based on petrophysical analysis, post-stack multi-parameter inversion constraint method, pre-stack and post-stack joint inversion method, seismic attribute threshold analysis method, seismic multi-attribute neural network prediction method, and SP curve reconstruction for acoustic curve. These techniques collectively improved the prediction accuracy of effective reservoirs in deep layers. These research findings provide theoretical guidance and technical support for the expansion of deep oil and gas exploration. Significant exploration progress has been made in deep layers such as slope zones, fault zones, and deep sag zones, enabling the expansion of deep oil and gas exploration. In the future, the research directions for addressing challenges in deep oil and gas exploration are clarified, which are continuing to consolidate and expand deep exploration to support the increase in oilfield reserves and production.

Key words: Subei Basin, deep oil and gas reservoirs, enrichment mechanisms, key exploration technologies, exploration progress and directions